diff --git a/selection-refactor/development/index.html b/selection-refactor/development/index.html index 70fe0cfa..78a439b5 100644 --- a/selection-refactor/development/index.html +++ b/selection-refactor/development/index.html @@ -805,7 +805,6 @@

Development

-

Contributing to Network Wrangler

Setup

@@ -1015,9 +1014,6 @@

Project GovernanceCode of Conduct

Contributors to the Network Wrangler Project are expected to read and follow the CODE_OF_CONDUCT for the project.

- - -

Contributors

  1. Lisa Z. - initial Network Wrangler implementation at SFCTA
    2. @@ -1032,10 +1028,7 @@

    ContributorsNote

    There are likely more contributors - feel free to add your name if we missed it!

    - -

    Release History

    -

    Changelog

    Notable changes and version history.

    @@ -1084,7 +1077,6 @@

    ChangelogHaving an issue?License

    Apache-2.0

    Release History

    -

    Changelog

    Notable changes and version history.

    @@ -936,7 +935,6 @@

    Changelog https://wsp-sag.github.io/network_wrangler/selection-refactor/ - 2024-10-21 + 2024-10-28 daily https://wsp-sag.github.io/network_wrangler/selection-refactor/api/ - 2024-10-21 + 2024-10-28 daily https://wsp-sag.github.io/network_wrangler/selection-refactor/data_models/ - 2024-10-21 + 2024-10-28 daily https://wsp-sag.github.io/network_wrangler/selection-refactor/design/ - 2024-10-21 + 2024-10-28 daily https://wsp-sag.github.io/network_wrangler/selection-refactor/development/ - 2024-10-21 + 2024-10-28 daily https://wsp-sag.github.io/network_wrangler/selection-refactor/how_to/ - 2024-10-21 + 2024-10-28 daily https://wsp-sag.github.io/network_wrangler/selection-refactor/networks/ - 2024-10-21 + 2024-10-28 daily \ No newline at end of file diff --git a/selection-refactor/sitemap.xml.gz b/selection-refactor/sitemap.xml.gz index 82aea057..6c84411f 100644 Binary files a/selection-refactor/sitemap.xml.gz and b/selection-refactor/sitemap.xml.gz differ diff --git a/v1.0-beta.2 b/v1.0-beta.2 new file mode 120000 index 00000000..edf1a62b --- /dev/null +++ b/v1.0-beta.2 @@ -0,0 +1 @@ +selection-refactor \ No newline at end of file diff --git a/v1.0-beta.2/404.html b/v1.0-beta.2/404.html deleted file mode 100644 index 31ffa553..00000000 --- a/v1.0-beta.2/404.html +++ /dev/null @@ -1,574 +0,0 @@ - - - - - - - - - - - - - - - - - - - Network Wrangler - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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    - - - - - - - - - - \ No newline at end of file diff --git a/v1.0-beta.2/api/index.html b/v1.0-beta.2/api/index.html deleted file mode 100644 index 6998736f..00000000 --- a/v1.0-beta.2/api/index.html +++ /dev/null @@ -1,40225 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - - - API Documentation - Network Wrangler - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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    API Documentation

    -

    Common Usage

    -

    Base Objects

    - - -
    - - - - -
    - -

    Scenario objects manage how a collection of projects is applied to the networks.

    -

    Scenarios are built from a base scenario and a list of project cards.

    -

    A project card is a YAML file (or similar) that describes a change to the network. The project -card can contain multiple changes, each of which is applied to the network in sequence.

    -

    Create a Scenario

    -

    Instantiate a scenario by seeding it with a base scenario and optionally some project cards.

    -
    from network_wrangler import create_scenario
-
-my_scenario = create_scenario(
-    base_scenario=my_base_year_scenario,
-    card_search_dir=project_card_directory,
-    filter_tags=["baseline2050"],
-)
-
    -

    A base_year_scenario is a dictionary representation of key components of a scenario:

    -
      -
    • road_net: RoadwayNetwork instance
      • -
    • transit_net: TransitNetwork instance
      • -
    • applied_projects: list of projects that have been applied to the base scenario so that the - scenario knows if there will be conflicts with future projects or if a future project’s - pre-requisite is satisfied.
      • -
    • conflicts: dictionary of conflicts for project that have been applied to the base scenario so - that the scenario knows if there will be conflicts with future projects.
      • -
    -
    my_base_year_scenario = {
-    "road_net": load_from_roadway_dir(STPAUL_DIR),
-    "transit_net": load_transit(STPAUL_DIR),
-    "applied_projects": [],
-    "conflicts": {},
-}
-
    -

    Add Projects to a Scenario

    -

    In addition to adding projects when you create the scenario, project cards can be added to a -scenario using the add_project_cards method.

    -
    from projectcard import read_cards
-
-project_card_dict = read_cards(card_location, filter_tags=["Baseline2030"], recursive=True)
-my_scenario.add_project_cards(project_card_dict.values())
-
    -

    Where card_location can be a single path, list of paths, a directory, or a glob pattern.

    -

    Apply Projects to a Scenario

    -

    Projects can be applied to a scenario using the apply_all_projects method. Before applying -projects, the scenario will check that all pre-requisites are satisfied, that there are no conflicts, -and that the projects are in the planned projects list.

    -

    If you want to check the order of projects before applying them, you can use the queued_projects -prooperty.

    -
    my_scenario.queued_projects
-my_scenario.apply_all_projects()
-
    -

    You can review the resulting scenario, roadway network, and transit networks.

    -
    my_scenario.applied_projects
-my_scenario.road_net.links_gdf.explore()
-my_scenario.transit_net.feed.shapes_gdf.explore()
-
    -

    Write a Scenario to Disk

    -

    Scenarios (and their networks) can be written to disk using the write method which -in addition to writing out roadway and transit networks, will serialize the scenario to -a yaml-like file and can also write out the project cards that have been applied.

    -
    my_scenario.write(
-    "output_dir",
-    "scenario_name_to_use",
-    overwrite=True,
-    projects_write=True,
-    file_format="parquet",
-)
-
    -
    Example Serialized Scenario File
    applied_projects: &id001
-- project a
-- project b
-base_scenario:
-applied_projects: *id001
-roadway:
-    dir: /Users/elizabeth/Documents/urbanlabs/MetCouncil/NetworkWrangler/working/network_wrangler/examples/small
-    file_format: geojson
-transit:
-    dir: /Users/elizabeth/Documents/urbanlabs/MetCouncil/NetworkWrangler/working/network_wrangler/examples/small
-config:
-CPU:
-    EST_PD_READ_SPEED:
-    csv: 0.03
-    geojson: 0.03
-    json: 0.15
-    parquet: 0.005
-    txt: 0.04
-IDS:
-    ML_LINK_ID_METHOD: range
-    ML_LINK_ID_RANGE: &id002 !!python/tuple
-    - 950000
-    - 999999
-    ML_LINK_ID_SCALAR: 15000
-    ML_NODE_ID_METHOD: range
-    ML_NODE_ID_RANGE: *id002
-    ML_NODE_ID_SCALAR: 15000
-    ROAD_SHAPE_ID_METHOD: scalar
-    ROAD_SHAPE_ID_SCALAR: 1000
-    TRANSIT_SHAPE_ID_METHOD: scalar
-    TRANSIT_SHAPE_ID_SCALAR: 1000000
-MODEL_ROADWAY:
-    ADDITIONAL_COPY_FROM_GP_TO_ML: []
-    ADDITIONAL_COPY_TO_ACCESS_EGRESS: []
-    ML_OFFSET_METERS: -10
-conflicts: {}
-corequisites: {}
-name: first_scenario
-prerequisites: {}
-roadway:
-dir: /Users/elizabeth/Documents/urbanlabs/MetCouncil/NetworkWrangler/working/network_wrangler/tests/out/first_scenario/roadway
-file_format: parquet
-transit:
-dir: /Users/elizabeth/Documents/urbanlabs/MetCouncil/NetworkWrangler/working/network_wrangler/tests/out/first_scenario/transit
-file_format: txt
-
    -
    -

    Load a scenario from disk

    -

    And if you want to reload scenario that you “wrote”, you can use the load_scenario function.

    -
    from network_wrangler import load_scenario
-
-my_scenario = load_scenario("output_dir/scenario_name_to_use_scenario.yml")
-
    - - - -
    - - - - - - - -
    - - - -

    - BASE_SCENARIO_SUGGESTED_PROPS: list[str] = ['road_net', 'transit_net', 'applied_projects', 'conflicts'] - - - module-attribute - - -

    - - -
    - -

    List of card types that that will be applied to the transit network.

    -
    - -
    - -
    - - - -

    - ROADWAY_CARD_TYPES: list[str] = ['roadway_property_change', 'roadway_deletion', 'roadway_addition', 'pycode'] - - - module-attribute - - -

    - - -
    - -

    List of card types that that will be applied to the transit network AFTER being applied to -the roadway network.

    -
    - -
    - -
    - - - -

    - TRANSIT_CARD_TYPES: list[str] = ['transit_property_change', 'transit_routing_change', 'transit_route_addition', 'transit_service_deletion'] - - - module-attribute - - -

    - - -
    - -

    List of card types that that will be applied to the roadway network.

    -
    - -
    - - -
    - - - -

    - Scenario - - -

    - - -
    - - -

    Holds information about a scenario.

    -

    Typical usage example:

    -
    my_base_year_scenario = {
-    "road_net": load_roadway(
-        links_file=STPAUL_LINK_FILE,
-        nodes_file=STPAUL_NODE_FILE,
-        shapes_file=STPAUL_SHAPE_FILE,
-    ),
-    "transit_net": load_transit(STPAUL_DIR),
-}
-
-# create a future baseline scenario from base by searching for all cards in dir w/ baseline tag
-project_card_directory = Path(STPAUL_DIR) / "project_cards"
-my_scenario = create_scenario(
-    base_scenario=my_base_year_scenario,
-    card_search_dir=project_card_directory,
-    filter_tags=["baseline2050"],
-)
-
-# check project card queue and then apply the projects
-my_scenario.queued_projects
-my_scenario.apply_all_projects()
-
-# check applied projects, write it out, and create a summary report.
-my_scenario.applied_projects
-my_scenario.write("baseline")
-my_scenario.summary
-
-# Add some projects to create a build scenario based on a list of files.
-build_card_filenames = [
-    "3_multiple_roadway_attribute_change.yml",
-    "road.prop_changes.segment.yml",
-    "4_simple_managed_lane.yml",
-]
-my_scenario.add_projects_from_files(build_card_filenames)
-my_scenario.write("build2050")
-my_scenario.summary
-
    - - -

    Attributes:

    -

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescription
    base_scenario - dict - -
    -

    dictionary representation of a scenario

    -
    -
    road_net - Optional[RoadwayNetwork] - -
    -

    instance of RoadwayNetwork for the scenario

    -
    -
    transit_net - Optional[TransitNetwork] - -
    -

    instance of TransitNetwork for the scenario

    -
    -
    project_cards - dict[str, ProjectCard] - -
    -

    Mapping[ProjectCard.name,ProjectCard] Storage of all project cards by name.

    -
    -
    queued_projects - -
    -

    Projects which are “shovel ready” - have had pre-requisits checked and -done any required re-ordering. Similar to a git staging, project cards aren’t -recognized in this collecton once they are moved to applied.

    -
    -
    applied_projects - list[str] - -
    -

    list of project names that have been applied

    -
    -
    projects - -
    -

    list of all projects either planned, queued, or applied

    -
    -
    prerequisites - dict[str, list[str]] - -
    -

    dictionary storing prerequiste info as projectA: [prereqs-for-projectA]

    -
    -
    corequisites - dict[str, list[str]] - -
    -

    dictionary storing corequisite info asprojectA: [coreqs-for-projectA]

    -
    -
    conflicts - dict[str, list[str]] - -
    -

    dictionary storing conflict info as projectA: [conflicts-for-projectA]

    -
    -
    config - -
    -

    WranglerConfig instance.

    -
    -
    - -
    - Source code in network_wrangler/scenario.py - 
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    class Scenario:
-    """Holds information about a scenario.
-
-    Typical usage example:
-
-    ```python
-    my_base_year_scenario = {
-        "road_net": load_roadway(
-            links_file=STPAUL_LINK_FILE,
-            nodes_file=STPAUL_NODE_FILE,
-            shapes_file=STPAUL_SHAPE_FILE,
-        ),
-        "transit_net": load_transit(STPAUL_DIR),
-    }
-
-    # create a future baseline scenario from base by searching for all cards in dir w/ baseline tag
-    project_card_directory = Path(STPAUL_DIR) / "project_cards"
-    my_scenario = create_scenario(
-        base_scenario=my_base_year_scenario,
-        card_search_dir=project_card_directory,
-        filter_tags=["baseline2050"],
-    )
-
-    # check project card queue and then apply the projects
-    my_scenario.queued_projects
-    my_scenario.apply_all_projects()
-
-    # check applied projects, write it out, and create a summary report.
-    my_scenario.applied_projects
-    my_scenario.write("baseline")
-    my_scenario.summary
-
-    # Add some projects to create a build scenario based on a list of files.
-    build_card_filenames = [
-        "3_multiple_roadway_attribute_change.yml",
-        "road.prop_changes.segment.yml",
-        "4_simple_managed_lane.yml",
-    ]
-    my_scenario.add_projects_from_files(build_card_filenames)
-    my_scenario.write("build2050")
-    my_scenario.summary
-    ```
-
-    Attributes:
-        base_scenario: dictionary representation of a scenario
-        road_net: instance of RoadwayNetwork for the scenario
-        transit_net: instance of TransitNetwork for the scenario
-        project_cards: Mapping[ProjectCard.name,ProjectCard] Storage of all project cards by name.
-        queued_projects: Projects which are "shovel ready" - have had pre-requisits checked and
-            done any required re-ordering. Similar to a git staging, project cards aren't
-            recognized in this collecton once they are moved to applied.
-        applied_projects: list of project names that have been applied
-        projects: list of all projects either planned, queued, or applied
-        prerequisites:  dictionary storing prerequiste info as `projectA: [prereqs-for-projectA]`
-        corequisites:  dictionary storing corequisite info as`projectA: [coreqs-for-projectA]`
-        conflicts: dictionary storing conflict info as `projectA: [conflicts-for-projectA]`
-        config: WranglerConfig instance.
-    """
-
-    def __init__(
-        self,
-        base_scenario: Union[Scenario, dict],
-        project_card_list: Optional[list[ProjectCard]] = None,
-        config: Optional[Union[WranglerConfig, dict, Path, list[Path]]] = None,
-        name: str = "",
-    ):
-        """Constructor.
-
-        Args:
-            base_scenario: A base scenario object to base this isntance off of, or a dict which
-                describes the scenario attributes including applied projects and respective
-                conflicts. `{"applied_projects": [],"conflicts":{...}}`
-            project_card_list: Optional list of ProjectCard instances to add to planned projects.
-                Defaults to None.
-            config: WranglerConfig instance or a dictionary of configuration settings or a path to
-                one or more configuration files. Configurations that are not explicity set will
-                default to the values in the default configuration in
-                `/configs/wrangler/default.yml`.
-            name: Optional name for the scenario.
-        """
-        WranglerLogger.info("Creating Scenario")
-        self.config = load_wrangler_config(config)
-
-        if project_card_list is None:
-            project_card_list = []
-
-        if isinstance(base_scenario, Scenario):
-            base_scenario = base_scenario.__dict__
-
-        self.base_scenario: dict = extract_base_scenario_metadata(base_scenario)
-
-        if not set(BASE_SCENARIO_SUGGESTED_PROPS) <= set(base_scenario.keys()):
-            WranglerLogger.warning(
-                f"Base_scenario doesn't contain {BASE_SCENARIO_SUGGESTED_PROPS}"
-            )
-        self.name: str = name
-        # if the base scenario had roadway or transit networks, use them as the basis.
-        self.road_net: Optional[RoadwayNetwork] = copy.deepcopy(
-            base_scenario.pop("road_net", None)
-        )
-
-        self.transit_net: Optional[TransitNetwork] = copy.deepcopy(
-            base_scenario.pop("transit_net", None)
-        )
-        if self.road_net and self.transit_net:
-            self.transit_net.road_net = self.road_net
-
-        # Set configs for networks to be the same as scenario.
-        if isinstance(self.road_net, RoadwayNetwork):
-            self.road_net.config = self.config
-        if isinstance(self.transit_net, TransitNetwork):
-            self.transit_net.config = self.config
-
-        self.project_cards: dict[str, ProjectCard] = {}
-        self._planned_projects: list[str] = []
-        self._queued_projects = None
-        self.applied_projects: list[str] = base_scenario.pop("applied_projects", [])
-
-        self.prerequisites: dict[str, list[str]] = base_scenario.pop("prerequisites", {})
-        self.corequisites: dict[str, list[str]] = base_scenario.pop("corequisites", {})
-        self.conflicts: dict[str, list[str]] = base_scenario.pop("conflicts", {})
-
-        for p in project_card_list:
-            self._add_project(p)
-
-    @property
-    def projects(self):
-        """Returns a list of all projects in the scenario: applied and planned."""
-        return self.applied_projects + self._planned_projects
-
-    @property
-    def queued_projects(self):
-        """Returns a list version of _queued_projects queue.
-
-        Queued projects are thos that have been planned, have all pre-requisites satisfied, and
-        have been ordered based on pre-requisites.
-
-        If no queued projects, will dynamically generate from planned projects based on
-        pre-requisites and return the queue.
-        """
-        if not self._queued_projects:
-            self._check_projects_requirements_satisfied(self._planned_projects)
-            self._queued_projects = self.order_projects(self._planned_projects)
-        return list(self._queued_projects)
-
-    def __str__(self):
-        """String representation of the Scenario object."""
-        s = [f"{key}: {value}" for key, value in self.__dict__.items()]
-        return "\n".join(s)
-
-    def _add_dependencies(self, project_name, dependencies: dict) -> None:
-        """Add dependencies from a project card to relevant scenario variables.
-
-        Updates existing "prerequisites", "corequisites" and "conflicts".
-        Lowercases everything to enable string matching.
-
-        Args:
-            project_name: name of project you are adding dependencies for.
-            dependencies: Dictionary of depndencies by dependency type and list of associated
-                projects.
-        """
-        project_name = project_name.lower()
-
-        for d, v in dependencies.items():
-            _dep = list(map(str.lower, v))
-            WranglerLogger.debug(f"Adding {_dep} to {project_name} dependency table.")
-            self.__dict__[d].update({project_name: _dep})
-
-    def _add_project(
-        self,
-        project_card: ProjectCard,
-        validate: bool = True,
-        filter_tags: Optional[list[str]] = None,
-    ) -> None:
-        """Adds a single ProjectCard instances to the Scenario.
-
-        Checks that a project of same name is not already in scenario.
-        If selected, will validate ProjectCard before adding.
-        If provided, will only add ProjectCard if it matches at least one filter_tags.
-
-        Resets scenario queued_projects.
-
-        Args:
-            project_card (ProjectCard): ProjectCard instance to add to scenario.
-            validate (bool, optional): If True, will validate the projectcard before
-                being adding it to the scenario. Defaults to True.
-            filter_tags: If used, will only add the project card if
-                its tags match one or more of these filter_tags. Defaults to []
-                which means no tag-filtering will occur.
-
-        """
-        filter_tags = filter_tags or []
-        project_name = project_card.project.lower()
-        filter_tags = list(map(str.lower, filter_tags))
-
-        if project_name in self.projects:
-            msg = f"Names not unique from existing scenario projects: {project_card.project}"
-            raise ProjectCardError(msg)
-
-        if filter_tags and set(project_card.tags).isdisjoint(set(filter_tags)):
-            WranglerLogger.debug(
-                f"Skipping {project_name} - no overlapping tags with {filter_tags}."
-            )
-            return
-
-        if validate:
-            project_card.validate()
-
-        WranglerLogger.info(f"Adding {project_name} to scenario.")
-        self.project_cards[project_name] = project_card
-        self._planned_projects.append(project_name)
-        self._queued_projects = None
-        self._add_dependencies(project_name, project_card.dependencies)
-
-    def add_project_cards(
-        self,
-        project_card_list: list[ProjectCard],
-        validate: bool = True,
-        filter_tags: Optional[list[str]] = None,
-    ) -> None:
-        """Adds a list of ProjectCard instances to the Scenario.
-
-        Checks that a project of same name is not already in scenario.
-        If selected, will validate ProjectCard before adding.
-        If provided, will only add ProjectCard if it matches at least one filter_tags.
-
-        Args:
-            project_card_list: List of ProjectCard instances to add to
-                scenario.
-            validate (bool, optional): If True, will require each ProjectCard is validated before
-                being added to scenario. Defaults to True.
-            filter_tags: If used, will filter ProjectCard instances
-                and only add those whose tags match one or more of these filter_tags.
-                Defaults to [] - which means no tag-filtering will occur.
-        """
-        filter_tags = filter_tags or []
-        for p in project_card_list:
-            self._add_project(p, validate=validate, filter_tags=filter_tags)
-
-    def _check_projects_requirements_satisfied(self, project_list: list[str]):
-        """Checks all requirements are satisified to apply this specific set of projects.
-
-        Including:
-        1. has an associaed project card
-        2. is in scenario's planned projects
-        3. pre-requisites satisfied
-        4. co-requisies satisfied by applied or co-applied projects
-        5. no conflicing applied or co-applied projects
-
-        Args:
-            project_list: list of projects to check requirements for.
-        """
-        self._check_projects_planned(project_list)
-        self._check_projects_have_project_cards(project_list)
-        self._check_projects_prerequisites(project_list)
-        self._check_projects_corequisites(project_list)
-        self._check_projects_conflicts(project_list)
-
-    def _check_projects_planned(self, project_names: list[str]) -> None:
-        """Checks that a list of projects are in the scenario's planned projects."""
-        _missing_ps = [p for p in project_names if p not in self._planned_projects]
-        if _missing_ps:
-            msg = f"Projects are not in planned projects: \n {_missing_ps}. \
-                Add them by using add_project_cards()."
-            WranglerLogger.debug(msg)
-            raise ValueError(msg)
-
-    def _check_projects_have_project_cards(self, project_list: list[str]) -> bool:
-        """Checks that a list of projects has an associated project card in the scenario."""
-        _missing = [p for p in project_list if p not in self.project_cards]
-        if _missing:
-            WranglerLogger.error(
-                f"Projects referenced which are missing project cards: {_missing}"
-            )
-            return False
-        return True
-
-    def _check_projects_prerequisites(self, project_names: list[str]) -> None:
-        """Check a list of projects' pre-requisites have been or will be applied to scenario."""
-        if set(project_names).isdisjoint(set(self.prerequisites.keys())):
-            return
-        _prereqs = []
-        for p in project_names:
-            _prereqs += self.prerequisites.get(p, [])
-        _projects_applied = self.applied_projects + project_names
-        _missing = list(set(_prereqs) - set(_projects_applied))
-        if _missing:
-            WranglerLogger.debug(
-                f"project_names: {project_names}\nprojects_have_or_will_be_applied: \
-                    {_projects_applied}\nmissing: {_missing}"
-            )
-            msg = f"Missing {len(_missing)} pre-requisites."
-            raise ScenarioPrerequisiteError(msg)
-
-    def _check_projects_corequisites(self, project_names: list[str]) -> None:
-        """Check a list of projects' co-requisites have been or will be applied to scenario."""
-        if set(project_names).isdisjoint(set(self.corequisites.keys())):
-            return
-        _coreqs = []
-        for p in project_names:
-            _coreqs += self.corequisites.get(p, [])
-        _projects_applied = self.applied_projects + project_names
-        _missing = list(set(_coreqs) - set(_projects_applied))
-        if _missing:
-            WranglerLogger.debug(
-                f"project_names: {project_names}\nprojects_have_or_will_be_applied: \
-                    {_projects_applied}\nmissing: {_missing}"
-            )
-            msg = f"Missing {len(_missing)} corequisites."
-            raise ScenarioCorequisiteError(msg)
-
-    def _check_projects_conflicts(self, project_names: list[str]) -> None:
-        """Checks that list of projects' conflicts have not been or will be applied to scenario."""
-        # WranglerLogger.debug("Checking Conflicts...")
-        projects_to_check = project_names + self.applied_projects
-        # WranglerLogger.debug(f"\nprojects_to_check:{projects_to_check}\nprojects_with_conflicts:{set(self.conflicts.keys())}")
-        if set(projects_to_check).isdisjoint(set(self.conflicts.keys())):
-            # WranglerLogger.debug("Projects have no conflicts to check")
-            return
-        _conflicts = []
-        for p in project_names:
-            _conflicts += self.conflicts.get(p, [])
-        _conflict_problems = [p for p in _conflicts if p in projects_to_check]
-        if _conflict_problems:
-            WranglerLogger.warning(f"Conflict Problems: \n{_conflict_problems}")
-            _conf_dict = {
-                k: v
-                for k, v in self.conflicts.items()
-                if k in projects_to_check and not set(v).isdisjoint(set(_conflict_problems))
-            }
-            WranglerLogger.debug(f"Problematic Conflicts: \n{_conf_dict}")
-            msg = f"Found {len(_conflict_problems)} conflicts: {_conflict_problems}"
-            raise ScenarioConflictError(msg)
-
-    def order_projects(self, project_list: list[str]) -> deque:
-        """Orders a list of projects based on moving up pre-requisites into a deque.
-
-        Args:
-            project_list: list of projects to order
-
-        Returns: deque for applying projects.
-        """
-        project_list = [p.lower() for p in project_list]
-        assert self._check_projects_have_project_cards(project_list)
-
-        # build prereq (adjacency) list for topological sort
-        adjacency_list: dict[str, list] = defaultdict(list)
-        visited_list: dict[str, bool] = defaultdict(bool)
-
-        for project in project_list:
-            visited_list[project] = False
-            if not self.prerequisites.get(project):
-                continue
-            for prereq in self.prerequisites[project]:
-                # this will always be true, else would have been flagged in missing \
-                # prerequsite check, but just in case
-                if prereq.lower() in project_list:
-                    if adjacency_list.get(prereq.lower()):
-                        adjacency_list[prereq.lower()].append(project)
-                    else:
-                        adjacency_list[prereq.lower()] = [project]
-
-        # sorted_project_names is topological sorted project card names (based on prerequsiite)
-        _ordered_projects = topological_sort(
-            adjacency_list=adjacency_list, visited_list=visited_list
-        )
-
-        if set(_ordered_projects) != set(project_list):
-            _missing = list(set(project_list) - set(_ordered_projects))
-            msg = f"Project sort resulted in missing projects: {_missing}"
-            raise ValueError(msg)
-
-        project_deque = deque(_ordered_projects)
-
-        WranglerLogger.debug(f"Ordered Projects: \n{project_deque}")
-
-        return project_deque
-
-    def apply_all_projects(self):
-        """Applies all planned projects in the queue."""
-        # Call this to make sure projects are appropriately queued in hidden variable.
-        self.queued_projects  # noqa: B018
-
-        # Use hidden variable.
-        while self._queued_projects:
-            self._apply_project(self._queued_projects.popleft())
-
-        # set this so it will trigger re-queuing any more projects.
-        self._queued_projects = None
-
-    def _apply_change(self, change: Union[ProjectCard, SubProject]) -> None:
-        """Applies a specific change specified in a project card.
-
-        Change type must be in at least one of:
-        - ROADWAY_CARD_TYPES
-        - TRANSIT_CARD_TYPES
-
-        Args:
-            change: a project card or subproject card
-        """
-        if change.change_type in ROADWAY_CARD_TYPES:
-            if not self.road_net:
-                msg = "Missing Roadway Network"
-                raise ValueError(msg)
-            if change.change_type in SECONDARY_TRANSIT_CARD_TYPES and self.transit_net:
-                self.road_net.apply(change, transit_net=self.transit_net)
-            else:
-                self.road_net.apply(change)
-        if change.change_type in TRANSIT_CARD_TYPES:
-            if not self.transit_net:
-                msg = "Missing Transit Network"
-                raise ValueError(msg)
-            self.transit_net.apply(change)
-
-        if change.change_type not in ROADWAY_CARD_TYPES + TRANSIT_CARD_TYPES:
-            msg = f"Project {change.project}: Don't understand project cat: {change.change_type}"
-            raise ProjectCardError(msg)
-
-    def _apply_project(self, project_name: str) -> None:
-        """Applies project card to scenario.
-
-        If a list of changes is specified in referenced project card, iterates through each change.
-
-        Args:
-            project_name (str): name of project to be applied.
-        """
-        project_name = project_name.lower()
-
-        WranglerLogger.info(f"Applying {project_name} from file:\
-                            {self.project_cards[project_name].file}")
-
-        p = self.project_cards[project_name]
-        WranglerLogger.debug(f"types: {p.change_types}")
-        WranglerLogger.debug(f"type: {p.change_type}")
-        if p._sub_projects:
-            for sp in p._sub_projects:
-                WranglerLogger.debug(f"- applying subproject: {sp.change_type}")
-                self._apply_change(sp)
-
-        else:
-            self._apply_change(p)
-
-        self._planned_projects.remove(project_name)
-        self.applied_projects.append(project_name)
-
-    def apply_projects(self, project_list: list[str]):
-        """Applies a specific list of projects from the planned project queue.
-
-        Will order the list of projects based on pre-requisites.
-
-        NOTE: does not check co-requisites b/c that isn't possible when applying a single project.
-
-        Args:
-            project_list: List of projects to be applied. All need to be in the planned project
-                queue.
-        """
-        project_list = [p.lower() for p in project_list]
-
-        self._check_projects_requirements_satisfied(project_list)
-        ordered_project_queue = self.order_projects(project_list)
-
-        while ordered_project_queue:
-            self._apply_project(ordered_project_queue.popleft())
-
-        # Set so that when called again it will retrigger queueing from planned projects.
-        self._ordered_projects = None
-
-    def write(
-        self,
-        path: Path,
-        name: str,
-        overwrite: bool = True,
-        roadway_write: bool = True,
-        transit_write: bool = True,
-        projects_write: bool = True,
-        roadway_convert_complex_link_properties_to_single_field: bool = False,
-        roadway_out_dir: Optional[Path] = None,
-        roadway_prefix: Optional[str] = None,
-        roadway_file_format: RoadwayFileTypes = "parquet",
-        roadway_true_shape: bool = False,
-        transit_out_dir: Optional[Path] = None,
-        transit_prefix: Optional[str] = None,
-        transit_file_format: TransitFileTypes = "txt",
-        projects_out_dir: Optional[Path] = None,
-    ) -> Path:
-        """Writes scenario networks and summary to disk and returns path to scenario file.
-
-        Args:
-            path: Path to write scenario networks and scenario summary to.
-            name: Name to use.
-            overwrite: If True, will overwrite the files if they already exist.
-            roadway_write: If True, will write out the roadway network.
-            transit_write: If True, will write out the transit network.
-            projects_write: If True, will write out the project cards.
-            roadway_convert_complex_link_properties_to_single_field: If True, will convert complex
-                link properties to a single field.
-            roadway_out_dir: Path to write the roadway network files to.
-            roadway_prefix: Prefix to add to the file name.
-            roadway_file_format: File format to write the roadway network to
-            roadway_true_shape: If True, will write the true shape of the roadway network
-            transit_out_dir: Path to write the transit network files to.
-            transit_prefix: Prefix to add to the file name.
-            transit_file_format: File format to write the transit network to
-            projects_out_dir: Path to write the project cards to.
-        """
-        path = Path(path)
-        path.mkdir(parents=True, exist_ok=True)
-
-        if self.road_net and roadway_write:
-            if roadway_out_dir is None:
-                roadway_out_dir = path / "roadway"
-            roadway_out_dir.mkdir(parents=True, exist_ok=True)
-
-            write_roadway(
-                net=self.road_net,
-                out_dir=roadway_out_dir,
-                prefix=roadway_prefix or name,
-                convert_complex_link_properties_to_single_field=roadway_convert_complex_link_properties_to_single_field,
-                file_format=roadway_file_format,
-                true_shape=roadway_true_shape,
-                overwrite=overwrite,
-            )
-        if self.transit_net and transit_write:
-            if transit_out_dir is None:
-                transit_out_dir = path / "transit"
-            transit_out_dir.mkdir(parents=True, exist_ok=True)
-            write_transit(
-                self.transit_net,
-                out_dir=transit_out_dir,
-                prefix=transit_prefix or name,
-                file_format=transit_file_format,
-                overwrite=overwrite,
-            )
-        if projects_write:
-            if projects_out_dir is None:
-                projects_out_dir = path / "projects"
-            write_applied_projects(
-                self,
-                out_dir=projects_out_dir,
-                overwrite=overwrite,
-            )
-
-        scenario_data = self.summary
-        if transit_write:
-            scenario_data["transit"] = {
-                "dir": str(transit_out_dir),
-                "file_format": transit_file_format,
-            }
-        if roadway_write:
-            scenario_data["roadway"] = {
-                "dir": str(roadway_out_dir),
-                "file_format": roadway_file_format,
-            }
-        if projects_write:
-            scenario_data["project_cards"] = {"dir": str(projects_out_dir)}
-        scenario_file_path = Path(path) / f"{name}_scenario.yml"
-        with scenario_file_path.open("w") as f:
-            yaml.dump(scenario_data, f, default_flow_style=False, allow_unicode=True)
-        return scenario_file_path
-
-    @property
-    def summary(self) -> dict:
-        """A high level summary of the created scenario and public attributes."""
-        skip = ["road_net", "base_scenario", "transit_net", "project_cards", "config"]
-        summary_dict = {
-            k: v for k, v in self.__dict__.items() if not k.startswith("_") and k not in skip
-        }
-        summary_dict["config"] = self.config.to_dict()
-
-        """
-        # Handle nested dictionary for "base_scenario"
-        skip_base = ["project_cards"]
-        if "base_scenario" in self.__dict__:
-            base_summary_dict = {
-                k: v
-                for k, v in self.base_scenario.items()
-                if not k.startswith("_") and k not in skip_base
-            }
-            summary_dict["base_scenario"] = base_summary_dict
-        """
-
-        return summary_dict
-
    -
    - - - -
    - - - - - - - -
    - - - -

    - projects - - - property - - -

    - - -
    - -

    Returns a list of all projects in the scenario: applied and planned.

    -
    - -
    - -
    - - - -

    - queued_projects - - - property - - -

    - - -
    - -

    Returns a list version of _queued_projects queue.

    -

    Queued projects are thos that have been planned, have all pre-requisites satisfied, and -have been ordered based on pre-requisites.

    -

    If no queued projects, will dynamically generate from planned projects based on -pre-requisites and return the queue.

    -
    - -
    - -
    - - - -

    - summary: dict - - - property - - -

    - - -
    - -

    A high level summary of the created scenario and public attributes.

    -
    - -
    - - - -
    - - -

    - __init__(base_scenario, project_card_list=None, config=None, name='') - -

    - - -
    - -

    Constructor.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    base_scenario - Union[Scenario, dict] - -
    -

    A base scenario object to base this isntance off of, or a dict which -describes the scenario attributes including applied projects and respective -conflicts. {"applied_projects": [],"conflicts":{...}}

    -
    -     		- required -
    project_card_list - Optional[list[ProjectCard]] - -
    -

    Optional list of ProjectCard instances to add to planned projects. -Defaults to None.

    -
    -     		- None -
    config - Optional[Union[WranglerConfig, dict, Path, list[Path]]] - -
    -

    WranglerConfig instance or a dictionary of configuration settings or a path to -one or more configuration files. Configurations that are not explicity set will -default to the values in the default configuration in -/configs/wrangler/default.yml.

    -
    -     		- None -
    name - str - -
    -

    Optional name for the scenario.

    -
    -     		- '' -
    - -
    - Source code in network_wrangler/scenario.py - 
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    def __init__(
-    self,
-    base_scenario: Union[Scenario, dict],
-    project_card_list: Optional[list[ProjectCard]] = None,
-    config: Optional[Union[WranglerConfig, dict, Path, list[Path]]] = None,
-    name: str = "",
-):
-    """Constructor.
-
-    Args:
-        base_scenario: A base scenario object to base this isntance off of, or a dict which
-            describes the scenario attributes including applied projects and respective
-            conflicts. `{"applied_projects": [],"conflicts":{...}}`
-        project_card_list: Optional list of ProjectCard instances to add to planned projects.
-            Defaults to None.
-        config: WranglerConfig instance or a dictionary of configuration settings or a path to
-            one or more configuration files. Configurations that are not explicity set will
-            default to the values in the default configuration in
-            `/configs/wrangler/default.yml`.
-        name: Optional name for the scenario.
-    """
-    WranglerLogger.info("Creating Scenario")
-    self.config = load_wrangler_config(config)
-
-    if project_card_list is None:
-        project_card_list = []
-
-    if isinstance(base_scenario, Scenario):
-        base_scenario = base_scenario.__dict__
-
-    self.base_scenario: dict = extract_base_scenario_metadata(base_scenario)
-
-    if not set(BASE_SCENARIO_SUGGESTED_PROPS) <= set(base_scenario.keys()):
-        WranglerLogger.warning(
-            f"Base_scenario doesn't contain {BASE_SCENARIO_SUGGESTED_PROPS}"
-        )
-    self.name: str = name
-    # if the base scenario had roadway or transit networks, use them as the basis.
-    self.road_net: Optional[RoadwayNetwork] = copy.deepcopy(
-        base_scenario.pop("road_net", None)
-    )
-
-    self.transit_net: Optional[TransitNetwork] = copy.deepcopy(
-        base_scenario.pop("transit_net", None)
-    )
-    if self.road_net and self.transit_net:
-        self.transit_net.road_net = self.road_net
-
-    # Set configs for networks to be the same as scenario.
-    if isinstance(self.road_net, RoadwayNetwork):
-        self.road_net.config = self.config
-    if isinstance(self.transit_net, TransitNetwork):
-        self.transit_net.config = self.config
-
-    self.project_cards: dict[str, ProjectCard] = {}
-    self._planned_projects: list[str] = []
-    self._queued_projects = None
-    self.applied_projects: list[str] = base_scenario.pop("applied_projects", [])
-
-    self.prerequisites: dict[str, list[str]] = base_scenario.pop("prerequisites", {})
-    self.corequisites: dict[str, list[str]] = base_scenario.pop("corequisites", {})
-    self.conflicts: dict[str, list[str]] = base_scenario.pop("conflicts", {})
-
-    for p in project_card_list:
-        self._add_project(p)
-
    -
    -
    - -
    - -
    - - -

    - __str__() - -

    - - -
    - -

    String representation of the Scenario object.

    - -
    - Source code in network_wrangler/scenario.py - 
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    def __str__(self):
-    """String representation of the Scenario object."""
-    s = [f"{key}: {value}" for key, value in self.__dict__.items()]
-    return "\n".join(s)
-
    -
    -
    - -
    - -
    - - -

    - add_project_cards(project_card_list, validate=True, filter_tags=None) - -

    - - -
    - -

    Adds a list of ProjectCard instances to the Scenario.

    -

    Checks that a project of same name is not already in scenario. -If selected, will validate ProjectCard before adding. -If provided, will only add ProjectCard if it matches at least one filter_tags.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    project_card_list - list[ProjectCard] - -
    -

    List of ProjectCard instances to add to -scenario.

    -
    -     		- required -
    validate - bool - -
    -

    If True, will require each ProjectCard is validated before -being added to scenario. Defaults to True.

    -
    -     		- True -
    filter_tags - Optional[list[str]] - -
    -

    If used, will filter ProjectCard instances -and only add those whose tags match one or more of these filter_tags. -Defaults to [] - which means no tag-filtering will occur.

    -
    -     		- None -
    - -
    - Source code in network_wrangler/scenario.py - 
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    def add_project_cards(
-    self,
-    project_card_list: list[ProjectCard],
-    validate: bool = True,
-    filter_tags: Optional[list[str]] = None,
-) -> None:
-    """Adds a list of ProjectCard instances to the Scenario.
-
-    Checks that a project of same name is not already in scenario.
-    If selected, will validate ProjectCard before adding.
-    If provided, will only add ProjectCard if it matches at least one filter_tags.
-
-    Args:
-        project_card_list: List of ProjectCard instances to add to
-            scenario.
-        validate (bool, optional): If True, will require each ProjectCard is validated before
-            being added to scenario. Defaults to True.
-        filter_tags: If used, will filter ProjectCard instances
-            and only add those whose tags match one or more of these filter_tags.
-            Defaults to [] - which means no tag-filtering will occur.
-    """
-    filter_tags = filter_tags or []
-    for p in project_card_list:
-        self._add_project(p, validate=validate, filter_tags=filter_tags)
-
    -
    -
    - -
    - -
    - - -

    - apply_all_projects() - -

    - - -
    - -

    Applies all planned projects in the queue.

    - -
    - Source code in network_wrangler/scenario.py - 
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    def apply_all_projects(self):
-    """Applies all planned projects in the queue."""
-    # Call this to make sure projects are appropriately queued in hidden variable.
-    self.queued_projects  # noqa: B018
-
-    # Use hidden variable.
-    while self._queued_projects:
-        self._apply_project(self._queued_projects.popleft())
-
-    # set this so it will trigger re-queuing any more projects.
-    self._queued_projects = None
-
    -
    -
    - -
    - -
    - - -

    - apply_projects(project_list) - -

    - - -
    - -

    Applies a specific list of projects from the planned project queue.

    -

    Will order the list of projects based on pre-requisites.

    -

    NOTE: does not check co-requisites b/c that isn’t possible when applying a single project.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    project_list - list[str] - -
    -

    List of projects to be applied. All need to be in the planned project -queue.

    -
    -     		- required -
    - -
    - Source code in network_wrangler/scenario.py - 
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    def apply_projects(self, project_list: list[str]):
-    """Applies a specific list of projects from the planned project queue.
-
-    Will order the list of projects based on pre-requisites.
-
-    NOTE: does not check co-requisites b/c that isn't possible when applying a single project.
-
-    Args:
-        project_list: List of projects to be applied. All need to be in the planned project
-            queue.
-    """
-    project_list = [p.lower() for p in project_list]
-
-    self._check_projects_requirements_satisfied(project_list)
-    ordered_project_queue = self.order_projects(project_list)
-
-    while ordered_project_queue:
-        self._apply_project(ordered_project_queue.popleft())
-
-    # Set so that when called again it will retrigger queueing from planned projects.
-    self._ordered_projects = None
-
    -
    -
    - -
    - -
    - - -

    - order_projects(project_list) - -

    - - -
    - -

    Orders a list of projects based on moving up pre-requisites into a deque.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    project_list - list[str] - -
    -

    list of projects to order

    -
    -     		- required -
    - - -
    - Source code in network_wrangler/scenario.py - 
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    def order_projects(self, project_list: list[str]) -> deque:
-    """Orders a list of projects based on moving up pre-requisites into a deque.
-
-    Args:
-        project_list: list of projects to order
-
-    Returns: deque for applying projects.
-    """
-    project_list = [p.lower() for p in project_list]
-    assert self._check_projects_have_project_cards(project_list)
-
-    # build prereq (adjacency) list for topological sort
-    adjacency_list: dict[str, list] = defaultdict(list)
-    visited_list: dict[str, bool] = defaultdict(bool)
-
-    for project in project_list:
-        visited_list[project] = False
-        if not self.prerequisites.get(project):
-            continue
-        for prereq in self.prerequisites[project]:
-            # this will always be true, else would have been flagged in missing \
-            # prerequsite check, but just in case
-            if prereq.lower() in project_list:
-                if adjacency_list.get(prereq.lower()):
-                    adjacency_list[prereq.lower()].append(project)
-                else:
-                    adjacency_list[prereq.lower()] = [project]
-
-    # sorted_project_names is topological sorted project card names (based on prerequsiite)
-    _ordered_projects = topological_sort(
-        adjacency_list=adjacency_list, visited_list=visited_list
-    )
-
-    if set(_ordered_projects) != set(project_list):
-        _missing = list(set(project_list) - set(_ordered_projects))
-        msg = f"Project sort resulted in missing projects: {_missing}"
-        raise ValueError(msg)
-
-    project_deque = deque(_ordered_projects)
-
-    WranglerLogger.debug(f"Ordered Projects: \n{project_deque}")
-
-    return project_deque
-
    -
    -
    - -
    - -
    - - -

    - write(path, name, overwrite=True, roadway_write=True, transit_write=True, projects_write=True, roadway_convert_complex_link_properties_to_single_field=False, roadway_out_dir=None, roadway_prefix=None, roadway_file_format='parquet', roadway_true_shape=False, transit_out_dir=None, transit_prefix=None, transit_file_format='txt', projects_out_dir=None) - -

    - - -
    - -

    Writes scenario networks and summary to disk and returns path to scenario file.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    path - Path - -
    -

    Path to write scenario networks and scenario summary to.

    -
    -     		- required -
    name - str - -
    -

    Name to use.

    -
    -     		- required -
    overwrite - bool - -
    -

    If True, will overwrite the files if they already exist.

    -
    -     		- True -
    roadway_write - bool - -
    -

    If True, will write out the roadway network.

    -
    -     		- True -
    transit_write - bool - -
    -

    If True, will write out the transit network.

    -
    -     		- True -
    projects_write - bool - -
    -

    If True, will write out the project cards.

    -
    -     		- True -
    roadway_convert_complex_link_properties_to_single_field - bool - -
    -

    If True, will convert complex -link properties to a single field.

    -
    -     		- False -
    roadway_out_dir - Optional[Path] - -
    -

    Path to write the roadway network files to.

    -
    -     		- None -
    roadway_prefix - Optional[str] - -
    -

    Prefix to add to the file name.

    -
    -     		- None -
    roadway_file_format - RoadwayFileTypes - -
    -

    File format to write the roadway network to

    -
    -     		- 'parquet' -
    roadway_true_shape - bool - -
    -

    If True, will write the true shape of the roadway network

    -
    -     		- False -
    transit_out_dir - Optional[Path] - -
    -

    Path to write the transit network files to.

    -
    -     		- None -
    transit_prefix - Optional[str] - -
    -

    Prefix to add to the file name.

    -
    -     		- None -
    transit_file_format - TransitFileTypes - -
    -

    File format to write the transit network to

    -
    -     		- 'txt' -
    projects_out_dir - Optional[Path] - -
    -

    Path to write the project cards to.

    -
    -     		- None -
    - -
    - Source code in network_wrangler/scenario.py - 
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    def write(
-    self,
-    path: Path,
-    name: str,
-    overwrite: bool = True,
-    roadway_write: bool = True,
-    transit_write: bool = True,
-    projects_write: bool = True,
-    roadway_convert_complex_link_properties_to_single_field: bool = False,
-    roadway_out_dir: Optional[Path] = None,
-    roadway_prefix: Optional[str] = None,
-    roadway_file_format: RoadwayFileTypes = "parquet",
-    roadway_true_shape: bool = False,
-    transit_out_dir: Optional[Path] = None,
-    transit_prefix: Optional[str] = None,
-    transit_file_format: TransitFileTypes = "txt",
-    projects_out_dir: Optional[Path] = None,
-) -> Path:
-    """Writes scenario networks and summary to disk and returns path to scenario file.
-
-    Args:
-        path: Path to write scenario networks and scenario summary to.
-        name: Name to use.
-        overwrite: If True, will overwrite the files if they already exist.
-        roadway_write: If True, will write out the roadway network.
-        transit_write: If True, will write out the transit network.
-        projects_write: If True, will write out the project cards.
-        roadway_convert_complex_link_properties_to_single_field: If True, will convert complex
-            link properties to a single field.
-        roadway_out_dir: Path to write the roadway network files to.
-        roadway_prefix: Prefix to add to the file name.
-        roadway_file_format: File format to write the roadway network to
-        roadway_true_shape: If True, will write the true shape of the roadway network
-        transit_out_dir: Path to write the transit network files to.
-        transit_prefix: Prefix to add to the file name.
-        transit_file_format: File format to write the transit network to
-        projects_out_dir: Path to write the project cards to.
-    """
-    path = Path(path)
-    path.mkdir(parents=True, exist_ok=True)
-
-    if self.road_net and roadway_write:
-        if roadway_out_dir is None:
-            roadway_out_dir = path / "roadway"
-        roadway_out_dir.mkdir(parents=True, exist_ok=True)
-
-        write_roadway(
-            net=self.road_net,
-            out_dir=roadway_out_dir,
-            prefix=roadway_prefix or name,
-            convert_complex_link_properties_to_single_field=roadway_convert_complex_link_properties_to_single_field,
-            file_format=roadway_file_format,
-            true_shape=roadway_true_shape,
-            overwrite=overwrite,
-        )
-    if self.transit_net and transit_write:
-        if transit_out_dir is None:
-            transit_out_dir = path / "transit"
-        transit_out_dir.mkdir(parents=True, exist_ok=True)
-        write_transit(
-            self.transit_net,
-            out_dir=transit_out_dir,
-            prefix=transit_prefix or name,
-            file_format=transit_file_format,
-            overwrite=overwrite,
-        )
-    if projects_write:
-        if projects_out_dir is None:
-            projects_out_dir = path / "projects"
-        write_applied_projects(
-            self,
-            out_dir=projects_out_dir,
-            overwrite=overwrite,
-        )
-
-    scenario_data = self.summary
-    if transit_write:
-        scenario_data["transit"] = {
-            "dir": str(transit_out_dir),
-            "file_format": transit_file_format,
-        }
-    if roadway_write:
-        scenario_data["roadway"] = {
-            "dir": str(roadway_out_dir),
-            "file_format": roadway_file_format,
-        }
-    if projects_write:
-        scenario_data["project_cards"] = {"dir": str(projects_out_dir)}
-    scenario_file_path = Path(path) / f"{name}_scenario.yml"
-    with scenario_file_path.open("w") as f:
-        yaml.dump(scenario_data, f, default_flow_style=False, allow_unicode=True)
-    return scenario_file_path
-
    -
    -
    - -
    - - - -
    - - - - - - -
    - - -

    - build_scenario_from_config(scenario_config) - -

    - - -
    - -

    Builds a scenario from a dictionary configuration.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    scenario_config - Union[Path, list[Path], ScenarioConfig, dict] - -
    -

    Path to a configuration file, list of paths, or a dictionary of -configuration.

    -
    -     		- required -
    - -
    - Source code in network_wrangler/scenario.py - 
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    def build_scenario_from_config(
-    scenario_config: Union[Path, list[Path], ScenarioConfig, dict],
-) -> Scenario:
-    """Builds a scenario from a dictionary configuration.
-
-    Args:
-        scenario_config: Path to a configuration file, list of paths, or a dictionary of
-            configuration.
-    """
-    WranglerLogger.info(f"Building Scenario from Configuration: {scenario_config}")
-    scenario_config = load_scenario_config(scenario_config)
-    WranglerLogger.debug(f"{pprint.pformat(scenario_config)}")
-
-    base_scenario = create_base_scenario(
-        **scenario_config.base_scenario.to_dict(), config=scenario_config.wrangler_config
-    )
-
-    my_scenario = create_scenario(
-        base_scenario=base_scenario,
-        config=scenario_config.wrangler_config,
-        **scenario_config.projects.to_dict(),
-    )
-
-    my_scenario.apply_all_projects()
-
-    write_args = _scenario_output_config_to_scenario_write(scenario_config.output_scenario)
-    my_scenario.write(**write_args, name=scenario_config.name)
-    return my_scenario
-
    -
    -
    - -
    - -
    - - -

    - create_base_scenario(roadway=None, transit=None, applied_projects=None, conflicts=None, config=DefaultConfig) - -

    - - -
    - -

    Creates a base scenario dictionary from roadway and transit network files.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    roadway - Optional[dict] - -
    -

    kwargs for load_roadway_from_dir

    -
    -     		- None -
    transit - Optional[dict] - -
    -

    kwargs for load_transit from dir

    -
    -     		- None -
    applied_projects - Optional[list] - -
    -

    list of projects that have been applied to the base scenario.

    -
    -     		- None -
    conflicts - Optional[dict] - -
    -

    dictionary of conflicts that have been identified in the base scenario. -Takes the format of {"projectA": ["projectB", "projectC"]} showing that projectA, -which has been applied, conflicts with projectB and projectC and so they shouldn’t be -applied in the future.

    -
    -     		- None -
    config - WranglerConfig - -
    -

    WranglerConfig instance.

    -
    -     		- DefaultConfig -
    - -
    - Source code in network_wrangler/scenario.py - 
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    def create_base_scenario(
-    roadway: Optional[dict] = None,
-    transit: Optional[dict] = None,
-    applied_projects: Optional[list] = None,
-    conflicts: Optional[dict] = None,
-    config: WranglerConfig = DefaultConfig,
-) -> dict:
-    """Creates a base scenario dictionary from roadway and transit network files.
-
-    Args:
-        roadway: kwargs for load_roadway_from_dir
-        transit: kwargs for load_transit from dir
-        applied_projects: list of projects that have been applied to the base scenario.
-        conflicts: dictionary of conflicts that have been identified in the base scenario.
-            Takes the format of `{"projectA": ["projectB", "projectC"]}` showing that projectA,
-            which has been applied, conflicts with projectB and projectC and so they shouldn't be
-            applied in the future.
-        config: WranglerConfig instance.
-    """
-    applied_projects = applied_projects or []
-    conflicts = conflicts or {}
-    if roadway:
-        road_net = load_roadway_from_dir(**roadway, config=config)
-    else:
-        road_net = None
-        WranglerLogger.info(
-            "No roadway directory specified, base scenario will have empty roadway network."
-        )
-
-    if transit:
-        transit_net = load_transit(**transit, config=config)
-        if roadway:
-            transit_net.road_net = road_net
-    else:
-        transit_net = None
-        WranglerLogger.info(
-            "No transit directory specified, base scenario will have empty transit network."
-        )
-
-    base_scenario = {
-        "road_net": road_net,
-        "transit_net": transit_net,
-        "applied_projects": applied_projects,
-        "conflicts": conflicts,
-    }
-
-    return base_scenario
-
    -
    -
    - -
    - -
    - - -

    - create_scenario(base_scenario=None, name=datetime.now().strftime('%Y%m%d%H%M%S'), project_card_list=None, project_card_filepath=None, filter_tags=None, config=None) - -

    - - -
    - -

    Creates scenario from a base scenario and adds project cards.

    -

    Project cards can be added using any/all of the following methods: -1. List of ProjectCard instances -2. List of ProjectCard files -3. Directory and optional glob search to find project card files in

    -

    Checks that a project of same name is not already in scenario. -If selected, will validate ProjectCard before adding. -If provided, will only add ProjectCard if it matches at least one filter_tags.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    base_scenario - Optional[Union[Scenario, dict]] - -
    -

    base Scenario scenario instances of dictionary of attributes.

    -
    -     		- None -
    name - str - -
    -

    Optional name for the scenario. Defaults to current datetime.

    -
    -     		- strftime('%Y%m%d%H%M%S') -
    project_card_list - -
    -

    List of ProjectCard instances to create Scenario from. Defaults -to [].

    -
    -     		- None -
    project_card_filepath - Optional[Union[list[Path], Path]] - -
    -

    where the project card is. A single path, list of paths,

    -
    -     		- None -
    filter_tags - Optional[list[str]] - -
    -

    If used, will only add the project card if -its tags match one or more of these filter_tags. Defaults to [] -which means no tag-filtering will occur.

    -
    -     		- None -
    config - Optional[Union[dict, Path, list[Path], WranglerConfig]] - -
    -

    Optional wrangler configuration file or dictionary or instance. Defaults to -default config.

    -
    -     		- None -
    - -
    - Source code in network_wrangler/scenario.py - 
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    def create_scenario(
-    base_scenario: Optional[Union[Scenario, dict]] = None,
-    name: str = datetime.now().strftime("%Y%m%d%H%M%S"),
-    project_card_list=None,
-    project_card_filepath: Optional[Union[list[Path], Path]] = None,
-    filter_tags: Optional[list[str]] = None,
-    config: Optional[Union[dict, Path, list[Path], WranglerConfig]] = None,
-) -> Scenario:
-    """Creates scenario from a base scenario and adds project cards.
-
-    Project cards can be added using any/all of the following methods:
-    1. List of ProjectCard instances
-    2. List of ProjectCard files
-    3. Directory and optional glob search to find project card files in
-
-    Checks that a project of same name is not already in scenario.
-    If selected, will validate ProjectCard before adding.
-    If provided, will only add ProjectCard if it matches at least one filter_tags.
-
-    Args:
-        base_scenario: base Scenario scenario instances of dictionary of attributes.
-        name: Optional name for the scenario. Defaults to current datetime.
-        project_card_list: List of ProjectCard instances to create Scenario from. Defaults
-            to [].
-        project_card_filepath: where the project card is.  A single path, list of paths,
-        a directory, or a glob pattern. Defaults to None.
-        filter_tags: If used, will only add the project card if
-            its tags match one or more of these filter_tags. Defaults to []
-            which means no tag-filtering will occur.
-        config: Optional wrangler configuration file or dictionary or instance. Defaults to
-            default config.
-    """
-    base_scenario = base_scenario or {}
-    project_card_list = project_card_list or []
-    filter_tags = filter_tags or []
-
-    scenario = Scenario(base_scenario, config=config, name=name)
-
-    if project_card_filepath:
-        project_card_list += list(
-            read_cards(project_card_filepath, filter_tags=filter_tags).values()
-        )
-
-    if project_card_list:
-        scenario.add_project_cards(project_card_list, filter_tags=filter_tags)
-
-    return scenario
-
    -
    -
    - -
    - -
    - - -

    - extract_base_scenario_metadata(base_scenario) - -

    - - -
    - -

    Extract metadata from base scenario rather than keeping all of big files.

    -

    Useful for summarizing a scenario.

    - -
    - Source code in network_wrangler/scenario.py - 
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    def extract_base_scenario_metadata(base_scenario: dict) -> dict:
-    """Extract metadata from base scenario rather than keeping all of big files.
-
-    Useful for summarizing a scenario.
-    """
-    _skip_copy = ["road_net", "transit_net", "config"]
-    out_dict = {k: v for k, v in base_scenario.items() if k not in _skip_copy}
-    if isinstance(base_scenario.get("road_net"), RoadwayNetwork):
-        nodes_file_path = base_scenario["road_net"].nodes_df.attrs.get("source_file", None)
-        if nodes_file_path is not None:
-            out_dict["roadway"] = {
-                "dir": str(Path(nodes_file_path).parent),
-                "file_format": str(nodes_file_path.suffix).lstrip("."),
-            }
-    if isinstance(base_scenario.get("transit_net"), TransitNetwork):
-        feed_path = base_scenario["transit_net"].feed.feed_path
-        if feed_path is not None:
-            out_dict["transit"] = {"dir": str(feed_path)}
-    return out_dict
-
    -
    -
    - -
    - -
    - - -

    - load_scenario(scenario_data, name=datetime.now().strftime('%Y%m%d%H%M%S')) - -

    - - -
    - -

    Loads a scenario from a file written by Scenario.write() as the base scenario.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    scenario_data - Union[dict, Path] - -
    -

    Scenario data as a dict or path to scenario data file

    -
    -     		- required -
    name - str - -
    -

    Optional name for the scenario. Defaults to current datetime.

    -
    -     		- strftime('%Y%m%d%H%M%S') -
    - -
    - Source code in network_wrangler/scenario.py - 
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    def load_scenario(
-    scenario_data: Union[dict, Path],
-    name: str = datetime.now().strftime("%Y%m%d%H%M%S"),
-) -> Scenario:
-    """Loads a scenario from a file written by Scenario.write() as the base scenario.
-
-    Args:
-        scenario_data: Scenario data as a dict or path to scenario data file
-        name: Optional name for the scenario. Defaults to current datetime.
-    """
-    if not isinstance(scenario_data, dict):
-        WranglerLogger.debug(f"Loading Scenario from file: {scenario_data}")
-        scenario_data = load_dict(scenario_data)
-    else:
-        WranglerLogger.debug("Loading Scenario from dict.")
-
-    base_scenario_data = {
-        "roadway": scenario_data.get("roadway"),
-        "transit": scenario_data.get("transit"),
-        "applied_projects": scenario_data.get("applied_projects", []),
-        "conflicts": scenario_data.get("conflicts", {}),
-    }
-    base_scenario = _load_base_scenario_from_config(
-        base_scenario_data, config=scenario_data["config"]
-    )
-    my_scenario = create_scenario(
-        base_scenario=base_scenario, name=name, config=scenario_data["config"]
-    )
-    return my_scenario
-
    -
    -
    - -
    - -
    - - -

    - write_applied_projects(scenario, out_dir, overwrite=True) - -

    - - -
    - -

    Summarizes all projects in a scenario to folder.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    scenario - Scenario - -
    -

    Scenario instance to summarize.

    -
    -     		- required -
    out_dir - Path - -
    -

    Path to write the project cards.

    -
    -     		- required -
    overwrite - bool - -
    -

    If True, will overwrite the files if they already exist.

    -
    -     		- True -
    - -
    - Source code in network_wrangler/scenario.py - 
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    def write_applied_projects(scenario: Scenario, out_dir: Path, overwrite: bool = True) -> None:
-    """Summarizes all projects in a scenario to folder.
-
-    Args:
-        scenario: Scenario instance to summarize.
-        out_dir: Path to write the project cards.
-        overwrite: If True, will overwrite the files if they already exist.
-    """
-    outdir = Path(out_dir)
-    prep_dir(out_dir, overwrite=overwrite)
-
-    for p in scenario.applied_projects:
-        if p in scenario.project_cards:
-            card = scenario.project_cards[p]
-        elif p in scenario.base_scenario["project_cards"]:
-            card = scenario.base_scenario["project_cards"][p]
-        else:
-            continue
-        filename = Path(card.__dict__.get("file", f"{p}.yml")).name
-        outpath = outdir / filename
-        write_card(card, outpath)
-
    -
    -
    - -
    - - - - - - - - - -
    - - - - -
    - -

    Roadway Network class and functions for Network Wrangler.

    -

    Used to represent a roadway network and perform operations on it.

    -

    Usage:

    -
    from network_wrangler import load_roadway_from_dir, write_roadway
-
-net = load_roadway_from_dir("my_dir")
-net.get_selection({"links": [{"name": ["I 35E"]}]})
-net.apply("my_project_card.yml")
-
-write_roadway(net, "my_out_prefix", "my_dir", file_format="parquet")
-
    - - - -
    - - - - - - - - -
    - - - -

    - RoadwayNetwork - - -

    - - -
    -

    - Bases: BaseModel

    - - -

    Representation of a Roadway Network.

    -

    Typical usage example:

    -
    net = load_roadway(
-    links_file=MY_LINK_FILE,
-    nodes_file=MY_NODE_FILE,
-    shapes_file=MY_SHAPE_FILE,
-)
-my_selection = {
-    "link": [{"name": ["I 35E"]}],
-    "A": {"osm_node_id": "961117623"},  # start searching for segments at A
-    "B": {"osm_node_id": "2564047368"},
-}
-net.get_selection(my_selection)
-
-my_change = [
-    {
-        'property': 'lanes',
-        'existing': 1,
-        'set': 2,
-    },
-    {
-        'property': 'drive_access',
-        'set': 0,
-    },
-]
-
-my_net.apply_roadway_feature_change(
-    my_net.get_selection(my_selection),
-    my_change
-)
-
-    net.model_net
-    net.is_network_connected(mode="drive", nodes=self.m_nodes_df, links=self.m_links_df)
-    _, disconnected_nodes = net.assess_connectivity(
-        mode="walk",
-        ignore_end_nodes=True,
-        nodes=self.m_nodes_df,
-        links=self.m_links_df
-    )
-    write_roadway(net,filename=my_out_prefix, path=my_dir, for_model = True)
-
    - - -

    Attributes:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescription
    nodes_df - RoadNodesTable - -
    -

    dataframe of of node records.

    -
    -
    links_df - RoadLinksTable - -
    -

    dataframe of link records and associated properties.

    -
    -
    shapes_df - RoadShapestable - -
    -

    data from of detailed shape records This is lazily -created iff it is called because shapes files can be expensive to read.

    -
    -
    _selections - dict - -
    -

    dictionary of stored roadway selection objects, mapped by -RoadwayLinkSelection.sel_key or RoadwayNodeSelection.sel_key in case they are - made repeatedly.

    -
    -
    network_hash - str - -
    -

    dynamic property of the hashed value of links_df and nodes_df. Used for -quickly identifying if a network has changed since various expensive operations have -taken place (i.e. generating a ModelRoadwayNetwork or a network graph)

    -
    -
    model_net - ModelRoadwayNetwork - -
    -

    referenced ModelRoadwayNetwork object which will be -lazily created if None or if the network_hash has changed.

    -
    -
    config - WranglerConfig - -
    -

    wrangler configuration object

    -
    -
    - -
    - Source code in network_wrangler/roadway/network.py - 
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    class RoadwayNetwork(BaseModel):
-    """Representation of a Roadway Network.
-
-    Typical usage example:
-
-    ```py
-    net = load_roadway(
-        links_file=MY_LINK_FILE,
-        nodes_file=MY_NODE_FILE,
-        shapes_file=MY_SHAPE_FILE,
-    )
-    my_selection = {
-        "link": [{"name": ["I 35E"]}],
-        "A": {"osm_node_id": "961117623"},  # start searching for segments at A
-        "B": {"osm_node_id": "2564047368"},
-    }
-    net.get_selection(my_selection)
-
-    my_change = [
-        {
-            'property': 'lanes',
-            'existing': 1,
-            'set': 2,
-        },
-        {
-            'property': 'drive_access',
-            'set': 0,
-        },
-    ]
-
-    my_net.apply_roadway_feature_change(
-        my_net.get_selection(my_selection),
-        my_change
-    )
-
-        net.model_net
-        net.is_network_connected(mode="drive", nodes=self.m_nodes_df, links=self.m_links_df)
-        _, disconnected_nodes = net.assess_connectivity(
-            mode="walk",
-            ignore_end_nodes=True,
-            nodes=self.m_nodes_df,
-            links=self.m_links_df
-        )
-        write_roadway(net,filename=my_out_prefix, path=my_dir, for_model = True)
-    ```
-
-    Attributes:
-        nodes_df (RoadNodesTable): dataframe of of node records.
-        links_df (RoadLinksTable): dataframe of link records and associated properties.
-        shapes_df (RoadShapestable): data from of detailed shape records  This is lazily
-            created iff it is called because shapes files can be expensive to read.
-        _selections (dict): dictionary of stored roadway selection objects, mapped by
-            `RoadwayLinkSelection.sel_key` or `RoadwayNodeSelection.sel_key` in case they are
-                made repeatedly.
-        network_hash: dynamic property of the hashed value of links_df and nodes_df. Used for
-            quickly identifying if a network has changed since various expensive operations have
-            taken place (i.e. generating a ModelRoadwayNetwork or a network graph)
-        model_net (ModelRoadwayNetwork): referenced `ModelRoadwayNetwork` object which will be
-            lazily created if None or if the `network_hash` has changed.
-        config (WranglerConfig): wrangler configuration object
-    """
-
-    nodes_df: DataFrame[RoadNodesTable]
-    links_df: DataFrame[RoadLinksTable]
-    _shapes_df: Optional[DataFrame[RoadShapesTable]] = None
-
-    _links_file: Optional[Path] = None
-    _nodes_file: Optional[Path] = None
-    _shapes_file: Optional[Path] = None
-
-    config: WranglerConfig = DefaultConfig
-
-    _model_net: Optional[ModelRoadwayNetwork] = None
-    _selections: dict[str, Selections] = {}
-    _modal_graphs: dict[str, dict] = defaultdict(lambda: {"graph": None, "hash": None})
-
-    @field_validator("config")
-    def validate_config(cls, v):
-        """Validate config."""
-        return load_wrangler_config(v)
-
-    @field_validator("nodes_df", "links_df")
-    def coerce_crs(cls, v):
-        """Coerce crs of nodes_df and links_df to LAT_LON_CRS."""
-        if v.crs != LAT_LON_CRS:
-            WranglerLogger.warning(
-                f"CRS of links_df ({v.crs}) doesn't match network crs {LAT_LON_CRS}. \
-                    Changing to network crs."
-            )
-            v.to_crs(LAT_LON_CRS)
-        return v
-
-    @property
-    def shapes_df(self) -> DataFrame[RoadShapesTable]:
-        """Load and return RoadShapesTable.
-
-        If not already loaded, will read from shapes_file and return. If shapes_file is None,
-        will return an empty dataframe with the right schema. If shapes_df is already set, will
-        return that.
-        """
-        if (self._shapes_df is None or self._shapes_df.empty) and self._shapes_file is not None:
-            self._shapes_df = read_shapes(
-                self._shapes_file,
-                filter_to_shape_ids=self.links_df.shape_id.to_list(),
-                config=self.config,
-            )
-        # if there is NONE, then at least create an empty dataframe with right schema
-        elif self._shapes_df is None:
-            self._shapes_df = empty_df_from_datamodel(RoadShapesTable)
-            self._shapes_df.set_index("shape_id_idx", inplace=True)
-
-        return self._shapes_df
-
-    @shapes_df.setter
-    def shapes_df(self, value):
-        self._shapes_df = df_to_shapes_df(value, config=self.config)
-
-    @property
-    def network_hash(self) -> str:
-        """Hash of the links and nodes dataframes."""
-        _value = str.encode(self.links_df.df_hash() + "-" + self.nodes_df.df_hash())
-
-        _hash = hashlib.sha256(_value).hexdigest()
-        return _hash
-
-    @property
-    def model_net(self) -> ModelRoadwayNetwork:
-        """Return a ModelRoadwayNetwork object for this network."""
-        if self._model_net is None or self._model_net._net_hash != self.network_hash:
-            self._model_net = ModelRoadwayNetwork(self)
-        return self._model_net
-
-    @property
-    def summary(self) -> dict:
-        """Quick summary dictionary of number of links, nodes."""
-        d = {
-            "links": len(self.links_df),
-            "nodes": len(self.nodes_df),
-        }
-        return d
-
-    @property
-    def link_shapes_df(self) -> gpd.GeoDataFrame:
-        """Add shape geometry to links if available.
-
-        returns: shapes merged to links dataframe
-        """
-        _links_df = copy.deepcopy(self.links_df)
-        link_shapes_df = _links_df.merge(
-            self.shapes_df,
-            left_on="shape_id",
-            right_on="shape_id",
-            how="left",
-        )
-        link_shapes_df["geometry"] = link_shapes_df["geometry_y"].combine_first(
-            link_shapes_df["geometry_x"]
-        )
-        link_shapes_df = link_shapes_df.drop(columns=["geometry_x", "geometry_y"])
-        link_shapes_df = link_shapes_df.set_geometry("geometry")
-        return link_shapes_df
-
-    def get_property_by_timespan_and_group(
-        self,
-        link_property: str,
-        category: Optional[Union[str, int]] = DEFAULT_CATEGORY,
-        timespan: Optional[TimespanString] = DEFAULT_TIMESPAN,
-        strict_timespan_match: bool = False,
-        min_overlap_minutes: int = 60,
-    ) -> Any:
-        """Returns a new dataframe with model_link_id and link property by category and timespan.
-
-        Convenience method for backward compatability.
-
-        Args:
-            link_property: link property to query
-            category: category to query or a list of categories. Defaults to DEFAULT_CATEGORY.
-            timespan: timespan to query in the form of ["HH:MM","HH:MM"].
-                Defaults to DEFAULT_TIMESPAN.
-            strict_timespan_match: If True, will only return links that match the timespan exactly.
-                Defaults to False.
-            min_overlap_minutes: If strict_timespan_match is False, will return links that overlap
-                with the timespan by at least this many minutes. Defaults to 60.
-        """
-        from .links.scopes import prop_for_scope
-
-        return prop_for_scope(
-            self.links_df,
-            link_property,
-            timespan=timespan,
-            category=category,
-            strict_timespan_match=strict_timespan_match,
-            min_overlap_minutes=min_overlap_minutes,
-        )
-
-    def get_selection(
-        self,
-        selection_dict: Union[dict, SelectFacility],
-        overwrite: bool = False,
-    ) -> Union[RoadwayNodeSelection, RoadwayLinkSelection]:
-        """Return selection if it already exists, otherwise performs selection.
-
-        Args:
-            selection_dict (dict): SelectFacility dictionary.
-            overwrite: if True, will overwrite any previously cached searches. Defaults to False.
-        """
-        key = _create_selection_key(selection_dict)
-        if (key in self._selections) and not overwrite:
-            WranglerLogger.debug(f"Using cached selection from key: {key}")
-            return self._selections[key]
-
-        if isinstance(selection_dict, SelectFacility):
-            selection_data = selection_dict
-        elif isinstance(selection_dict, SelectLinksDict):
-            selection_data = SelectFacility(links=selection_dict)
-        elif isinstance(selection_dict, SelectNodesDict):
-            selection_data = SelectFacility(nodes=selection_dict)
-        elif isinstance(selection_dict, dict):
-            selection_data = SelectFacility(**selection_dict)
-        else:
-            msg = "selection_dict arg must be a dictionary or SelectFacility model."
-            WranglerLogger.error(
-                msg + f" Received: {selection_dict} of type {type(selection_dict)}"
-            )
-            raise SelectionError(msg)
-
-        WranglerLogger.debug(f"Getting selection from key: {key}")
-        if "links" in selection_data.fields:
-            return RoadwayLinkSelection(self, selection_dict)
-        if "nodes" in selection_data.fields:
-            return RoadwayNodeSelection(self, selection_dict)
-        msg = "Selection data should have either 'links' or 'nodes'."
-        WranglerLogger.error(msg + f" Received: {selection_dict}")
-        raise SelectionError(msg)
-
-    def modal_graph_hash(self, mode) -> str:
-        """Hash of the links in order to detect a network change from when graph created."""
-        _value = str.encode(self.links_df.df_hash() + "-" + mode)
-        _hash = hashlib.sha256(_value).hexdigest()
-
-        return _hash
-
-    def get_modal_graph(self, mode) -> MultiDiGraph:
-        """Return a networkx graph of the network for a specific mode.
-
-        Args:
-            mode: mode of the network, one of `drive`,`transit`,`walk`, `bike`
-        """
-        from .graph import net_to_graph
-
-        if self._modal_graphs[mode]["hash"] != self.modal_graph_hash(mode):
-            self._modal_graphs[mode]["graph"] = net_to_graph(self, mode)
-
-        return self._modal_graphs[mode]["graph"]
-
-    def apply(
-        self,
-        project_card: Union[ProjectCard, dict],
-        transit_net: Optional[TransitNetwork] = None,
-        **kwargs,
-    ) -> RoadwayNetwork:
-        """Wrapper method to apply a roadway project, returning a new RoadwayNetwork instance.
-
-        Args:
-            project_card: either a dictionary of the project card object or ProjectCard instance
-            transit_net: optional transit network which will be used to if project requires as
-                noted in `SECONDARY_TRANSIT_CARD_TYPES`.  If no transit network is provided, will
-                skip anything related to transit network.
-            **kwargs: keyword arguments to pass to project application
-        """
-        if not (isinstance(project_card, (ProjectCard, SubProject))):
-            project_card = ProjectCard(project_card)
-
-        # project_card.validate()
-        if not project_card.valid:
-            msg = f"Project card {project_card.project} not valid."
-            WranglerLogger.error(msg)
-            raise ProjectCardError(msg)
-
-        if project_card._sub_projects:
-            for sp in project_card._sub_projects:
-                WranglerLogger.debug(f"- applying subproject: {sp.change_type}")
-                self._apply_change(sp, transit_net=transit_net, **kwargs)
-            return self
-        return self._apply_change(project_card, transit_net=transit_net, **kwargs)
-
-    def _apply_change(
-        self,
-        change: Union[ProjectCard, SubProject],
-        transit_net: Optional[TransitNetwork] = None,
-    ) -> RoadwayNetwork:
-        """Apply a single change: a single-project project or a sub-project."""
-        if not isinstance(change, SubProject):
-            WranglerLogger.info(f"Applying Project to Roadway Network: {change.project}")
-
-        if change.change_type == "roadway_property_change":
-            return apply_roadway_property_change(
-                self,
-                self.get_selection(change.roadway_property_change["facility"]),
-                change.roadway_property_change["property_changes"],
-                project_name=change.project,
-            )
-
-        if change.change_type == "roadway_addition":
-            return apply_new_roadway(
-                self,
-                change.roadway_addition,
-                project_name=change.project,
-            )
-
-        if change.change_type == "roadway_deletion":
-            return apply_roadway_deletion(
-                self,
-                change.roadway_deletion,
-                transit_net=transit_net,
-            )
-
-        if change.change_type == "pycode":
-            return apply_calculated_roadway(self, change.pycode)
-        WranglerLogger.error(f"Couldn't find project in: \n{change.__dict__}")
-        msg = f"Invalid Project Card Category: {change.change_type}"
-        raise ProjectCardError(msg)
-
-    def links_with_link_ids(self, link_ids: list[int]) -> DataFrame[RoadLinksTable]:
-        """Return subset of links_df based on link_ids list."""
-        return filter_links_to_ids(self.links_df, link_ids)
-
-    def links_with_nodes(self, node_ids: list[int]) -> DataFrame[RoadLinksTable]:
-        """Return subset of links_df based on node_ids list."""
-        return filter_links_to_node_ids(self.links_df, node_ids)
-
-    def nodes_in_links(self) -> DataFrame[RoadNodesTable]:
-        """Returns subset of self.nodes_df that are in self.links_df."""
-        return filter_nodes_to_links(self.links_df, self.nodes_df)
-
-    def node_coords(self, model_node_id: int) -> tuple:
-        """Return coordinates (x, y) of a node based on model_node_id."""
-        try:
-            node = self.nodes_df[self.nodes_df.model_node_id == model_node_id]
-        except ValueError as err:
-            msg = f"Node with model_node_id {model_node_id} not found."
-            WranglerLogger.error(msg)
-            raise NodeNotFoundError(msg) from err
-        return node.geometry.x.values[0], node.geometry.y.values[0]
-
-    def add_links(
-        self,
-        add_links_df: Union[pd.DataFrame, DataFrame[RoadLinksTable]],
-        in_crs: int = LAT_LON_CRS,
-    ):
-        """Validate combined links_df with LinksSchema before adding to self.links_df.
-
-        Args:
-            add_links_df: Dataframe of additional links to add.
-            in_crs: crs of input data. Defaults to LAT_LON_CRS.
-        """
-        dupe_recs = self.links_df.model_link_id.isin(add_links_df.model_link_id)
-
-        if dupe_recs.any():
-            dupe_ids = self.links_df.loc[dupe_recs, "model_link_id"]
-            WranglerLogger.error(
-                f"Cannot add links with model_link_id already in network: {dupe_ids}"
-            )
-            msg = "Cannot add links with model_link_id already in network."
-            raise LinkAddError(msg)
-
-        if add_links_df.attrs.get("name") != "road_links":
-            add_links_df = data_to_links_df(add_links_df, nodes_df=self.nodes_df, in_crs=in_crs)
-        self.links_df = validate_df_to_model(
-            concat_with_attr([self.links_df, add_links_df], axis=0), RoadLinksTable
-        )
-
-    def add_nodes(
-        self,
-        add_nodes_df: Union[pd.DataFrame, DataFrame[RoadNodesTable]],
-        in_crs: int = LAT_LON_CRS,
-    ):
-        """Validate combined nodes_df with NodesSchema before adding to self.nodes_df.
-
-        Args:
-            add_nodes_df: Dataframe of additional nodes to add.
-            in_crs: crs of input data. Defaults to LAT_LON_CRS.
-        """
-        dupe_ids = self.nodes_df.model_node_id.isin(add_nodes_df.model_node_id)
-        if dupe_ids.any():
-            WranglerLogger.error(
-                f"Cannot add nodes with model_node_id already in network: {dupe_ids}"
-            )
-            msg = "Cannot add nodes with model_node_id already in network."
-            raise NodeAddError(msg)
-
-        if add_nodes_df.attrs.get("name") != "road_nodes":
-            add_nodes_df = data_to_nodes_df(add_nodes_df, in_crs=in_crs, config=self.config)
-        self.nodes_df = validate_df_to_model(
-            concat_with_attr([self.nodes_df, add_nodes_df], axis=0), RoadNodesTable
-        )
-        if self.nodes_df.attrs.get("name") != "road_nodes":
-            msg = f"Expected nodes_df to have name 'road_nodes', got {self.nodes_df.attrs.get('name')}"
-            raise NotNodesError(msg)
-
-    def add_shapes(
-        self,
-        add_shapes_df: Union[pd.DataFrame, DataFrame[RoadShapesTable]],
-        in_crs: int = LAT_LON_CRS,
-    ):
-        """Validate combined shapes_df with RoadShapesTable efore adding to self.shapes_df.
-
-        Args:
-            add_shapes_df: Dataframe of additional shapes to add.
-            in_crs: crs of input data. Defaults to LAT_LON_CRS.
-        """
-        dupe_ids = self.shapes_df.shape_id.isin(add_shapes_df.shape_id)
-        if dupe_ids.any():
-            msg = "Cannot add shapes with shape_id already in network."
-            WranglerLogger.error(msg + f"\nDuplicates: {dupe_ids}")
-            raise ShapeAddError(msg)
-
-        if add_shapes_df.attrs.get("name") != "road_shapes":
-            add_shapes_df = df_to_shapes_df(add_shapes_df, in_crs=in_crs, config=self.config)
-
-        WranglerLogger.debug(f"add_shapes_df: \n{add_shapes_df}")
-        WranglerLogger.debug(f"self.shapes_df: \n{self.shapes_df}")
-
-        self.shapes_df = validate_df_to_model(
-            concat_with_attr([self.shapes_df, add_shapes_df], axis=0), RoadShapesTable
-        )
-
-    def delete_links(
-        self,
-        selection_dict: Union[dict, SelectLinksDict],
-        clean_nodes: bool = False,
-        clean_shapes: bool = False,
-        transit_net: Optional[TransitNetwork] = None,
-    ):
-        """Deletes links based on selection dictionary and optionally associated nodes and shapes.
-
-        Args:
-            selection_dict (SelectLinks): Dictionary describing link selections as follows:
-                `all`: Optional[bool] = False. If true, will select all.
-                `name`: Optional[list[str]]
-                `ref`: Optional[list[str]]
-                `osm_link_id`:Optional[list[str]]
-                `model_link_id`: Optional[list[int]]
-                `modes`: Optional[list[str]]. Defaults to "any"
-                `ignore_missing`: if true, will not error when defaults to True.
-                ...plus any other link property to select on top of these.
-            clean_nodes (bool, optional): If True, will clean nodes uniquely associated with
-                deleted links. Defaults to False.
-            clean_shapes (bool, optional): If True, will clean nodes uniquely associated with
-                deleted links. Defaults to False.
-            transit_net (TransitNetwork, optional): If provided, will check TransitNetwork and
-                warn if deletion breaks transit shapes. Defaults to None.
-        """
-        if not isinstance(selection_dict, SelectLinksDict):
-            selection_dict = SelectLinksDict(**selection_dict)
-        selection_dict = selection_dict.model_dump(exclude_none=True, by_alias=True)
-        selection = self.get_selection({"links": selection_dict})
-        if isinstance(selection, RoadwayNodeSelection):
-            msg = "Selection should be for links, but got nodes."
-            raise SelectionError(msg)
-        if clean_nodes:
-            node_ids_to_delete = node_ids_unique_to_link_ids(
-                selection.selected_links, selection.selected_links_df, self.nodes_df
-            )
-            WranglerLogger.debug(
-                f"Dropping nodes associated with dropped links: \n{node_ids_to_delete}"
-            )
-            self.nodes_df = delete_nodes_by_ids(self.nodes_df, del_node_ids=node_ids_to_delete)
-
-        if clean_shapes:
-            shape_ids_to_delete = shape_ids_unique_to_link_ids(
-                selection.selected_links, selection.selected_links_df, self.shapes_df
-            )
-            WranglerLogger.debug(
-                f"Dropping shapes associated with dropped links: \n{shape_ids_to_delete}"
-            )
-            self.shapes_df = delete_shapes_by_ids(
-                self.shapes_df, del_shape_ids=shape_ids_to_delete
-            )
-
-        self.links_df = delete_links_by_ids(
-            self.links_df,
-            selection.selected_links,
-            ignore_missing=selection.ignore_missing,
-            transit_net=transit_net,
-        )
-
-    def delete_nodes(
-        self,
-        selection_dict: Union[dict, SelectNodesDict],
-        remove_links: bool = False,
-    ) -> None:
-        """Deletes nodes from roadway network. Wont delete nodes used by links in network.
-
-        Args:
-            selection_dict: dictionary of node selection criteria in the form of a SelectNodesDict.
-            remove_links: if True, will remove any links that are associated with the nodes.
-                If False, will only remove nodes if they are not associated with any links.
-                Defaults to False.
-
-        raises:
-            NodeDeletionError: If not ignore_missing and selected nodes to delete aren't in network
-        """
-        if not isinstance(selection_dict, SelectNodesDict):
-            selection_dict = SelectNodesDict(**selection_dict)
-        selection_dict = selection_dict.model_dump(exclude_none=True, by_alias=True)
-        _selection = self.get_selection({"nodes": selection_dict})
-        assert isinstance(_selection, RoadwayNodeSelection)  # for mypy
-        selection: RoadwayNodeSelection = _selection
-        if remove_links:
-            del_node_ids = selection.selected_nodes
-            link_ids = self.links_with_nodes(selection.selected_nodes).model_link_id.to_list()
-            WranglerLogger.info(f"Removing {len(link_ids)} links associated with nodes.")
-            self.delete_links({"model_link_id": link_ids})
-        else:
-            unused_node_ids = node_ids_without_links(self.nodes_df, self.links_df)
-            del_node_ids = list(set(selection.selected_nodes).intersection(unused_node_ids))
-
-        self.nodes_df = delete_nodes_by_ids(
-            self.nodes_df, del_node_ids, ignore_missing=selection.ignore_missing
-        )
-
-    def clean_unused_shapes(self):
-        """Removes any unused shapes from network that aren't referenced by links_df."""
-        from .shapes.shapes import shape_ids_without_links
-
-        del_shape_ids = shape_ids_without_links(self.shapes_df, self.links_df)
-        self.shapes_df = self.shapes_df.drop(del_shape_ids)
-
-    def clean_unused_nodes(self):
-        """Removes any unused nodes from network that aren't referenced by links_df.
-
-        NOTE: does not check if these nodes are used by transit, so use with caution.
-        """
-        from .nodes.nodes import node_ids_without_links
-
-        node_ids = node_ids_without_links(self.nodes_df, self.links_df)
-        self.nodes_df = self.nodes_df.drop(node_ids)
-
-    def move_nodes(
-        self,
-        node_geometry_change_table: DataFrame[NodeGeometryChangeTable],
-    ):
-        """Moves nodes based on updated geometry along with associated links and shape geometry.
-
-        Args:
-            node_geometry_change_table: a table with model_node_id, X, Y, and CRS.
-        """
-        node_geometry_change_table = NodeGeometryChangeTable(node_geometry_change_table)
-        node_ids = node_geometry_change_table.model_node_id.to_list()
-        WranglerLogger.debug(f"Moving nodes: {node_ids}")
-        self.nodes_df = edit_node_geometry(self.nodes_df, node_geometry_change_table)
-        self.links_df = edit_link_geometry_from_nodes(self.links_df, self.nodes_df, node_ids)
-        self.shapes_df = edit_shape_geometry_from_nodes(
-            self.shapes_df, self.links_df, self.nodes_df, node_ids
-        )
-
-    def has_node(self, model_node_id: int) -> bool:
-        """Queries if network has node based on model_node_id.
-
-        Args:
-            model_node_id: model_node_id to check for.
-        """
-        has_node = self.nodes_df[self.nodes_df.model_node_id].isin([model_node_id]).any()
-
-        return has_node
-
-    def has_link(self, ab: tuple) -> bool:
-        """Returns true if network has links with AB values.
-
-        Args:
-            ab: Tuple of values corresponding with A and B.
-        """
-        sel_a, sel_b = ab
-        has_link = (
-            self.links_df[self.links_df[["A", "B"]]].isin_dict({"A": sel_a, "B": sel_b}).any()
-        )
-        return has_link
-
-    def is_connected(self, mode: str) -> bool:
-        """Determines if the network graph is "strongly" connected.
-
-        A graph is strongly connected if each vertex is reachable from every other vertex.
-
-        Args:
-            mode:  mode of the network, one of `drive`,`transit`,`walk`, `bike`
-        """
-        is_connected = nx.is_strongly_connected(self.get_modal_graph(mode))
-
-        return is_connected
-
    -
    - - - -
    - - - - - - - -
    - - - - - - -
    - -

    Add shape geometry to links if available.

    -

    returns: shapes merged to links dataframe

    -
    - -
    - -
    - - - -

    - model_net: ModelRoadwayNetwork - - - property - - -

    - - -
    - -

    Return a ModelRoadwayNetwork object for this network.

    -
    - -
    - -
    - - - -

    - network_hash: str - - - property - - -

    - - -
    - -

    Hash of the links and nodes dataframes.

    -
    - -
    - -
    - - - -

    - shapes_df: DataFrame[RoadShapesTable] - - - property - writable - - -

    - - -
    - -

    Load and return RoadShapesTable.

    -

    If not already loaded, will read from shapes_file and return. If shapes_file is None, -will return an empty dataframe with the right schema. If shapes_df is already set, will -return that.

    -
    - -
    - -
    - - - -

    - summary: dict - - - property - - -

    - - -
    - -

    Quick summary dictionary of number of links, nodes.

    -
    - -
    - - - -
    - - - - - -
    - -

    Validate combined links_df with LinksSchema before adding to self.links_df.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    add_links_df - Union[DataFrame, DataFrame[RoadLinksTable]] - -
    -

    Dataframe of additional links to add.

    -
    -     		- required -
    in_crs - int - -
    -

    crs of input data. Defaults to LAT_LON_CRS.

    -
    -     		- LAT_LON_CRS -
    - -
    - Source code in network_wrangler/roadway/network.py - 
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    def add_links(
-    self,
-    add_links_df: Union[pd.DataFrame, DataFrame[RoadLinksTable]],
-    in_crs: int = LAT_LON_CRS,
-):
-    """Validate combined links_df with LinksSchema before adding to self.links_df.
-
-    Args:
-        add_links_df: Dataframe of additional links to add.
-        in_crs: crs of input data. Defaults to LAT_LON_CRS.
-    """
-    dupe_recs = self.links_df.model_link_id.isin(add_links_df.model_link_id)
-
-    if dupe_recs.any():
-        dupe_ids = self.links_df.loc[dupe_recs, "model_link_id"]
-        WranglerLogger.error(
-            f"Cannot add links with model_link_id already in network: {dupe_ids}"
-        )
-        msg = "Cannot add links with model_link_id already in network."
-        raise LinkAddError(msg)
-
-    if add_links_df.attrs.get("name") != "road_links":
-        add_links_df = data_to_links_df(add_links_df, nodes_df=self.nodes_df, in_crs=in_crs)
-    self.links_df = validate_df_to_model(
-        concat_with_attr([self.links_df, add_links_df], axis=0), RoadLinksTable
-    )
-
    -
    -
    - -
    - -
    - - -

    - add_nodes(add_nodes_df, in_crs=LAT_LON_CRS) - -

    - - -
    - -

    Validate combined nodes_df with NodesSchema before adding to self.nodes_df.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    add_nodes_df - Union[DataFrame, DataFrame[RoadNodesTable]] - -
    -

    Dataframe of additional nodes to add.

    -
    -     		- required -
    in_crs - int - -
    -

    crs of input data. Defaults to LAT_LON_CRS.

    -
    -     		- LAT_LON_CRS -
    - -
    - Source code in network_wrangler/roadway/network.py - 
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    def add_nodes(
-    self,
-    add_nodes_df: Union[pd.DataFrame, DataFrame[RoadNodesTable]],
-    in_crs: int = LAT_LON_CRS,
-):
-    """Validate combined nodes_df with NodesSchema before adding to self.nodes_df.
-
-    Args:
-        add_nodes_df: Dataframe of additional nodes to add.
-        in_crs: crs of input data. Defaults to LAT_LON_CRS.
-    """
-    dupe_ids = self.nodes_df.model_node_id.isin(add_nodes_df.model_node_id)
-    if dupe_ids.any():
-        WranglerLogger.error(
-            f"Cannot add nodes with model_node_id already in network: {dupe_ids}"
-        )
-        msg = "Cannot add nodes with model_node_id already in network."
-        raise NodeAddError(msg)
-
-    if add_nodes_df.attrs.get("name") != "road_nodes":
-        add_nodes_df = data_to_nodes_df(add_nodes_df, in_crs=in_crs, config=self.config)
-    self.nodes_df = validate_df_to_model(
-        concat_with_attr([self.nodes_df, add_nodes_df], axis=0), RoadNodesTable
-    )
-    if self.nodes_df.attrs.get("name") != "road_nodes":
-        msg = f"Expected nodes_df to have name 'road_nodes', got {self.nodes_df.attrs.get('name')}"
-        raise NotNodesError(msg)
-
    -
    -
    - -
    - -
    - - -

    - add_shapes(add_shapes_df, in_crs=LAT_LON_CRS) - -

    - - -
    - -

    Validate combined shapes_df with RoadShapesTable efore adding to self.shapes_df.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    add_shapes_df - Union[DataFrame, DataFrame[RoadShapesTable]] - -
    -

    Dataframe of additional shapes to add.

    -
    -     		- required -
    in_crs - int - -
    -

    crs of input data. Defaults to LAT_LON_CRS.

    -
    -     		- LAT_LON_CRS -
    - -
    - Source code in network_wrangler/roadway/network.py - 
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    def add_shapes(
-    self,
-    add_shapes_df: Union[pd.DataFrame, DataFrame[RoadShapesTable]],
-    in_crs: int = LAT_LON_CRS,
-):
-    """Validate combined shapes_df with RoadShapesTable efore adding to self.shapes_df.
-
-    Args:
-        add_shapes_df: Dataframe of additional shapes to add.
-        in_crs: crs of input data. Defaults to LAT_LON_CRS.
-    """
-    dupe_ids = self.shapes_df.shape_id.isin(add_shapes_df.shape_id)
-    if dupe_ids.any():
-        msg = "Cannot add shapes with shape_id already in network."
-        WranglerLogger.error(msg + f"\nDuplicates: {dupe_ids}")
-        raise ShapeAddError(msg)
-
-    if add_shapes_df.attrs.get("name") != "road_shapes":
-        add_shapes_df = df_to_shapes_df(add_shapes_df, in_crs=in_crs, config=self.config)
-
-    WranglerLogger.debug(f"add_shapes_df: \n{add_shapes_df}")
-    WranglerLogger.debug(f"self.shapes_df: \n{self.shapes_df}")
-
-    self.shapes_df = validate_df_to_model(
-        concat_with_attr([self.shapes_df, add_shapes_df], axis=0), RoadShapesTable
-    )
-
    -
    -
    - -
    - -
    - - -

    - apply(project_card, transit_net=None, **kwargs) - -

    - - -
    - -

    Wrapper method to apply a roadway project, returning a new RoadwayNetwork instance.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    project_card - Union[ProjectCard, dict] - -
    -

    either a dictionary of the project card object or ProjectCard instance

    -
    -     		- required -
    transit_net - Optional[TransitNetwork] - -
    -

    optional transit network which will be used to if project requires as -noted in SECONDARY_TRANSIT_CARD_TYPES. If no transit network is provided, will -skip anything related to transit network.

    -
    -     		- None -
    **kwargs - -
    -

    keyword arguments to pass to project application

    -
    -     		- {} -
    - -
    - Source code in network_wrangler/roadway/network.py - 
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    def apply(
-    self,
-    project_card: Union[ProjectCard, dict],
-    transit_net: Optional[TransitNetwork] = None,
-    **kwargs,
-) -> RoadwayNetwork:
-    """Wrapper method to apply a roadway project, returning a new RoadwayNetwork instance.
-
-    Args:
-        project_card: either a dictionary of the project card object or ProjectCard instance
-        transit_net: optional transit network which will be used to if project requires as
-            noted in `SECONDARY_TRANSIT_CARD_TYPES`.  If no transit network is provided, will
-            skip anything related to transit network.
-        **kwargs: keyword arguments to pass to project application
-    """
-    if not (isinstance(project_card, (ProjectCard, SubProject))):
-        project_card = ProjectCard(project_card)
-
-    # project_card.validate()
-    if not project_card.valid:
-        msg = f"Project card {project_card.project} not valid."
-        WranglerLogger.error(msg)
-        raise ProjectCardError(msg)
-
-    if project_card._sub_projects:
-        for sp in project_card._sub_projects:
-            WranglerLogger.debug(f"- applying subproject: {sp.change_type}")
-            self._apply_change(sp, transit_net=transit_net, **kwargs)
-        return self
-    return self._apply_change(project_card, transit_net=transit_net, **kwargs)
-
    -
    -
    - -
    - -
    - - -

    - clean_unused_nodes() - -

    - - -
    - -

    Removes any unused nodes from network that aren’t referenced by links_df.

    -

    NOTE: does not check if these nodes are used by transit, so use with caution.

    - -
    - Source code in network_wrangler/roadway/network.py - 
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    def clean_unused_nodes(self):
-    """Removes any unused nodes from network that aren't referenced by links_df.
-
-    NOTE: does not check if these nodes are used by transit, so use with caution.
-    """
-    from .nodes.nodes import node_ids_without_links
-
-    node_ids = node_ids_without_links(self.nodes_df, self.links_df)
-    self.nodes_df = self.nodes_df.drop(node_ids)
-
    -
    -
    - -
    - -
    - - -

    - clean_unused_shapes() - -

    - - -
    - -

    Removes any unused shapes from network that aren’t referenced by links_df.

    - -
    - Source code in network_wrangler/roadway/network.py - 
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    def clean_unused_shapes(self):
-    """Removes any unused shapes from network that aren't referenced by links_df."""
-    from .shapes.shapes import shape_ids_without_links
-
-    del_shape_ids = shape_ids_without_links(self.shapes_df, self.links_df)
-    self.shapes_df = self.shapes_df.drop(del_shape_ids)
-
    -
    -
    - -
    - -
    - - -

    - coerce_crs(v) - -

    - - -
    - -

    Coerce crs of nodes_df and links_df to LAT_LON_CRS.

    - -
    - Source code in network_wrangler/roadway/network.py - 
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    @field_validator("nodes_df", "links_df")
-def coerce_crs(cls, v):
-    """Coerce crs of nodes_df and links_df to LAT_LON_CRS."""
-    if v.crs != LAT_LON_CRS:
-        WranglerLogger.warning(
-            f"CRS of links_df ({v.crs}) doesn't match network crs {LAT_LON_CRS}. \
-                Changing to network crs."
-        )
-        v.to_crs(LAT_LON_CRS)
-    return v
-
    -
    -
    - -
    - -
    - - - - - -
    - -

    Deletes links based on selection dictionary and optionally associated nodes and shapes.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    selection_dict - SelectLinks - -
    -

    Dictionary describing link selections as follows: -all: Optional[bool] = False. If true, will select all. -name: Optional[list[str]] -ref: Optional[list[str]] -osm_link_id:Optional[list[str]] -model_link_id: Optional[list[int]] -modes: Optional[list[str]]. Defaults to “any” -ignore_missing: if true, will not error when defaults to True. -…plus any other link property to select on top of these.

    -
    -     		- required -
    clean_nodes - bool - -
    -

    If True, will clean nodes uniquely associated with -deleted links. Defaults to False.

    -
    -     		- False -
    clean_shapes - bool - -
    -

    If True, will clean nodes uniquely associated with -deleted links. Defaults to False.

    -
    -     		- False -
    transit_net - TransitNetwork - -
    -

    If provided, will check TransitNetwork and -warn if deletion breaks transit shapes. Defaults to None.

    -
    -     		- None -
    - -
    - Source code in network_wrangler/roadway/network.py - 
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    def delete_links(
-    self,
-    selection_dict: Union[dict, SelectLinksDict],
-    clean_nodes: bool = False,
-    clean_shapes: bool = False,
-    transit_net: Optional[TransitNetwork] = None,
-):
-    """Deletes links based on selection dictionary and optionally associated nodes and shapes.
-
-    Args:
-        selection_dict (SelectLinks): Dictionary describing link selections as follows:
-            `all`: Optional[bool] = False. If true, will select all.
-            `name`: Optional[list[str]]
-            `ref`: Optional[list[str]]
-            `osm_link_id`:Optional[list[str]]
-            `model_link_id`: Optional[list[int]]
-            `modes`: Optional[list[str]]. Defaults to "any"
-            `ignore_missing`: if true, will not error when defaults to True.
-            ...plus any other link property to select on top of these.
-        clean_nodes (bool, optional): If True, will clean nodes uniquely associated with
-            deleted links. Defaults to False.
-        clean_shapes (bool, optional): If True, will clean nodes uniquely associated with
-            deleted links. Defaults to False.
-        transit_net (TransitNetwork, optional): If provided, will check TransitNetwork and
-            warn if deletion breaks transit shapes. Defaults to None.
-    """
-    if not isinstance(selection_dict, SelectLinksDict):
-        selection_dict = SelectLinksDict(**selection_dict)
-    selection_dict = selection_dict.model_dump(exclude_none=True, by_alias=True)
-    selection = self.get_selection({"links": selection_dict})
-    if isinstance(selection, RoadwayNodeSelection):
-        msg = "Selection should be for links, but got nodes."
-        raise SelectionError(msg)
-    if clean_nodes:
-        node_ids_to_delete = node_ids_unique_to_link_ids(
-            selection.selected_links, selection.selected_links_df, self.nodes_df
-        )
-        WranglerLogger.debug(
-            f"Dropping nodes associated with dropped links: \n{node_ids_to_delete}"
-        )
-        self.nodes_df = delete_nodes_by_ids(self.nodes_df, del_node_ids=node_ids_to_delete)
-
-    if clean_shapes:
-        shape_ids_to_delete = shape_ids_unique_to_link_ids(
-            selection.selected_links, selection.selected_links_df, self.shapes_df
-        )
-        WranglerLogger.debug(
-            f"Dropping shapes associated with dropped links: \n{shape_ids_to_delete}"
-        )
-        self.shapes_df = delete_shapes_by_ids(
-            self.shapes_df, del_shape_ids=shape_ids_to_delete
-        )
-
-    self.links_df = delete_links_by_ids(
-        self.links_df,
-        selection.selected_links,
-        ignore_missing=selection.ignore_missing,
-        transit_net=transit_net,
-    )
-
    -
    -
    - -
    - -
    - - -

    - delete_nodes(selection_dict, remove_links=False) - -

    - - -
    - -

    Deletes nodes from roadway network. Wont delete nodes used by links in network.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    selection_dict - Union[dict, SelectNodesDict] - -
    -

    dictionary of node selection criteria in the form of a SelectNodesDict.

    -
    -     		- required -
    remove_links - bool - -
    -

    if True, will remove any links that are associated with the nodes. -If False, will only remove nodes if they are not associated with any links. -Defaults to False.

    -
    -     		- False -
    - - -

    Raises:

    - - - - - - - - - - - - - -
    TypeDescription
    - NodeDeletionError - -
    -

    If not ignore_missing and selected nodes to delete aren’t in network

    -
    -
    - -
    - Source code in network_wrangler/roadway/network.py - 
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    def delete_nodes(
-    self,
-    selection_dict: Union[dict, SelectNodesDict],
-    remove_links: bool = False,
-) -> None:
-    """Deletes nodes from roadway network. Wont delete nodes used by links in network.
-
-    Args:
-        selection_dict: dictionary of node selection criteria in the form of a SelectNodesDict.
-        remove_links: if True, will remove any links that are associated with the nodes.
-            If False, will only remove nodes if they are not associated with any links.
-            Defaults to False.
-
-    raises:
-        NodeDeletionError: If not ignore_missing and selected nodes to delete aren't in network
-    """
-    if not isinstance(selection_dict, SelectNodesDict):
-        selection_dict = SelectNodesDict(**selection_dict)
-    selection_dict = selection_dict.model_dump(exclude_none=True, by_alias=True)
-    _selection = self.get_selection({"nodes": selection_dict})
-    assert isinstance(_selection, RoadwayNodeSelection)  # for mypy
-    selection: RoadwayNodeSelection = _selection
-    if remove_links:
-        del_node_ids = selection.selected_nodes
-        link_ids = self.links_with_nodes(selection.selected_nodes).model_link_id.to_list()
-        WranglerLogger.info(f"Removing {len(link_ids)} links associated with nodes.")
-        self.delete_links({"model_link_id": link_ids})
-    else:
-        unused_node_ids = node_ids_without_links(self.nodes_df, self.links_df)
-        del_node_ids = list(set(selection.selected_nodes).intersection(unused_node_ids))
-
-    self.nodes_df = delete_nodes_by_ids(
-        self.nodes_df, del_node_ids, ignore_missing=selection.ignore_missing
-    )
-
    -
    -
    - -
    - -
    - - -

    - get_modal_graph(mode) - -

    - - -
    - -

    Return a networkx graph of the network for a specific mode.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    mode - -
    -

    mode of the network, one of drive,transit,walk, bike

    -
    -     		- required -
    - -
    - Source code in network_wrangler/roadway/network.py - 
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    def get_modal_graph(self, mode) -> MultiDiGraph:
-    """Return a networkx graph of the network for a specific mode.
-
-    Args:
-        mode: mode of the network, one of `drive`,`transit`,`walk`, `bike`
-    """
-    from .graph import net_to_graph
-
-    if self._modal_graphs[mode]["hash"] != self.modal_graph_hash(mode):
-        self._modal_graphs[mode]["graph"] = net_to_graph(self, mode)
-
-    return self._modal_graphs[mode]["graph"]
-
    -
    -
    - -
    - -
    - - -

    - get_property_by_timespan_and_group(link_property, category=DEFAULT_CATEGORY, timespan=DEFAULT_TIMESPAN, strict_timespan_match=False, min_overlap_minutes=60) - -

    - - -
    - -

    Returns a new dataframe with model_link_id and link property by category and timespan.

    -

    Convenience method for backward compatability.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    link_property - str - -
    -

    link property to query

    -
    -     		- required -
    category - Optional[Union[str, int]] - -
    -

    category to query or a list of categories. Defaults to DEFAULT_CATEGORY.

    -
    -     		- DEFAULT_CATEGORY -
    timespan - Optional[TimespanString] - -
    -

    timespan to query in the form of [“HH:MM”,”HH:MM”]. -Defaults to DEFAULT_TIMESPAN.

    -
    -     		- DEFAULT_TIMESPAN -
    strict_timespan_match - bool - -
    -

    If True, will only return links that match the timespan exactly. -Defaults to False.

    -
    -     		- False -
    min_overlap_minutes - int - -
    -

    If strict_timespan_match is False, will return links that overlap -with the timespan by at least this many minutes. Defaults to 60.

    -
    -     		- 60 -
    - -
    - Source code in network_wrangler/roadway/network.py - 
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    def get_property_by_timespan_and_group(
-    self,
-    link_property: str,
-    category: Optional[Union[str, int]] = DEFAULT_CATEGORY,
-    timespan: Optional[TimespanString] = DEFAULT_TIMESPAN,
-    strict_timespan_match: bool = False,
-    min_overlap_minutes: int = 60,
-) -> Any:
-    """Returns a new dataframe with model_link_id and link property by category and timespan.
-
-    Convenience method for backward compatability.
-
-    Args:
-        link_property: link property to query
-        category: category to query or a list of categories. Defaults to DEFAULT_CATEGORY.
-        timespan: timespan to query in the form of ["HH:MM","HH:MM"].
-            Defaults to DEFAULT_TIMESPAN.
-        strict_timespan_match: If True, will only return links that match the timespan exactly.
-            Defaults to False.
-        min_overlap_minutes: If strict_timespan_match is False, will return links that overlap
-            with the timespan by at least this many minutes. Defaults to 60.
-    """
-    from .links.scopes import prop_for_scope
-
-    return prop_for_scope(
-        self.links_df,
-        link_property,
-        timespan=timespan,
-        category=category,
-        strict_timespan_match=strict_timespan_match,
-        min_overlap_minutes=min_overlap_minutes,
-    )
-
    -
    -
    - -
    - -
    - - -

    - get_selection(selection_dict, overwrite=False) - -

    - - -
    - -

    Return selection if it already exists, otherwise performs selection.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    selection_dict - dict - -
    -

    SelectFacility dictionary.

    -
    -     		- required -
    overwrite - bool - -
    -

    if True, will overwrite any previously cached searches. Defaults to False.

    -
    -     		- False -
    - -
    - Source code in network_wrangler/roadway/network.py - 
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    def get_selection(
-    self,
-    selection_dict: Union[dict, SelectFacility],
-    overwrite: bool = False,
-) -> Union[RoadwayNodeSelection, RoadwayLinkSelection]:
-    """Return selection if it already exists, otherwise performs selection.
-
-    Args:
-        selection_dict (dict): SelectFacility dictionary.
-        overwrite: if True, will overwrite any previously cached searches. Defaults to False.
-    """
-    key = _create_selection_key(selection_dict)
-    if (key in self._selections) and not overwrite:
-        WranglerLogger.debug(f"Using cached selection from key: {key}")
-        return self._selections[key]
-
-    if isinstance(selection_dict, SelectFacility):
-        selection_data = selection_dict
-    elif isinstance(selection_dict, SelectLinksDict):
-        selection_data = SelectFacility(links=selection_dict)
-    elif isinstance(selection_dict, SelectNodesDict):
-        selection_data = SelectFacility(nodes=selection_dict)
-    elif isinstance(selection_dict, dict):
-        selection_data = SelectFacility(**selection_dict)
-    else:
-        msg = "selection_dict arg must be a dictionary or SelectFacility model."
-        WranglerLogger.error(
-            msg + f" Received: {selection_dict} of type {type(selection_dict)}"
-        )
-        raise SelectionError(msg)
-
-    WranglerLogger.debug(f"Getting selection from key: {key}")
-    if "links" in selection_data.fields:
-        return RoadwayLinkSelection(self, selection_dict)
-    if "nodes" in selection_data.fields:
-        return RoadwayNodeSelection(self, selection_dict)
-    msg = "Selection data should have either 'links' or 'nodes'."
-    WranglerLogger.error(msg + f" Received: {selection_dict}")
-    raise SelectionError(msg)
-
    -
    -
    - -
    - -
    - - - - - -
    - -

    Returns true if network has links with AB values.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    ab - tuple - -
    -

    Tuple of values corresponding with A and B.

    -
    -     		- required -
    - -
    - Source code in network_wrangler/roadway/network.py - 
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    def has_link(self, ab: tuple) -> bool:
-    """Returns true if network has links with AB values.
-
-    Args:
-        ab: Tuple of values corresponding with A and B.
-    """
-    sel_a, sel_b = ab
-    has_link = (
-        self.links_df[self.links_df[["A", "B"]]].isin_dict({"A": sel_a, "B": sel_b}).any()
-    )
-    return has_link
-
    -
    -
    - -
    - -
    - - -

    - has_node(model_node_id) - -

    - - -
    - -

    Queries if network has node based on model_node_id.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    model_node_id - int - -
    -

    model_node_id to check for.

    -
    -     		- required -
    - -
    - Source code in network_wrangler/roadway/network.py - 
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    def has_node(self, model_node_id: int) -> bool:
-    """Queries if network has node based on model_node_id.
-
-    Args:
-        model_node_id: model_node_id to check for.
-    """
-    has_node = self.nodes_df[self.nodes_df.model_node_id].isin([model_node_id]).any()
-
-    return has_node
-
    -
    -
    - -
    - -
    - - -

    - is_connected(mode) - -

    - - -
    - -

    Determines if the network graph is “strongly” connected.

    -

    A graph is strongly connected if each vertex is reachable from every other vertex.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    mode - str - -
    -

    mode of the network, one of drive,transit,walk, bike

    -
    -     		- required -
    - -
    - Source code in network_wrangler/roadway/network.py - 
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    def is_connected(self, mode: str) -> bool:
-    """Determines if the network graph is "strongly" connected.
-
-    A graph is strongly connected if each vertex is reachable from every other vertex.
-
-    Args:
-        mode:  mode of the network, one of `drive`,`transit`,`walk`, `bike`
-    """
-    is_connected = nx.is_strongly_connected(self.get_modal_graph(mode))
-
-    return is_connected
-
    -
    -
    - -
    - -
    - - - - - -
    - -

    Return subset of links_df based on link_ids list.

    - -
    - Source code in network_wrangler/roadway/network.py - 
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    def links_with_link_ids(self, link_ids: list[int]) -> DataFrame[RoadLinksTable]:
-    """Return subset of links_df based on link_ids list."""
-    return filter_links_to_ids(self.links_df, link_ids)
-
    -
    -
    - -
    - -
    - - - - - -
    - -

    Return subset of links_df based on node_ids list.

    - -
    - Source code in network_wrangler/roadway/network.py - 
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    def links_with_nodes(self, node_ids: list[int]) -> DataFrame[RoadLinksTable]:
-    """Return subset of links_df based on node_ids list."""
-    return filter_links_to_node_ids(self.links_df, node_ids)
-
    -
    -
    - -
    - -
    - - -

    - modal_graph_hash(mode) - -

    - - -
    - -

    Hash of the links in order to detect a network change from when graph created.

    - -
    - Source code in network_wrangler/roadway/network.py - 
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    def modal_graph_hash(self, mode) -> str:
-    """Hash of the links in order to detect a network change from when graph created."""
-    _value = str.encode(self.links_df.df_hash() + "-" + mode)
-    _hash = hashlib.sha256(_value).hexdigest()
-
-    return _hash
-
    -
    -
    - -
    - -
    - - -

    - move_nodes(node_geometry_change_table) - -

    - - -
    - -

    Moves nodes based on updated geometry along with associated links and shape geometry.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    node_geometry_change_table - DataFrame[NodeGeometryChangeTable] - -
    -

    a table with model_node_id, X, Y, and CRS.

    -
    -     		- required -
    - -
    - Source code in network_wrangler/roadway/network.py - 
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    def move_nodes(
-    self,
-    node_geometry_change_table: DataFrame[NodeGeometryChangeTable],
-):
-    """Moves nodes based on updated geometry along with associated links and shape geometry.
-
-    Args:
-        node_geometry_change_table: a table with model_node_id, X, Y, and CRS.
-    """
-    node_geometry_change_table = NodeGeometryChangeTable(node_geometry_change_table)
-    node_ids = node_geometry_change_table.model_node_id.to_list()
-    WranglerLogger.debug(f"Moving nodes: {node_ids}")
-    self.nodes_df = edit_node_geometry(self.nodes_df, node_geometry_change_table)
-    self.links_df = edit_link_geometry_from_nodes(self.links_df, self.nodes_df, node_ids)
-    self.shapes_df = edit_shape_geometry_from_nodes(
-        self.shapes_df, self.links_df, self.nodes_df, node_ids
-    )
-
    -
    -
    - -
    - -
    - - -

    - node_coords(model_node_id) - -

    - - -
    - -

    Return coordinates (x, y) of a node based on model_node_id.

    - -
    - Source code in network_wrangler/roadway/network.py - 
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    def node_coords(self, model_node_id: int) -> tuple:
-    """Return coordinates (x, y) of a node based on model_node_id."""
-    try:
-        node = self.nodes_df[self.nodes_df.model_node_id == model_node_id]
-    except ValueError as err:
-        msg = f"Node with model_node_id {model_node_id} not found."
-        WranglerLogger.error(msg)
-        raise NodeNotFoundError(msg) from err
-    return node.geometry.x.values[0], node.geometry.y.values[0]
-
    -
    -
    - -
    - -
    - - - - - -
    - -

    Returns subset of self.nodes_df that are in self.links_df.

    - -
    - Source code in network_wrangler/roadway/network.py - 
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    def nodes_in_links(self) -> DataFrame[RoadNodesTable]:
-    """Returns subset of self.nodes_df that are in self.links_df."""
-    return filter_nodes_to_links(self.links_df, self.nodes_df)
-
    -
    -
    - -
    - -
    - - -

    - validate_config(v) - -

    - - -
    - -

    Validate config.

    - -
    - Source code in network_wrangler/roadway/network.py - 
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    @field_validator("config")
-def validate_config(cls, v):
-    """Validate config."""
-    return load_wrangler_config(v)
-
    -
    -
    - -
    - - - -
    - -
    - -
    - - -
    - - - - - -
    - -

    Add data from links going to/from nodes to node.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    links_df - DataFrame[RoadLinksTable] - -
    -

    Will assess connectivity of this links list

    -
    -     		- required -
    nodes_df - DataFrame[RoadNodesTable] - -
    -

    Will assess connectivity of this nodes list

    -
    -     		- required -
    link_variables - Optional[list] - -
    -

    list of columns in links dataframe to add to incident nodes

    -
    -     		- None -
    - - -

    Returns:

    - - - - - - - - - - - - - -
    TypeDescription
    - DataFrame[RoadNodesTable] - -
    -

    nodes DataFrame with link data where length is N*number of links going in/out

    -
    -
    - -
    - Source code in network_wrangler/roadway/network.py - 
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    def add_incident_link_data_to_nodes(
-    links_df: DataFrame[RoadLinksTable],
-    nodes_df: DataFrame[RoadNodesTable],
-    link_variables: Optional[list] = None,
-) -> DataFrame[RoadNodesTable]:
-    """Add data from links going to/from nodes to node.
-
-    Args:
-        links_df: Will assess connectivity of this links list
-        nodes_df: Will assess connectivity of this nodes list
-        link_variables: list of columns in links dataframe to add to incident nodes
-
-    Returns:
-        nodes DataFrame with link data where length is N*number of links going in/out
-    """
-    WranglerLogger.debug("Adding following link data to nodes: ".format())
-    link_variables = link_variables or []
-
-    _link_vals_to_nodes = [x for x in link_variables if x in links_df.columns]
-    if link_variables not in _link_vals_to_nodes:
-        WranglerLogger.warning(
-            f"Following columns not in links_df and wont be added to nodes: {list(set(link_variables) - set(_link_vals_to_nodes))} "
-        )
-
-    _nodes_from_links_A = nodes_df.merge(
-        links_df[[links_df.A, *_link_vals_to_nodes]],
-        how="outer",
-        left_on=nodes_df.model_node_id,
-        right_on=links_df.A,
-    )
-    _nodes_from_links_B = nodes_df.merge(
-        links_df[[links_df.B, *_link_vals_to_nodes]],
-        how="outer",
-        left_on=nodes_df.model_node_id,
-        right_on=links_df.B,
-    )
-    _nodes_from_links_ab = concat_with_attr([_nodes_from_links_A, _nodes_from_links_B])
-
-    return _nodes_from_links_ab
-
    -
    -
    - -
    - - - -
    - -
    - -
    - -
    - - - - -
    - -

    TransitNetwork class for representing a transit network.

    -

    Transit Networks are represented as a Wrangler-flavored GTFS Feed and optionally mapped to -a RoadwayNetwork object. The TransitNetwork object is the primary object for managing transit -networks in Wrangler.

    -

    Usage:

    -
    1
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    ```python
-import network_wrangler as wr
-
-t = wr.load_transit(stpaul_gtfs)
-t.road_net = wr.load_roadway(stpaul_roadway)
-t = t.apply(project_card)
-write_transit(t, "output_dir")
-```
-
    - - - -
    - - - - - - - - -
    - - - -

    - TransitNetwork - - -

    - - -
    - - -

    Representation of a Transit Network.

    -

    Typical usage example: -

    import network_wrangler as wr
-
-tc = wr.load_transit(stpaul_gtfs)
-

    - - -

    Attributes:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescription
    feed - -
    -

    gtfs feed object with interlinked tables.

    -
    -
    road_net - RoadwayNetwork - -
    -

    Associated roadway network object.

    -
    -
    graph - MultiDiGraph - -
    -

    Graph for associated roadway network object.

    -
    -
    config - WranglerConfig - -
    -

    Configuration object for the transit network.

    -
    -
    feed_path - str - -
    -

    Where the feed was read in from.

    -
    -
    validated_frequencies - bool - -
    -

    The frequencies have been validated.

    -
    -
    validated_road_network_consistency - -
    -

    The network has been validated against -the road network.

    -
    -
    - -
    - Source code in network_wrangler/transit/network.py - 
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    class TransitNetwork:
-    """Representation of a Transit Network.
-
-    Typical usage example:
-    ``` py
-    import network_wrangler as wr
-
-    tc = wr.load_transit(stpaul_gtfs)
-    ```
-
-    Attributes:
-        feed: gtfs feed object with interlinked tables.
-        road_net (RoadwayNetwork): Associated roadway network object.
-        graph (nx.MultiDiGraph): Graph for associated roadway network object.
-        config (WranglerConfig): Configuration object for the transit network.
-        feed_path (str): Where the feed was read in from.
-        validated_frequencies (bool): The frequencies have been validated.
-        validated_road_network_consistency (): The network has been validated against
-            the road network.
-    """
-
-    TIME_COLS: ClassVar = ["arrival_time", "departure_time", "start_time", "end_time"]
-
-    def __init__(self, feed: Feed, config: WranglerConfig = DefaultConfig) -> None:
-        """Constructor for TransitNetwork.
-
-        Args:
-            feed: Feed object representing the transit network gtfs tables
-            config: WranglerConfig object. Defaults to DefaultConfig.
-        """
-        WranglerLogger.debug("Creating new TransitNetwork.")
-
-        self._road_net: Optional[RoadwayNetwork] = None
-        self.feed: Feed = feed
-        self.graph: nx.MultiDiGraph = None
-        self.config: WranglerConfig = config
-        # initialize
-        self._consistent_with_road_net = False
-
-        # cached selections
-        self._selections: dict[str, TransitSelection] = {}
-
-    @property
-    def feed_path(self):
-        """Pass through property from Feed."""
-        return self.feed.feed_path
-
-    @property
-    def applied_projects(self) -> list[str]:
-        """List of projects applied to the network.
-
-        Note: This may or may not return a full accurate account of all the applied projects.
-        For better project accounting, please leverage the scenario object.
-        """
-        return _get_applied_projects_from_tables(self.feed)
-
-    @property
-    def feed(self):
-        """Feed associated with the transit network."""
-        return self._feed
-
-    @feed.setter
-    def feed(self, feed: Feed):
-        if not isinstance(feed, Feed):
-            msg = f"TransitNetwork's feed value must be a valid Feed instance. \
-                             This is a {type(feed)}."
-            WranglerLogger.error(msg)
-            raise TransitValidationError(msg)
-        if self._road_net is None or transit_road_net_consistency(feed, self._road_net):
-            self._feed = feed
-            self._stored_feed_hash = copy.deepcopy(feed.hash)
-        else:
-            msg = "Can't assign Feed inconsistent with set Roadway Network."
-            WranglerLogger.error(msg)
-            raise TransitRoadwayConsistencyError(msg)
-
-    @property
-    def road_net(self) -> Union[None, RoadwayNetwork]:
-        """Roadway network associated with the transit network."""
-        return self._road_net
-
-    @road_net.setter
-    def road_net(self, road_net_in: RoadwayNetwork):
-        if road_net_in is None or road_net_in.__class__.__name__ != "RoadwayNetwork":
-            msg = f"TransitNetwork's road_net: value must be a valid RoadwayNetwork instance. \
-                             This is a {type(road_net_in)}."
-            WranglerLogger.error(msg)
-            raise TransitValidationError(msg)
-        if transit_road_net_consistency(self.feed, road_net_in):
-            self._road_net = road_net_in
-            self._stored_road_net_hash = copy.deepcopy(road_net_in.network_hash)
-            self._consistent_with_road_net = True
-        else:
-            msg = "Can't assign inconsistent RoadwayNetwork - Roadway Network not \
-                   set, but can be referenced separately."
-            WranglerLogger.error(msg)
-            raise TransitRoadwayConsistencyError(msg)
-
-    @property
-    def feed_hash(self):
-        """Return the hash of the feed."""
-        return self.feed.hash
-
-    @property
-    def consistent_with_road_net(self) -> bool:
-        """Indicate if road_net is consistent with transit network.
-
-        Will return True if road_net is None, but provide a warning.
-
-        Checks the network hash of when consistency was last evaluated. If transit network or
-        roadway network has changed, will re-evaluate consistency and return the updated value and
-        update self._stored_road_net_hash.
-
-        Returns:
-            Boolean indicating if road_net is consistent with transit network.
-        """
-        if self.road_net is None:
-            WranglerLogger.warning("Roadway Network not set, cannot accurately check consistency.")
-            return True
-        updated_road = self.road_net.network_hash != self._stored_road_net_hash
-        updated_feed = self.feed_hash != self._stored_feed_hash
-
-        if updated_road or updated_feed:
-            self._consistent_with_road_net = transit_road_net_consistency(self.feed, self.road_net)
-            self._stored_road_net_hash = copy.deepcopy(self.road_net.network_hash)
-            self._stored_feed_hash = copy.deepcopy(self.feed_hash)
-        return self._consistent_with_road_net
-
-    def __deepcopy__(self, memo):
-        """Returns copied TransitNetwork instance with deep copy of Feed but not roadway net."""
-        COPY_REF_NOT_VALUE = ["_road_net"]
-        # Create a new, empty instance
-        copied_net = self.__class__.__new__(self.__class__)
-        # Return the new TransitNetwork instance
-        attribute_dict = vars(self)
-
-        # Copy the attributes to the new instance
-        for attr_name, attr_value in attribute_dict.items():
-            # WranglerLogger.debug(f"Copying {attr_name}")
-            if attr_name in COPY_REF_NOT_VALUE:
-                # If the attribute is in the COPY_REF_NOT_VALUE list, assign the reference
-                setattr(copied_net, attr_name, attr_value)
-            else:
-                # WranglerLogger.debug(f"making deep copy: {attr_name}")
-                # For other attributes, perform a deep copy
-                setattr(copied_net, attr_name, copy.deepcopy(attr_value, memo))
-
-        return copied_net
-
-    def deepcopy(self):
-        """Returns copied TransitNetwork instance with deep copy of Feed but not roadway net."""
-        return copy.deepcopy(self)
-
-    @property
-    def stops_gdf(self) -> gpd.GeoDataFrame:
-        """Return stops as a GeoDataFrame using set roadway geometry."""
-        ref_nodes = self.road_net.nodes_df if self.road_net is not None else None
-        return to_points_gdf(self.feed.stops, ref_nodes_df=ref_nodes)
-
-    @property
-    def shapes_gdf(self) -> gpd.GeoDataFrame:
-        """Return aggregated shapes as a GeoDataFrame using set roadway geometry."""
-        ref_nodes = self.road_net.nodes_df if self.road_net is not None else None
-        return shapes_to_trip_shapes_gdf(self.feed.shapes, ref_nodes_df=ref_nodes)
-
-    @property
-    def shape_links_gdf(self) -> gpd.GeoDataFrame:
-        """Return shape-links as a GeoDataFrame using set roadway geometry."""
-        ref_nodes = self.road_net.nodes_df if self.road_net is not None else None
-        return shapes_to_shape_links_gdf(self.feed.shapes, ref_nodes_df=ref_nodes)
-
-    @property
-    def stop_time_links_gdf(self) -> gpd.GeoDataFrame:
-        """Return stop-time-links as a GeoDataFrame using set roadway geometry."""
-        ref_nodes = self.road_net.nodes_df if self.road_net is not None else None
-        return stop_times_to_stop_time_links_gdf(
-            self.feed.stop_times, self.feed.stops, ref_nodes_df=ref_nodes
-        )
-
-    @property
-    def stop_times_points_gdf(self) -> gpd.GeoDataFrame:
-        """Return stop-time-points as a GeoDataFrame using set roadway geometry."""
-        ref_nodes = self.road_net.nodes_df if self.road_net is not None else None
-
-        return stop_times_to_stop_time_points_gdf(
-            self.feed.stop_times, self.feed.stops, ref_nodes_df=ref_nodes
-        )
-
-    def get_selection(
-        self,
-        selection_dict: dict,
-        overwrite: bool = False,
-    ) -> TransitSelection:
-        """Return selection if it already exists, otherwise performs selection.
-
-        Will raise an error if no trips found.
-
-        Args:
-            selection_dict (dict): _description_
-            overwrite: if True, will overwrite any previously cached searches. Defaults to False.
-
-        Returns:
-            Selection: Selection object
-        """
-        key = dict_to_hexkey(selection_dict)
-
-        if (key not in self._selections) or overwrite:
-            WranglerLogger.debug(f"Performing selection from key: {key}")
-            self._selections[key] = TransitSelection(self, selection_dict)
-        else:
-            WranglerLogger.debug(f"Using cached selection from key: {key}")
-
-        if not self._selections[key]:
-            msg = f"No links or nodes found for selection dict: \n {selection_dict}"
-            WranglerLogger.error(msg)
-            raise TransitSelectionEmptyError(msg)
-        return self._selections[key]
-
-    def apply(self, project_card: Union[ProjectCard, dict], **kwargs) -> TransitNetwork:
-        """Wrapper method to apply a roadway project, returning a new TransitNetwork instance.
-
-        Args:
-            project_card: either a dictionary of the project card object or ProjectCard instance
-            **kwargs: keyword arguments to pass to project application
-        """
-        if not (isinstance(project_card, (ProjectCard, SubProject))):
-            project_card = ProjectCard(project_card)
-
-        if not project_card.valid:
-            msg = f"Project card {project_card.project} not valid."
-            WranglerLogger.error(msg)
-            raise ProjectCardError(msg)
-
-        if project_card._sub_projects:
-            for sp in project_card._sub_projects:
-                WranglerLogger.debug(f"- applying subproject: {sp.change_type}")
-                self._apply_change(sp, **kwargs)
-            return self
-        return self._apply_change(project_card, **kwargs)
-
-    def _apply_change(
-        self,
-        change: Union[ProjectCard, SubProject],
-        reference_road_net: Optional[RoadwayNetwork] = None,
-    ) -> TransitNetwork:
-        """Apply a single change: a single-project project or a sub-project."""
-        if not isinstance(change, SubProject):
-            WranglerLogger.info(f"Applying Project to Transit Network: {change.project}")
-
-        if change.change_type == "transit_property_change":
-            return apply_transit_property_change(
-                self,
-                self.get_selection(change.transit_property_change["service"]),
-                change.transit_property_change["property_changes"],
-                project_name=change.project,
-            )
-
-        if change.change_type == "transit_routing_change":
-            return apply_transit_routing_change(
-                self,
-                self.get_selection(change.transit_routing_change["service"]),
-                change.transit_routing_change["routing"],
-                reference_road_net=reference_road_net,
-                project_name=change.project,
-            )
-
-        if change.change_type == "pycode":
-            return apply_calculated_transit(self, change.pycode)
-
-        if change.change_type == "transit_route_addition":
-            return apply_transit_route_addition(
-                self,
-                change.transit_route_addition,
-                reference_road_net=reference_road_net,
-            )
-        if change.change_type == "transit_service_deletion":
-            return apply_transit_service_deletion(
-                self,
-                self.get_selection(change.transit_service_deletion["service"]),
-                clean_shapes=change.transit_service_deletion.get("clean_shapes"),
-                clean_routes=change.transit_service_deletion.get("clean_routes"),
-            )
-        msg = f"Not a currently valid transit project: {change}."
-        WranglerLogger.error(msg)
-        raise NotImplementedError(msg)
-
    -
    - - - -
    - - - - - - - -
    - - - -

    - applied_projects: list[str] - - - property - - -

    - - -
    - -

    List of projects applied to the network.

    -

    Note: This may or may not return a full accurate account of all the applied projects. -For better project accounting, please leverage the scenario object.

    -
    - -
    - -
    - - - -

    - consistent_with_road_net: bool - - - property - - -

    - - -
    - -

    Indicate if road_net is consistent with transit network.

    -

    Will return True if road_net is None, but provide a warning.

    -

    Checks the network hash of when consistency was last evaluated. If transit network or -roadway network has changed, will re-evaluate consistency and return the updated value and -update self._stored_road_net_hash.

    - - -

    Returns:

    - - - - - - - - - - - - - -
    TypeDescription
    - bool - -
    -

    Boolean indicating if road_net is consistent with transit network.

    -
    -
    -
    - -
    - -
    - - - -

    - feed - - - property - writable - - -

    - - -
    - -

    Feed associated with the transit network.

    -
    - -
    - -
    - - - -

    - feed_hash - - - property - - -

    - - -
    - -

    Return the hash of the feed.

    -
    - -
    - -
    - - - -

    - feed_path - - - property - - -

    - - -
    - -

    Pass through property from Feed.

    -
    - -
    - -
    - - - -

    - road_net: Union[None, RoadwayNetwork] - - - property - writable - - -

    - - -
    - -

    Roadway network associated with the transit network.

    -
    - -
    - -
    - - - - - - -
    - -

    Return shape-links as a GeoDataFrame using set roadway geometry.

    -
    - -
    - -
    - - - -

    - shapes_gdf: gpd.GeoDataFrame - - - property - - -

    - - -
    - -

    Return aggregated shapes as a GeoDataFrame using set roadway geometry.

    -
    - -
    - -
    - - - - - - -
    - -

    Return stop-time-links as a GeoDataFrame using set roadway geometry.

    -
    - -
    - -
    - - - -

    - stop_times_points_gdf: gpd.GeoDataFrame - - - property - - -

    - - -
    - -

    Return stop-time-points as a GeoDataFrame using set roadway geometry.

    -
    - -
    - -
    - - - -

    - stops_gdf: gpd.GeoDataFrame - - - property - - -

    - - -
    - -

    Return stops as a GeoDataFrame using set roadway geometry.

    -
    - -
    - - - -
    - - -

    - __deepcopy__(memo) - -

    - - -
    - -

    Returns copied TransitNetwork instance with deep copy of Feed but not roadway net.

    - -
    - Source code in network_wrangler/transit/network.py - 
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    def __deepcopy__(self, memo):
-    """Returns copied TransitNetwork instance with deep copy of Feed but not roadway net."""
-    COPY_REF_NOT_VALUE = ["_road_net"]
-    # Create a new, empty instance
-    copied_net = self.__class__.__new__(self.__class__)
-    # Return the new TransitNetwork instance
-    attribute_dict = vars(self)
-
-    # Copy the attributes to the new instance
-    for attr_name, attr_value in attribute_dict.items():
-        # WranglerLogger.debug(f"Copying {attr_name}")
-        if attr_name in COPY_REF_NOT_VALUE:
-            # If the attribute is in the COPY_REF_NOT_VALUE list, assign the reference
-            setattr(copied_net, attr_name, attr_value)
-        else:
-            # WranglerLogger.debug(f"making deep copy: {attr_name}")
-            # For other attributes, perform a deep copy
-            setattr(copied_net, attr_name, copy.deepcopy(attr_value, memo))
-
-    return copied_net
-
    -
    -
    - -
    - -
    - - -

    - __init__(feed, config=DefaultConfig) - -

    - - -
    - -

    Constructor for TransitNetwork.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    feed - Feed - -
    -

    Feed object representing the transit network gtfs tables

    -
    -     		- required -
    config - WranglerConfig - -
    -

    WranglerConfig object. Defaults to DefaultConfig.

    -
    -     		- DefaultConfig -
    - -
    - Source code in network_wrangler/transit/network.py - 
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    def __init__(self, feed: Feed, config: WranglerConfig = DefaultConfig) -> None:
-    """Constructor for TransitNetwork.
-
-    Args:
-        feed: Feed object representing the transit network gtfs tables
-        config: WranglerConfig object. Defaults to DefaultConfig.
-    """
-    WranglerLogger.debug("Creating new TransitNetwork.")
-
-    self._road_net: Optional[RoadwayNetwork] = None
-    self.feed: Feed = feed
-    self.graph: nx.MultiDiGraph = None
-    self.config: WranglerConfig = config
-    # initialize
-    self._consistent_with_road_net = False
-
-    # cached selections
-    self._selections: dict[str, TransitSelection] = {}
-
    -
    -
    - -
    - -
    - - -

    - apply(project_card, **kwargs) - -

    - - -
    - -

    Wrapper method to apply a roadway project, returning a new TransitNetwork instance.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    project_card - Union[ProjectCard, dict] - -
    -

    either a dictionary of the project card object or ProjectCard instance

    -
    -     		- required -
    **kwargs - -
    -

    keyword arguments to pass to project application

    -
    -     		- {} -
    - -
    - Source code in network_wrangler/transit/network.py - 
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    def apply(self, project_card: Union[ProjectCard, dict], **kwargs) -> TransitNetwork:
-    """Wrapper method to apply a roadway project, returning a new TransitNetwork instance.
-
-    Args:
-        project_card: either a dictionary of the project card object or ProjectCard instance
-        **kwargs: keyword arguments to pass to project application
-    """
-    if not (isinstance(project_card, (ProjectCard, SubProject))):
-        project_card = ProjectCard(project_card)
-
-    if not project_card.valid:
-        msg = f"Project card {project_card.project} not valid."
-        WranglerLogger.error(msg)
-        raise ProjectCardError(msg)
-
-    if project_card._sub_projects:
-        for sp in project_card._sub_projects:
-            WranglerLogger.debug(f"- applying subproject: {sp.change_type}")
-            self._apply_change(sp, **kwargs)
-        return self
-    return self._apply_change(project_card, **kwargs)
-
    -
    -
    - -
    - -
    - - -

    - deepcopy() - -

    - - -
    - -

    Returns copied TransitNetwork instance with deep copy of Feed but not roadway net.

    - -
    - Source code in network_wrangler/transit/network.py - 
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    def deepcopy(self):
-    """Returns copied TransitNetwork instance with deep copy of Feed but not roadway net."""
-    return copy.deepcopy(self)
-
    -
    -
    - -
    - -
    - - -

    - get_selection(selection_dict, overwrite=False) - -

    - - -
    - -

    Return selection if it already exists, otherwise performs selection.

    -

    Will raise an error if no trips found.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    selection_dict - dict - -
    -

    description

    -
    -     		- required -
    overwrite - bool - -
    -

    if True, will overwrite any previously cached searches. Defaults to False.

    -
    -     		- False -
    - - -

    Returns:

    - - - - - - - - - - - - - -
    Name TypeDescription
    Selection - TransitSelection - -
    -

    Selection object

    -
    -
    - -
    - Source code in network_wrangler/transit/network.py - 
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    def get_selection(
-    self,
-    selection_dict: dict,
-    overwrite: bool = False,
-) -> TransitSelection:
-    """Return selection if it already exists, otherwise performs selection.
-
-    Will raise an error if no trips found.
-
-    Args:
-        selection_dict (dict): _description_
-        overwrite: if True, will overwrite any previously cached searches. Defaults to False.
-
-    Returns:
-        Selection: Selection object
-    """
-    key = dict_to_hexkey(selection_dict)
-
-    if (key not in self._selections) or overwrite:
-        WranglerLogger.debug(f"Performing selection from key: {key}")
-        self._selections[key] = TransitSelection(self, selection_dict)
-    else:
-        WranglerLogger.debug(f"Using cached selection from key: {key}")
-
-    if not self._selections[key]:
-        msg = f"No links or nodes found for selection dict: \n {selection_dict}"
-        WranglerLogger.error(msg)
-        raise TransitSelectionEmptyError(msg)
-    return self._selections[key]
-
    -
    -
    - -
    - - - -
    - -
    - -
    - - - - -
    - -
    - -

    Configs

    - - -
    - - - - -
    - -

    Configuration for parameters for Network Wrangler.

    -

    Users can change a handful of parameters which control the way Wrangler runs. These parameters -can be saved as a wrangler config file which can be read in repeatedly to make sure the same -parameters are used each time.

    - - -
    - Usage -

    At runtime, you can specify configurable parameters at the scenario level which will then also -be assigned and accessible to the roadway and transit networks.

    -
    create_scenario(...config = myconfig)
-
    -

    Or if you are not using Scenario functionality, you can specify the config when you read in a -RoadwayNetwork.

    -
    load_roadway_from_dir(**roadway, config=myconfig)
-load_transit(**transit, config=myconfig)
-
    -

    my_config can be a:

    -
      -
    • Path to a config file in yaml/toml/json (recommended),
      • -
    • List of paths to config files (in case you want to split up various sub-configurations)
      • -
    • Dictionary which is in the same structure of a config file, or
      • -
    • A WranglerConfig() instance.
      • -
    -

    If not provided, Wrangler will use reasonable defaults.

    -
    Default Wrangler Configuration Values

    If not explicitly provided, the following default values are used:

    -
    IDS:
-    TRANSIT_SHAPE_ID_METHOD: scalar
-    TRANSIT_SHAPE_ID_SCALAR: 1000000
-    ROAD_SHAPE_ID_METHOD: scalar
-    ROAD_SHAPE_ID_SCALAR: 1000
-    ML_LINK_ID_METHOD: range
-    ML_LINK_ID_RANGE: (950000, 999999)
-    ML_LINK_ID_SCALAR: 15000
-    ML_NODE_ID_METHOD: range
-    ML_NODE_ID_RANGE: (950000, 999999)
-    ML_NODE_ID_SCALAR: 15000
-EDITS:
-    EXISTING_VALUE_CONFLIC: warn
-    OVERWRITE_SCOPED: conflicting
-MODEL_ROADWAY:
-    ML_OFFSET_METERS: int = -10
-    ADDITIONAL_COPY_FROM_GP_TO_ML: []
-    ADDITIONAL_COPY_TO_ACCESS_EGRESS: []
-CPU:
-    EST_PD_READ_SPEED:
-        csv: 0.03
-        parquet: 0.005
-        geojson: 0.03
-        json: 0.15
-        txt: 0.04
-
    -
    - - -
    - Extended usage -

    Load the default configuration:

    -
    from network_wrangler.configs import DefaultConfig
-
    -

    Access the configuration:

    -
    from network_wrangler.configs import DefaultConfig
-DefaultConfig.MODEL_ROADWAY.ML_OFFSET_METERS
->> -10
-
    -

    Modify the default configuration in-line:

    -
    from network_wrangler.configs import DefaultConfig
-
-DefaultConfig.MODEL_ROADWAY.ML_OFFSET_METERS = 20
-
    -

    Load a configuration from a file:

    -
    from network_wrangler.configs import load_wrangler_config
-
-config = load_wrangler_config("path/to/config.yaml")
-
    -

    Set a configuration value:

    -
    config.MODEL_ROADWAY.ML_OFFSET_METERS = 10
-
    -
    - - -
    - - - - - - - - -
    - - - -

    - CpuConfig - - -

    - - -
    -

    - Bases: ConfigItem

    - - -

    CPU Configuration - Will not change any outcomes.

    - - -

    Attributes:

    - - - - - - - - - - - - - - - -
    NameTypeDescription
    EST_PD_READ_SPEED - dict[str, float] - -
    -

    Read sec / MB - WILL DEPEND ON SPECIFIC COMPUTER

    -
    -
    - -
    - Source code in network_wrangler/configs/wrangler.py - 
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    @dataclass
-class CpuConfig(ConfigItem):
-    """CPU Configuration -  Will not change any outcomes.
-
-    Attributes:
-        EST_PD_READ_SPEED: Read sec / MB - WILL DEPEND ON SPECIFIC COMPUTER
-    """
-
-    EST_PD_READ_SPEED: dict[str, float] = Field(
-        default_factory=lambda: {
-            "csv": 0.03,
-            "parquet": 0.005,
-            "geojson": 0.03,
-            "json": 0.15,
-            "txt": 0.04,
-        }
-    )
-
    -
    - - - -
    - - - - - - - - - - - -
    - -
    - -
    - -
    - - - -

    - EditsConfig - - -

    - - -
    -

    - Bases: ConfigItem

    - - -

    Configuration for Edits.

    - - -

    Attributes:

    - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescription
    EXISTING_VALUE_CONFLICT - Literal['warn', 'error', 'skip'] - -
    -

    Only used if ‘existing’ provided in project card and -existing doesn’t match the existing network value. One of error, warn, or skip. -error will raise an error, warn will warn the user, and skip will skip the change -for that specific property (note it will still apply any remaining property changes). -Defaults to warn. Can be overridden by setting existing_value_conflict in -a roadway_property_change project card.

    -
    -
    OVERWRITE_SCOPED - Literal['conflicting', 'all', 'error'] - -
    -

    How to handle conflicts with existing values. -Should be one of “conflicting”, “all”, or False. -“conflicting” will only overwrite values where the scope only partially overlaps with -the existing value. “all” will overwrite all the scoped values. “error” will error if -there is any overlap. Default is “conflicting”. Can be changed at the project-level -by setting overwrite_scoped in a roadway_property_change project card.

    -
    -
    - -
    - Source code in network_wrangler/configs/wrangler.py - 
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    @dataclass
-class EditsConfig(ConfigItem):
-    """Configuration for Edits.
-
-    Attributes:
-        EXISTING_VALUE_CONFLICT: Only used if 'existing' provided in project card and
-            `existing` doesn't match the existing network value. One of `error`, `warn`, or `skip`.
-            `error` will raise an error, `warn` will warn the user, and `skip` will skip the change
-            for that specific property (note it will still apply any remaining property changes).
-            Defaults to `warn`. Can be overridden by setting `existing_value_conflict` in
-            a `roadway_property_change` project card.
-
-        OVERWRITE_SCOPED: How to handle conflicts with existing values.
-            Should be one of "conflicting", "all", or False.
-            "conflicting" will only overwrite values where the scope only partially overlaps with
-            the existing value. "all" will overwrite all the scoped values. "error" will error if
-            there is any overlap. Default is "conflicting". Can be changed at the project-level
-            by setting `overwrite_scoped` in a `roadway_property_change` project card.
-    """
-
-    EXISTING_VALUE_CONFLICT: Literal["warn", "error", "skip"] = "warn"
-    OVERWRITE_SCOPED: Literal["conflicting", "all", "error"] = "conflicting"
-
    -
    - - - -
    - - - - - - - - - - - -
    - -
    - -
    - -
    - - - -

    - IdGenerationConfig - - -

    - - -
    -

    - Bases: ConfigItem

    - - -

    Model Roadway Configuration.

    - - -

    Attributes:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescription
    TRANSIT_SHAPE_ID_METHOD - Literal['scalar'] - -
    -

    method for creating a shape_id for a transit shape. -Should be “scalar”.

    -
    -
    TRANSIT_SHAPE_ID_SCALAR - int - -
    -

    scalar value to add to general purpose lane to create a -shape_id for a transit shape.

    -
    -
    ROAD_SHAPE_ID_METHOD - Literal['scalar'] - -
    -

    method for creating a shape_id for a roadway shape. -Should be “scalar”.

    -
    -
    ROAD_SHAPE_ID_SCALAR - int - -
    -

    scalar value to add to general purpose lane to create a -shape_id for a roadway shape.

    -
    -
    ML_LINK_ID_METHOD - Literal['range', 'scalar'] - -
    -

    method for creating a model_link_id for an associated -link for a parallel managed lane.

    -
    -
    ML_LINK_ID_RANGE - tuple[int, int] - -
    -

    range of model_link_ids to use when creating an associated -link for a parallel managed lane.

    -
    -
    ML_LINK_ID_SCALAR - int - -
    -

    scalar value to add to general purpose lane to create a -model_link_id when creating an associated link for a parallel managed lane.

    -
    -
    ML_NODE_ID_METHOD - Literal['range', 'scalar'] - -
    -

    method for creating a model_node_id for an associated node -for a parallel managed lane.

    -
    -
    ML_NODE_ID_RANGE - tuple[int, int] - -
    -

    range of model_node_ids to use when creating an associated -node for a parallel managed lane.

    -
    -
    ML_NODE_ID_SCALAR - int - -
    -

    scalar value to add to general purpose lane node ides create -a model_node_id when creating an associated nodes for parallel managed lane.

    -
    -
    - -
    - Source code in network_wrangler/configs/wrangler.py - 
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    @dataclass
-class IdGenerationConfig(ConfigItem):
-    """Model Roadway Configuration.
-
-    Attributes:
-        TRANSIT_SHAPE_ID_METHOD: method for creating a shape_id for a transit shape.
-            Should be "scalar".
-        TRANSIT_SHAPE_ID_SCALAR: scalar value to add to general purpose lane to create a
-            shape_id for a transit shape.
-        ROAD_SHAPE_ID_METHOD: method for creating a shape_id for a roadway shape.
-            Should be "scalar".
-        ROAD_SHAPE_ID_SCALAR: scalar value to add to general purpose lane to create a
-            shape_id for a roadway shape.
-        ML_LINK_ID_METHOD: method for creating a model_link_id for an associated
-            link for a parallel managed lane.
-        ML_LINK_ID_RANGE: range of model_link_ids to use when creating an associated
-            link for a parallel managed lane.
-        ML_LINK_ID_SCALAR: scalar value to add to general purpose lane to create a
-            model_link_id when creating an associated link for a parallel managed lane.
-        ML_NODE_ID_METHOD: method for creating a model_node_id for an associated node
-            for a parallel managed lane.
-        ML_NODE_ID_RANGE: range of model_node_ids to use when creating an associated
-            node for a parallel managed lane.
-        ML_NODE_ID_SCALAR: scalar value to add to general purpose lane node ides create
-            a model_node_id when creating an associated nodes for parallel managed lane.
-    """
-
-    TRANSIT_SHAPE_ID_METHOD: Literal["scalar"] = "scalar"
-    TRANSIT_SHAPE_ID_SCALAR: int = 1000000
-    ROAD_SHAPE_ID_METHOD: Literal["scalar"] = "scalar"
-    ROAD_SHAPE_ID_SCALAR: int = 1000
-    ML_LINK_ID_METHOD: Literal["range", "scalar"] = "scalar"
-    ML_LINK_ID_RANGE: tuple[int, int] = (950000, 999999)
-    ML_LINK_ID_SCALAR: int = 3000000
-    ML_NODE_ID_METHOD: Literal["range", "scalar"] = "range"
-    ML_NODE_ID_RANGE: tuple[int, int] = (950000, 999999)
-    ML_NODE_ID_SCALAR: int = 15000
-
    -
    - - - -
    - - - - - - - - - - - -
    - -
    - -
    - -
    - - - -

    - ModelRoadwayConfig - - -

    - - -
    -

    - Bases: ConfigItem

    - - -

    Model Roadway Configuration.

    - - -

    Attributes:

    - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescription
    ML_OFFSET_METERS - int - -
    -

    Offset in meters for managed lanes.

    -
    -
    ADDITIONAL_COPY_FROM_GP_TO_ML - list[str] - -
    -

    Additional fields to copy from general purpose to managed -lanes.

    -
    -
    ADDITIONAL_COPY_TO_ACCESS_EGRESS - list[str] - -
    -

    Additional fields to copy to access and egress links.

    -
    -
    - -
    - Source code in network_wrangler/configs/wrangler.py - 
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    @dataclass
-class ModelRoadwayConfig(ConfigItem):
-    """Model Roadway Configuration.
-
-    Attributes:
-        ML_OFFSET_METERS: Offset in meters for managed lanes.
-        ADDITIONAL_COPY_FROM_GP_TO_ML: Additional fields to copy from general purpose to managed
-            lanes.
-        ADDITIONAL_COPY_TO_ACCESS_EGRESS: Additional fields to copy to access and egress links.
-    """
-
-    ML_OFFSET_METERS: int = -10
-    ADDITIONAL_COPY_FROM_GP_TO_ML: list[str] = Field(default_factory=list)
-    ADDITIONAL_COPY_TO_ACCESS_EGRESS: list[str] = Field(default_factory=list)
-
    -
    - - - -
    - - - - - - - - - - - -
    - -
    - -
    - -
    - - - -

    - WranglerConfig - - -

    - - -
    -

    - Bases: ConfigItem

    - - -

    Configuration for Network Wrangler.

    - - -

    Attributes:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescription
    IDS - IdGenerationConfig - -
    -

    Parameteters governing how new ids are generated.

    -
    -
    MODEL_ROADWAY - ModelRoadwayConfig - -
    -

    Parameters governing how the model roadway is created.

    -
    -
    CPU - CpuConfig - -
    -

    Parameters for accessing CPU information. Will not change any outcomes.

    -
    -
    EDITS - EditsConfig - -
    -

    Parameters governing how edits are handled.

    -
    -
    - -
    - Source code in network_wrangler/configs/wrangler.py - 
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    @dataclass
-class WranglerConfig(ConfigItem):
-    """Configuration for Network Wrangler.
-
-    Attributes:
-        IDS: Parameteters governing how new ids are generated.
-        MODEL_ROADWAY: Parameters governing how the model roadway is created.
-        CPU: Parameters for accessing CPU information. Will not change any outcomes.
-        EDITS: Parameters governing how edits are handled.
-    """
-
-    IDS: IdGenerationConfig = IdGenerationConfig()
-    MODEL_ROADWAY: ModelRoadwayConfig = ModelRoadwayConfig()
-    CPU: CpuConfig = CpuConfig()
-    EDITS: EditsConfig = EditsConfig()
-
    -
    - - - -
    - - - - - - - - - - - -
    - -
    - -
    - - - - -
    - -
    - -
    - -
    - - - - -
    - -

    Scenario configuration for Network Wrangler.

    -

    You can build a scenario and write out the output from a scenario configuration file using the code below. This is very useful when you are running a specific scenario with minor variations over again because you can enter your config file into version control. In addition to the completed roadway and transit files, the output will provide a record of how the scenario was run.

    - - -
    - Usage - 
        from scenario import build_scenario_from_config
-    my_scenario = build_scenario_from_config(my_scenario_config)
-
    -

    Where my_scenario_config can be a:

    -
      -
    • Path to a scenario config file in yaml/toml/json (recommended),
      • -
    • Dictionary which is in the same structure of a scenario config file, or
      • -
    • A ScenarioConfig() instance.
      • -
    -
    -

    Notes on relative paths in scenario configs

    -
      -
    • Relative paths are recognized by a preceeding “.”.
      • -
    • Relative paths within output_scenario for roadway, transit, and project_cards are interpreted to be relative to output_scenario.path.
      • -
    • All other relative paths are interpreted to be relative to directory of the scenario config file. (Or if scenario config is provided as a dictionary, relative paths will be interpreted as relative to the current working directory.)
      • -
    -
    -
    Example Scenario Config
    name: "my_scenario"
-base_scenario:
-    roadway:
-        dir: "path/to/roadway_network"
-        file_format: "geojson"
-        read_in_shapes: True
-    transit:
-        dir: "path/to/transit_network"
-        file_format: "txt"
-    applied_projects:
-        - "project1"
-        - "project2"
-    conflicts:
-        "project3": ["project1", "project2"]
-        "project4": ["project1"]
-projects:
-    project_card_filepath:
-        - "path/to/projectA.yaml"
-        - "path/to/projectB.yaml"
-    filter_tags:
-        - "tag1"
-output_scenario:
-    overwrite: True
-    roadway:
-        out_dir: "path/to/output/roadway"
-        prefix: "my_scenario"
-        file_format: "geojson"
-        true_shape: False
-    transit:
-        out_dir: "path/to/output/transit"
-        prefix: "my_scenario"
-        file_format: "txt"
-    project_cards:
-        out_dir: "path/to/output/project_cards"
-
-wrangler_config: "path/to/wrangler_config.yaml"
-
    -
    - - -
    - Extended Usage -

    Load a configuration from a file:

    -
    from network_wrangler.configs import load_scenario_config
-
-my_scenario_config = load_scenario_config("path/to/config.yaml")
-
    -

    Access the configuration:

    -
    my_scenario_config.base_transit_network.path
->> path/to/transit_network
-
    -
    - - -
    - - - - - - - - -
    - - - -

    - ProjectCardOutputConfig - - -

    - - -
    -

    - Bases: ConfigItem

    - - -

    Configuration for outputing project cards in a scenario.

    - - -

    Attributes:

    - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescription
    out_dir - -
    -

    Path to write the project card files to if you don’t want to use the default.

    -
    -
    write - -
    -

    If True, will write the project cards. Defaults to True.

    -
    -
    - -
    - Source code in network_wrangler/configs/scenario.py - 
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    class ProjectCardOutputConfig(ConfigItem):
-    """Configuration for outputing project cards in a scenario.
-
-    Attributes:
-        out_dir: Path to write the project card files to if you don't want to use the default.
-        write: If True, will write the project cards. Defaults to True.
-    """
-
-    def __init__(
-        self,
-        base_path: Path = DEFAULT_BASE_DIR,
-        out_dir: Path = DEFAULT_PROJECT_OUT_DIR,
-        write: bool = DEFAULT_PROJECT_WRITE,
-    ):
-        """Constructor for ProjectCardOutputConfig."""
-        if out_dir is not None and not Path(out_dir).is_absolute():
-            self.out_dir = (base_path / Path(out_dir)).resolve()
-        else:
-            self.out_dir = Path(out_dir)
-        self.write = write
-
    -
    - - - -
    - - - - - - - - - -
    - - -

    - __init__(base_path=DEFAULT_BASE_DIR, out_dir=DEFAULT_PROJECT_OUT_DIR, write=DEFAULT_PROJECT_WRITE) - -

    - - -
    - -

    Constructor for ProjectCardOutputConfig.

    - -
    - Source code in network_wrangler/configs/scenario.py - 
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    def __init__(
-    self,
-    base_path: Path = DEFAULT_BASE_DIR,
-    out_dir: Path = DEFAULT_PROJECT_OUT_DIR,
-    write: bool = DEFAULT_PROJECT_WRITE,
-):
-    """Constructor for ProjectCardOutputConfig."""
-    if out_dir is not None and not Path(out_dir).is_absolute():
-        self.out_dir = (base_path / Path(out_dir)).resolve()
-    else:
-        self.out_dir = Path(out_dir)
-    self.write = write
-
    -
    -
    - -
    - - - -
    - -
    - -
    - -
    - - - -

    - ProjectsConfig - - -

    - - -
    -

    - Bases: ConfigItem

    - - -

    Configuration for projects in a scenario.

    - - -

    Attributes:

    - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescription
    project_card_filepath - -
    -

    where the project card is. A single path, list of paths, -a directory, or a glob pattern. Defaults to None.

    -
    -
    filter_tags - -
    -

    List of tags to filter the project cards by.

    -
    -
    - -
    - Source code in network_wrangler/configs/scenario.py - 
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    class ProjectsConfig(ConfigItem):
-    """Configuration for projects in a scenario.
-
-    Attributes:
-        project_card_filepath: where the project card is.  A single path, list of paths,
-            a directory, or a glob pattern. Defaults to None.
-        filter_tags: List of tags to filter the project cards by.
-    """
-
-    def __init__(
-        self,
-        base_path: Path = DEFAULT_BASE_DIR,
-        project_card_filepath: ProjectCardFilepaths = DEFAULT_PROJECT_IN_PATHS,
-        filter_tags: list[str] = DEFAULT_PROJECT_TAGS,
-    ):
-        """Constructor for ProjectsConfig."""
-        self.project_card_filepath = _resolve_rel_paths(project_card_filepath, base_path=base_path)
-        self.filter_tags = filter_tags
-
    -
    - - - -
    - - - - - - - - - -
    - - -

    - __init__(base_path=DEFAULT_BASE_DIR, project_card_filepath=DEFAULT_PROJECT_IN_PATHS, filter_tags=DEFAULT_PROJECT_TAGS) - -

    - - -
    - -

    Constructor for ProjectsConfig.

    - -
    - Source code in network_wrangler/configs/scenario.py - 
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    def __init__(
-    self,
-    base_path: Path = DEFAULT_BASE_DIR,
-    project_card_filepath: ProjectCardFilepaths = DEFAULT_PROJECT_IN_PATHS,
-    filter_tags: list[str] = DEFAULT_PROJECT_TAGS,
-):
-    """Constructor for ProjectsConfig."""
-    self.project_card_filepath = _resolve_rel_paths(project_card_filepath, base_path=base_path)
-    self.filter_tags = filter_tags
-
    -
    -
    - -
    - - - -
    - -
    - -
    - -
    - - - -

    - RoadwayNetworkInputConfig - - -

    - - -
    -

    - Bases: ConfigItem

    - - -

    Configuration for the road network in a scenario.

    - - -

    Attributes:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescription
    dir - -
    -

    Path to directory with roadway network files.

    -
    -
    file_format - -
    -

    File format for the roadway network files. Should be one of RoadwayFileTypes. -Defaults to “geojson”.

    -
    -
    read_in_shapes - -
    -

    If True, will read in the shapes of the roadway network. Defaults to False.

    -
    -
    boundary_geocode - -
    -

    Geocode of the boundary. Will use this to filter the roadway network.

    -
    -
    boundary_file - -
    -

    Path to the boundary file. If provided and both boundary_gdf and -boundary_geocode are not provided, will use this to filter the roadway network.

    -
    -
    - -
    - Source code in network_wrangler/configs/scenario.py - 
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    class RoadwayNetworkInputConfig(ConfigItem):
-    """Configuration for the road network in a scenario.
-
-    Attributes:
-        dir: Path to directory with roadway network files.
-        file_format: File format for the roadway network files. Should be one of RoadwayFileTypes.
-            Defaults to "geojson".
-        read_in_shapes: If True, will read in the shapes of the roadway network. Defaults to False.
-        boundary_geocode: Geocode of the boundary. Will use this to filter the roadway network.
-        boundary_file: Path to the boundary file. If provided and both boundary_gdf and
-            boundary_geocode are not provided, will use this to filter the roadway network.
-    """
-
-    def __init__(
-        self,
-        base_path: Path = DEFAULT_BASE_DIR,
-        dir: Path = DEFAULT_ROADWAY_IN_DIR,
-        file_format: RoadwayFileTypes = DEFAULT_ROADWAY_IN_FORMAT,
-        read_in_shapes: bool = DEFAULT_ROADWAY_SHAPE_READ,
-        boundary_geocode: Optional[str] = None,
-        boundary_file: Optional[Path] = None,
-    ):
-        """Constructor for RoadwayNetworkInputConfig."""
-        if dir is not None and not Path(dir).is_absolute():
-            self.dir = (base_path / Path(dir)).resolve()
-        else:
-            self.dir = Path(dir)
-        self.file_format = file_format
-        self.read_in_shapes = read_in_shapes
-        self.boundary_geocode = boundary_geocode
-        self.boundary_file = boundary_file
-
    -
    - - - -
    - - - - - - - - - -
    - - -

    - __init__(base_path=DEFAULT_BASE_DIR, dir=DEFAULT_ROADWAY_IN_DIR, file_format=DEFAULT_ROADWAY_IN_FORMAT, read_in_shapes=DEFAULT_ROADWAY_SHAPE_READ, boundary_geocode=None, boundary_file=None) - -

    - - -
    - -

    Constructor for RoadwayNetworkInputConfig.

    - -
    - Source code in network_wrangler/configs/scenario.py - 
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    def __init__(
-    self,
-    base_path: Path = DEFAULT_BASE_DIR,
-    dir: Path = DEFAULT_ROADWAY_IN_DIR,
-    file_format: RoadwayFileTypes = DEFAULT_ROADWAY_IN_FORMAT,
-    read_in_shapes: bool = DEFAULT_ROADWAY_SHAPE_READ,
-    boundary_geocode: Optional[str] = None,
-    boundary_file: Optional[Path] = None,
-):
-    """Constructor for RoadwayNetworkInputConfig."""
-    if dir is not None and not Path(dir).is_absolute():
-        self.dir = (base_path / Path(dir)).resolve()
-    else:
-        self.dir = Path(dir)
-    self.file_format = file_format
-    self.read_in_shapes = read_in_shapes
-    self.boundary_geocode = boundary_geocode
-    self.boundary_file = boundary_file
-
    -
    -
    - -
    - - - -
    - -
    - -
    - -
    - - - -

    - RoadwayNetworkOutputConfig - - -

    - - -
    -

    - Bases: ConfigItem

    - - -

    Configuration for writing out the resulting roadway network for a scenario.

    - - -

    Attributes:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescription
    out_dir - -
    -

    Path to write the roadway network files to if you don’t want to use the default.

    -
    -
    prefix - -
    -

    Prefix to add to the file name. If not provided will use the scenario name.

    -
    -
    file_format - -
    -

    File format to write the roadway network to. Should be one of -RoadwayFileTypes. Defaults to “geojson”.

    -
    -
    true_shape - -
    -

    If True, will write the true shape of the roadway network. Defaults to False.

    -
    -
    write - -
    -

    If True, will write the roadway network. Defaults to True.

    -
    -
    - -
    - Source code in network_wrangler/configs/scenario.py - 
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    class RoadwayNetworkOutputConfig(ConfigItem):
-    """Configuration for writing out the resulting roadway network for a scenario.
-
-    Attributes:
-        out_dir: Path to write the roadway network files to if you don't want to use the default.
-        prefix: Prefix to add to the file name. If not provided will use the scenario name.
-        file_format: File format to write the roadway network to. Should be one of
-            RoadwayFileTypes. Defaults to "geojson".
-        true_shape: If True, will write the true shape of the roadway network. Defaults to False.
-        write: If True, will write the roadway network. Defaults to True.
-    """
-
-    def __init__(
-        self,
-        out_dir: Path = DEFAULT_ROADWAY_OUT_DIR,
-        base_path: Path = DEFAULT_BASE_DIR,
-        convert_complex_link_properties_to_single_field: bool = False,
-        prefix: Optional[str] = None,
-        file_format: RoadwayFileTypes = DEFAULT_ROADWAY_OUT_FORMAT,
-        true_shape: bool = False,
-        write: bool = DEFAULT_ROADWAY_WRITE,
-    ):
-        """Constructor for RoadwayNetworkOutputConfig."""
-        if out_dir is not None and not Path(out_dir).is_absolute():
-            self.out_dir = (base_path / Path(out_dir)).resolve()
-        else:
-            self.out_dir = Path(out_dir)
-
-        self.convert_complex_link_properties_to_single_field = (
-            convert_complex_link_properties_to_single_field
-        )
-        self.prefix = prefix
-        self.file_format = file_format
-        self.true_shape = true_shape
-        self.write = write
-
    -
    - - - -
    - - - - - - - - - -
    - - -

    - __init__(out_dir=DEFAULT_ROADWAY_OUT_DIR, base_path=DEFAULT_BASE_DIR, convert_complex_link_properties_to_single_field=False, prefix=None, file_format=DEFAULT_ROADWAY_OUT_FORMAT, true_shape=False, write=DEFAULT_ROADWAY_WRITE) - -

    - - -
    - -

    Constructor for RoadwayNetworkOutputConfig.

    - -
    - Source code in network_wrangler/configs/scenario.py - 
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    def __init__(
-    self,
-    out_dir: Path = DEFAULT_ROADWAY_OUT_DIR,
-    base_path: Path = DEFAULT_BASE_DIR,
-    convert_complex_link_properties_to_single_field: bool = False,
-    prefix: Optional[str] = None,
-    file_format: RoadwayFileTypes = DEFAULT_ROADWAY_OUT_FORMAT,
-    true_shape: bool = False,
-    write: bool = DEFAULT_ROADWAY_WRITE,
-):
-    """Constructor for RoadwayNetworkOutputConfig."""
-    if out_dir is not None and not Path(out_dir).is_absolute():
-        self.out_dir = (base_path / Path(out_dir)).resolve()
-    else:
-        self.out_dir = Path(out_dir)
-
-    self.convert_complex_link_properties_to_single_field = (
-        convert_complex_link_properties_to_single_field
-    )
-    self.prefix = prefix
-    self.file_format = file_format
-    self.true_shape = true_shape
-    self.write = write
-
    -
    -
    - -
    - - - -
    - -
    - -
    - -
    - - - -

    - ScenarioConfig - - -

    - - -
    -

    - Bases: ConfigItem

    - - -

    Scenario configuration for Network Wrangler.

    - - -

    Attributes:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescription
    base_path - -
    -

    base path of the scenario. Defaults to cwd.

    -
    -
    name - -
    -

    Name of the scenario.

    -
    -
    base_scenario - -
    -

    information about the base scenario

    -
    -
    projects - -
    -

    information about the projects to apply on top of the base scenario

    -
    -
    output_scenario - -
    -

    information about how to output the scenario

    -
    -
    wrangler_config - -
    -

    wrangler configuration to use

    -
    -
    - -
    - Source code in network_wrangler/configs/scenario.py - 
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    class ScenarioConfig(ConfigItem):
-    """Scenario configuration for Network Wrangler.
-
-    Attributes:
-        base_path: base path of the scenario. Defaults to cwd.
-        name: Name of the scenario.
-        base_scenario: information about the base scenario
-        projects: information about the projects to apply on top of the base scenario
-        output_scenario: information about how to output the scenario
-        wrangler_config: wrangler configuration to use
-    """
-
-    def __init__(
-        self,
-        base_scenario: dict,
-        projects: dict,
-        output_scenario: dict,
-        base_path: Path = DEFAULT_BASE_DIR,
-        name: str = DEFAULT_SCENARIO_NAME,
-        wrangler_config=DefaultConfig,
-    ):
-        """Constructor for ScenarioConfig."""
-        self.base_path = Path(base_path) if base_path is not None else Path.cwd()
-        self.name = name
-        self.base_scenario = ScenarioInputConfig(**base_scenario, base_path=base_path)
-        self.projects = ProjectsConfig(**projects, base_path=base_path)
-        self.output_scenario = ScenarioOutputConfig(**output_scenario, base_path=base_path)
-        self.wrangler_config = wrangler_config
-
    -
    - - - -
    - - - - - - - - - -
    - - -

    - __init__(base_scenario, projects, output_scenario, base_path=DEFAULT_BASE_DIR, name=DEFAULT_SCENARIO_NAME, wrangler_config=DefaultConfig) - -

    - - -
    - -

    Constructor for ScenarioConfig.

    - -
    - Source code in network_wrangler/configs/scenario.py - 
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    def __init__(
-    self,
-    base_scenario: dict,
-    projects: dict,
-    output_scenario: dict,
-    base_path: Path = DEFAULT_BASE_DIR,
-    name: str = DEFAULT_SCENARIO_NAME,
-    wrangler_config=DefaultConfig,
-):
-    """Constructor for ScenarioConfig."""
-    self.base_path = Path(base_path) if base_path is not None else Path.cwd()
-    self.name = name
-    self.base_scenario = ScenarioInputConfig(**base_scenario, base_path=base_path)
-    self.projects = ProjectsConfig(**projects, base_path=base_path)
-    self.output_scenario = ScenarioOutputConfig(**output_scenario, base_path=base_path)
-    self.wrangler_config = wrangler_config
-
    -
    -
    - -
    - - - -
    - -
    - -
    - -
    - - - -

    - ScenarioInputConfig - - -

    - - -
    -

    - Bases: ConfigItem

    - - -

    Configuration for the writing the output of a scenario.

    - - -

    Attributes:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescription
    roadway - Optional[RoadwayNetworkInputConfig] - -
    -

    Configuration for writing out the roadway network.

    -
    -
    transit - Optional[TransitNetworkInputConfig] - -
    -

    Configuration for writing out the transit network.

    -
    -
    applied_projects - -
    -

    List of projects to apply to the base scenario.

    -
    -
    conflicts - -
    -

    Dict of projects that conflict with the applied_projects.

    -
    -
    - -
    - Source code in network_wrangler/configs/scenario.py - 
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    class ScenarioInputConfig(ConfigItem):
-    """Configuration for the writing the output of a scenario.
-
-    Attributes:
-        roadway: Configuration for writing out the roadway network.
-        transit: Configuration for writing out the transit network.
-        applied_projects: List of projects to apply to the base scenario.
-        conflicts: Dict of projects that conflict with the applied_projects.
-    """
-
-    def __init__(
-        self,
-        base_path: Path = DEFAULT_BASE_DIR,
-        roadway: Optional[dict] = None,
-        transit: Optional[dict] = None,
-        applied_projects: Optional[list[str]] = None,
-        conflicts: Optional[dict] = None,
-    ):
-        """Constructor for ScenarioInputConfig."""
-        if roadway is not None:
-            self.roadway: Optional[RoadwayNetworkInputConfig] = RoadwayNetworkInputConfig(
-                **roadway, base_path=base_path
-            )
-        else:
-            self.roadway = None
-
-        if transit is not None:
-            self.transit: Optional[TransitNetworkInputConfig] = TransitNetworkInputConfig(
-                **transit, base_path=base_path
-            )
-        else:
-            self.transit = None
-
-        self.applied_projects = applied_projects if applied_projects is not None else []
-        self.conflicts = conflicts if conflicts is not None else {}
-
    -
    - - - -
    - - - - - - - - - -
    - - -

    - __init__(base_path=DEFAULT_BASE_DIR, roadway=None, transit=None, applied_projects=None, conflicts=None) - -

    - - -
    - -

    Constructor for ScenarioInputConfig.

    - -
    - Source code in network_wrangler/configs/scenario.py - 
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    def __init__(
-    self,
-    base_path: Path = DEFAULT_BASE_DIR,
-    roadway: Optional[dict] = None,
-    transit: Optional[dict] = None,
-    applied_projects: Optional[list[str]] = None,
-    conflicts: Optional[dict] = None,
-):
-    """Constructor for ScenarioInputConfig."""
-    if roadway is not None:
-        self.roadway: Optional[RoadwayNetworkInputConfig] = RoadwayNetworkInputConfig(
-            **roadway, base_path=base_path
-        )
-    else:
-        self.roadway = None
-
-    if transit is not None:
-        self.transit: Optional[TransitNetworkInputConfig] = TransitNetworkInputConfig(
-            **transit, base_path=base_path
-        )
-    else:
-        self.transit = None
-
-    self.applied_projects = applied_projects if applied_projects is not None else []
-    self.conflicts = conflicts if conflicts is not None else {}
-
    -
    -
    - -
    - - - -
    - -
    - -
    - -
    - - - -

    - ScenarioOutputConfig - - -

    - - -
    -

    - Bases: ConfigItem

    - - -

    Configuration for the writing the output of a scenario.

    - - -

    Attributes:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescription
    roadway - -
    -

    Configuration for writing out the roadway network.

    -
    -
    transit - -
    -

    Configuration for writing out the transit network.

    -
    -
    project_cards - Optional[ProjectCardOutputConfig] - -
    -

    Configuration for writing out the project cards.

    -
    -
    overwrite - -
    -

    If True, will overwrite the files if they already exist. Defaults to True

    -
    -
    - -
    - Source code in network_wrangler/configs/scenario.py - 
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    class ScenarioOutputConfig(ConfigItem):
-    """Configuration for the writing the output of a scenario.
-
-    Attributes:
-        roadway: Configuration for writing out the roadway network.
-        transit: Configuration for writing out the transit network.
-        project_cards: Configuration for writing out the project cards.
-        overwrite: If True, will overwrite the files if they already exist. Defaults to True
-    """
-
-    def __init__(
-        self,
-        path: Path = DEFAULT_OUTPUT_DIR,
-        base_path: Path = DEFAULT_BASE_DIR,
-        roadway: Optional[dict] = None,
-        transit: Optional[dict] = None,
-        project_cards: Optional[dict] = None,
-        overwrite: bool = True,
-    ):
-        """Constructor for ScenarioOutputConfig."""
-        if not Path(path).is_absolute():
-            self.path = (base_path / Path(path)).resolve()
-        else:
-            self.path = Path(path)
-
-        roadway = roadway if roadway else RoadwayNetworkOutputConfig().to_dict()
-        transit = transit if transit else TransitNetworkOutputConfig().to_dict()
-        self.roadway = RoadwayNetworkOutputConfig(**roadway, base_path=self.path)
-        self.transit = TransitNetworkOutputConfig(**transit, base_path=self.path)
-
-        if project_cards is not None:
-            self.project_cards: Optional[ProjectCardOutputConfig] = ProjectCardOutputConfig(
-                **project_cards, base_path=self.path
-            )
-        else:
-            self.project_cards = None
-
-        self.overwrite = overwrite
-
    -
    - - - -
    - - - - - - - - - -
    - - -

    - __init__(path=DEFAULT_OUTPUT_DIR, base_path=DEFAULT_BASE_DIR, roadway=None, transit=None, project_cards=None, overwrite=True) - -

    - - -
    - -

    Constructor for ScenarioOutputConfig.

    - -
    - Source code in network_wrangler/configs/scenario.py - 
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    def __init__(
-    self,
-    path: Path = DEFAULT_OUTPUT_DIR,
-    base_path: Path = DEFAULT_BASE_DIR,
-    roadway: Optional[dict] = None,
-    transit: Optional[dict] = None,
-    project_cards: Optional[dict] = None,
-    overwrite: bool = True,
-):
-    """Constructor for ScenarioOutputConfig."""
-    if not Path(path).is_absolute():
-        self.path = (base_path / Path(path)).resolve()
-    else:
-        self.path = Path(path)
-
-    roadway = roadway if roadway else RoadwayNetworkOutputConfig().to_dict()
-    transit = transit if transit else TransitNetworkOutputConfig().to_dict()
-    self.roadway = RoadwayNetworkOutputConfig(**roadway, base_path=self.path)
-    self.transit = TransitNetworkOutputConfig(**transit, base_path=self.path)
-
-    if project_cards is not None:
-        self.project_cards: Optional[ProjectCardOutputConfig] = ProjectCardOutputConfig(
-            **project_cards, base_path=self.path
-        )
-    else:
-        self.project_cards = None
-
-    self.overwrite = overwrite
-
    -
    -
    - -
    - - - -
    - -
    - -
    - -
    - - - -

    - TransitNetworkInputConfig - - -

    - - -
    -

    - Bases: ConfigItem

    - - -

    Configuration for the transit network in a scenario.

    - - -

    Attributes:

    - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescription
    dir - -
    -

    Path to the transit network files. Defaults to “.”.

    -
    -
    file_format - -
    -

    File format for the transit network files. Should be one of TransitFileTypes. -Defaults to “txt”.

    -
    -
    - -
    - Source code in network_wrangler/configs/scenario.py - 
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    class TransitNetworkInputConfig(ConfigItem):
-    """Configuration for the transit network in a scenario.
-
-    Attributes:
-        dir: Path to the transit network files. Defaults to ".".
-        file_format: File format for the transit network files. Should be one of TransitFileTypes.
-            Defaults to "txt".
-    """
-
-    def __init__(
-        self,
-        base_path: Path = DEFAULT_BASE_DIR,
-        dir: Path = DEFAULT_TRANSIT_IN_DIR,
-        file_format: TransitFileTypes = DEFAULT_TRANSIT_IN_FORMAT,
-    ):
-        """Constructor for TransitNetworkInputConfig."""
-        if dir is not None and not Path(dir).is_absolute():
-            self.feed = (base_path / Path(dir)).resolve()
-        else:
-            self.feed = Path(dir)
-        self.file_format = file_format
-
    -
    - - - -
    - - - - - - - - - -
    - - -

    - __init__(base_path=DEFAULT_BASE_DIR, dir=DEFAULT_TRANSIT_IN_DIR, file_format=DEFAULT_TRANSIT_IN_FORMAT) - -

    - - -
    - -

    Constructor for TransitNetworkInputConfig.

    - -
    - Source code in network_wrangler/configs/scenario.py - 
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    def __init__(
-    self,
-    base_path: Path = DEFAULT_BASE_DIR,
-    dir: Path = DEFAULT_TRANSIT_IN_DIR,
-    file_format: TransitFileTypes = DEFAULT_TRANSIT_IN_FORMAT,
-):
-    """Constructor for TransitNetworkInputConfig."""
-    if dir is not None and not Path(dir).is_absolute():
-        self.feed = (base_path / Path(dir)).resolve()
-    else:
-        self.feed = Path(dir)
-    self.file_format = file_format
-
    -
    -
    - -
    - - - -
    - -
    - -
    - -
    - - - -

    - TransitNetworkOutputConfig - - -

    - - -
    -

    - Bases: ConfigItem

    - - -

    Configuration for the transit network in a scenario.

    - - -

    Attributes:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescription
    out_dir - -
    -

    Path to write the transit network files to if you don’t want to use the default.

    -
    -
    prefix - -
    -

    Prefix to add to the file name. If not provided will use the scenario name.

    -
    -
    file_format - -
    -

    File format to write the transit network to. Should be one of -TransitFileTypes. Defaults to “txt”.

    -
    -
    write - -
    -

    If True, will write the transit network. Defaults to True.

    -
    -
    - -
    - Source code in network_wrangler/configs/scenario.py - 
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    class TransitNetworkOutputConfig(ConfigItem):
-    """Configuration for the transit network in a scenario.
-
-    Attributes:
-        out_dir: Path to write the transit network files to if you don't want to use the default.
-        prefix: Prefix to add to the file name. If not provided will use the scenario name.
-        file_format: File format to write the transit network to. Should be one of
-            TransitFileTypes. Defaults to "txt".
-        write: If True, will write the transit network. Defaults to True.
-    """
-
-    def __init__(
-        self,
-        base_path: Path = DEFAULT_BASE_DIR,
-        out_dir: Path = DEFAULT_TRANSIT_OUT_DIR,
-        prefix: Optional[str] = None,
-        file_format: TransitFileTypes = DEFAULT_TRANSIT_OUT_FORMAT,
-        write: bool = DEFAULT_TRANSIT_WRITE,
-    ):
-        """Constructor for TransitNetworkOutputCOnfig."""
-        if out_dir is not None and not Path(out_dir).is_absolute():
-            self.out_dir = (base_path / Path(out_dir)).resolve()
-        else:
-            self.out_dir = Path(out_dir)
-        self.write = write
-        self.prefix = prefix
-        self.file_format = file_format
-
    -
    - - - -
    - - - - - - - - - -
    - - -

    - __init__(base_path=DEFAULT_BASE_DIR, out_dir=DEFAULT_TRANSIT_OUT_DIR, prefix=None, file_format=DEFAULT_TRANSIT_OUT_FORMAT, write=DEFAULT_TRANSIT_WRITE) - -

    - - -
    - -

    Constructor for TransitNetworkOutputCOnfig.

    - -
    - Source code in network_wrangler/configs/scenario.py - 
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    def __init__(
-    self,
-    base_path: Path = DEFAULT_BASE_DIR,
-    out_dir: Path = DEFAULT_TRANSIT_OUT_DIR,
-    prefix: Optional[str] = None,
-    file_format: TransitFileTypes = DEFAULT_TRANSIT_OUT_FORMAT,
-    write: bool = DEFAULT_TRANSIT_WRITE,
-):
-    """Constructor for TransitNetworkOutputCOnfig."""
-    if out_dir is not None and not Path(out_dir).is_absolute():
-        self.out_dir = (base_path / Path(out_dir)).resolve()
-    else:
-        self.out_dir = Path(out_dir)
-    self.write = write
-    self.prefix = prefix
-    self.file_format = file_format
-
    -
    -
    - -
    - - - -
    - -
    - -
    - - - - -
    - -
    - -

    Projects

    -

    Projects are how you manipulate the networks. Each project type is defined in a module in the projects folder and accepts a RoadwayNetwork and or TransitNetwork as an input and returns the same objects (manipulated) as an output.

    -

    Roadway

    -

    The roadway module contains submodules which define and extend the links, nodes, and shapes dataframe objects which within a RoadwayNetwork object as well as other classes and methods which support and extend the RoadwayNetwork class.

    -

    Roadway Network Objects

    -

    Submodules which define and extend the links, nodes, and shapes dataframe objects which within a RoadwayNetwork object. Includes classes which define:

    - - -

    :: network_wrangler.roadway.links.io - options: - heading_level: 5 -:: network_wrangler.roadway.links.create - options: - heading_level: 5 -:: network_wrangler.roadway.links.delete - options: - heading_level: 5 -:: network_wrangler.roadway.links.edit - options: - heading_level: 5 -:: network_wrangler.roadway.links.filters - options: - heading_level: 5 -:: network_wrangler.roadway.links.geo - options: - heading_level: 5 -:: network_wrangler.roadway.links.scopes - options: - heading_level: 5 -:: network_wrangler.roadway.links.summary - options: - heading_level: 5 -:: network_wrangler.roadway.links.validate - options: - heading_level: 5 -:: network_wrangler.roadway.links.df_accessors - options: - heading_level: 5

    -

    Roadway Nodes

    -

    :: network_wrangler.roadway.nodes.io - options: - heading_level: 5 -:: network_wrangler.roadway.nodes.create - options: - heading_level: 5 -:: network_wrangler.roadway.nodes.delete - options: - heading_level: 5 -:: network_wrangler.roadway.nodes.edit - options: - heading_level: 5 -:: network_wrangler.roadway.nodes.filters - options: - heading_level: 5 -:: network_wrangler.roadway.nodes - options: - heading_level: 5

    -

    Roadway Shapes

    -

    :: network_wrangler.roadway.shapes.io - options: - heading_level: 5 -:: network_wrangler.roadway.shapes.create - options: - heading_level: 5 -:: network_wrangler.roadway.shapes.edit - options: - heading_level: 5 -:: network_wrangler.roadway.shapes.delete - options: - heading_level: 5 -:: network_wrangler.roadway.shapes.filters - options: - heading_level: 5 -:: network_wrangler.roadway.shapes.shapes - options: - heading_level: 5

    -

    Roadway Projects

    -

    :: network_wrangler.roadway.projects.add - options: - heading_level: 4 -:: network_wrangler.roadway.projects.calculate - options: - heading_level: 4 -:: network_wrangler.roadway.projects.delete - options: - heading_level: 4 -:: network_wrangler.roadway.projects.edit_property - options: - heading_level: 4

    -

    Roadway Supporting Modules

    -

    :: network_wrangler.roadway.io - options: - heading_level: 4 -:: network_wrangler.roadway.clip - options: - heading_level: 4 -:: network_wrangler.roadway.model_roadway - options: - heading_level: 4 -:: network_wrangler.roadway.utils - options: - heading_level: 4 -:: network_wrangler.roadway.validate - options: - heading_level: 4 -:: network_wrangler.roadway.segment - options: - heading_level: 4 -:: network_wrangler.roadway.subnet - options: - heading_level: 4 -:: network_wrangler.roadway.graph - options: - heading_level: 4

    -

    Transit

    -

    Feed

    - - -
    - - - - -
    - -

    Main functionality for GTFS tables including Feed object.

    - - - -
    - - - - - - - - -
    - - - -

    - Feed - - -

    - - -
    -

    - Bases: DBModelMixin

    - - -

    Wrapper class around Wrangler flavored GTFS feed.

    -

    Most functionality derives from mixin class DBModelMixin which provides:

    -
      -
    • validation of tables to schemas when setting a table attribute (e.g. self.trips = trips_df)
      • -
    • validation of fks when setting a table attribute (e.g. self.trips = trips_df)
      • -
    • hashing and deep copy functionality
      • -
    • overload of eq to apply only to tables in table_names.
      • -
    • convenience methods for accessing tables
      • -
    - - -

    Attributes:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescription
    table_names - list[str] - -
    -

    list of table names in GTFS feed.

    -
    -
    tables - list[DataFrame] - -
    -

    : list tables as dataframes.

    -
    -
    stop_times - DataFrame[WranglerStopTimesTable] - -
    -

    : stop_times dataframe with roadway node_ids

    -
    -
    stops - DataFrame[WranglerStopsTable] - -
    -

    stops dataframe

    -
    -
    shapes(DataFrame[WranglerShapesTable]) - DataFrame[WranglerStopsTable] - -
    -

    shapes dataframe

    -
    -
    trips - DataFrame[WranglerTripsTable] - -
    -

    trips dataframe

    -
    -
    frequencies - DataFrame[WranglerFrequenciesTable] - -
    -

    frequencies dataframe

    -
    -
    routes - DataFrame[RoutesTable] - -
    -

    route dataframe

    -
    -
    agencies - Optional[DataFrame[AgenciesTable]] - -
    -

    agencies dataframe

    -
    -
    net - Optional[TransitNetwork] - -
    -

    TransitNetwork object

    -
    -
    - -
    - Source code in network_wrangler/transit/feed/feed.py - 
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    class Feed(DBModelMixin):
-    """Wrapper class around Wrangler flavored GTFS feed.
-
-    Most functionality derives from mixin class DBModelMixin which provides:
-
-    - validation of tables to schemas when setting a table attribute (e.g. self.trips = trips_df)
-    - validation of fks when setting a table attribute (e.g. self.trips = trips_df)
-    - hashing and deep copy functionality
-    - overload of __eq__ to apply only to tables in table_names.
-    - convenience methods for accessing tables
-
-    Attributes:
-        table_names (list[str]): list of table names in GTFS feed.
-        tables (list[DataFrame]):: list tables as dataframes.
-        stop_times (DataFrame[WranglerStopTimesTable]):: stop_times dataframe with roadway node_ids
-        stops (DataFrame[WranglerStopsTable]):stops dataframe
-        shapes(DataFrame[WranglerShapesTable]): shapes dataframe
-        trips (DataFrame[WranglerTripsTable]): trips dataframe
-        frequencies (DataFrame[WranglerFrequenciesTable]): frequencies dataframe
-        routes (DataFrame[RoutesTable]): route dataframe
-        agencies (Optional[DataFrame[AgenciesTable]]): agencies dataframe
-        net (Optional[TransitNetwork]): TransitNetwork object
-    """
-
-    # the ordering here matters because the stops need to be added before stop_times if
-    # stop times needs to be converted
-    _table_models: ClassVar[dict] = {
-        "agencies": AgenciesTable,
-        "frequencies": WranglerFrequenciesTable,
-        "routes": RoutesTable,
-        "shapes": WranglerShapesTable,
-        "stops": WranglerStopsTable,
-        "trips": WranglerTripsTable,
-        "stop_times": WranglerStopTimesTable,
-    }
-
-    # Define the converters if the table needs to be converted to a Wrangler table.
-    # Format: "table_name": converter_function
-    _converters: ClassVar[dict[str, Callable]] = {}
-
-    table_names: ClassVar[list[str]] = [
-        "frequencies",
-        "routes",
-        "shapes",
-        "stops",
-        "trips",
-        "stop_times",
-    ]
-
-    optional_table_names: ClassVar[list[str]] = ["agencies"]
-
-    def __init__(self, **kwargs):
-        """Create a Feed object from a dictionary of DataFrames representing a GTFS feed.
-
-        Args:
-            kwargs: A dictionary containing DataFrames representing the tables of a GTFS feed.
-        """
-        self._net = None
-        self.feed_path: Path = None
-        self.initialize_tables(**kwargs)
-
-        # Set extra provided attributes but just FYI in logger.
-        extra_attr = {k: v for k, v in kwargs.items() if k not in self.table_names}
-        if extra_attr:
-            WranglerLogger.info(f"Adding additional attributes to Feed: {extra_attr.keys()}")
-        for k, v in extra_attr:
-            self.__setattr__(k, v)
-
-    def set_by_id(
-        self,
-        table_name: str,
-        set_df: pd.DataFrame,
-        id_property: str = "index",
-        properties: Optional[list[str]] = None,
-    ):
-        """Set one or more property values based on an ID property for a given table.
-
-        Args:
-            table_name (str): Name of the table to modify.
-            set_df (pd.DataFrame): DataFrame with columns `<id_property>` and `value` containing
-                values to set for the specified property where `<id_property>` is unique.
-            id_property: Property to use as ID to set by. Defaults to "index".
-            properties: List of properties to set which are in set_df. If not specified, will set
-                all properties.
-        """
-        if not set_df[id_property].is_unique:
-            msg = f"{id_property} must be unique in set_df."
-            _dupes = set_df[id_property][set_df[id_property].duplicated()]
-            WranglerLogger.error(msg + f"Found duplicates: {_dupes.sum()}")
-
-            raise ValueError(msg)
-        table_df = self.get_table(table_name)
-        updated_df = update_df_by_col_value(table_df, set_df, id_property, properties=properties)
-        self.__dict__[table_name] = updated_df
-
    -
    - - - -
    - - - - - - - - - -
    - - -
    - __init__(**kwargs) - -
    - - -
    - -

    Create a Feed object from a dictionary of DataFrames representing a GTFS feed.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    kwargs - -
    -

    A dictionary containing DataFrames representing the tables of a GTFS feed.

    -
    -     		- {} -
    - -
    - Source code in network_wrangler/transit/feed/feed.py - 
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    def __init__(self, **kwargs):
-    """Create a Feed object from a dictionary of DataFrames representing a GTFS feed.
-
-    Args:
-        kwargs: A dictionary containing DataFrames representing the tables of a GTFS feed.
-    """
-    self._net = None
-    self.feed_path: Path = None
-    self.initialize_tables(**kwargs)
-
-    # Set extra provided attributes but just FYI in logger.
-    extra_attr = {k: v for k, v in kwargs.items() if k not in self.table_names}
-    if extra_attr:
-        WranglerLogger.info(f"Adding additional attributes to Feed: {extra_attr.keys()}")
-    for k, v in extra_attr:
-        self.__setattr__(k, v)
-
    -
    -
    - -
    - -
    - - -
    - set_by_id(table_name, set_df, id_property='index', properties=None) - -
    - - -
    - -

    Set one or more property values based on an ID property for a given table.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    table_name - str - -
    -

    Name of the table to modify.

    -
    -     		- required -
    set_df - DataFrame - -
    -

    DataFrame with columns <id_property> and value containing -values to set for the specified property where <id_property> is unique.

    -
    -     		- required -
    id_property - str - -
    -

    Property to use as ID to set by. Defaults to “index”.

    -
    -     		- 'index' -
    properties - Optional[list[str]] - -
    -

    List of properties to set which are in set_df. If not specified, will set -all properties.

    -
    -     		- None -
    - -
    - Source code in network_wrangler/transit/feed/feed.py - 
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    def set_by_id(
-    self,
-    table_name: str,
-    set_df: pd.DataFrame,
-    id_property: str = "index",
-    properties: Optional[list[str]] = None,
-):
-    """Set one or more property values based on an ID property for a given table.
-
-    Args:
-        table_name (str): Name of the table to modify.
-        set_df (pd.DataFrame): DataFrame with columns `<id_property>` and `value` containing
-            values to set for the specified property where `<id_property>` is unique.
-        id_property: Property to use as ID to set by. Defaults to "index".
-        properties: List of properties to set which are in set_df. If not specified, will set
-            all properties.
-    """
-    if not set_df[id_property].is_unique:
-        msg = f"{id_property} must be unique in set_df."
-        _dupes = set_df[id_property][set_df[id_property].duplicated()]
-        WranglerLogger.error(msg + f"Found duplicates: {_dupes.sum()}")
-
-        raise ValueError(msg)
-    table_df = self.get_table(table_name)
-    updated_df = update_df_by_col_value(table_df, set_df, id_property, properties=properties)
-    self.__dict__[table_name] = updated_df
-
    -
    -
    - -
    - - - -
    - -
    - -
    - - -
    - - -

    - merge_shapes_to_stop_times(stop_times, shapes, trips) - -

    - - -
    - -

    Add shape_id and shape_pt_sequence to stop_times dataframe.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    stop_times - DataFrame[WranglerStopTimesTable] - -
    -

    stop_times dataframe to add shape_id and shape_pt_sequence to.

    -
    -     		- required -
    shapes - DataFrame[WranglerShapesTable] - -
    -

    shapes dataframe to add to stop_times.

    -
    -     		- required -
    trips - DataFrame[WranglerTripsTable] - -
    -

    trips dataframe to link stop_times to shapes

    -
    -     		- required -
    - - -

    Returns:

    - - - - - - - - - - - - - -
    TypeDescription
    - DataFrame[WranglerStopTimesTable] - -
    -

    stop_times dataframe with shape_id and shape_pt_sequence added.

    -
    -
    - -
    - Source code in network_wrangler/transit/feed/feed.py - 
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    def merge_shapes_to_stop_times(
-    stop_times: DataFrame[WranglerStopTimesTable],
-    shapes: DataFrame[WranglerShapesTable],
-    trips: DataFrame[WranglerTripsTable],
-) -> DataFrame[WranglerStopTimesTable]:
-    """Add shape_id and shape_pt_sequence to stop_times dataframe.
-
-    Args:
-        stop_times: stop_times dataframe to add shape_id and shape_pt_sequence to.
-        shapes: shapes dataframe to add to stop_times.
-        trips: trips dataframe to link stop_times to shapes
-
-    Returns:
-        stop_times dataframe with shape_id and shape_pt_sequence added.
-    """
-    stop_times_w_shape_id = stop_times.merge(
-        trips[["trip_id", "shape_id"]], on="trip_id", how="left"
-    )
-
-    stop_times_w_shapes = stop_times_w_shape_id.merge(
-        shapes,
-        how="left",
-        left_on=["shape_id", "stop_id"],
-        right_on=["shape_id", "shape_model_node_id"],
-    )
-    stop_times_w_shapes = stop_times_w_shapes.drop(columns=["shape_model_node_id"])
-    return stop_times_w_shapes
-
    -
    -
    - -
    - -
    - - -

    - stop_count_by_trip(stop_times) - -

    - - -
    - -

    Returns dataframe with trip_id and stop_count from stop_times.

    - -
    - Source code in network_wrangler/transit/feed/feed.py - 
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    def stop_count_by_trip(
-    stop_times: DataFrame[WranglerStopTimesTable],
-) -> pd.DataFrame:
-    """Returns dataframe with trip_id and stop_count from stop_times."""
-    stops_count = stop_times.groupby("trip_id").size()
-    return stops_count.reset_index(name="stop_count")
-
    -
    -
    - -
    - - - -
    - -
    - -
    - -
    - - - - -
    - -

    Filters and queries of a gtfs frequencies table.

    - - - -
    - - - - - - - - - -
    - - -

    - frequencies_for_trips(frequencies, trips) - -

    - - -
    - -

    Filter frequenceis dataframe to records associated with trips table.

    - -
    - Source code in network_wrangler/transit/feed/frequencies.py - 
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    def frequencies_for_trips(
-    frequencies: DataFrame[WranglerFrequenciesTable], trips: DataFrame[WranglerTripsTable]
-) -> DataFrame[WranglerFrequenciesTable]:
-    """Filter frequenceis dataframe to records associated with trips table."""
-    _sel_trips = trips.trip_id.unique().tolist()
-    filtered_frequencies = frequencies[frequencies.trip_id.isin(_sel_trips)]
-    WranglerLogger.debug(
-        f"Filtered frequencies to {len(filtered_frequencies)}/{len(frequencies)} \
-                         records that referenced one of {len(trips)} trips."
-    )
-    return filtered_frequencies
-
    -
    -
    - -
    - - - -
    - -
    - -
    - -
    - - - - -
    - -

    Filters and queries of a gtfs routes table and route_ids.

    - - - -
    - - - - - - - - - -
    - - -

    - route_ids_for_trip_ids(trips, trip_ids) - -

    - - -
    - -

    Returns route ids for given list of trip_ids.

    - -
    - Source code in network_wrangler/transit/feed/routes.py - 
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-12
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    def route_ids_for_trip_ids(trips: DataFrame[WranglerTripsTable], trip_ids: list[str]) -> list[str]:
-    """Returns route ids for given list of trip_ids."""
-    return trips[trips["trip_id"].isin(trip_ids)].route_id.unique().tolist()
-
    -
    -
    - -
    - -
    - - -

    - routes_for_trip_ids(routes, trips, trip_ids) - -

    - - -
    - -

    Returns route records for given list of trip_ids.

    - -
    - Source code in network_wrangler/transit/feed/routes.py - 
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    def routes_for_trip_ids(
-    routes: DataFrame[RoutesTable], trips: DataFrame[WranglerTripsTable], trip_ids: list[str]
-) -> DataFrame[RoutesTable]:
-    """Returns route records for given list of trip_ids."""
-    route_ids = route_ids_for_trip_ids(trips, trip_ids)
-    return routes.loc[routes.route_id.isin(route_ids)]
-
    -
    -
    - -
    - -
    - - -

    - routes_for_trips(routes, trips) - -

    - - -
    - -

    Filter routes dataframe to records associated with trip records.

    - -
    - Source code in network_wrangler/transit/feed/routes.py - 
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    def routes_for_trips(
-    routes: DataFrame[RoutesTable], trips: DataFrame[WranglerTripsTable]
-) -> DataFrame[RoutesTable]:
-    """Filter routes dataframe to records associated with trip records."""
-    _sel_routes = trips.route_id.unique().tolist()
-    filtered_routes = routes[routes.route_id.isin(_sel_routes)]
-    WranglerLogger.debug(
-        f"Filtered routes to {len(filtered_routes)}/{len(routes)} \
-                         records that referenced one of {len(trips)} trips."
-    )
-    return filtered_routes
-
    -
    -
    - -
    - - - -
    - -
    - -
    - -
    - - - - -
    - -

    Filters, queries of a gtfs shapes table and node patterns.

    - - - -
    - - - - - - - - - -
    - - -

    - find_nearest_stops(shapes, trips, stop_times, trip_id, node_id, pickup_dropoff='either') - -

    - - -
    - -

    Returns node_ids (before and after) of nearest node_ids that are stops for a given trip_id.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    shapes - WranglerShapesTable - -
    -

    WranglerShapesTable

    -
    -     		- required -
    trips - WranglerTripsTable - -
    -

    WranglerTripsTable

    -
    -     		- required -
    stop_times - WranglerStopTimesTable - -
    -

    WranglerStopTimesTable

    -
    -     		- required -
    trip_id - str - -
    -

    trip id to find nearest stops for

    -
    -     		- required -
    node_id - int - -
    -

    node_id to find nearest stops for

    -
    -     		- required -
    pickup_dropoff - PickupDropoffAvailability - -
    -

    str indicating logic for selecting stops based on piackup and dropoff -availability at stop. Defaults to “either”. -“either”: either pickup_type or dropoff_type > 0 -“both”: both pickup_type or dropoff_type > 0 -“pickup_only”: only pickup > 0 -“dropoff_only”: only dropoff > 0

    -
    -     		- 'either' -
    - - -

    Returns:

    - - - - - - - - - - - - - -
    Name TypeDescription
    tuple - tuple[int, int] - -
    -

    node_ids for stop before and stop after

    -
    -
    - -
    - Source code in network_wrangler/transit/feed/shapes.py - 
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    def find_nearest_stops(
-    shapes: WranglerShapesTable,
-    trips: WranglerTripsTable,
-    stop_times: WranglerStopTimesTable,
-    trip_id: str,
-    node_id: int,
-    pickup_dropoff: PickupDropoffAvailability = "either",
-) -> tuple[int, int]:
-    """Returns node_ids (before and after) of nearest node_ids that are stops for a given trip_id.
-
-    Args:
-        shapes: WranglerShapesTable
-        trips: WranglerTripsTable
-        stop_times: WranglerStopTimesTable
-        trip_id: trip id to find nearest stops for
-        node_id: node_id to find nearest stops for
-        pickup_dropoff: str indicating logic for selecting stops based on piackup and dropoff
-            availability at stop. Defaults to "either".
-            "either": either pickup_type or dropoff_type > 0
-            "both": both pickup_type or dropoff_type > 0
-            "pickup_only": only pickup > 0
-            "dropoff_only": only dropoff > 0
-
-    Returns:
-        tuple: node_ids for stop before and stop after
-    """
-    shapes = shapes_with_stop_id_for_trip_id(
-        shapes, trips, stop_times, trip_id, pickup_dropoff=pickup_dropoff
-    )
-    WranglerLogger.debug(f"Looking for stops near node_id: {node_id}")
-    if node_id not in shapes["shape_model_node_id"].values:
-        msg = f"Node ID {node_id} not in shapes for trip {trip_id}"
-        raise ValueError(msg)
-    # Find index of node_id in shapes
-    node_idx = shapes[shapes["shape_model_node_id"] == node_id].index[0]
-
-    # Find stops before and after new stop in shapes sequence
-    nodes_before = shapes.loc[: node_idx - 1]
-    stops_before = nodes_before.loc[nodes_before["stop_id"].notna()]
-    stop_node_before = 0 if stops_before.empty else stops_before.iloc[-1]["shape_model_node_id"]
-
-    nodes_after = shapes.loc[node_idx + 1 :]
-    stops_after = nodes_after.loc[nodes_after["stop_id"].notna()]
-    stop_node_after = 0 if stops_after.empty else stops_after.iloc[0]["shape_model_node_id"]
-
-    return stop_node_before, stop_node_after
-
    -
    -
    - -
    - -
    - - -

    - node_pattern_for_shape_id(shapes, shape_id) - -

    - - -
    - -

    Returns node pattern of a shape.

    - -
    - Source code in network_wrangler/transit/feed/shapes.py - 
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    def node_pattern_for_shape_id(shapes: DataFrame[WranglerShapesTable], shape_id: str) -> list[int]:
-    """Returns node pattern of a shape."""
-    shape_df = shapes.loc[shapes["shape_id"] == shape_id]
-    shape_df = shape_df.sort_values(by=["shape_pt_sequence"])
-    return shape_df["shape_model_node_id"].to_list()
-
    -
    -
    - -
    - -
    - - -

    - shape_id_for_trip_id(trips, trip_id) - -

    - - -
    - -

    Returns a shape_id for a given trip_id.

    - -
    - Source code in network_wrangler/transit/feed/shapes.py - 
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    def shape_id_for_trip_id(trips: WranglerTripsTable, trip_id: str) -> str:
-    """Returns a shape_id for a given trip_id."""
-    return trips.loc[trips.trip_id == trip_id, "shape_id"].values[0]
-
    -
    -
    - -
    - -
    - - -

    - shape_ids_for_trip_ids(trips, trip_ids) - -

    - - -
    - -

    Returns a list of shape_ids for a given list of trip_ids.

    - -
    - Source code in network_wrangler/transit/feed/shapes.py - 
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-24
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    def shape_ids_for_trip_ids(trips: DataFrame[WranglerTripsTable], trip_ids: list[str]) -> list[str]:
-    """Returns a list of shape_ids for a given list of trip_ids."""
-    return trips[trips["trip_id"].isin(trip_ids)].shape_id.unique().tolist()
-
    -
    -
    - -
    - -
    - - - - - -
    - -

    Filter shapes dataframe to records associated with links dataframe.

    -

    EX:

    -
    -

    shapes = pd.DataFrame({ - “shape_id”: [“1”, “1”, “1”, “1”, “2”, “2”, “2”, “2”, “2”], - “shape_pt_sequence”: [1, 2, 3, 4, 1, 2, 3, 4, 5], - “shape_model_node_id”: [1, 2, 3, 4, 2, 3, 1, 5, 4] -})

    -

    links_df = pd.DataFrame({ - “A”: [1, 2, 3], - “B”: [2, 3, 4] -})

    -

    shapes

    -
    -

    shape_id shape_pt_sequence shape_model_node_id should retain -1 1 1 TRUE -1 2 2 TRUE -1 3 3 TRUE -1 4 4 TRUE -1 5 5 FALSE -2 1 1 TRUE -2 2 2 TRUE -2 3 3 TRUE -2 4 1 FALSE -2 5 5 FALSE -2 6 4 FALSE -2 7 1 FALSE - not largest segment -2 8 2 FALSE - not largest segment

    -
    -

    links_df

    -
    -

    A B -1 2 -2 3 -3 4

    - -
    - Source code in network_wrangler/transit/feed/shapes.py - 
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    def shapes_for_road_links(
-    shapes: DataFrame[WranglerShapesTable], links_df: pd.DataFrame
-) -> DataFrame[WranglerShapesTable]:
-    """Filter shapes dataframe to records associated with links dataframe.
-
-    EX:
-
-    > shapes = pd.DataFrame({
-        "shape_id": ["1", "1", "1", "1", "2", "2", "2", "2", "2"],
-        "shape_pt_sequence": [1, 2, 3, 4, 1, 2, 3, 4, 5],
-        "shape_model_node_id": [1, 2, 3, 4, 2, 3, 1, 5, 4]
-    })
-
-    > links_df = pd.DataFrame({
-        "A": [1, 2, 3],
-        "B": [2, 3, 4]
-    })
-
-    > shapes
-
-    shape_id   shape_pt_sequence   shape_model_node_id *should retain*
-    1          1                  1                        TRUE
-    1          2                  2                        TRUE
-    1          3                  3                        TRUE
-    1          4                  4                        TRUE
-    1          5                  5                       FALSE
-    2          1                  1                        TRUE
-    2          2                  2                        TRUE
-    2          3                  3                        TRUE
-    2          4                  1                       FALSE
-    2          5                  5                       FALSE
-    2          6                  4                       FALSE
-    2          7                  1                       FALSE - not largest segment
-    2          8                  2                       FALSE - not largest segment
-
-    > links_df
-
-    A   B
-    1   2
-    2   3
-    3   4
-    """
-    """
-    > shape_links
-
-    shape_id  shape_pt_sequence_A  shape_model_node_id_A shape_pt_sequence_B shape_model_node_id_B
-    1          1                        1                       2                        2
-    1          2                        2                       3                        3
-    1          3                        3                       4                        4
-    1          4                        4                       5                        5
-    2          1                        1                       2                        2
-    2          2                        2                       3                        3
-    2          3                        3                       4                        1
-    2          4                        1                       5                        5
-    2          5                        5                       6                        4
-    2          6                        4                       7                        1
-    2          7                        1                       8                        2
-    """
-    shape_links = shapes_to_shape_links(shapes)
-
-    """
-    > shape_links_w_links
-
-    shape_id  shape_pt_sequence_A shape_pt_sequence_B  A  B
-    1          1                         2             1  2
-    1          2                         3             2  3
-    1          3                         4             3  4
-    2          1                         2             1  2
-    2          2                         3             2  3
-    2          7                         8             1  2
-    """
-
-    shape_links_w_links = shape_links.merge(
-        links_df[["A", "B"]],
-        how="inner",
-        on=["A", "B"],
-    )
-
-    """
-    Find largest segment of each shape_id that is in the links
-
-    > longest_shape_segments
-    shape_id, segment_id, segment_start_shape_pt_seq, segment_end_shape_pt_seq
-    1          1                        1                       4
-    2          1                        1                       3
-    """
-    longest_shape_segments = shape_links_to_longest_shape_segments(shape_links_w_links)
-
-    """
-    > shapes
-
-    shape_id   shape_pt_sequence   shape_model_node_id
-    1          1                  1
-    1          2                  2
-    1          3                  3
-    1          4                  4
-    2          1                  1
-    2          2                  2
-    2          3                  3
-    """
-    filtered_shapes = filter_shapes_to_segments(shapes, longest_shape_segments)
-    filtered_shapes = filtered_shapes.reset_index(drop=True)
-    return filtered_shapes
-
    -
    -
    - -
    - -
    - - -

    - shapes_for_shape_id(shapes, shape_id) - -

    - - -
    - -

    Returns shape records for a given shape_id.

    - -
    - Source code in network_wrangler/transit/feed/shapes.py - 
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    def shapes_for_shape_id(
-    shapes: DataFrame[WranglerShapesTable], shape_id: str
-) -> DataFrame[WranglerShapesTable]:
-    """Returns shape records for a given shape_id."""
-    shapes = shapes.loc[shapes.shape_id == shape_id]
-    return shapes.sort_values(by=["shape_pt_sequence"])
-
    -
    -
    - -
    - -
    - - -

    - shapes_for_trip_id(shapes, trips, trip_id) - -

    - - -
    - -

    Returns shape records for a single given trip_id.

    - -
    - Source code in network_wrangler/transit/feed/shapes.py - 
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    def shapes_for_trip_id(
-    shapes: DataFrame[WranglerShapesTable], trips: DataFrame[WranglerTripsTable], trip_id: str
-) -> DataFrame[WranglerShapesTable]:
-    """Returns shape records for a single given trip_id."""
-    from .shapes import shape_id_for_trip_id
-
-    shape_id = shape_id_for_trip_id(trips, trip_id)
-    return shapes.loc[shapes.shape_id == shape_id]
-
    -
    -
    - -
    - -
    - - -

    - shapes_for_trip_ids(shapes, trips, trip_ids) - -

    - - -
    - -

    Returns shape records for list of trip_ids.

    - -
    - Source code in network_wrangler/transit/feed/shapes.py - 
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    def shapes_for_trip_ids(
-    shapes: DataFrame[WranglerShapesTable],
-    trips: DataFrame[WranglerTripsTable],
-    trip_ids: list[str],
-) -> DataFrame[WranglerShapesTable]:
-    """Returns shape records for list of trip_ids."""
-    shape_ids = shape_ids_for_trip_ids(trips, trip_ids)
-    return shapes.loc[shapes.shape_id.isin(shape_ids)]
-
    -
    -
    - -
    - -
    - - -

    - shapes_for_trips(shapes, trips) - -

    - - -
    - -

    Filter shapes dataframe to records associated with trips table.

    - -
    - Source code in network_wrangler/transit/feed/shapes.py - 
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    def shapes_for_trips(
-    shapes: DataFrame[WranglerShapesTable], trips: DataFrame[WranglerTripsTable]
-) -> DataFrame[WranglerShapesTable]:
-    """Filter shapes dataframe to records associated with trips table."""
-    _sel_shapes = trips.shape_id.unique().tolist()
-    filtered_shapes = shapes[shapes.shape_id.isin(_sel_shapes)]
-    WranglerLogger.debug(
-        f"Filtered shapes to {len(filtered_shapes)}/{len(shapes)} \
-                         records that referenced one of {len(trips)} trips."
-    )
-    return filtered_shapes
-
    -
    -
    - -
    - -
    - - -

    - shapes_with_stop_id_for_trip_id(shapes, trips, stop_times, trip_id, pickup_dropoff='either') - -

    - - -
    - -

    Returns shapes.txt for a given trip_id with the stop_id added based on pickup_type.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    shapes - DataFrame[WranglerShapesTable] - -
    -

    WranglerShapesTable

    -
    -     		- required -
    trips - DataFrame[WranglerTripsTable] - -
    -

    WranglerTripsTable

    -
    -     		- required -
    stop_times - DataFrame[WranglerStopTimesTable] - -
    -

    WranglerStopTimesTable

    -
    -     		- required -
    trip_id - str - -
    -

    trip id to select

    -
    -     		- required -
    pickup_dropoff - PickupDropoffAvailability - -
    -

    str indicating logic for selecting stops based on piackup and dropoff -availability at stop. Defaults to “either”. -“either”: either pickup_type or dropoff_type > 0 -“both”: both pickup_type or dropoff_type > 0 -“pickup_only”: only pickup > 0 -“dropoff_only”: only dropoff > 0

    -
    -     		- 'either' -
    - -
    - Source code in network_wrangler/transit/feed/shapes.py - 
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    def shapes_with_stop_id_for_trip_id(
-    shapes: DataFrame[WranglerShapesTable],
-    trips: DataFrame[WranglerTripsTable],
-    stop_times: DataFrame[WranglerStopTimesTable],
-    trip_id: str,
-    pickup_dropoff: PickupDropoffAvailability = "either",
-) -> DataFrame[WranglerShapesTable]:
-    """Returns shapes.txt for a given trip_id with the stop_id added based on pickup_type.
-
-    Args:
-        shapes: WranglerShapesTable
-        trips: WranglerTripsTable
-        stop_times: WranglerStopTimesTable
-        trip_id: trip id to select
-        pickup_dropoff: str indicating logic for selecting stops based on piackup and dropoff
-            availability at stop. Defaults to "either".
-            "either": either pickup_type or dropoff_type > 0
-            "both": both pickup_type or dropoff_type > 0
-            "pickup_only": only pickup > 0
-            "dropoff_only": only dropoff > 0
-    """
-    from .stop_times import stop_times_for_pickup_dropoff_trip_id
-
-    shapes = shapes_for_trip_id(shapes, trips, trip_id)
-    trip_stop_times = stop_times_for_pickup_dropoff_trip_id(
-        stop_times, trip_id, pickup_dropoff=pickup_dropoff
-    )
-
-    stop_times_cols = [
-        "stop_id",
-        "trip_id",
-        "pickup_type",
-        "drop_off_type",
-    ]
-
-    shape_with_trip_stops = shapes.merge(
-        trip_stop_times[stop_times_cols],
-        how="left",
-        right_on="stop_id",
-        left_on="shape_model_node_id",
-    )
-    shape_with_trip_stops = shape_with_trip_stops.sort_values(by=["shape_pt_sequence"])
-    return shape_with_trip_stops
-
    -
    -
    - -
    - -
    - - -

    - shapes_with_stops_for_shape_id(shapes, trips, stop_times, shape_id) - -

    - - -
    - -

    Returns a DataFrame containing shapes with associated stops for a given shape_id.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    shapes - DataFrame[WranglerShapesTable] - -
    -

    DataFrame containing shape data.

    -
    -     		- required -
    trips - DataFrame[WranglerTripsTable] - -
    -

    DataFrame containing trip data.

    -
    -     		- required -
    stop_times - DataFrame[WranglerStopTimesTable] - -
    -

    DataFrame containing stop times data.

    -
    -     		- required -
    shape_id - str - -
    -

    The shape_id for which to retrieve shapes with stops.

    -
    -     		- required -
    - - -

    Returns:

    - - - - - - - - - - - - - -
    TypeDescription
    - DataFrame[WranglerShapesTable] - -
    -

    DataFrame[WranglerShapesTable]: DataFrame containing shapes with associated stops.

    -
    -
    - -
    - Source code in network_wrangler/transit/feed/shapes.py - 
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    def shapes_with_stops_for_shape_id(
-    shapes: DataFrame[WranglerShapesTable],
-    trips: DataFrame[WranglerTripsTable],
-    stop_times: DataFrame[WranglerStopTimesTable],
-    shape_id: str,
-) -> DataFrame[WranglerShapesTable]:
-    """Returns a DataFrame containing shapes with associated stops for a given shape_id.
-
-    Parameters:
-        shapes (DataFrame[WranglerShapesTable]): DataFrame containing shape data.
-        trips (DataFrame[WranglerTripsTable]): DataFrame containing trip data.
-        stop_times (DataFrame[WranglerStopTimesTable]): DataFrame containing stop times data.
-        shape_id (str): The shape_id for which to retrieve shapes with stops.
-
-    Returns:
-        DataFrame[WranglerShapesTable]: DataFrame containing shapes with associated stops.
-    """
-    from .trips import trip_ids_for_shape_id
-
-    trip_ids = trip_ids_for_shape_id(trips, shape_id)
-    all_shape_stop_times = concat_with_attr(
-        [shapes_with_stop_id_for_trip_id(shapes, trips, stop_times, t) for t in trip_ids]
-    )
-    shapes_with_stops = all_shape_stop_times[all_shape_stop_times["stop_id"].notna()]
-    shapes_with_stops = shapes_with_stops.sort_values(by=["shape_pt_sequence"])
-    return shapes_with_stops
-
    -
    -
    - -
    - - - -
    - -
    - -
    - -
    - - - - -
    - -

    Filters and queries of a gtfs stop_times table.

    - - - -
    - - - - - - - - - -
    - - -

    - stop_times_for_longest_segments(stop_times) - -

    - - -
    - -

    Find the longest segment of each trip_id that is in the stop_times.

    -

    Segment ends defined based on interruptions in stop_sequence.

    - -
    - Source code in network_wrangler/transit/feed/stop_times.py - 
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    def stop_times_for_longest_segments(
-    stop_times: DataFrame[WranglerStopTimesTable],
-) -> pd.DataFrame:
-    """Find the longest segment of each trip_id that is in the stop_times.
-
-    Segment ends defined based on interruptions in `stop_sequence`.
-    """
-    stop_times = stop_times.sort_values(by=["trip_id", "stop_sequence"])
-
-    stop_times["prev_stop_sequence"] = stop_times.groupby("trip_id")["stop_sequence"].shift(1)
-    stop_times["gap"] = (stop_times["stop_sequence"] - stop_times["prev_stop_sequence"]).ne(
-        1
-    ) | stop_times["prev_stop_sequence"].isna()
-
-    stop_times["segment_id"] = stop_times["gap"].cumsum()
-    # WranglerLogger.debug(f"stop_times with segment_id:\n{stop_times}")
-
-    # Calculate the length of each segment
-    segment_lengths = (
-        stop_times.groupby(["trip_id", "segment_id"]).size().reset_index(name="segment_length")
-    )
-
-    # Identify the longest segment for each trip
-    idx = segment_lengths.groupby("trip_id")["segment_length"].idxmax()
-    longest_segments = segment_lengths.loc[idx]
-
-    # Merge longest segment info back to stop_times
-    stop_times = stop_times.merge(
-        longest_segments[["trip_id", "segment_id"]],
-        on=["trip_id", "segment_id"],
-        how="inner",
-    )
-
-    # Drop temporary columns used for calculations
-    stop_times.drop(columns=["prev_stop_sequence", "gap", "segment_id"], inplace=True)
-    # WranglerLogger.debug(f"stop_timesw/longest segments:\n{stop_times}")
-    return stop_times
-
    -
    -
    - -
    - -
    - - -

    - stop_times_for_min_stops(stop_times, min_stops) - -

    - - -
    - -

    Filter stop_times dataframe to only the records which have >= min_stops for the trip.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    stop_times - DataFrame[WranglerStopTimesTable] - -
    -

    stoptimestable to filter

    -
    -     		- required -
    min_stops - int - -
    -

    minimum stops to require to keep trip in stoptimes

    -
    -     		- required -
    - -
    - Source code in network_wrangler/transit/feed/stop_times.py - 
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    def stop_times_for_min_stops(
-    stop_times: DataFrame[WranglerStopTimesTable], min_stops: int
-) -> DataFrame[WranglerStopTimesTable]:
-    """Filter stop_times dataframe to only the records which have >= min_stops for the trip.
-
-    Args:
-        stop_times: stoptimestable to filter
-        min_stops: minimum stops to require to keep trip in stoptimes
-    """
-    stop_ct_by_trip_df = stop_count_by_trip(stop_times)
-
-    # Filter to obtain DataFrame of trips with stop counts >= min_stops
-    min_stop_ct_trip_df = stop_ct_by_trip_df[stop_ct_by_trip_df.stop_count >= min_stops]
-    if len(min_stop_ct_trip_df) == 0:
-        msg = f"No trips meet threshold of minimum stops: {min_stops}"
-        raise ValueError(msg)
-    WranglerLogger.debug(
-        f"Found {len(min_stop_ct_trip_df)} trips with a minimum of {min_stops} stops."
-    )
-
-    # Filter the original stop_times DataFrame to only include trips with >= min_stops
-    filtered_stop_times = stop_times.merge(
-        min_stop_ct_trip_df["trip_id"], on="trip_id", how="inner"
-    )
-    WranglerLogger.debug(
-        f"Filter stop times to {len(filtered_stop_times)}/{len(stop_times)}\
-            w/a minimum of {min_stops} stops."
-    )
-
-    return filtered_stop_times
-
    -
    -
    - -
    - -
    - - -

    - stop_times_for_pickup_dropoff_trip_id(stop_times, trip_id, pickup_dropoff='either') - -

    - - -
    - -

    Filters stop_times for a given trip_id based on pickup type.

    -

    GTFS values for pickup_type and drop_off_type” - 0 or empty - Regularly scheduled pickup/dropoff. - 1 - No pickup/dropoff available. - 2 - Must phone agency to arrange pickup/dropoff. - 3 - Must coordinate with driver to arrange pickup/dropoff.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    stop_times - DataFrame[WranglerStopTimesTable] - -
    -

    A WranglerStopTimesTable to query.

    -
    -     		- required -
    trip_id - str - -
    -

    trip_id to get stop pattern for

    -
    -     		- required -
    pickup_dropoff - PickupDropoffAvailability - -
    -

    str indicating logic for selecting stops based on pickup and dropoff -availability at stop. Defaults to “either”. -“any”: all stoptime records -“either”: either pickup_type or dropoff_type != 1 -“both”: both pickup_type and dropoff_type != 1 -“pickup_only”: dropoff = 1; pickup != 1 -“dropoff_only”: pickup = 1; dropoff != 1

    -
    -     		- 'either' -
    - -
    - Source code in network_wrangler/transit/feed/stop_times.py - 
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    @validate_call_pyd
-def stop_times_for_pickup_dropoff_trip_id(
-    stop_times: DataFrame[WranglerStopTimesTable],
-    trip_id: str,
-    pickup_dropoff: PickupDropoffAvailability = "either",
-) -> DataFrame[WranglerStopTimesTable]:
-    """Filters stop_times for a given trip_id based on pickup type.
-
-    GTFS values for pickup_type and drop_off_type"
-        0 or empty - Regularly scheduled pickup/dropoff.
-        1 - No pickup/dropoff available.
-        2 - Must phone agency to arrange pickup/dropoff.
-        3 - Must coordinate with driver to arrange pickup/dropoff.
-
-    Args:
-        stop_times: A WranglerStopTimesTable to query.
-        trip_id: trip_id to get stop pattern for
-        pickup_dropoff: str indicating logic for selecting stops based on pickup and dropoff
-            availability at stop. Defaults to "either".
-            "any": all stoptime records
-            "either": either pickup_type or dropoff_type != 1
-            "both": both pickup_type and dropoff_type != 1
-            "pickup_only": dropoff = 1; pickup != 1
-            "dropoff_only":  pickup = 1; dropoff != 1
-    """
-    trip_stop_pattern = stop_times_for_trip_id(stop_times, trip_id)
-
-    if pickup_dropoff == "any":
-        return trip_stop_pattern
-
-    pickup_type_selection = {
-        "either": (trip_stop_pattern.pickup_type != 1) | (trip_stop_pattern.drop_off_type != 1),
-        "both": (trip_stop_pattern.pickup_type != 1) & (trip_stop_pattern.drop_off_type != 1),
-        "pickup_only": (trip_stop_pattern.pickup_type != 1)
-        & (trip_stop_pattern.drop_off_type == 1),
-        "dropoff_only": (trip_stop_pattern.drop_off_type != 1)
-        & (trip_stop_pattern.pickup_type == 1),
-    }
-
-    selection = pickup_type_selection[pickup_dropoff]
-    trip_stops = trip_stop_pattern[selection]
-
-    return trip_stops
-
    -
    -
    - -
    - -
    - - -

    - stop_times_for_route_ids(stop_times, trips, route_ids) - -

    - - -
    - -

    Returns a stop_time records for a list of route_ids.

    - -
    - Source code in network_wrangler/transit/feed/stop_times.py - 
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    def stop_times_for_route_ids(
-    stop_times: DataFrame[WranglerStopTimesTable],
-    trips: DataFrame[WranglerTripsTable],
-    route_ids: list[str],
-) -> DataFrame[WranglerStopTimesTable]:
-    """Returns a stop_time records for a list of route_ids."""
-    trip_ids = trips.loc[trips.route_id.isin(route_ids)].trip_id.unique()
-    return stop_times_for_trip_ids(stop_times, trip_ids)
-
    -
    -
    - -
    - -
    - - -

    - stop_times_for_shapes(stop_times, shapes, trips) - -

    - - -
    - -

    Filter stop_times dataframe to records associated with shapes dataframe.

    -

    Where multiple segments of stop_times are found to match shapes, retain only the longest.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    stop_times - DataFrame[WranglerStopTimesTable] - -
    -

    stop_times dataframe to filter

    -
    -     		- required -
    shapes - DataFrame[WranglerShapesTable] - -
    -

    shapes dataframe to stop_times to.

    -
    -     		- required -
    trips - DataFrame[WranglerTripsTable] - -
    -

    trips to link stop_times to shapess

    -
    -     		- required -
    - - -

    Returns:

    - - - - - - - - - - - - - -
    TypeDescription
    - DataFrame[WranglerStopTimesTable] - -
    -

    filtered stop_times dataframe

    -
    -
    -
      -
    • should be retained
      -

      stop_times

      -
      -
      • -
    -

    trip_id stop_sequence stop_id -t1 1 1 -t1 2 2 -t1 3 3 -t1 4 5 -t2 1 1 -*t2 2 3 -t2 3 7

    -
    -

    shapes

    -
    -

    shape_id shape_pt_sequence shape_model_node_id -s1 1 1 -s1 2 2 -s1 3 3 -s1 4 4 -s2 1 1 -s2 2 2 -s2 3 3

    -
    -

    trips

    -
    -

    trip_id shape_id -t1 s1 -t2 s2

    - -
    - Source code in network_wrangler/transit/feed/stop_times.py - 
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    def stop_times_for_shapes(
-    stop_times: DataFrame[WranglerStopTimesTable],
-    shapes: DataFrame[WranglerShapesTable],
-    trips: DataFrame[WranglerTripsTable],
-) -> DataFrame[WranglerStopTimesTable]:
-    """Filter stop_times dataframe to records associated with shapes dataframe.
-
-    Where multiple segments of stop_times are found to match shapes, retain only the longest.
-
-    Args:
-        stop_times: stop_times dataframe to filter
-        shapes: shapes dataframe to stop_times to.
-        trips: trips to link stop_times to shapess
-
-    Returns:
-        filtered stop_times dataframe
-
-    EX:
-    * should be retained
-    > stop_times
-
-    trip_id   stop_sequence   stop_id
-    *t1          1                  1
-    *t1          2                  2
-    *t1          3                  3
-    t1           4                  5
-    *t2          1                  1
-    *t2          2                  3
-    t2           3                  7
-
-    > shapes
-
-    shape_id   shape_pt_sequence   shape_model_node_id
-    s1          1                  1
-    s1          2                  2
-    s1          3                  3
-    s1          4                  4
-    s2          1                  1
-    s2          2                  2
-    s2          3                  3
-
-    > trips
-
-    trip_id   shape_id
-    t1          s1
-    t2          s2
-    """
-    """
-    > stop_times_w_shapes
-
-    trip_id   stop_sequence   stop_id    shape_id   shape_pt_sequence
-    *t1          1                  1        s1          1
-    *t1          2                  2        s1          2
-    *t1          3                  3        s1          3
-    t1           4                  5        NA          NA
-    *t2          1                  1        s2          1
-    *t2          2                  3        s2          2
-    t2           3                  7        NA          NA
-
-    """
-    stop_times_w_shapes = merge_shapes_to_stop_times(stop_times, shapes, trips)
-    # WranglerLogger.debug(f"stop_times_w_shapes :\n{stop_times_w_shapes}")
-    """
-    > stop_times_w_shapes
-
-    trip_id   stop_sequence   stop_id   shape_id   shape_pt_sequence
-    *t1          1               1        s1          1
-    *t1          2               2        s1          2
-    *t1          3               3        s1          3
-    *t2          1               1        s2          1
-    *t2          2               3        s2          2
-
-    """
-    filtered_stop_times = stop_times_w_shapes[stop_times_w_shapes["shape_pt_sequence"].notna()]
-    # WranglerLogger.debug(f"filtered_stop_times:\n{filtered_stop_times}")
-
-    # Filter out any stop_times the shape_pt_sequence is not ascending
-    valid_stop_times = filtered_stop_times.groupby("trip_id").filter(
-        lambda x: x["shape_pt_sequence"].is_monotonic_increasing
-    )
-    # WranglerLogger.debug(f"valid_stop_times:\n{valid_stop_times}")
-
-    valid_stop_times = valid_stop_times.drop(columns=["shape_id", "shape_pt_sequence"])
-
-    longest_valid_stop_times = stop_times_for_longest_segments(valid_stop_times)
-    longest_valid_stop_times = longest_valid_stop_times.reset_index(drop=True)
-
-    return longest_valid_stop_times
-
    -
    -
    - -
    - -
    - - -

    - stop_times_for_stops(stop_times, stops) - -

    - - -
    - -

    Filter stop_times dataframe to only have stop_times associated with stops records.

    - -
    - Source code in network_wrangler/transit/feed/stop_times.py - 
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    def stop_times_for_stops(
-    stop_times: DataFrame[WranglerStopTimesTable], stops: DataFrame[WranglerStopsTable]
-) -> DataFrame[WranglerStopTimesTable]:
-    """Filter stop_times dataframe to only have stop_times associated with stops records."""
-    _sel_stops = stops.stop_id.unique().tolist()
-    filtered_stop_times = stop_times[stop_times.stop_id.isin(_sel_stops)]
-    WranglerLogger.debug(
-        f"Filtered stop_times to {len(filtered_stop_times)}/{len(stop_times)} \
-                         records that referenced one of {len(stops)} stops."
-    )
-    return filtered_stop_times
-
    -
    -
    - -
    - -
    - - -

    - stop_times_for_trip_id(stop_times, trip_id) - -

    - - -
    - -

    Returns a stop_time records for a given trip_id.

    - -
    - Source code in network_wrangler/transit/feed/stop_times.py - 
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    def stop_times_for_trip_id(
-    stop_times: DataFrame[WranglerStopTimesTable], trip_id: str
-) -> DataFrame[WranglerStopTimesTable]:
-    """Returns a stop_time records for a given trip_id."""
-    stop_times = stop_times.loc[stop_times.trip_id == trip_id]
-    return stop_times.sort_values(by=["stop_sequence"])
-
    -
    -
    - -
    - -
    - - -

    - stop_times_for_trip_ids(stop_times, trip_ids) - -

    - - -
    - -

    Returns a stop_time records for a given list of trip_ids.

    - -
    - Source code in network_wrangler/transit/feed/stop_times.py - 
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    def stop_times_for_trip_ids(
-    stop_times: DataFrame[WranglerStopTimesTable], trip_ids: list[str]
-) -> DataFrame[WranglerStopTimesTable]:
-    """Returns a stop_time records for a given list of trip_ids."""
-    stop_times = stop_times.loc[stop_times.trip_id.isin(trip_ids)]
-    return stop_times.sort_values(by=["stop_sequence"])
-
    -
    -
    - -
    - -
    - - -

    - stop_times_for_trip_node_segment(stop_times, trip_id, node_id_start, node_id_end, include_start=True, include_end=True) - -

    - - -
    - -

    Returns stop_times for a given trip_id between two nodes or with those nodes included.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    stop_times - DataFrame[WranglerStopTimesTable] - -
    -

    WranglerStopTimesTable

    -
    -     		- required -
    trip_id - str - -
    -

    trip id to select

    -
    -     		- required -
    node_id_start - int - -
    -

    int of the starting node

    -
    -     		- required -
    node_id_end - int - -
    -

    int of the ending node

    -
    -     		- required -
    include_start - bool - -
    -

    bool indicating if the start node should be included in the segment. -Defaults to True.

    -
    -     		- True -
    include_end - bool - -
    -

    bool indicating if the end node should be included in the segment. -Defaults to True.

    -
    -     		- True -
    - -
    - Source code in network_wrangler/transit/feed/stop_times.py - 
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    def stop_times_for_trip_node_segment(
-    stop_times: DataFrame[WranglerStopTimesTable],
-    trip_id: str,
-    node_id_start: int,
-    node_id_end: int,
-    include_start: bool = True,
-    include_end: bool = True,
-) -> DataFrame[WranglerStopTimesTable]:
-    """Returns stop_times for a given trip_id between two nodes or with those nodes included.
-
-    Args:
-        stop_times: WranglerStopTimesTable
-        trip_id: trip id to select
-        node_id_start: int of the starting node
-        node_id_end: int of the ending node
-        include_start: bool indicating if the start node should be included in the segment.
-            Defaults to True.
-        include_end: bool indicating if the end node should be included in the segment.
-            Defaults to True.
-    """
-    stop_times = stop_times_for_trip_id(stop_times, trip_id)
-    start_idx = stop_times[stop_times["stop_id"] == node_id_start].index[0]
-    end_idx = stop_times[stop_times["stop_id"] == node_id_end].index[0]
-    if not include_start:
-        start_idx += 1
-    if include_end:
-        end_idx += 1
-    return stop_times.loc[start_idx:end_idx]
-
    -
    -
    - -
    - - - -
    - -
    - -
    - -
    - - - - -
    - -

    Filters and queries of a gtfs stops table and stop_ids.

    - - - -
    - - - - - - - - - -
    - - -

    - node_is_stop(stops, stop_times, node_id, trip_id, pickup_dropoff='either') - -

    - - -
    - -

    Returns boolean indicating if a (or list of) node(s)) is (are) stops for a given trip_id.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    stops - DataFrame[WranglerStopsTable] - -
    -

    WranglerStopsTable

    -
    -     		- required -
    stop_times - DataFrame[WranglerStopTimesTable] - -
    -

    WranglerStopTimesTable

    -
    -     		- required -
    node_id - Union[int, list[int]] - -
    -

    node ID for roadway

    -
    -     		- required -
    trip_id - str - -
    -

    trip_id to get stop pattern for

    -
    -     		- required -
    pickup_dropoff - PickupDropoffAvailability - -
    -

    str indicating logic for selecting stops based on piackup and dropoff -availability at stop. Defaults to “either”. -“either”: either pickup_type or dropoff_type > 0 -“both”: both pickup_type or dropoff_type > 0 -“pickup_only”: only pickup > 0 -“dropoff_only”: only dropoff > 0

    -
    -     		- 'either' -
    - -
    - Source code in network_wrangler/transit/feed/stops.py - 
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    def node_is_stop(
-    stops: DataFrame[WranglerStopsTable],
-    stop_times: DataFrame[WranglerStopTimesTable],
-    node_id: Union[int, list[int]],
-    trip_id: str,
-    pickup_dropoff: PickupDropoffAvailability = "either",
-) -> Union[bool, list[bool]]:
-    """Returns boolean indicating if a (or list of) node(s)) is (are) stops for a given trip_id.
-
-    Args:
-        stops: WranglerStopsTable
-        stop_times: WranglerStopTimesTable
-        node_id: node ID for roadway
-        trip_id: trip_id to get stop pattern for
-        pickup_dropoff: str indicating logic for selecting stops based on piackup and dropoff
-            availability at stop. Defaults to "either".
-            "either": either pickup_type or dropoff_type > 0
-            "both": both pickup_type or dropoff_type > 0
-            "pickup_only": only pickup > 0
-            "dropoff_only": only dropoff > 0
-    """
-    trip_stop_nodes = stops_for_trip_id(stops, stop_times, trip_id, pickup_dropoff=pickup_dropoff)[
-        "stop_id"
-    ]
-    if isinstance(node_id, list):
-        return [n in trip_stop_nodes.values for n in node_id]
-    return node_id in trip_stop_nodes.values
-
    -
    -
    - -
    - -
    - - -

    - stop_id_pattern_for_trip(stop_times, trip_id, pickup_dropoff='either') - -

    - - -
    - -

    Returns a stop pattern for a given trip_id given by a list of stop_ids.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    stop_times - DataFrame[WranglerStopTimesTable] - -
    -

    WranglerStopTimesTable

    -
    -     		- required -
    trip_id - str - -
    -

    trip_id to get stop pattern for

    -
    -     		- required -
    pickup_dropoff - PickupDropoffAvailability - -
    -

    str indicating logic for selecting stops based on piackup and dropoff -availability at stop. Defaults to “either”. -“either”: either pickup_type or dropoff_type > 0 -“both”: both pickup_type or dropoff_type > 0 -“pickup_only”: only pickup > 0 -“dropoff_only”: only dropoff > 0

    -
    -     		- 'either' -
    - -
    - Source code in network_wrangler/transit/feed/stops.py - 
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    @validate_call_pyd
-def stop_id_pattern_for_trip(
-    stop_times: DataFrame[WranglerStopTimesTable],
-    trip_id: str,
-    pickup_dropoff: PickupDropoffAvailability = "either",
-) -> list[str]:
-    """Returns a stop pattern for a given trip_id given by a list of stop_ids.
-
-    Args:
-        stop_times: WranglerStopTimesTable
-        trip_id: trip_id to get stop pattern for
-        pickup_dropoff: str indicating logic for selecting stops based on piackup and dropoff
-            availability at stop. Defaults to "either".
-            "either": either pickup_type or dropoff_type > 0
-            "both": both pickup_type or dropoff_type > 0
-            "pickup_only": only pickup > 0
-            "dropoff_only": only dropoff > 0
-    """
-    from .stop_times import stop_times_for_pickup_dropoff_trip_id
-
-    trip_stops = stop_times_for_pickup_dropoff_trip_id(
-        stop_times, trip_id, pickup_dropoff=pickup_dropoff
-    )
-    return trip_stops.stop_id.to_list()
-
    -
    -
    - -
    - -
    - - -

    - stops_for_stop_times(stops, stop_times) - -

    - - -
    - -

    Filter stops dataframe to only have stops associated with stop_times records.

    - -
    - Source code in network_wrangler/transit/feed/stops.py - 
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    def stops_for_stop_times(
-    stops: DataFrame[WranglerStopsTable], stop_times: DataFrame[WranglerStopTimesTable]
-) -> DataFrame[WranglerStopsTable]:
-    """Filter stops dataframe to only have stops associated with stop_times records."""
-    _sel_stops_ge_min = stop_times.stop_id.unique().tolist()
-    filtered_stops = stops[stops.stop_id.isin(_sel_stops_ge_min)]
-    WranglerLogger.debug(
-        f"Filtered stops to {len(filtered_stops)}/{len(stops)} \
-                         records that referenced one of {len(stop_times)} stop_times."
-    )
-    return filtered_stops
-
    -
    -
    - -
    - -
    - - -

    - stops_for_trip_id(stops, stop_times, trip_id, pickup_dropoff='any') - -

    - - -
    - -

    Returns stops.txt which are used for a given trip_id.

    - -
    - Source code in network_wrangler/transit/feed/stops.py - 
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    def stops_for_trip_id(
-    stops: DataFrame[WranglerStopsTable],
-    stop_times: DataFrame[WranglerStopTimesTable],
-    trip_id: str,
-    pickup_dropoff: PickupDropoffAvailability = "any",
-) -> DataFrame[WranglerStopsTable]:
-    """Returns stops.txt which are used for a given trip_id."""
-    stop_ids = stop_id_pattern_for_trip(stop_times, trip_id, pickup_dropoff=pickup_dropoff)
-    return stops.loc[stops.stop_id.isin(stop_ids)]
-
    -
    -
    - -
    - - - -
    - -
    - -
    - -
    - - - - -
    - -

    Filters and queries of a gtfs trips table and trip_ids.

    - - - -
    - - - - - - - - - -
    - - -

    - trip_ids_for_shape_id(trips, shape_id) - -

    - - -
    - -

    Returns a list of trip_ids for a given shape_id.

    - -
    - Source code in network_wrangler/transit/feed/trips.py - 
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    def trip_ids_for_shape_id(trips: DataFrame[WranglerTripsTable], shape_id: str) -> list[str]:
-    """Returns a list of trip_ids for a given shape_id."""
-    return trips_for_shape_id(trips, shape_id)["trip_id"].unique().tolist()
-
    -
    -
    - -
    - -
    - - -

    - trips_for_shape_id(trips, shape_id) - -

    - - -
    - -

    Returns a trips records for a given shape_id.

    - -
    - Source code in network_wrangler/transit/feed/trips.py - 
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    def trips_for_shape_id(
-    trips: DataFrame[WranglerTripsTable], shape_id: str
-) -> DataFrame[WranglerTripsTable]:
-    """Returns a trips records for a given shape_id."""
-    return trips.loc[trips.shape_id == shape_id]
-
    -
    -
    - -
    - -
    - - -

    - trips_for_stop_times(trips, stop_times) - -

    - - -
    - -

    Filter trips dataframe to records associated with stop_time records.

    - -
    - Source code in network_wrangler/transit/feed/trips.py - 
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    def trips_for_stop_times(
-    trips: DataFrame[WranglerTripsTable], stop_times: DataFrame[WranglerStopTimesTable]
-) -> DataFrame[WranglerTripsTable]:
-    """Filter trips dataframe to records associated with stop_time records."""
-    _sel_trips = stop_times.trip_id.unique().tolist()
-    filtered_trips = trips[trips.trip_id.isin(_sel_trips)]
-    WranglerLogger.debug(
-        f"Filtered trips to {len(filtered_trips)}/{len(trips)} \
-                         records that referenced one of {len(stop_times)} stop_times."
-    )
-    return filtered_trips
-
    -
    -
    - -
    - - - -
    - -
    - -
    - -
    - - - - -
    - -

    Functions for translating transit tables into visualizable links relatable to roadway network.

    - - - -
    - - - - - - - - - -
    - - - - - -
    - -

    Converts shapes DataFrame to shape links DataFrame.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    shapes - DataFrame[WranglerShapesTable] - -
    -

    The input shapes DataFrame.

    -
    -     		- required -
    - - -

    Returns:

    - - - - - - - - - - - - - -
    TypeDescription
    - DataFrame - -
    -

    pd.DataFrame: The resulting shape links DataFrame.

    -
    -
    - -
    - Source code in network_wrangler/transit/feed/transit_links.py - 
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    def shapes_to_shape_links(shapes: DataFrame[WranglerShapesTable]) -> pd.DataFrame:
-    """Converts shapes DataFrame to shape links DataFrame.
-
-    Args:
-        shapes (DataFrame[WranglerShapesTable]): The input shapes DataFrame.
-
-    Returns:
-        pd.DataFrame: The resulting shape links DataFrame.
-    """
-    return point_seq_to_links(
-        shapes,
-        id_field="shape_id",
-        seq_field="shape_pt_sequence",
-        node_id_field="shape_model_node_id",
-    )
-
    -
    -
    - -
    - -
    - - - - - -
    - -

    Converts stop times to stop times links.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    stop_times - DataFrame[WranglerStopTimesTable] - -
    -

    The stop times data.

    -
    -     		- required -
    from_field - str - -
    -

    The name of the field representing the ‘from’ stop. -Defaults to “A”.

    -
    -     		- 'A' -
    to_field - str - -
    -

    The name of the field representing the ‘to’ stop. -Defaults to “B”.

    -
    -     		- 'B' -
    - - -

    Returns:

    - - - - - - - - - - - - - -
    TypeDescription
    - DataFrame - -
    -

    pd.DataFrame: The resulting stop times links.

    -
    -
    - -
    - Source code in network_wrangler/transit/feed/transit_links.py - 
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    def stop_times_to_stop_times_links(
-    stop_times: DataFrame[WranglerStopTimesTable],
-    from_field: str = "A",
-    to_field: str = "B",
-) -> pd.DataFrame:
-    """Converts stop times to stop times links.
-
-    Args:
-        stop_times (DataFrame[WranglerStopTimesTable]): The stop times data.
-        from_field (str, optional): The name of the field representing the 'from' stop.
-            Defaults to "A".
-        to_field (str, optional): The name of the field representing the 'to' stop.
-            Defaults to "B".
-
-    Returns:
-        pd.DataFrame: The resulting stop times links.
-    """
-    return point_seq_to_links(
-        stop_times,
-        id_field="trip_id",
-        seq_field="stop_sequence",
-        node_id_field="stop_id",
-        from_field=from_field,
-        to_field=to_field,
-    )
-
    -
    -
    - -
    - -
    - - - - - -
    - -

    Returns a DataFrame containing unique shape links based on the provided shapes DataFrame.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    shapes - DataFrame[WranglerShapesTable] - -
    -

    The input DataFrame containing shape information.

    -
    -     		- required -
    from_field - str - -
    -

    The name of the column representing the ‘from’ field. -Defaults to “A”.

    -
    -     		- 'A' -
    to_field - str - -
    -

    The name of the column representing the ‘to’ field. -Defaults to “B”.

    -
    -     		- 'B' -
    - - -

    Returns:

    - - - - - - - - - - - - - -
    TypeDescription
    - DataFrame - -
    -

    pd.DataFrame: DataFrame containing unique shape links based on the provided shapes df.

    -
    -
    - -
    - Source code in network_wrangler/transit/feed/transit_links.py - 
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    def unique_shape_links(
-    shapes: DataFrame[WranglerShapesTable], from_field: str = "A", to_field: str = "B"
-) -> pd.DataFrame:
-    """Returns a DataFrame containing unique shape links based on the provided shapes DataFrame.
-
-    Parameters:
-        shapes (DataFrame[WranglerShapesTable]): The input DataFrame containing shape information.
-        from_field (str, optional): The name of the column representing the 'from' field.
-            Defaults to "A".
-        to_field (str, optional): The name of the column representing the 'to' field.
-            Defaults to "B".
-
-    Returns:
-        pd.DataFrame: DataFrame containing unique shape links based on the provided shapes df.
-    """
-    shape_links = shapes_to_shape_links(shapes)
-    # WranglerLogger.debug(f"Shape links: \n {shape_links[['shape_id', from_field, to_field]]}")
-
-    _agg_dict: dict[str, Union[type, str]] = {"shape_id": list}
-    _opt_fields = [f"shape_pt_{v}_{t}" for v in ["lat", "lon"] for t in [from_field, to_field]]
-    for f in _opt_fields:
-        if f in shape_links:
-            _agg_dict[f] = "first"
-
-    unique_shape_links = shape_links.groupby([from_field, to_field]).agg(_agg_dict).reset_index()
-    return unique_shape_links
-
    -
    -
    - -
    - -
    - - - - - -
    - -

    Returns a DataFrame containing unique stop time links based on the given stop times DataFrame.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    stop_times - DataFrame[WranglerStopTimesTable] - -
    -

    The DataFrame containing stop times data.

    -
    -     		- required -
    from_field - str - -
    -

    The name of the column representing the ‘from’ field in the -stop times DataFrame. Defaults to “A”.

    -
    -     		- 'A' -
    to_field - str - -
    -

    The name of the column representing the ‘to’ field in the stop -times DataFrame. Defaults to “B”.

    -
    -     		- 'B' -
    - - -

    Returns:

    - - - - - - - - - - - - - -
    TypeDescription
    - DataFrame - -
    -

    pd.DataFrame: A DataFrame containing unique stop time links with columns ‘from_field’, -‘to_field’, and ‘trip_id’.

    -
    -
    - -
    - Source code in network_wrangler/transit/feed/transit_links.py - 
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    def unique_stop_time_links(
-    stop_times: DataFrame[WranglerStopTimesTable],
-    from_field: str = "A",
-    to_field: str = "B",
-) -> pd.DataFrame:
-    """Returns a DataFrame containing unique stop time links based on the given stop times DataFrame.
-
-    Parameters:
-        stop_times (DataFrame[WranglerStopTimesTable]): The DataFrame containing stop times data.
-        from_field (str, optional): The name of the column representing the 'from' field in the
-            stop times DataFrame. Defaults to "A".
-        to_field (str, optional): The name of the column representing the 'to' field in the stop
-            times DataFrame. Defaults to "B".
-
-    Returns:
-        pd.DataFrame: A DataFrame containing unique stop time links with columns 'from_field',
-            'to_field', and 'trip_id'.
-    """
-    links = stop_times_to_stop_times_links(stop_times, from_field=from_field, to_field=to_field)
-    unique_links = links.groupby([from_field, to_field])["trip_id"].apply(list).reset_index()
-    return unique_links
-
    -
    -
    - -
    - - - -
    - -
    - -
    - -
    - - - - -
    - -

    Functions to create segments from shapes and shape_links.

    - - - -
    - - - - - - - - - -
    - - -

    - filter_shapes_to_segments(shapes, segments) - -

    - - -
    - -

    Filter shapes dataframe to records associated with segments dataframe.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    shapes - DataFrame[WranglerShapesTable] - -
    -

    shapes dataframe to filter

    -
    -     		- required -
    segments - DataFrame - -
    -

    segments dataframe to filter by with shape_id, segment_start_shape_pt_seq, -segment_end_shape_pt_seq . Should have one record per shape_id.

    -
    -     		- required -
    - - -

    Returns:

    - - - - - - - - - - - - - -
    TypeDescription
    - DataFrame[WranglerShapesTable] - -
    -

    filtered shapes dataframe

    -
    -
    - -
    - Source code in network_wrangler/transit/feed/transit_segments.py - 
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    def filter_shapes_to_segments(
-    shapes: DataFrame[WranglerShapesTable], segments: pd.DataFrame
-) -> DataFrame[WranglerShapesTable]:
-    """Filter shapes dataframe to records associated with segments dataframe.
-
-    Args:
-        shapes: shapes dataframe to filter
-        segments: segments dataframe to filter by with shape_id, segment_start_shape_pt_seq,
-            segment_end_shape_pt_seq . Should have one record per shape_id.
-
-    Returns:
-        filtered shapes dataframe
-    """
-    shapes_w_segs = shapes.merge(segments, on="shape_id", how="left")
-
-    # Retain only those points within the segment sequences
-    filtered_shapes = shapes_w_segs[
-        (shapes_w_segs["shape_pt_sequence"] >= shapes_w_segs["segment_start_shape_pt_seq"])
-        & (shapes_w_segs["shape_pt_sequence"] <= shapes_w_segs["segment_end_shape_pt_seq"])
-    ]
-
-    drop_cols = [
-        "segment_id",
-        "segment_start_shape_pt_seq",
-        "segment_end_shape_pt_seq",
-        "segment_length",
-    ]
-    filtered_shapes = filtered_shapes.drop(columns=drop_cols)
-
-    return filtered_shapes
-
    -
    -
    - -
    - -
    - - - - - -
    - -

    Find the longest segment of each shape_id that is in the links.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    shape_links - -
    -

    DataFrame with shape_id, shape_pt_sequence_A, shape_pt_sequence_B

    -
    -     		- required -
    - - -

    Returns:

    - - - - - - - - - - - - - -
    TypeDescription
    - DataFrame - -
    -

    DataFrame with shape_id, segment_id, segment_start_shape_pt_seq, segment_end_shape_pt_seq

    -
    -
    - -
    - Source code in network_wrangler/transit/feed/transit_segments.py - 
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    def shape_links_to_longest_shape_segments(shape_links) -> pd.DataFrame:
-    """Find the longest segment of each shape_id that is in the links.
-
-    Args:
-        shape_links: DataFrame with shape_id, shape_pt_sequence_A, shape_pt_sequence_B
-
-    Returns:
-        DataFrame with shape_id, segment_id, segment_start_shape_pt_seq, segment_end_shape_pt_seq
-    """
-    segments = shape_links_to_segments(shape_links)
-    idx = segments.groupby("shape_id")["segment_length"].idxmax()
-    longest_segments = segments.loc[idx]
-    return longest_segments
-
    -
    -
    - -
    - -
    - - - - - -
    - -

    Convert shape_links to segments by shape_id with segments of continuous shape_pt_sequence.

    - - -

    DataFrame with shape_id, segment_id, segment_start_shape_pt_seq,

    - - - - - - - - - - - - - -
    TypeDescription
    - DataFrame - -
    -

    segment_end_shape_pt_seq

    -
    -
    - -
    - Source code in network_wrangler/transit/feed/transit_segments.py - 
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    def shape_links_to_segments(shape_links) -> pd.DataFrame:
-    """Convert shape_links to segments by shape_id with segments of continuous shape_pt_sequence.
-
-    Returns: DataFrame with shape_id, segment_id, segment_start_shape_pt_seq,
-        segment_end_shape_pt_seq
-    """
-    shape_links["gap"] = shape_links.groupby("shape_id")["shape_pt_sequence_A"].diff().gt(1)
-    shape_links["segment_id"] = shape_links.groupby("shape_id")["gap"].cumsum()
-
-    # Define segment starts and ends
-    segment_definitions = (
-        shape_links.groupby(["shape_id", "segment_id"])
-        .agg(
-            segment_start_shape_pt_seq=("shape_pt_sequence_A", "min"),
-            segment_end_shape_pt_seq=("shape_pt_sequence_B", "max"),
-        )
-        .reset_index()
-    )
-
-    # Optionally calculate segment lengths for further uses
-    segment_definitions["segment_length"] = (
-        segment_definitions["segment_end_shape_pt_seq"]
-        - segment_definitions["segment_start_shape_pt_seq"]
-        + 1
-    )
-
-    return segment_definitions
-
    -
    -
    - -
    - - - -
    - -
    - -

    Transit Projects

    - - -
    - - - - -
    - -

    Functions for adding a transit route to a TransitNetwork.

    - - - -
    - - - - - - - - - -
    - - -

    - apply_transit_route_addition(net, transit_route_addition, reference_road_net=None) - -

    - - -
    - -

    Add transit route to TransitNetwork.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    net - TransitNetwork - -
    -

    Network to modify.

    -
    -     		- required -
    transit_route_addition - dict - -
    -

    route dictionary to add to the feed.

    -
    -     		- required -
    reference_road_net - Optional[RoadwayNetwork] - -
    -

    (RoadwayNetwork, optional): Reference roadway network to use for adding shapes and stops. Defaults to None.

    -
    -     		- None -
    - - -

    Returns:

    - - - - - - - - - - - - - -
    Name TypeDescription
    TransitNetwork - TransitNetwork - -
    -

    Modified network.

    -
    -
    - -
    - Source code in network_wrangler/transit/projects/add_route.py - 
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    def apply_transit_route_addition(
-    net: TransitNetwork,
-    transit_route_addition: dict,
-    reference_road_net: Optional[RoadwayNetwork] = None,
-) -> TransitNetwork:
-    """Add transit route to TransitNetwork.
-
-    Args:
-        net (TransitNetwork): Network to modify.
-        transit_route_addition: route dictionary to add to the feed.
-        reference_road_net: (RoadwayNetwork, optional): Reference roadway network to use for adding shapes and stops. Defaults to None.
-
-    Returns:
-        TransitNetwork: Modified network.
-    """
-    WranglerLogger.debug("Applying add transit route project.")
-
-    add_routes = transit_route_addition["routes"]
-
-    road_net = net.road_net if reference_road_net is None else reference_road_net
-    if road_net is None:
-        WranglerLogger.error(
-            "! Must have a reference road network set in order to update transit \
-                         routin.  Either provide as an input to this function or set it for the \
-                         transit network: >> transit_net.road_net = ..."
-        )
-        msg = "Must have a reference road network set in order to update transit routing."
-        raise TransitRouteAddError(msg)
-
-    net.feed = _add_route_to_feed(net.feed, add_routes, road_net)
-
-    return net
-
    -
    -
    - -
    - - - -
    - -
    - -
    - -
    - - - - -
    - -

    Module for applying calculated transit projects to a transit network object.

    -

    These projects are stored in project card pycode property as python code strings which are -executed to change the transit network object.

    - - - -
    - - - - - - - - - -
    - - -

    - apply_calculated_transit(net, pycode) - -

    - - -
    - -

    Changes transit network object by executing pycode.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    net - TransitNetwork - -
    -

    transit network to manipulate

    -
    -     		- required -
    pycode - str - -
    -

    python code which changes values in the transit network object

    -
    -     		- required -
    - -
    - Source code in network_wrangler/transit/projects/calculate.py - 
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    def apply_calculated_transit(
-    net: TransitNetwork,
-    pycode: str,
-) -> TransitNetwork:
-    """Changes transit network object by executing pycode.
-
-    Args:
-        net: transit network to manipulate
-        pycode: python code which changes values in the transit network object
-    """
-    WranglerLogger.debug("Applying calculated transit project.")
-    exec(pycode)
-
-    return net
-
    -
    -
    - -
    - - - -
    - -
    - -
    - -
    - - - - -
    - -

    Functions for adding a transit route to a TransitNetwork.

    - - - -
    - - - - - - - - - -
    - - -

    - apply_transit_service_deletion(net, selection, clean_shapes=False, clean_routes=False) - -

    - - -
    - -

    Delete transit service to TransitNetwork.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    net - TransitNetwork - -
    -

    Network to modify.

    -
    -     		- required -
    selection - TransitSelection - -
    -

    TransitSelection object, created from a selection dictionary.

    -
    -     		- required -
    clean_shapes - bool - -
    -

    If True, remove shapes not used by any trips. -Defaults to False.

    -
    -     		- False -
    clean_routes - bool - -
    -

    If True, remove routes not used by any trips. -Defaults to False.

    -
    -     		- False -
    - - -

    Returns:

    - - - - - - - - - - - - - -
    Name TypeDescription
    TransitNetwork - TransitNetwork - -
    -

    Modified network.

    -
    -
    - -
    - Source code in network_wrangler/transit/projects/delete_service.py - 
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    def apply_transit_service_deletion(
-    net: TransitNetwork,
-    selection: TransitSelection,
-    clean_shapes: Optional[bool] = False,
-    clean_routes: Optional[bool] = False,
-) -> TransitNetwork:
-    """Delete transit service to TransitNetwork.
-
-    Args:
-        net (TransitNetwork): Network to modify.
-        selection: TransitSelection object, created from a selection dictionary.
-        clean_shapes (bool, optional): If True, remove shapes not used by any trips.
-            Defaults to False.
-        clean_routes (bool, optional): If True, remove routes not used by any trips.
-            Defaults to False.
-
-    Returns:
-        TransitNetwork: Modified network.
-    """
-    WranglerLogger.debug("Applying delete transit service project.")
-
-    trip_ids = selection.selected_trips
-    net.feed = _delete_trips_from_feed(
-        net.feed, trip_ids, clean_shapes=clean_shapes, clean_routes=clean_routes
-    )
-
-    return net
-
    -
    -
    - -
    - - - -
    - -
    - -
    - -
    - - - - -
    - -

    Functions for editing transit properties in a TransitNetwork.

    - - - -
    - - - - - - - - - -
    - - -

    - apply_transit_property_change(net, selection, property_changes, project_name=None) - -

    - - -
    - -

    Apply changes to transit properties.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    net - TransitNetwork - -
    -

    Network to modify.

    -
    -     		- required -
    selection - TransitSelection - -
    -

    Selection of trips to modify.

    -
    -     		- required -
    property_changes - dict - -
    -

    Dictionary of properties to change.

    -
    -     		- required -
    project_name - str - -
    -

    Name of the project. Defaults to None.

    -
    -     		- None -
    - - -

    Returns:

    - - - - - - - - - - - - - -
    Name TypeDescription
    TransitNetwork - TransitNetwork - -
    -

    Modified network.

    -
    -
    - -
    - Source code in network_wrangler/transit/projects/edit_property.py - 
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    def apply_transit_property_change(
-    net: TransitNetwork,
-    selection: TransitSelection,
-    property_changes: dict,
-    project_name: Optional[str] = None,
-) -> TransitNetwork:
-    """Apply changes to transit properties.
-
-    Args:
-        net (TransitNetwork): Network to modify.
-        selection (TransitSelection): Selection of trips to modify.
-        property_changes (dict): Dictionary of properties to change.
-        project_name (str, optional): Name of the project. Defaults to None.
-
-    Returns:
-        TransitNetwork: Modified network.
-    """
-    WranglerLogger.debug("Applying transit property change project.")
-    for property, property_change in property_changes.items():
-        net = _apply_transit_property_change_to_table(
-            net,
-            selection,
-            property,
-            property_change,
-            project_name=project_name,
-        )
-    return net
-
    -
    -
    - -
    - - - -
    - -
    - -
    - -
    - - - - -
    - -

    Functions for editing the transit route shapes and stop patterns.

    - - - -
    - - - - - - - - - -
    - - -

    - apply_transit_routing_change(net, selection, routing_change, reference_road_net=None, project_name=None) - -

    - - -
    - -

    Apply a routing change to the transit network, including stop updates.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    net - TransitNetwork - -
    -

    TransitNetwork object to apply routing change to.

    -
    -     		- required -
    selection - Selection - -
    -

    TransitSelection object, created from a selection dictionary.

    -
    -     		- required -
    routing_change - dict - -
    -

    Routing Change dictionary, e.g. -

    {
-    "existing": [46665, 150855],
-    "set": [-46665, 150855, 46665, 150855],
-}
-

    -
    -     		- required -
    shape_id_scalar - int - -
    -

    Initial scalar value to add to duplicated shape_ids to -create a new shape_id. Defaults to SHAPE_ID_SCALAR.

    -
    -     		- required -
    reference_road_net - RoadwayNetwork - -
    -

    Reference roadway network to use for -updating shapes and stops. Defaults to None.

    -
    -     		- None -
    project_name - str - -
    -

    Name of the project. Defaults to None.

    -
    -     		- None -
    - -
    - Source code in network_wrangler/transit/projects/edit_routing.py - 
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    def apply_transit_routing_change(
-    net: TransitNetwork,
-    selection: TransitSelection,
-    routing_change: dict,
-    reference_road_net: Optional[RoadwayNetwork] = None,
-    project_name: Optional[str] = None,
-) -> TransitNetwork:
-    """Apply a routing change to the transit network, including stop updates.
-
-    Args:
-        net (TransitNetwork): TransitNetwork object to apply routing change to.
-        selection (Selection): TransitSelection object, created from a selection dictionary.
-        routing_change (dict): Routing Change dictionary, e.g.
-            ```python
-            {
-                "existing": [46665, 150855],
-                "set": [-46665, 150855, 46665, 150855],
-            }
-            ```
-        shape_id_scalar (int, optional): Initial scalar value to add to duplicated shape_ids to
-            create a new shape_id. Defaults to SHAPE_ID_SCALAR.
-        reference_road_net (RoadwayNetwork, optional): Reference roadway network to use for
-            updating shapes and stops. Defaults to None.
-        project_name (str, optional): Name of the project. Defaults to None.
-    """
-    WranglerLogger.debug("Applying transit routing change project.")
-    WranglerLogger.debug(f"...selection: {selection.selection_dict}")
-    WranglerLogger.debug(f"...routing: {routing_change}")
-
-    # ---- Secure all inputs needed --------------
-    updated_feed = copy.deepcopy(net.feed)
-    trip_ids = selection.selected_trips
-    if project_name:
-        updated_feed.trips.loc[updated_feed.trips.trip_id.isin(trip_ids), "projects"] += (
-            f"{project_name},"
-        )
-
-    road_net = net.road_net if reference_road_net is None else reference_road_net
-    if road_net is None:
-        WranglerLogger.error(
-            "! Must have a reference road network set in order to update transit \
-                         routin.  Either provide as an input to this function or set it for the \
-                         transit network: >> transit_net.road_net = ..."
-        )
-        msg = "Must have a reference road network set in order to update transit routing."
-        raise TransitRoutingChangeError(msg)
-
-    # ---- update each shape that is used by selected trips to use new routing -------
-    shape_ids = shape_ids_for_trip_ids(updated_feed.trips, trip_ids)
-    # WranglerLogger.debug(f"shape_ids: {shape_ids}")
-    for shape_id in shape_ids:
-        updated_feed.shapes, updated_feed.trips = _update_shapes_and_trips(
-            updated_feed,
-            shape_id,
-            trip_ids,
-            routing_change["set"],
-            net.config.IDS.TRANSIT_SHAPE_ID_SCALAR,
-            road_net,
-            routing_existing=routing_change.get("existing", []),
-            project_name=project_name,
-        )
-    # WranglerLogger.debug(f"updated_feed.shapes: \n{updated_feed.shapes}")
-    # WranglerLogger.debug(f"updated_feed.trips: \n{updated_feed.trips}")
-    # ---- Check if any stops need adding to stops.txt and add if they do ----------
-    updated_feed.stops = _update_stops(
-        updated_feed, routing_change["set"], road_net, project_name=project_name
-    )
-    # WranglerLogger.debug(f"updated_feed.stops: \n{updated_feed.stops}")
-    # ---- Update stop_times --------------------------------------------------------
-    for trip_id in trip_ids:
-        updated_feed.stop_times = _update_stop_times_for_trip(
-            updated_feed,
-            trip_id,
-            routing_change["set"],
-            routing_change.get("existing", []),
-        )
-
-    # ---- Check result -------------------------------------------------------------
-    _show_col = [
-        "trip_id",
-        "stop_id",
-        "stop_sequence",
-        "departure_time",
-        "arrival_time",
-    ]
-    _ex_stoptimes = updated_feed.stop_times.loc[
-        updated_feed.stop_times.trip_id == trip_ids[0], _show_col
-    ]
-    # WranglerLogger.debug(f"stop_times for first updated trip: \n {_ex_stoptimes}")
-
-    # ---- Update transit network with updated feed.
-    net.feed = updated_feed
-    # WranglerLogger.debug(f"net.feed.stops: \n {net.feed.stops}")
-    return net
-
    -
    -
    - -
    - - - -
    - -
    - -

    Transit Helper Modules

    - - -
    - - - - -
    - -

    Functions to clip a TransitNetwork object to a boundary.

    -

    Clipped transit is an independent transit network that is a subset of the original transit network.

    -

    Example usage:

    -
    from network_wrangler.transit load_transit, write_transit
-from network_wrangler.transit.clip import clip_transit
-
-stpaul_transit = load_transit(example_dir / "stpaul")
-boundary_file = test_dir / "data" / "ecolab.geojson"
-clipped_network = clip_transit(stpaul_transit, boundary_file=boundary_file)
-write_transit(clipped_network, out_dir, prefix="ecolab", format="geojson", true_shape=True)
-
    - - - -
    - - - - - - - - - -
    - - -

    - clip_feed_to_boundary(feed, ref_nodes_df, boundary_gdf=None, boundary_geocode=None, boundary_file=None, min_stops=DEFAULT_MIN_STOPS) - -

    - - -
    - -

    Clips a transit Feed object to a boundary and returns the resulting GeoDataFrames.

    -

    Retains only the stops within the boundary and trips that traverse them subject to a minimum -number of stops per trip as defined by min_stops.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    feed - Feed - -
    -

    Feed object to be clipped.

    -
    -     		- required -
    ref_nodes_df - GeoDataFrame - -
    -

    geodataframe with node geometry to reference

    -
    -     		- required -
    boundary_geocode - Union[str, dict] - -
    -

    A geocode string or dictionary -representing the boundary. Defaults to None.

    -
    -     		- None -
    boundary_file - Union[str, Path] - -
    -

    A path to the boundary file. Only used if -boundary_geocode is None. Defaults to None.

    -
    -     		- None -
    boundary_gdf - GeoDataFrame - -
    -

    A GeoDataFrame representing the boundary. -Only used if boundary_geocode and boundary_file are None. Defaults to None.

    -
    -     		- None -
    min_stops - int - -
    -

    minimum number of stops needed to retain a transit trip within clipped area. -Defaults to DEFAULT_MIN_STOPS which is set to 2.

    -
    -     		- DEFAULT_MIN_STOPS -
    - - -
    - Source code in network_wrangler/transit/clip.py - 
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    def clip_feed_to_boundary(
-    feed: Feed,
-    ref_nodes_df: gpd.GeoDataFrame,
-    boundary_gdf: Optional[gpd.GeoDataFrame] = None,
-    boundary_geocode: Optional[Union[str, dict]] = None,
-    boundary_file: Optional[Union[str, Path]] = None,
-    min_stops: int = DEFAULT_MIN_STOPS,
-) -> Feed:
-    """Clips a transit Feed object to a boundary and returns the resulting GeoDataFrames.
-
-    Retains only the stops within the boundary and trips that traverse them subject to a minimum
-    number of stops per trip as defined by `min_stops`.
-
-    Args:
-        feed: Feed object to be clipped.
-        ref_nodes_df: geodataframe with node geometry to reference
-        boundary_geocode (Union[str, dict], optional): A geocode string or dictionary
-            representing the boundary. Defaults to None.
-        boundary_file (Union[str, Path], optional): A path to the boundary file. Only used if
-            boundary_geocode is None. Defaults to None.
-        boundary_gdf (gpd.GeoDataFrame, optional): A GeoDataFrame representing the boundary.
-            Only used if boundary_geocode and boundary_file are None. Defaults to None.
-        min_stops: minimum number of stops needed to retain a transit trip within clipped area.
-            Defaults to DEFAULT_MIN_STOPS which is set to 2.
-
-    Returns: Feed object trimmed to the boundary.
-    """
-    WranglerLogger.info("Clipping transit network to boundary.")
-
-    boundary_gdf = get_bounding_polygon(
-        boundary_gdf=boundary_gdf,
-        boundary_geocode=boundary_geocode,
-        boundary_file=boundary_file,
-    )
-
-    shape_links_gdf = shapes_to_shape_links_gdf(feed.shapes, ref_nodes_df=ref_nodes_df)
-
-    # make sure boundary_gdf.crs == network.crs
-    if boundary_gdf.crs != shape_links_gdf.crs:
-        boundary_gdf = boundary_gdf.to_crs(shape_links_gdf.crs)
-
-    # get the boundary as a single polygon
-    boundary = boundary_gdf.geometry.union_all()
-    # get the shape_links that intersect the boundary
-    clipped_shape_links = shape_links_gdf[shape_links_gdf.geometry.intersects(boundary)]
-
-    # nodes within clipped_shape_links
-    node_ids = list(set(clipped_shape_links.A.to_list() + clipped_shape_links.B.to_list()))
-    WranglerLogger.debug(f"Clipping network to {len(node_ids)} nodes.")
-    if not node_ids:
-        msg = "No nodes found within the boundary."
-        raise ValueError(msg)
-    return _clip_feed_to_nodes(feed, node_ids, min_stops=min_stops)
-
    -
    -
    - -
    - -
    - - -

    - clip_feed_to_roadway(feed, roadway_net, min_stops=DEFAULT_MIN_STOPS) - -

    - - -
    - -

    Returns a copy of transit feed clipped to the roadway network.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    feed - Feed - -
    -

    Transit Feed to clip.

    -
    -     		- required -
    roadway_net - RoadwayNetwork - -
    -

    Roadway network to clip to.

    -
    -     		- required -
    min_stops - int - -
    -

    minimum number of stops needed to retain a transit trip within clipped area. -Defaults to DEFAULT_MIN_STOPS which is set to 2.

    -
    -     		- DEFAULT_MIN_STOPS -
    - - -

    Raises:

    - - - - - - - - - - - - - -
    TypeDescription
    - ValueError - -
    -

    If no stops found within the roadway network.

    -
    -
    - - -

    Returns:

    - - - - - - - - - - - - - -
    Name TypeDescription
    Feed - Feed - -
    -

    Clipped deep copy of feed limited to the roadway network.

    -
    -
    - -
    - Source code in network_wrangler/transit/clip.py - 
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    def clip_feed_to_roadway(
-    feed: Feed,
-    roadway_net: RoadwayNetwork,
-    min_stops: int = DEFAULT_MIN_STOPS,
-) -> Feed:
-    """Returns a copy of transit feed clipped to the roadway network.
-
-    Args:
-        feed (Feed): Transit Feed to clip.
-        roadway_net: Roadway network to clip to.
-        min_stops: minimum number of stops needed to retain a transit trip within clipped area.
-            Defaults to DEFAULT_MIN_STOPS which is set to 2.
-
-    Raises:
-        ValueError: If no stops found within the roadway network.
-
-    Returns:
-        Feed: Clipped deep copy of feed limited to the roadway network.
-    """
-    WranglerLogger.info("Clipping transit network to roadway network.")
-
-    clipped_feed = _remove_links_from_feed(feed, roadway_net.links_df, min_stops=min_stops)
-
-    return clipped_feed
-
    -
    -
    - -
    - -
    - - -

    - clip_transit(network, node_ids=None, boundary_geocode=None, boundary_file=None, boundary_gdf=None, ref_nodes_df=None, roadway_net=None, min_stops=DEFAULT_MIN_STOPS) - -

    - - -
    - -

    Returns a new TransitNetwork clipped to a boundary as determined by arguments.

    -

    Will clip based on which arguments are provided as prioritized below:

    -
      -
    1. If node_ids provided, will clip based on node_ids
      2. -
    2. If boundary_geocode provided, will clip based on on search in OSM for that jurisdiction - boundary using reference geometry from ref_nodes_df, roadway_net, or roadway_path
      3. -
    3. If boundary_file provided, will clip based on that polygon using reference geometry - from ref_nodes_df, roadway_net, or roadway_path
      4. -
    4. If boundary_gdf provided, will clip based on that geodataframe using reference geometry - from ref_nodes_df, roadway_net, or roadway_path
      5. -
    5. If roadway_net provided, will clip based on that roadway network
      6. -
    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    network - TransitNetwork - -
    -

    TransitNetwork to clip.

    -
    -     		- required -
    node_ids - list[str] - -
    -

    A list of node_ids to clip to. Defaults to None.

    -
    -     		- None -
    boundary_geocode - Union[str, dict] - -
    -

    A geocode string or dictionary -representing the boundary. Only used if node_ids are None. Defaults to None.

    -
    -     		- None -
    boundary_file - Union[str, Path] - -
    -

    A path to the boundary file. Only used if -node_ids and boundary_geocode are None. Defaults to None.

    -
    -     		- None -
    boundary_gdf - GeoDataFrame - -
    -

    A GeoDataFrame representing the boundary. -Only used if node_ids, boundary_geocode and boundary_file are None. Defaults to None.

    -
    -     		- None -
    ref_nodes_df - Optional[Union[None, GeoDataFrame]] - -
    -

    GeoDataFrame of geographic references for node_ids. Only used if -node_ids is None and one of boundary_* is not None.

    -
    -     		- None -
    roadway_net - Optional[Union[None, RoadwayNetwork]] - -
    -

    Roadway Network instance to clip transit network to. Only used if -node_ids is None and allof boundary_* are None

    -
    -     		- None -
    min_stops - int - -
    -

    minimum number of stops needed to retain a transit trip within clipped area. -Defaults to DEFAULT_MIN_STOPS which is set to 2.

    -
    -     		- DEFAULT_MIN_STOPS -
    - -
    - Source code in network_wrangler/transit/clip.py - 
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    def clip_transit(
-    network: Union[TransitNetwork, str, Path],
-    node_ids: Optional[Union[None, list[str]]] = None,
-    boundary_geocode: Optional[Union[str, dict, None]] = None,
-    boundary_file: Optional[Union[str, Path]] = None,
-    boundary_gdf: Optional[Union[None, gpd.GeoDataFrame]] = None,
-    ref_nodes_df: Optional[Union[None, gpd.GeoDataFrame]] = None,
-    roadway_net: Optional[Union[None, RoadwayNetwork]] = None,
-    min_stops: int = DEFAULT_MIN_STOPS,
-) -> TransitNetwork:
-    """Returns a new TransitNetwork clipped to a boundary as determined by arguments.
-
-    Will clip based on which arguments are provided as prioritized below:
-
-    1. If `node_ids` provided, will clip based on `node_ids`
-    2. If `boundary_geocode` provided, will clip based on on search in OSM for that jurisdiction
-        boundary using reference geometry from `ref_nodes_df`, `roadway_net`, or `roadway_path`
-    3. If `boundary_file` provided, will clip based on that polygon  using reference geometry
-        from `ref_nodes_df`, `roadway_net`, or `roadway_path`
-    4. If `boundary_gdf` provided, will clip based on that geodataframe  using reference geometry
-        from `ref_nodes_df`, `roadway_net`, or `roadway_path`
-    5. If `roadway_net` provided, will clip based on that roadway network
-
-    Args:
-        network (TransitNetwork): TransitNetwork to clip.
-        node_ids (list[str], optional): A list of node_ids to clip to. Defaults to None.
-        boundary_geocode (Union[str, dict], optional): A geocode string or dictionary
-            representing the boundary. Only used if node_ids are None. Defaults to None.
-        boundary_file (Union[str, Path], optional): A path to the boundary file. Only used if
-            node_ids and boundary_geocode are None. Defaults to None.
-        boundary_gdf (gpd.GeoDataFrame, optional): A GeoDataFrame representing the boundary.
-            Only used if node_ids, boundary_geocode and boundary_file are None. Defaults to None.
-        ref_nodes_df: GeoDataFrame of geographic references for node_ids.  Only used if
-            node_ids is None and one of boundary_* is not None.
-        roadway_net: Roadway Network  instance to clip transit network to.  Only used if
-            node_ids is None and allof boundary_* are None
-        min_stops: minimum number of stops needed to retain a transit trip within clipped area.
-            Defaults to DEFAULT_MIN_STOPS which is set to 2.
-    """
-    if not isinstance(network, TransitNetwork):
-        network = load_transit(network)
-    set_roadway_network = False
-    feed = network.feed
-
-    if node_ids is not None:
-        clipped_feed = _clip_feed_to_nodes(feed, node_ids=node_ids, min_stops=min_stops)
-    elif any(i is not None for i in [boundary_file, boundary_geocode, boundary_gdf]):
-        if ref_nodes_df is None:
-            ref_nodes_df = get_nodes(transit_net=network, roadway_net=roadway_net)
-
-        clipped_feed = clip_feed_to_boundary(
-            feed,
-            ref_nodes_df,
-            boundary_file=boundary_file,
-            boundary_geocode=boundary_geocode,
-            boundary_gdf=boundary_gdf,
-            min_stops=min_stops,
-        )
-    elif roadway_net is not None:
-        clipped_feed = clip_feed_to_roadway(feed, roadway_net=roadway_net)
-        set_roadway_network = True
-    else:
-        msg = "Missing required arguments from clip_transit"
-        raise ValueError(msg)
-
-    # create a new TransitNetwork object with the clipped feed dataframes
-    clipped_net = TransitNetwork(clipped_feed)
-
-    if set_roadway_network:
-        WranglerLogger.info("Setting roadway network for clipped transit network.")
-        clipped_net.road_net = roadway_net
-    return clipped_net
-
    -
    -
    - -
    - - - -
    - -
    - -
    - -
    - - - - -
    - -

    Utilities for working with transit geodataframes.

    - - - -
    - - - - - - - - - -
    - - - - - -
    - -

    Translates shapes to shape links geodataframe using geometry from ref_nodes_df if provided.

    -

    TODO: Add join to links and then shapes to get true geometry.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    shapes - DataFrame[WranglerShapesTable] - -
    -

    Feed shapes table

    -
    -     		- required -
    ref_nodes_df - Optional[DataFrame[RoadNodesTable]] - -
    -

    If specified, will use geometry from these nodes. Otherwise, will use -geometry in shapes file. Defaults to None.

    -
    -     		- None -
    from_field - str - -
    -

    Field used for the link’s from node model_node_id. Defaults to “A”.

    -
    -     		- 'A' -
    to_field - str - -
    -

    Field used for the link’s to node model_node_id. Defaults to “B”.

    -
    -     		- 'B' -
    crs - int - -
    -

    Coordinate reference system. SHouldn’t be changed unless you know -what you are doing. Defaults to LAT_LON_CRS which is WGS84 lat/long.

    -
    -     		- LAT_LON_CRS -
    - - -

    Returns:

    - - - - - - - - - - - - - -
    TypeDescription
    - GeoDataFrame - -
    -

    gpd.GeoDataFrame: description

    -
    -
    - -
    - Source code in network_wrangler/transit/geo.py - 
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    def shapes_to_shape_links_gdf(
-    shapes: DataFrame[WranglerShapesTable],
-    ref_nodes_df: Optional[DataFrame[RoadNodesTable]] = None,
-    from_field: str = "A",
-    to_field: str = "B",
-    crs: int = LAT_LON_CRS,
-) -> gpd.GeoDataFrame:
-    """Translates shapes to shape links geodataframe using geometry from ref_nodes_df if provided.
-
-    TODO: Add join to links and then shapes to get true geometry.
-
-    Args:
-        shapes: Feed shapes table
-        ref_nodes_df: If specified, will use geometry from these nodes.  Otherwise, will use
-            geometry in shapes file. Defaults to None.
-        from_field: Field used for the link's from node `model_node_id`. Defaults to "A".
-        to_field: Field used for the link's to node `model_node_id`. Defaults to "B".
-        crs (int, optional): Coordinate reference system. SHouldn't be changed unless you know
-            what you are doing. Defaults to LAT_LON_CRS which is WGS84 lat/long.
-
-    Returns:
-        gpd.GeoDataFrame: _description_
-    """
-    if ref_nodes_df is not None:
-        shapes = update_shapes_geometry(shapes, ref_nodes_df)
-    tr_links = unique_shape_links(shapes, from_field=from_field, to_field=to_field)
-    # WranglerLogger.debug(f"tr_links :\n{tr_links }")
-
-    geometry = linestring_from_lats_lons(
-        tr_links,
-        [f"shape_pt_lat_{from_field}", f"shape_pt_lat_{to_field}"],
-        [f"shape_pt_lon_{from_field}", f"shape_pt_lon_{to_field}"],
-    )
-    # WranglerLogger.debug(f"geometry\n{geometry}")
-    shapes_gdf = gpd.GeoDataFrame(tr_links, geometry=geometry, crs=crs).set_crs(LAT_LON_CRS)
-    return shapes_gdf
-
    -
    -
    - -
    - -
    - - -

    - shapes_to_trip_shapes_gdf(shapes, ref_nodes_df=None, crs=LAT_LON_CRS) - -

    - - -
    - -

    Geodataframe with one polyline shape per shape_id.

    -

    TODO: add information about the route and trips.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    shapes - DataFrame[WranglerShapesTable] - -
    -

    WranglerShapesTable

    -
    -     		- required -
    trips - -
    -

    WranglerTripsTable

    -
    -     		- required -
    ref_nodes_df - Optional[DataFrame[RoadNodesTable]] - -
    -

    If specified, will use geometry from these nodes. Otherwise, will use -geometry in shapes file. Defaults to None.

    -
    -     		- None -
    crs - int - -
    -

    int, optional, default 4326

    -
    -     		- LAT_LON_CRS -
    - -
    - Source code in network_wrangler/transit/geo.py - 
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    def shapes_to_trip_shapes_gdf(
-    shapes: DataFrame[WranglerShapesTable],
-    # trips: WranglerTripsTable,
-    ref_nodes_df: Optional[DataFrame[RoadNodesTable]] = None,
-    crs: int = LAT_LON_CRS,
-) -> gpd.GeoDataFrame:
-    """Geodataframe with one polyline shape per shape_id.
-
-    TODO: add information about the route and trips.
-
-    Args:
-        shapes: WranglerShapesTable
-        trips: WranglerTripsTable
-        ref_nodes_df: If specified, will use geometry from these nodes.  Otherwise, will use
-            geometry in shapes file. Defaults to None.
-        crs: int, optional, default 4326
-    """
-    if ref_nodes_df is not None:
-        shapes = update_shapes_geometry(shapes, ref_nodes_df)
-
-    shape_geom = (
-        shapes[["shape_id", "shape_pt_lat", "shape_pt_lon"]]
-        .groupby("shape_id")
-        .agg(list)
-        .apply(lambda x: LineString(zip(x[1], x[0])), axis=1)
-    )
-
-    route_shapes_gdf = gpd.GeoDataFrame(
-        data=shape_geom.index, geometry=shape_geom.values, crs=crs
-    ).set_crs(LAT_LON_CRS)
-
-    return route_shapes_gdf
-
    -
    -
    - -
    - -
    - - - - - -
    - -

    Stop times geodataframe as links using geometry from stops.txt or optionally another df.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    stop_times - WranglerStopTimesTable - -
    -

    Feed stop times table.

    -
    -     		- required -
    stops - WranglerStopsTable - -
    -

    Feed stops table.

    -
    -     		- required -
    ref_nodes_df - DataFrame - -
    -

    If specified, will use geometry from these nodes. -Otherwise, will use geometry in shapes file. Defaults to None.

    -
    -     		- None -
    from_field - str - -
    -

    Field used for the link’s from node model_node_id. Defaults to “A”.

    -
    -     		- 'A' -
    to_field - str - -
    -

    Field used for the link’s to node model_node_id. Defaults to “B”.

    -
    -     		- 'B' -
    - -
    - Source code in network_wrangler/transit/geo.py - 
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    def stop_times_to_stop_time_links_gdf(
-    stop_times: DataFrame[WranglerStopTimesTable],
-    stops: DataFrame[WranglerStopsTable],
-    ref_nodes_df: Optional[DataFrame[RoadNodesTable]] = None,
-    from_field: str = "A",
-    to_field: str = "B",
-) -> gpd.GeoDataFrame:
-    """Stop times geodataframe as links using geometry from stops.txt or optionally another df.
-
-    Args:
-        stop_times (WranglerStopTimesTable): Feed stop times table.
-        stops (WranglerStopsTable): Feed stops table.
-        ref_nodes_df (pd.DataFrame, optional): If specified, will use geometry from these nodes.
-            Otherwise, will use geometry in shapes file. Defaults to None.
-        from_field: Field used for the link's from node `model_node_id`. Defaults to "A".
-        to_field: Field used for the link's to node `model_node_id`. Defaults to "B".
-    """
-    from ..utils.geo import linestring_from_lats_lons
-
-    if ref_nodes_df is not None:
-        stops = update_stops_geometry(stops, ref_nodes_df)
-
-    lat_fields = []
-    lon_fields = []
-    tr_links = unique_stop_time_links(stop_times, from_field=from_field, to_field=to_field)
-    for f in (from_field, to_field):
-        tr_links = tr_links.merge(
-            stops[["stop_id", "stop_lat", "stop_lon"]],
-            right_on="stop_id",
-            left_on=f,
-            how="left",
-        )
-        lon_f = f"{f}_X"
-        lat_f = f"{f}_Y"
-        tr_links = tr_links.rename(columns={"stop_lon": lon_f, "stop_lat": lat_f})
-        lon_fields.append(lon_f)
-        lat_fields.append(lat_f)
-
-    geometry = linestring_from_lats_lons(tr_links, lat_fields, lon_fields)
-    return gpd.GeoDataFrame(tr_links, geometry=geometry).set_crs(LAT_LON_CRS)
-
    -
    -
    - -
    - -
    - - -

    - stop_times_to_stop_time_points_gdf(stop_times, stops, ref_nodes_df=None) - -

    - - -
    - -

    Stoptimes geodataframe as points using geometry from stops.txt or optionally another df.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    stop_times - WranglerStopTimesTable - -
    -

    Feed stop times table.

    -
    -     		- required -
    stops - WranglerStopsTable - -
    -

    Feed stops table.

    -
    -     		- required -
    ref_nodes_df - DataFrame - -
    -

    If specified, will use geometry from these nodes. -Otherwise, will use geometry in shapes file. Defaults to None.

    -
    -     		- None -
    - -
    - Source code in network_wrangler/transit/geo.py - 
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    def stop_times_to_stop_time_points_gdf(
-    stop_times: DataFrame[WranglerStopTimesTable],
-    stops: DataFrame[WranglerStopsTable],
-    ref_nodes_df: Optional[DataFrame[RoadNodesTable]] = None,
-) -> gpd.GeoDataFrame:
-    """Stoptimes geodataframe as points using geometry from stops.txt or optionally another df.
-
-    Args:
-        stop_times (WranglerStopTimesTable): Feed stop times table.
-        stops (WranglerStopsTable): Feed stops table.
-        ref_nodes_df (pd.DataFrame, optional): If specified, will use geometry from these nodes.
-            Otherwise, will use geometry in shapes file. Defaults to None.
-    """
-    if ref_nodes_df is not None:
-        stops = update_stops_geometry(stops, ref_nodes_df)
-
-    stop_times_geo = stop_times.merge(
-        stops[["stop_id", "stop_lat", "stop_lon"]],
-        right_on="stop_id",
-        left_on="stop_id",
-        how="left",
-    )
-    return gpd.GeoDataFrame(
-        stop_times_geo,
-        geometry=gpd.points_from_xy(stop_times_geo["stop_lon"], stop_times_geo["stop_lat"]),
-        crs=LAT_LON_CRS,
-    )
-
    -
    -
    - -
    - -
    - - -

    - update_shapes_geometry(shapes, ref_nodes_df) - -

    - - -
    - -

    Returns shapes table with geometry updated from ref_nodes_df.

    -

    NOTE: does not update “geometry” field if it exists.

    - -
    - Source code in network_wrangler/transit/geo.py - 
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    def update_shapes_geometry(
-    shapes: DataFrame[WranglerShapesTable], ref_nodes_df: DataFrame[RoadNodesTable]
-) -> DataFrame[WranglerShapesTable]:
-    """Returns shapes table with geometry updated from ref_nodes_df.
-
-    NOTE: does not update "geometry" field if it exists.
-    """
-    return update_point_geometry(
-        shapes,
-        ref_nodes_df,
-        id_field="shape_model_node_id",
-        lon_field="shape_pt_lon",
-        lat_field="shape_pt_lat",
-    )
-
    -
    -
    - -
    - -
    - - -

    - update_stops_geometry(stops, ref_nodes_df) - -

    - - -
    - -

    Returns stops table with geometry updated from ref_nodes_df.

    -

    NOTE: does not update “geometry” field if it exists.

    - -
    - Source code in network_wrangler/transit/geo.py - 
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    def update_stops_geometry(
-    stops: DataFrame[WranglerStopsTable], ref_nodes_df: DataFrame[RoadNodesTable]
-) -> DataFrame[WranglerStopsTable]:
-    """Returns stops table with geometry updated from ref_nodes_df.
-
-    NOTE: does not update "geometry" field if it exists.
-    """
-    return update_point_geometry(
-        stops, ref_nodes_df, id_field="stop_id", lon_field="stop_lon", lat_field="stop_lat"
-    )
-
    -
    -
    - -
    - - - -
    - -
    - -
    - -
    - - - - -
    - -

    Functions for reading and writing transit feeds and networks.

    - - - -
    - - - - - - - - - -
    - - -

    - convert_transit_serialization(input_path, output_format, out_dir='.', input_file_format='csv', out_prefix='', overwrite=True) - -

    - - -
    - -

    Converts a transit network from one serialization to another.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    input_path - Union[str, Path] - -
    -

    path to the input network

    -
    -     		- required -
    output_format - TransitFileTypes - -
    -

    the format of the output files. Should be txt, csv, or parquet.

    -
    -     		- required -
    out_dir - Union[Path, str] - -
    -

    directory to write the network to. Defaults to current directory.

    -
    -     		- '.' -
    input_file_format - TransitFileTypes - -
    -

    the file_format of the files to read. Should be txt, csv, or parquet. -Defaults to “txt”

    -
    -     		- 'csv' -
    out_prefix - str - -
    -

    prefix to add to the file name. Defaults to “”

    -
    -     		- '' -
    overwrite - bool - -
    -

    if True, will overwrite the files if they already exist. Defaults to True

    -
    -     		- True -
    - -
    - Source code in network_wrangler/transit/io.py - 
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    def convert_transit_serialization(
-    input_path: Union[str, Path],
-    output_format: TransitFileTypes,
-    out_dir: Union[Path, str] = ".",
-    input_file_format: TransitFileTypes = "csv",
-    out_prefix: str = "",
-    overwrite: bool = True,
-):
-    """Converts a transit network from one serialization to another.
-
-    Args:
-        input_path: path to the input network
-        output_format: the format of the output files. Should be txt, csv, or parquet.
-        out_dir: directory to write the network to. Defaults to current directory.
-        input_file_format: the file_format of the files to read. Should be txt, csv, or parquet.
-            Defaults to "txt"
-        out_prefix: prefix to add to the file name. Defaults to ""
-        overwrite: if True, will overwrite the files if they already exist. Defaults to True
-    """
-    WranglerLogger.info(
-        f"Loading transit net from {input_path} with input type {input_file_format}"
-    )
-    net = load_transit(input_path, file_format=input_file_format)
-    WranglerLogger.info(f"Writing transit network to {out_dir} in {output_format} format.")
-    write_transit(
-        net,
-        prefix=out_prefix,
-        out_dir=out_dir,
-        file_format=output_format,
-        overwrite=overwrite,
-    )
-
    -
    -
    - -
    - -
    - - -

    - load_feed_from_dfs(feed_dfs) - -

    - - -
    - -

    Create a TransitNetwork object from a dictionary of DataFrames representing a GTFS feed.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    feed_dfs - dict - -
    -

    A dictionary containing DataFrames representing the tables of a GTFS feed.

    -
    -     		- required -
    - - -

    Returns:

    - - - - - - - - - - - - - -
    Name TypeDescription
    Feed - Feed - -
    -

    A Feed object representing the transit network.

    -
    -
    - - -

    Raises:

    - - - - - - - - - - - - - -
    TypeDescription
    - ValueError - -
    -

    If the feed_dfs dictionary does not contain all the required tables.

    -
    -
    - - -
    - Example -
    -
    -
    -

    feed_dfs = { -… “agency”: agency_df, -… “routes”: routes_df, -… “stops”: stops_df, -… “trips”: trips_df, -… “stop_times”: stop_times_df, -… } -feed = load_feed_from_dfs(feed_dfs)

    -
    -
    -
    -
    -
    - Source code in network_wrangler/transit/io.py - 
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    def load_feed_from_dfs(feed_dfs: dict) -> Feed:
-    """Create a TransitNetwork object from a dictionary of DataFrames representing a GTFS feed.
-
-    Args:
-        feed_dfs (dict): A dictionary containing DataFrames representing the tables of a GTFS feed.
-
-    Returns:
-        Feed: A Feed object representing the transit network.
-
-    Raises:
-        ValueError: If the feed_dfs dictionary does not contain all the required tables.
-
-    Example:
-        >>> feed_dfs = {
-        ...     "agency": agency_df,
-        ...     "routes": routes_df,
-        ...     "stops": stops_df,
-        ...     "trips": trips_df,
-        ...     "stop_times": stop_times_df,
-        ... }
-        >>> feed = load_feed_from_dfs(feed_dfs)
-    """
-    if not all(table in feed_dfs for table in Feed.table_names):
-        msg = f"feed_dfs must contain the following tables: {Feed.table_names}"
-        raise ValueError(msg)
-
-    feed = Feed(**feed_dfs)
-
-    return feed
-
    -
    -
    - -
    - -
    - - -

    - load_feed_from_path(feed_path, file_format='txt') - -

    - - -
    - -

    Create a Feed object from the path to a GTFS transit feed.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    feed_path - Union[Path, str] - -
    -

    The path to the GTFS transit feed.

    -
    -     		- required -
    file_format - TransitFileTypes - -
    -

    the format of the files to read. Defaults to “txt”

    -
    -     		- 'txt' -
    - - -

    Returns:

    - - - - - - - - - - - - - -
    Name TypeDescription
    Feed - Feed - -
    -

    The TransitNetwork object created from the GTFS transit feed.

    -
    -
    - -
    - Source code in network_wrangler/transit/io.py - 
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    def load_feed_from_path(
-    feed_path: Union[Path, str], file_format: TransitFileTypes = "txt"
-) -> Feed:
-    """Create a Feed object from the path to a GTFS transit feed.
-
-    Args:
-        feed_path (Union[Path, str]): The path to the GTFS transit feed.
-        file_format: the format of the files to read. Defaults to "txt"
-
-    Returns:
-        Feed: The TransitNetwork object created from the GTFS transit feed.
-    """
-    feed_path = _feed_path_ref(Path(feed_path))  # unzips if needs to be unzipped
-
-    if not feed_path.is_dir():
-        msg = f"Feed path not a directory: {feed_path}"
-        raise NotADirectoryError(msg)
-
-    WranglerLogger.info(f"Reading GTFS feed tables from {feed_path}")
-
-    feed_possible_files = {
-        table: list(feed_path.glob(f"*{table}.{file_format}")) for table in Feed.table_names
-    }
-
-    # make sure we have all the tables we need
-    _missing_files = [t for t, v in feed_possible_files.items() if not v]
-
-    if _missing_files:
-        WranglerLogger.debug(f"!!! Missing transit files: {_missing_files}")
-        msg = f"Required GTFS Feed table(s) not in {feed_path}: \n  {_missing_files}"
-        raise RequiredTableError(msg)
-
-    # but don't want to have more than one file per search
-    _ambiguous_files = [t for t, v in feed_possible_files.items() if len(v) > 1]
-    if _ambiguous_files:
-        WranglerLogger.warning(
-            f"! More than one file matches following tables. \
-                               Using the first on the list: {_ambiguous_files}"
-        )
-
-    feed_files = {t: f[0] for t, f in feed_possible_files.items()}
-    feed_dfs = {table: _read_table_from_file(table, file) for table, file in feed_files.items()}
-
-    return load_feed_from_dfs(feed_dfs)
-
    -
    -
    - -
    - -
    - - -

    - load_transit(feed, file_format='txt', config=DefaultConfig) - -

    - - -
    - -

    Create a TransitNetwork object.

    -

    This function takes in a feed parameter, which can be one of the following types: -- Feed: A Feed object representing a transit feed. -- dict[str, pd.DataFrame]: A dictionary of DataFrames representing transit data. -- str or Path: A string or a Path object representing the path to a transit feed file.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    feed - Union[Feed, GtfsModel, dict[str, DataFrame], str, Path] - -
    -

    Feed boject, dict of transit data frames, or path to transit feed data

    -
    -     		- required -
    file_format - TransitFileTypes - -
    -

    the format of the files to read. Defaults to “txt”

    -
    -     		- 'txt' -
    config - WranglerConfig - -
    -

    WranglerConfig object. Defaults to DefaultConfig.

    -
    -     		- DefaultConfig -
    -

    A TransitNetwork object representing the loaded transit network.

    -

    Raises: -ValueError: If the feed parameter is not one of the supported types.

    -

    Example usage: -

    transit_network_from_zip = load_transit("path/to/gtfs.zip")
-
-transit_network_from_unzipped_dir = load_transit("path/to/files")
-
-transit_network_from_parquet = load_transit("path/to/files", file_format="parquet")
-
-dfs_of_transit_data = {"routes": routes_df, "stops": stops_df, "trips": trips_df...}
-transit_network_from_dfs = load_transit(dfs_of_transit_data)
-

    - -
    - Source code in network_wrangler/transit/io.py - 
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    def load_transit(
-    feed: Union[Feed, GtfsModel, dict[str, pd.DataFrame], str, Path],
-    file_format: TransitFileTypes = "txt",
-    config: WranglerConfig = DefaultConfig,
-) -> "TransitNetwork":
-    """Create a TransitNetwork object.
-
-    This function takes in a `feed` parameter, which can be one of the following types:
-    - `Feed`: A Feed object representing a transit feed.
-    - `dict[str, pd.DataFrame]`: A dictionary of DataFrames representing transit data.
-    - `str` or `Path`: A string or a Path object representing the path to a transit feed file.
-
-    Args:
-        feed: Feed boject, dict of transit data frames, or path to transit feed data
-        file_format: the format of the files to read. Defaults to "txt"
-        config: WranglerConfig object. Defaults to DefaultConfig.
-
-    Returns:
-    A TransitNetwork object representing the loaded transit network.
-
-    Raises:
-    ValueError: If the `feed` parameter is not one of the supported types.
-
-    Example usage:
-    ```
-    transit_network_from_zip = load_transit("path/to/gtfs.zip")
-
-    transit_network_from_unzipped_dir = load_transit("path/to/files")
-
-    transit_network_from_parquet = load_transit("path/to/files", file_format="parquet")
-
-    dfs_of_transit_data = {"routes": routes_df, "stops": stops_df, "trips": trips_df...}
-    transit_network_from_dfs = load_transit(dfs_of_transit_data)
-    ```
-
-    """
-    if isinstance(feed, (Path, str)):
-        feed = Path(feed)
-        feed_obj = load_feed_from_path(feed, file_format=file_format)
-        feed_obj.feed_path = feed
-    elif isinstance(feed, dict):
-        feed_obj = load_feed_from_dfs(feed)
-    elif isinstance(feed, GtfsModel):
-        feed_obj = Feed(**feed.__dict__)
-    else:
-        if not isinstance(feed, Feed):
-            msg = f"TransitNetwork must be seeded with a Feed, dict of dfs or Path. Found {type(feed)}"
-            raise ValueError(msg)
-        feed_obj = feed
-
-    return TransitNetwork(feed_obj, config=config)
-
    -
    -
    - -
    - -
    - - -

    - write_feed_geo(feed, ref_nodes_df, out_dir, file_format='geojson', out_prefix=None, overwrite=True) - -

    - - -
    - -

    Write a Feed object to a directory in a geospatial format.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    feed - Feed - -
    -

    Feed object to write

    -
    -     		- required -
    ref_nodes_df - GeoDataFrame - -
    -

    Reference nodes dataframe to use for geometry

    -
    -     		- required -
    out_dir - Union[str, Path] - -
    -

    directory to write the network to

    -
    -     		- required -
    file_format - Literal['geojson', 'shp', 'parquet'] - -
    -

    the format of the output files. Defaults to “geojson”

    -
    -     		- 'geojson' -
    out_prefix - -
    -

    prefix to add to the file name

    -
    -     		- None -
    overwrite - bool - -
    -

    if True, will overwrite the files if they already exist. Defaults to True

    -
    -     		- True -
    - -
    - Source code in network_wrangler/transit/io.py - 
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    def write_feed_geo(
-    feed: Feed,
-    ref_nodes_df: gpd.GeoDataFrame,
-    out_dir: Union[str, Path],
-    file_format: Literal["geojson", "shp", "parquet"] = "geojson",
-    out_prefix=None,
-    overwrite: bool = True,
-) -> None:
-    """Write a Feed object to a directory in a geospatial format.
-
-    Args:
-        feed: Feed object to write
-        ref_nodes_df: Reference nodes dataframe to use for geometry
-        out_dir: directory to write the network to
-        file_format: the format of the output files. Defaults to "geojson"
-        out_prefix: prefix to add to the file name
-        overwrite: if True, will overwrite the files if they already exist. Defaults to True
-    """
-    from .geo import shapes_to_shape_links_gdf
-
-    out_dir = Path(out_dir)
-    if not out_dir.is_dir():
-        if out_dir.parent.is_dir():
-            out_dir.mkdir()
-        else:
-            msg = f"Output directory {out_dir} ands its parent path does not exist"
-            raise FileNotFoundError(msg)
-
-    prefix = f"{out_prefix}_" if out_prefix else ""
-    shapes_outpath = out_dir / f"{prefix}trn_shapes.{file_format}"
-    shapes_gdf = shapes_to_shape_links_gdf(feed.shapes, ref_nodes_df=ref_nodes_df)
-    write_table(shapes_gdf, shapes_outpath, overwrite=overwrite)
-
-    stops_outpath = out_dir / f"{prefix}trn_stops.{file_format}"
-    stops_gdf = to_points_gdf(feed.stops, ref_nodes_df=ref_nodes_df)
-    write_table(stops_gdf, stops_outpath, overwrite=overwrite)
-
    -
    -
    - -
    - -
    - - -

    - write_transit(transit_net, out_dir='.', prefix=None, file_format='txt', overwrite=True) - -

    - - -
    - -

    Writes a network in the transit network standard.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    transit_net - -
    -

    a TransitNetwork instance

    -
    -     		- required -
    out_dir - Union[Path, str] - -
    -

    directory to write the network to

    -
    -     		- '.' -
    file_format - Literal['txt', 'csv', 'parquet'] - -
    -

    the format of the output files. Defaults to “txt” which is csv with txt -file format.

    -
    -     		- 'txt' -
    prefix - Optional[Union[Path, str]] - -
    -

    prefix to add to the file name

    -
    -     		- None -
    overwrite - bool - -
    -

    if True, will overwrite the files if they already exist. Defaults to True

    -
    -     		- True -
    - -
    - Source code in network_wrangler/transit/io.py - 
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    def write_transit(
-    transit_net,
-    out_dir: Union[Path, str] = ".",
-    prefix: Optional[Union[Path, str]] = None,
-    file_format: Literal["txt", "csv", "parquet"] = "txt",
-    overwrite: bool = True,
-) -> None:
-    """Writes a network in the transit network standard.
-
-    Args:
-        transit_net: a TransitNetwork instance
-        out_dir: directory to write the network to
-        file_format: the format of the output files. Defaults to "txt" which is csv with txt
-            file format.
-        prefix: prefix to add to the file name
-        overwrite: if True, will overwrite the files if they already exist. Defaults to True
-    """
-    out_dir = Path(out_dir)
-    prefix = f"{prefix}_" if prefix else ""
-    for table in transit_net.feed.table_names:
-        df = transit_net.feed.get_table(table)
-        outpath = out_dir / f"{prefix}{table}.{file_format}"
-        write_table(df, outpath, overwrite=overwrite)
-    WranglerLogger.info(f"Wrote {len(transit_net.feed.tables)} files to {out_dir}")
-
    -
    -
    - -
    - - - -
    - -
    - -
    - -
    - - - - -
    - -

    ModelTransit class and functions for managing consistency between roadway and transit networks.

    -

    NOTE: this is not thoroughly tested and may not be fully functional.

    - - - -
    - - - - - - - - -
    - - - -

    - ModelTransit - - -

    - - -
    - - -

    ModelTransit class for managing consistency between roadway and transit networks.

    - -
    - Source code in network_wrangler/transit/model_transit.py - 
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    class ModelTransit:
-    """ModelTransit class for managing consistency between roadway and transit networks."""
-
-    def __init__(
-        self,
-        transit_net: TransitNetwork,
-        roadway_net: RoadwayNetwork,
-        shift_transit_to_managed_lanes: bool = True,
-    ):
-        """ModelTransit class for managing consistency between roadway and transit networks."""
-        self.transit_net = transit_net
-        self.roadway_net = roadway_net
-        self._roadway_net_hash = None
-        self._transit_feed_hash = None
-        self._transit_shifted_to_ML = shift_transit_to_managed_lanes
-
-    @property
-    def model_roadway_net(self):
-        """ModelRoadwayNetwork associated with this ModelTransit."""
-        return self.roadway_net.model_net
-
-    @property
-    def consistent_nets(self) -> bool:
-        """Indicate if roadway and transit networks have changed since self.m_feed updated."""
-        return bool(
-            self.roadway_net.network_hash == self._roadway_net_hash
-            and self.transit_net.feed_hash == self._transit_feed_hash
-        )
-
-    @property
-    def m_feed(self):
-        """TransitNetwork.feed with updates for consistency with associated ModelRoadwayNetwork."""
-        if self.consistent_nets:
-            return self._m_feed
-        # NOTE: look at this
-        # If netoworks have changed, updated model transit and update reference hash
-        self._roadway_net_hash = copy.deepcopy(self.roadway_net.network_hash)
-        self._transit_feed_hash = copy.deepcopy(self.transit_net.feed_hash)
-
-        if not self._transit_shifted_to_ML:
-            self._m_feed = copy.deepcopy(self.transit_net.feed)
-            return self._m_feed
-        return None
-
    -
    - - - -
    - - - - - - - -
    - - - -
    - consistent_nets: bool - - - property - - -
    - - -
    - -

    Indicate if roadway and transit networks have changed since self.m_feed updated.

    -
    - -
    - -
    - - - -
    - m_feed - - - property - - -
    - - -
    - -

    TransitNetwork.feed with updates for consistency with associated ModelRoadwayNetwork.

    -
    - -
    - -
    - - - -
    - model_roadway_net - - - property - - -
    - - -
    - -

    ModelRoadwayNetwork associated with this ModelTransit.

    -
    - -
    - - - -
    - - -
    - __init__(transit_net, roadway_net, shift_transit_to_managed_lanes=True) - -
    - - -
    - -

    ModelTransit class for managing consistency between roadway and transit networks.

    - -
    - Source code in network_wrangler/transit/model_transit.py - 
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    def __init__(
-    self,
-    transit_net: TransitNetwork,
-    roadway_net: RoadwayNetwork,
-    shift_transit_to_managed_lanes: bool = True,
-):
-    """ModelTransit class for managing consistency between roadway and transit networks."""
-    self.transit_net = transit_net
-    self.roadway_net = roadway_net
-    self._roadway_net_hash = None
-    self._transit_feed_hash = None
-    self._transit_shifted_to_ML = shift_transit_to_managed_lanes
-
    -
    -
    - -
    - - - -
    - -
    - -
    - - - - -
    - -
    - -
    - -
    - - - - -
    - -

    Classes and functions for selecting transit trips from a transit network.

    -

    Usage:

    -

    Create a TransitSelection object by providing a TransitNetwork object and a selection dictionary:

    -
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    ```python
-selection_dict = {
-    "links": {...},
-    "nodes": {...},
-    "route_properties": {...},
-    "trip_properties": {...},
-    "timespans": {...},
-}
-transit_selection = TransitSelection(transit_network, selection_dict)
-```
-
    - -

    Access the selected trip ids or dataframe as follows:

    -
    1
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    ```python
-selected_trips = transit_selection.selected_trips
-selected_trips_df = transit_selection.selected_trips_df
-```
-
    - -

    Note: The selection dictionary should conform to the SelectTransitTrips model defined in -the models.projects.transit_selection module.

    - - - -
    - - - - - - - - -
    - - - -

    - TransitSelection - - -

    - - -
    - - -

    Object to perform and store information about a selection from a project card “facility”.

    - - -

    Attributes:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescription
    selection_dict - -
    - -
    -
    selected_trips - list - -
    - -
    -
    selected_trips_df - DataFrame[WranglerTripsTable] - -
    -

    pd.DataFrame: DataFrame of selected trips

    -
    -
    sel_key - -
    - -
    -
    net - -
    - -
    -
    - -
    - Source code in network_wrangler/transit/selection.py - 
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    class TransitSelection:
-    """Object to perform and store information about a selection from a project card "facility".
-
-    Attributes:
-        selection_dict: dict: Dictionary of selection criteria
-        selected_trips: list: List of selected trips
-        selected_trips_df: pd.DataFrame: DataFrame of selected trips
-        sel_key: str: Hash of selection_dict
-        net: TransitNetwork: Network to select from
-    """
-
-    def __init__(
-        self,
-        net: TransitNetwork,
-        selection_dict: Union[dict, SelectTransitTrips],
-    ):
-        """Constructor for TransitSelection object.
-
-        Args:
-            net (TransitNetwork): Transit network object to select from.
-            selection_dict: Selection dictionary conforming to SelectTransitTrips
-        """
-        self.net = net
-        self.selection_dict = selection_dict
-
-        # Initialize
-        self._selected_trips_df = None
-        self.sel_key = dict_to_hexkey(selection_dict)
-        self._stored_feed_hash = copy.deepcopy(self.net.feed.hash)
-
-        WranglerLogger.debug(f"...created TransitSelection object: {selection_dict}")
-
-    def __nonzero__(self):
-        """Return True if there are selected trips."""
-        return len(self.selected_trips_df) > 0
-
-    @property
-    def selection_dict(self):
-        """Getter for selection_dict."""
-        return self._selection_dict
-
-    @selection_dict.setter
-    def selection_dict(self, value: Union[dict, SelectTransitTrips]):
-        self._selection_dict = self.validate_selection_dict(value)
-
-    def validate_selection_dict(self, selection_dict: Union[dict, SelectTransitTrips]) -> dict:
-        """Check that selection dictionary has valid and used properties consistent with network.
-
-        Checks that selection_dict is a valid TransitSelectionDict:
-            - query vars exist in respective Feed tables
-        Args:
-            selection_dict (dict): selection dictionary
-
-        Raises:
-            TransitSelectionNetworkConsistencyError: If not consistent with transit network
-            ValidationError: if format not consistent with SelectTransitTrips
-        """
-        if not isinstance(selection_dict, SelectTransitTrips):
-            selection_dict = SelectTransitTrips(**selection_dict)
-        selection_dict = selection_dict.model_dump(exclude_none=True, by_alias=True)
-        WranglerLogger.debug(f"SELECT DICT - before Validation: \n{selection_dict}")
-        _trip_selection_fields = list((selection_dict.get("trip_properties", {}) or {}).keys())
-        _missing_trip_fields = set(_trip_selection_fields) - set(self.net.feed.trips.columns)
-
-        if _missing_trip_fields:
-            msg = f"Fields in trip selection dictionary but not trips.txt: {_missing_trip_fields}"
-            raise TransitSelectionNetworkConsistencyError(msg)
-
-        _route_selection_fields = list((selection_dict.get("route_properties", {}) or {}).keys())
-        _missing_route_fields = set(_route_selection_fields) - set(self.net.feed.routes.columns)
-
-        if _missing_route_fields:
-            msg = (
-                f"Fields in route selection dictionary but not routes.txt: {_missing_route_fields}"
-            )
-            raise TransitSelectionNetworkConsistencyError(msg)
-        return selection_dict
-
-    @property
-    def selected_trips(self) -> list:
-        """List of selected trip_ids."""
-        if self.selected_trips_df is None:
-            return []
-        return self.selected_trips_df.trip_id.tolist()
-
-    @property
-    def selected_trips_df(self) -> DataFrame[WranglerTripsTable]:
-        """Lazily evaluates selection for trips or returns stored value in self._selected_trips_df.
-
-        Will re-evaluate if the current network hash is different than the stored one from the
-        last selection.
-
-        Returns:
-            DataFrame[WranglerTripsTable] of selected trips
-        """
-        if (self._selected_trips_df is not None) and self._stored_feed_hash == self.net.feed_hash:
-            return self._selected_trips_df
-
-        self._selected_trips_df = self._select_trips()
-        self._stored_feed_hash = copy.deepcopy(self.net.feed_hash)
-        return self._selected_trips_df
-
-    @property
-    def selected_frequencies_df(self) -> DataFrame[WranglerFrequenciesTable]:
-        """DataFrame of selected frequencies."""
-        sel_freq_df = self.net.feed.frequencies.loc[
-            self.net.feed.frequencies.trip_id.isin(self.selected_trips_df.trip_id)
-        ]
-        # if timespans are selected, filter to those that overlap
-        if self.selection_dict.get("timespans"):
-            sel_freq_df = filter_df_to_overlapping_timespans(
-                sel_freq_df, self.selection_dict.get("timespans")
-            )
-        return sel_freq_df
-
-    @property
-    def selected_shapes_df(self) -> DataFrame[WranglerShapesTable]:
-        """DataFrame of selected shapes.
-
-        Can visualize the selected shapes quickly using the following code:
-
-        ```python
-        all_routes = net.feed.shapes.plot(color="gray")
-        selection.selected_shapes_df.plot(ax=all_routes, color="red")
-        ```
-
-        """
-        return self.net.feed.shapes.loc[
-            self.net.feed.shapes.shape_id.isin(self.selected_trips_df.shape_id)
-        ]
-
-    def _select_trips(self) -> DataFrame[WranglerTripsTable]:
-        """Selects transit trips based on selection dictionary.
-
-        Returns:
-            DataFrame[WranglerTripsTable]: trips_df DataFrame of selected trips
-        """
-        return _filter_trips_by_selection_dict(
-            self.net.feed,
-            self.selection_dict,
-        )
-
    -
    - - - -
    - - - - - - - -
    - - - -
    - selected_frequencies_df: DataFrame[WranglerFrequenciesTable] - - - property - - -
    - - -
    - -

    DataFrame of selected frequencies.

    -
    - -
    - -
    - - - -
    - selected_shapes_df: DataFrame[WranglerShapesTable] - - - property - - -
    - - -
    - -

    DataFrame of selected shapes.

    -

    Can visualize the selected shapes quickly using the following code:

    -
    all_routes = net.feed.shapes.plot(color="gray")
-selection.selected_shapes_df.plot(ax=all_routes, color="red")
-
    -
    - -
    - -
    - - - -
    - selected_trips: list - - - property - - -
    - - -
    - -

    List of selected trip_ids.

    -
    - -
    - -
    - - - -
    - selected_trips_df: DataFrame[WranglerTripsTable] - - - property - - -
    - - -
    - -

    Lazily evaluates selection for trips or returns stored value in self._selected_trips_df.

    -

    Will re-evaluate if the current network hash is different than the stored one from the -last selection.

    - - -

    Returns:

    - - - - - - - - - - - - - -
    TypeDescription
    - DataFrame[WranglerTripsTable] - -
    -

    DataFrame[WranglerTripsTable] of selected trips

    -
    -
    -
    - -
    - -
    - - - -
    - selection_dict - - - property - writable - - -
    - - -
    - -

    Getter for selection_dict.

    -
    - -
    - - - -
    - - -
    - __init__(net, selection_dict) - -
    - - -
    - -

    Constructor for TransitSelection object.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    net - TransitNetwork - -
    -

    Transit network object to select from.

    -
    -     		- required -
    selection_dict - Union[dict, SelectTransitTrips] - -
    -

    Selection dictionary conforming to SelectTransitTrips

    -
    -     		- required -
    - -
    - Source code in network_wrangler/transit/selection.py - 
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    def __init__(
-    self,
-    net: TransitNetwork,
-    selection_dict: Union[dict, SelectTransitTrips],
-):
-    """Constructor for TransitSelection object.
-
-    Args:
-        net (TransitNetwork): Transit network object to select from.
-        selection_dict: Selection dictionary conforming to SelectTransitTrips
-    """
-    self.net = net
-    self.selection_dict = selection_dict
-
-    # Initialize
-    self._selected_trips_df = None
-    self.sel_key = dict_to_hexkey(selection_dict)
-    self._stored_feed_hash = copy.deepcopy(self.net.feed.hash)
-
-    WranglerLogger.debug(f"...created TransitSelection object: {selection_dict}")
-
    -
    -
    - -
    - -
    - - -
    - __nonzero__() - -
    - - -
    - -

    Return True if there are selected trips.

    - -
    - Source code in network_wrangler/transit/selection.py - 
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    def __nonzero__(self):
-    """Return True if there are selected trips."""
-    return len(self.selected_trips_df) > 0
-
    -
    -
    - -
    - -
    - - -
    - validate_selection_dict(selection_dict) - -
    - - -
    - -

    Check that selection dictionary has valid and used properties consistent with network.

    - - -
    - Checks that selection_dict is a valid TransitSelectionDict -
      -
    • query vars exist in respective Feed tables
      • -
    -
    - - -

    Raises:

    - - - - - - - - - - - - - - - - - -
    TypeDescription
    - TransitSelectionNetworkConsistencyError - -
    -

    If not consistent with transit network

    -
    -
    - ValidationError - -
    -

    if format not consistent with SelectTransitTrips

    -
    -
    - -
    - Source code in network_wrangler/transit/selection.py - 
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    def validate_selection_dict(self, selection_dict: Union[dict, SelectTransitTrips]) -> dict:
-    """Check that selection dictionary has valid and used properties consistent with network.
-
-    Checks that selection_dict is a valid TransitSelectionDict:
-        - query vars exist in respective Feed tables
-    Args:
-        selection_dict (dict): selection dictionary
-
-    Raises:
-        TransitSelectionNetworkConsistencyError: If not consistent with transit network
-        ValidationError: if format not consistent with SelectTransitTrips
-    """
-    if not isinstance(selection_dict, SelectTransitTrips):
-        selection_dict = SelectTransitTrips(**selection_dict)
-    selection_dict = selection_dict.model_dump(exclude_none=True, by_alias=True)
-    WranglerLogger.debug(f"SELECT DICT - before Validation: \n{selection_dict}")
-    _trip_selection_fields = list((selection_dict.get("trip_properties", {}) or {}).keys())
-    _missing_trip_fields = set(_trip_selection_fields) - set(self.net.feed.trips.columns)
-
-    if _missing_trip_fields:
-        msg = f"Fields in trip selection dictionary but not trips.txt: {_missing_trip_fields}"
-        raise TransitSelectionNetworkConsistencyError(msg)
-
-    _route_selection_fields = list((selection_dict.get("route_properties", {}) or {}).keys())
-    _missing_route_fields = set(_route_selection_fields) - set(self.net.feed.routes.columns)
-
-    if _missing_route_fields:
-        msg = (
-            f"Fields in route selection dictionary but not routes.txt: {_missing_route_fields}"
-        )
-        raise TransitSelectionNetworkConsistencyError(msg)
-    return selection_dict
-
    -
    -
    - -
    - - - -
    - -
    - -
    - - - - -
    - -
    - -
    - -
    - - - - -
    - -

    Functions to check for transit network validity and consistency with roadway network.

    - - - -
    - - - - - - - - - -
    - - - - - -
    - -

    Validate that links in transit shapes exist in referenced roadway links.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    tr_shapes - DataFrame[WranglerShapesTable] - -
    -

    transit shapes from shapes.txt to validate foreign key to.

    -
    -     		- required -
    rd_links_df - DataFrame[RoadLinksTable] - -
    -

    Links dataframe from roadway network to validate

    -
    -     		- required -
    - - -

    Returns:

    - - - - - - - - - - - - - -
    TypeDescription
    - DataFrame - -
    -

    df with shape_id and A, B

    -
    -
    - -
    - Source code in network_wrangler/transit/validate.py - 
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    def shape_links_without_road_links(
-    tr_shapes: DataFrame[WranglerShapesTable],
-    rd_links_df: DataFrame[RoadLinksTable],
-) -> pd.DataFrame:
-    """Validate that links in transit shapes exist in referenced roadway links.
-
-    Args:
-        tr_shapes: transit shapes from shapes.txt to validate foreign key to.
-        rd_links_df: Links dataframe from roadway network to validate
-
-    Returns:
-        df with shape_id and A, B
-    """
-    tr_shape_links = unique_shape_links(tr_shapes)
-    # WranglerLogger.debug(f"Unique shape links: \n {tr_shape_links}")
-    rd_links_transit_ok = rd_links_df[
-        (rd_links_df["drive_access"]) | (rd_links_df["bus_only"]) | (rd_links_df["rail_only"])
-    ]
-
-    merged_df = tr_shape_links.merge(
-        rd_links_transit_ok[["A", "B"]],
-        how="left",
-        on=["A", "B"],
-        indicator=True,
-    )
-
-    missing_links_df = merged_df.loc[merged_df._merge == "left_only", ["shape_id", "A", "B"]]
-    if len(missing_links_df):
-        WranglerLogger.error(
-            f"! Transit shape links missing in roadway network: \n {missing_links_df}"
-        )
-    return missing_links_df[["shape_id", "A", "B"]]
-
    -
    -
    - -
    - -
    - - - - - -
    - -

    Validate that links in transit shapes exist in referenced roadway links.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    tr_stop_times - DataFrame[WranglerStopTimesTable] - -
    -

    transit stop_times from stop_times.txt to validate foreign key to.

    -
    -     		- required -
    rd_links_df - DataFrame[RoadLinksTable] - -
    -

    Links dataframe from roadway network to validate

    -
    -     		- required -
    - - -

    Returns:

    - - - - - - - - - - - - - -
    TypeDescription
    - DataFrame - -
    -

    df with shape_id and A, B

    -
    -
    - -
    - Source code in network_wrangler/transit/validate.py - 
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    def stop_times_without_road_links(
-    tr_stop_times: DataFrame[WranglerStopTimesTable],
-    rd_links_df: DataFrame[RoadLinksTable],
-) -> pd.DataFrame:
-    """Validate that links in transit shapes exist in referenced roadway links.
-
-    Args:
-        tr_stop_times: transit stop_times from stop_times.txt to validate foreign key to.
-        rd_links_df: Links dataframe from roadway network to validate
-
-    Returns:
-        df with shape_id and A, B
-    """
-    tr_links = unique_stop_time_links(tr_stop_times)
-
-    rd_links_transit_ok = rd_links_df[
-        (rd_links_df["drive_access"]) | (rd_links_df["bus_only"]) | (rd_links_df["rail_only"])
-    ]
-
-    merged_df = tr_links.merge(
-        rd_links_transit_ok[["A", "B"]],
-        how="left",
-        on=["A", "B"],
-        indicator=True,
-    )
-
-    missing_links_df = merged_df.loc[merged_df._merge == "left_only", ["trip_id", "A", "B"]]
-    if len(missing_links_df):
-        WranglerLogger.error(
-            f"! Transit stop_time links missing in roadway network: \n {missing_links_df}"
-        )
-    return missing_links_df[["trip_id", "A", "B"]]
-
    -
    -
    - -
    - -
    - - -

    - transit_nodes_without_road_nodes(feed, nodes_df, rd_field='model_node_id') - -

    - - -
    - -

    Validate all of a transit feeds node foreign keys exist in referenced roadway nodes.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    feed - Feed - -
    -

    Transit Feed to query.

    -
    -     		- required -
    nodes_df - DataFrame - -
    -

    Nodes dataframe from roadway network to validate -foreign key to. Defaults to self.roadway_net.nodes_df

    -
    -     		- required -
    rd_field - str - -
    -

    field in roadway nodes to check against. Defaults to “model_node_id”

    -
    -     		- 'model_node_id' -
    - - -

    Returns:

    - - - - - - - - - - - - - -
    TypeDescription
    - list[int] - -
    -

    boolean indicating if relationships are all valid

    -
    -
    - -
    - Source code in network_wrangler/transit/validate.py - 
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    def transit_nodes_without_road_nodes(
-    feed: Feed,
-    nodes_df: DataFrame[RoadNodesTable],
-    rd_field: str = "model_node_id",
-) -> list[int]:
-    """Validate all of a transit feeds node foreign keys exist in referenced roadway nodes.
-
-    Args:
-        feed: Transit Feed to query.
-        nodes_df (pd.DataFrame, optional): Nodes dataframe from roadway network to validate
-            foreign key to. Defaults to self.roadway_net.nodes_df
-        rd_field: field in roadway nodes to check against. Defaults to "model_node_id"
-
-    Returns:
-        boolean indicating if relationships are all valid
-    """
-    feed_nodes_series = [
-        feed.stops["stop_id"],
-        feed.shapes["shape_model_node_id"],
-        feed.stop_times["stop_id"],
-    ]
-    tr_nodes = set(concat_with_attr(feed_nodes_series).unique())
-    rd_nodes = set(nodes_df[rd_field].unique().tolist())
-    # nodes in tr_nodes but not rd_nodes
-    missing_tr_nodes = list(tr_nodes - rd_nodes)
-
-    if missing_tr_nodes:
-        WranglerLogger.error(
-            f"! Transit nodes in missing in roadway network: \n {missing_tr_nodes}"
-        )
-    return missing_tr_nodes
-
    -
    -
    - -
    - -
    - - -

    - transit_road_net_consistency(feed, road_net) - -

    - - -
    - -

    Checks foreign key and network link relationships between transit feed and a road_net.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    feed - Feed - -
    -

    Transit Feed.

    -
    -     		- required -
    road_net - RoadwayNetwork - -
    -

    Roadway network to check relationship with.

    -
    -     		- required -
    - - -

    Returns:

    - - - - - - - - - - - - - -
    Name TypeDescription
    bool - bool - -
    -

    boolean indicating if road_net is consistent with transit network.

    -
    -
    - -
    - Source code in network_wrangler/transit/validate.py - 
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    def transit_road_net_consistency(feed: Feed, road_net: RoadwayNetwork) -> bool:
-    """Checks foreign key and network link relationships between transit feed and a road_net.
-
-    Args:
-        feed: Transit Feed.
-        road_net (RoadwayNetwork): Roadway network to check relationship with.
-
-    Returns:
-        bool: boolean indicating if road_net is consistent with transit network.
-    """
-    _missing_links = shape_links_without_road_links(feed.shapes, road_net.links_df)
-    _missing_nodes = transit_nodes_without_road_nodes(feed, road_net.nodes_df)
-    _consistency = _missing_links.empty and not _missing_nodes
-    return _consistency
-
    -
    -
    - -
    - -
    - - -

    - validate_transit_in_dir(dir, file_format='txt', road_dir=None, road_file_format='geojson') - -

    - - -
    - -

    Validates a roadway network in a directory to the wrangler data model specifications.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    dir - Path - -
    -

    The transit network file directory.

    -
    -     		- required -
    file_format - str - -
    -

    The format of roadway network file name. Defaults to “txt”.

    -
    -     		- 'txt' -
    road_dir - Path - -
    -

    The roadway network file directory. Defaults to None.

    -
    -     		- None -
    road_file_format - str - -
    -

    The format of roadway network file name. Defaults to “geojson”.

    -
    -     		- 'geojson' -
    output_dir - str - -
    -

    The output directory for the validation report. Defaults to “.”.

    -
    -     		- required -
    - -
    - Source code in network_wrangler/transit/validate.py - 
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    def validate_transit_in_dir(
-    dir: Path,
-    file_format: TransitFileTypes = "txt",
-    road_dir: Optional[Path] = None,
-    road_file_format: RoadwayFileTypes = "geojson",
-) -> bool:
-    """Validates a roadway network in a directory to the wrangler data model specifications.
-
-    Args:
-        dir (Path): The transit network file directory.
-        file_format (str): The format of roadway network file name. Defaults to "txt".
-        road_dir (Path): The roadway network file directory. Defaults to None.
-        road_file_format (str): The format of roadway network file name. Defaults to "geojson".
-        output_dir (str): The output directory for the validation report. Defaults to ".".
-    """
-    from .io import load_transit
-
-    try:
-        t = load_transit(dir, file_format=file_format)
-    except SchemaErrors as e:
-        WranglerLogger.error(f"!!! [Transit Network invalid] - Failed Loading to Feed object\n{e}")
-        return False
-    if road_dir is not None:
-        from ..roadway import load_roadway_from_dir
-        from .network import TransitRoadwayConsistencyError
-
-        try:
-            r = load_roadway_from_dir(road_dir, file_format=road_file_format)
-        except FileNotFoundError:
-            WranglerLogger.error(f"! Roadway network not found in {road_dir}")
-            return False
-        except Exception as e:
-            WranglerLogger.error(f"! Error loading roadway network. \
-                                 Skipping validation of road to transit network.\n{e}")
-        try:
-            t.road_net = r
-        except TransitRoadwayConsistencyError as e:
-            WranglerLogger.error(f"!!! [Tranit Network inconsistent] Error in road to transit \
-                                 network consistency.\n{e}")
-            return False
-
-    return True
-
    -
    -
    - -
    - - - -
    - -
    - -

    Utils and Functions

    - - -
    - - - - -
    - -

    General utility functions used throughout package.

    - - - -
    - - - - - - - - -
    - - - -

    - DictionaryMergeError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Error raised when there is a conflict in merging two dictionaries.

    - -
    - Source code in network_wrangler/utils/utils.py - 
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-13
    class DictionaryMergeError(Exception):
-    """Error raised when there is a conflict in merging two dictionaries."""
-
    -
    - -
    - -
    - - -
    - - -

    - check_one_or_one_superset_present(mixed_list, all_fields_present) - -

    - - -
    - -

    Checks that exactly one of the fields in mixed_list is in fields_present or one superset.

    - -
    - Source code in network_wrangler/utils/utils.py - 
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    def check_one_or_one_superset_present(
-    mixed_list: list[Union[str, list[str]]], all_fields_present: list[str]
-) -> bool:
-    """Checks that exactly one of the fields in mixed_list is in fields_present or one superset."""
-    normalized_list = normalize_to_lists(mixed_list)
-
-    list_items_present = [i for i in normalized_list if set(i).issubset(all_fields_present)]
-
-    if len(list_items_present) == 1:
-        return True
-
-    return list_elements_subset_of_single_element(list_items_present)
-
    -
    -
    - -
    - -
    - - -

    - combine_unique_unhashable_list(list1, list2) - -

    - - -
    - -

    Combines lists preserving order of first and removing duplicates.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    list1 - list - -
    -

    The first list.

    -
    -     		- required -
    list2 - list - -
    -

    The second list.

    -
    -     		- required -
    - - -

    Returns:

    - - - - - - - - - - - - - - - - - -
    Name TypeDescription
    list - -
    -

    A new list containing the elements from list1 followed by the

    -
    -
    - -
    -

    unique elements from list2.

    -
    -
    - - -
    - Example -
    -
    -
    -

    list1 = [1, 2, 3] -list2 = [2, 3, 4, 5] -combine_unique_unhashable_list(list1, list2) -[1, 2, 3, 4, 5]

    -
    -
    -
    -
    -
    - Source code in network_wrangler/utils/utils.py - 
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    def combine_unique_unhashable_list(list1: list, list2: list):
-    """Combines lists preserving order of first and removing duplicates.
-
-    Args:
-        list1 (list): The first list.
-        list2 (list): The second list.
-
-    Returns:
-        list: A new list containing the elements from list1 followed by the
-        unique elements from list2.
-
-    Example:
-        >>> list1 = [1, 2, 3]
-        >>> list2 = [2, 3, 4, 5]
-        >>> combine_unique_unhashable_list(list1, list2)
-        [1, 2, 3, 4, 5]
-    """
-    return [item for item in list1 if item not in list2] + list2
-
    -
    -
    - -
    - -
    - - -

    - delete_keys_from_dict(dictionary, keys) - -

    - - -
    - -

    Removes list of keys from potentially nested dictionary.

    -

    SOURCE: https://stackoverflow.com/questions/3405715/ -User: @mseifert

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    dictionary - dict - -
    -

    dictionary to remove keys from

    -
    -     		- required -
    keys - list - -
    -

    list of keys to remove

    -
    -     		- required -
    - -
    - Source code in network_wrangler/utils/utils.py - 
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    def delete_keys_from_dict(dictionary: dict, keys: list) -> dict:
-    """Removes list of keys from potentially nested dictionary.
-
-    SOURCE: https://stackoverflow.com/questions/3405715/
-    User: @mseifert
-
-    Args:
-        dictionary: dictionary to remove keys from
-        keys: list of keys to remove
-
-    """
-    keys_set = list(set(keys))  # Just an optimization for the "if key in keys" lookup.
-
-    modified_dict = {}
-    for key, value in dictionary.items():
-        if key not in keys_set:
-            if isinstance(value, dict):
-                modified_dict[key] = delete_keys_from_dict(value, keys_set)
-            else:
-                modified_dict[key] = (
-                    value  # or copy.deepcopy(value) if a copy is desired for non-dicts.
-                )
-    return modified_dict
-
    -
    -
    - -
    - -
    - - -

    - dict_to_hexkey(d) - -

    - - -
    - -

    Converts a dictionary to a hexdigest of the sha1 hash of the dictionary.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    d - dict - -
    -

    dictionary to convert to string

    -
    -     		- required -
    - - -

    Returns:

    - - - - - - - - - - - - - -
    Name TypeDescription
    str - str - -
    -

    hexdigest of the sha1 hash of dictionary

    -
    -
    - -
    - Source code in network_wrangler/utils/utils.py - 
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    def dict_to_hexkey(d: dict) -> str:
-    """Converts a dictionary to a hexdigest of the sha1 hash of the dictionary.
-
-    Args:
-        d (dict): dictionary to convert to string
-
-    Returns:
-        str: hexdigest of the sha1 hash of dictionary
-    """
-    return hashlib.sha1(str(d).encode()).hexdigest()
-
    -
    -
    - -
    - -
    - - -

    - findkeys(node, kv) - -

    - - -
    - -

    Returns values of all keys in various objects.

    -

    Adapted from arainchi on Stack Overflow: -https://stackoverflow.com/questions/9807634/find-all-occurrences-of-a-key-in-nested-dictionaries-and-lists

    - -
    - Source code in network_wrangler/utils/utils.py - 
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    def findkeys(node, kv):
-    """Returns values of all keys in various objects.
-
-    Adapted from arainchi on Stack Overflow:
-    https://stackoverflow.com/questions/9807634/find-all-occurrences-of-a-key-in-nested-dictionaries-and-lists
-    """
-    if isinstance(node, list):
-        for i in node:
-            for x in findkeys(i, kv):
-                yield x
-    elif isinstance(node, dict):
-        if kv in node:
-            yield node[kv]
-        for j in node.values():
-            for x in findkeys(j, kv):
-                yield x
-
    -
    -
    - -
    - -
    - - -

    - get_overlapping_range(ranges) - -

    - - -
    - -

    Returns the overlapping range for a list of ranges or tuples defining ranges.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    ranges - list[Union[tuple[int], range]] - -
    -

    A list of ranges or tuples defining ranges.

    -
    -     		- required -
    - - -

    Returns:

    - - - - - - - - - - - - - -
    TypeDescription
    - Union[None, range] - -
    -

    Union[None, range]: The overlapping range if found, otherwise None.

    -
    -
    - - -
    - Example -
    -
    -
    -

    ranges = [(1, 5), (3, 7), (6, 10)] -get_overlapping_range(ranges) -range(3, 5)

    -
    -
    -
    -
    -
    - Source code in network_wrangler/utils/utils.py - 
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    def get_overlapping_range(ranges: list[Union[tuple[int, int], range]]) -> Union[None, range]:
-    """Returns the overlapping range for a list of ranges or tuples defining ranges.
-
-    Args:
-        ranges (list[Union[tuple[int], range]]): A list of ranges or tuples defining ranges.
-
-    Returns:
-        Union[None, range]: The overlapping range if found, otherwise None.
-
-    Example:
-        >>> ranges = [(1, 5), (3, 7), (6, 10)]
-        >>> get_overlapping_range(ranges)
-        range(3, 5)
-
-    """
-    # check that any tuples have two values
-    if any(isinstance(r, tuple) and len(r) != 2 for r in ranges):  # noqa: PLR2004
-        msg = "Tuple ranges must have two values."
-        WranglerLogger.error(msg)
-        raise ValueError(msg)
-
-    _ranges = [r if isinstance(r, range) else range(r[0], r[1]) for r in ranges]
-
-    _overlap_start = max(r.start for r in _ranges)
-    _overlap_end = min(r.stop for r in _ranges)
-
-    if _overlap_start < _overlap_end:
-        return range(_overlap_start, _overlap_end)
-    return None
-
    -
    -
    - -
    - -
    - - -

    - list_elements_subset_of_single_element(mixed_list) - -

    - - -
    - -

    Find the first list in the mixed_list.

    - -
    - Source code in network_wrangler/utils/utils.py - 
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    @validate_call
-def list_elements_subset_of_single_element(mixed_list: list[Union[str, list[str]]]) -> bool:
-    """Find the first list in the mixed_list."""
-    potential_supersets = []
-    for item in mixed_list:
-        if isinstance(item, list) and len(item) > 0:
-            potential_supersets.append(set(item))
-
-    # If no list is found, return False
-    if not potential_supersets:
-        return False
-
-    normalized_list = normalize_to_lists(mixed_list)
-
-    valid_supersets = []
-    for ss in potential_supersets:
-        if all(ss.issuperset(i) for i in normalized_list):
-            valid_supersets.append(ss)
-
-    return len(valid_supersets) == 1
-
    -
    -
    - -
    - -
    - - -

    - make_slug(text, delimiter='_') - -

    - - -
    - -

    Makes a slug from text.

    - -
    - Source code in network_wrangler/utils/utils.py - 
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    def make_slug(text: str, delimiter: str = "_") -> str:
-    """Makes a slug from text."""
-    text = re.sub("[,.;@#?!&$']+", "", text.lower())
-    return re.sub("[\ ]+", delimiter, text)
-
    -
    -
    - -
    - -
    - - -

    - merge_dicts(right, left, path=None) - -

    - - -
    - -

    Merges the contents of nested dict left into nested dict right.

    -

    Raises errors in case of namespace conflicts.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    right - -
    -

    dict, modified in place

    -
    -     		- required -
    left - -
    -

    dict to be merged into right

    -
    -     		- required -
    path - -
    -

    default None, sequence of keys to be reported in case of -error in merging nested dictionaries

    -
    -     		- None -
    - -
    - Source code in network_wrangler/utils/utils.py - 
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    def merge_dicts(right, left, path=None):
-    """Merges the contents of nested dict left into nested dict right.
-
-    Raises errors in case of namespace conflicts.
-
-    Args:
-        right: dict, modified in place
-        left: dict to be merged into right
-        path: default None, sequence of keys to be reported in case of
-            error in merging nested dictionaries
-    """
-    if path is None:
-        path = []
-    for key in left:
-        if key in right:
-            if isinstance(right[key], dict) and isinstance(left[key], dict):
-                merge_dicts(right[key], left[key], [*path, str(key)])
-            else:
-                path = ".".join([*path, str(key)])
-                msg = f"duplicate keys in source dict files: {path}"
-                WranglerLogger.error(msg)
-                raise DictionaryMergeError(msg)
-        else:
-            right[key] = left[key]
-
    -
    -
    - -
    - -
    - - -

    - normalize_to_lists(mixed_list) - -

    - - -
    - -

    Turn a mixed list of scalars and lists into a list of lists.

    - -
    - Source code in network_wrangler/utils/utils.py - 
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    def normalize_to_lists(mixed_list: list[Union[str, list]]) -> list[list]:
-    """Turn a mixed list of scalars and lists into a list of lists."""
-    normalized_list = []
-    for item in mixed_list:
-        if isinstance(item, str):
-            normalized_list.append([item])
-        else:
-            normalized_list.append(item)
-    return normalized_list
-
    -
    -
    - -
    - -
    - - -

    - split_string_prefix_suffix_from_num(input_string) - -

    - - -
    - -

    Split a string prefix and suffix from last number.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    input_string - str - -
    -

    The input string to be processed.

    -
    -     		- required -
    - - -

    Returns:

    - - - - - - - - - - - - - -
    Name TypeDescription
    tuple - -
    -

    A tuple containing the prefix (including preceding numbers), - the last numeric part as an integer, and the suffix.

    -
    -
    - - -
    - Notes -

    This function uses regular expressions to split a string into three parts: -the prefix, the last numeric part, and the suffix. The prefix includes any -preceding numbers, the last numeric part is converted to an integer, and -the suffix includes any non-digit characters after the last numeric part.

    -
    - -

    Examples:

    - 
    >>> split_string_prefix_suffix_from_num("abc123def456")
-('abc', 123, 'def456')
-
    - 
    >>> split_string_prefix_suffix_from_num("hello")
-('hello', 0, '')
-
    - 
    >>> split_string_prefix_suffix_from_num("123")
-('', 123, '')
-
    - -
    - Source code in network_wrangler/utils/utils.py - 
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    def split_string_prefix_suffix_from_num(input_string: str):
-    """Split a string prefix and suffix from *last* number.
-
-    Args:
-        input_string (str): The input string to be processed.
-
-    Returns:
-        tuple: A tuple containing the prefix (including preceding numbers),
-               the last numeric part as an integer, and the suffix.
-
-    Notes:
-        This function uses regular expressions to split a string into three parts:
-        the prefix, the last numeric part, and the suffix. The prefix includes any
-        preceding numbers, the last numeric part is converted to an integer, and
-        the suffix includes any non-digit characters after the last numeric part.
-
-    Examples:
-        >>> split_string_prefix_suffix_from_num("abc123def456")
-        ('abc', 123, 'def456')
-
-        >>> split_string_prefix_suffix_from_num("hello")
-        ('hello', 0, '')
-
-        >>> split_string_prefix_suffix_from_num("123")
-        ('', 123, '')
-
-    """
-    input_string = str(input_string)
-    pattern = re.compile(r"(.*?)(\d+)(\D*)$")
-    match = pattern.match(input_string)
-
-    if match:
-        # Extract the groups: prefix (including preceding numbers), last numeric part, suffix
-        prefix, numeric_part, suffix = match.groups()
-        # Convert the numeric part to an integer
-        num_variable = int(numeric_part)
-        return prefix, num_variable, suffix
-    return input_string, 0, ""
-
    -
    -
    - -
    - -
    - - -

    - topological_sort(adjacency_list, visited_list) - -

    - - -
    - -

    Topological sorting for Acyclic Directed Graph.

    -

    Parameters: -- adjacency_list (dict): A dictionary representing the adjacency list of the graph. -- visited_list (list): A list representing the visited status of each vertex in the graph.

    -

    Returns: -- output_stack (list): A list containing the vertices in topological order.

    -

    This function performs a topological sort on an acyclic directed graph. It takes an adjacency -list and a visited list as input. The adjacency list represents the connections between -vertices in the graph, and the visited list keeps track of the visited status of each vertex.

    -

    The function uses a recursive helper function to perform the topological sort. It starts by -iterating over each vertex in the visited list. For each unvisited vertex, it calls the helper -function, which recursively visits all the neighbors of the vertex and adds them to the output -stack in reverse order. Finally, it returns the output stack, which contains the vertices in -topological order.

    - -
    - Source code in network_wrangler/utils/utils.py - 
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    def topological_sort(adjacency_list, visited_list):
-    """Topological sorting for Acyclic Directed Graph.
-
-    Parameters:
-    - adjacency_list (dict): A dictionary representing the adjacency list of the graph.
-    - visited_list (list): A list representing the visited status of each vertex in the graph.
-
-    Returns:
-    - output_stack (list): A list containing the vertices in topological order.
-
-    This function performs a topological sort on an acyclic directed graph. It takes an adjacency
-    list and a visited list as input. The adjacency list represents the connections between
-    vertices in the graph, and the visited list keeps track of the visited status of each vertex.
-
-    The function uses a recursive helper function to perform the topological sort. It starts by
-    iterating over each vertex in the visited list. For each unvisited vertex, it calls the helper
-    function, which recursively visits all the neighbors of the vertex and adds them to the output
-    stack in reverse order. Finally, it returns the output stack, which contains the vertices in
-    topological order.
-    """
-    output_stack = []
-
-    def _topology_sort_util(vertex):
-        if not visited_list[vertex]:
-            visited_list[vertex] = True
-            for neighbor in adjacency_list[vertex]:
-                _topology_sort_util(neighbor)
-            output_stack.insert(0, vertex)
-
-    for vertex in visited_list:
-        _topology_sort_util(vertex)
-
-    return output_stack
-
    -
    -
    - -
    - - - -
    - -
    - -
    - -
    - - - - -
    - -

    Helper functions for reading and writing files to reduce boilerplate.

    - - - -
    - - - - - - - - -
    - - - -

    - FileReadError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Raised when there is an error reading a file.

    - -
    - Source code in network_wrangler/utils/io_table.py - 
    36
-37
    class FileReadError(Exception):
-    """Raised when there is an error reading a file."""
-
    -
    - -
    - -
    - -
    - - - -

    - FileWriteError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Raised when there is an error writing a file.

    - -
    - Source code in network_wrangler/utils/io_table.py - 
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-41
    class FileWriteError(Exception):
-    """Raised when there is an error writing a file."""
-
    -
    - -
    - -
    - - -
    - - -

    - convert_file_serialization(input_file, output_file, overwrite=True, boundary_gdf=None, boundary_geocode=None, boundary_file=None, node_filter_s=None, chunk_size=None) - -

    - - -
    - -

    Convert a file serialization format to another and optionally filter to a boundary.

    -

    If the input file is a JSON file that is larger than a reasonable portion of available -memory, and the output file is a Parquet file the JSON file will be read in chunks.

    -

    If the input file is a Geographic data type (shp, geojon, geoparquet) and a boundary is -provided, the data will be filtered to the boundary.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    input_file - Path - -
    -

    Path to the input JSON or GEOJSON file.

    -
    -     		- required -
    output_file - Path - -
    -

    Path to the output Parquet file.

    -
    -     		- required -
    overwrite - bool - -
    -

    If True, overwrite the output file if it exists.

    -
    -     		- True -
    boundary_gdf - Optional[GeoDataFrame] - -
    -

    GeoDataFrame to filter the input data to. Only used for geographic data. -Defaults to None.

    -
    -     		- None -
    boundary_geocode - Optional[str] - -
    -

    Geocode to filter the input data to. Only used for geographic data. -Defaults to None.

    -
    -     		- None -
    boundary_file - Optional[Path] - -
    -

    File to load as a boundary to filter the input data to. Only used for -geographic data. Defaults to None.

    -
    -     		- None -
    node_filter_s - Optional[Series] - -
    -

    If provided, will filter links in .json file to only those that connect to -nodes. Defaults to None.

    -
    -     		- None -
    chunk_size - Optional[int] - -
    -

    Number of JSON objects to process in each chunk. Only works for -JSON to Parquet. If None, will determine if chunking needed and what size.

    -
    -     		- None -
    - -
    - Source code in network_wrangler/utils/io_table.py - 
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    def convert_file_serialization(
-    input_file: Path,
-    output_file: Path,
-    overwrite: bool = True,
-    boundary_gdf: Optional[gpd.GeoDataFrame] = None,
-    boundary_geocode: Optional[str] = None,
-    boundary_file: Optional[Path] = None,
-    node_filter_s: Optional[pd.Series] = None,
-    chunk_size: Optional[int] = None,
-):
-    """Convert a file serialization format to another and optionally filter to a boundary.
-
-    If the input file is a JSON file that is larger than a reasonable portion of available
-    memory, *and* the output file is a Parquet file the JSON file will be read in chunks.
-
-    If the input file is a Geographic data type (shp, geojon, geoparquet) and a boundary is
-    provided, the data will be filtered to the boundary.
-
-    Args:
-        input_file: Path to the input JSON or GEOJSON file.
-        output_file: Path to the output Parquet file.
-        overwrite: If True, overwrite the output file if it exists.
-        boundary_gdf: GeoDataFrame to filter the input data to. Only used for geographic data.
-            Defaults to None.
-        boundary_geocode: Geocode to filter the input data to. Only used for geographic data.
-            Defaults to None.
-        boundary_file: File to load as a boundary to filter the input data to. Only used for
-            geographic data. Defaults to None.
-        node_filter_s: If provided, will filter links in .json file to only those that connect to
-            nodes. Defaults to None.
-        chunk_size: Number of JSON objects to process in each chunk. Only works for
-            JSON to Parquet. If None, will determine if chunking needed and what size.
-    """
-    WranglerLogger.debug(f"Converting {input_file} to {output_file}.")
-
-    if output_file.exists() and not overwrite:
-        msg = f"File {output_file} already exists and overwrite is False."
-        raise FileExistsError(msg)
-
-    if Path(input_file).suffix == ".json" and Path(output_file).suffix == ".parquet":
-        if chunk_size is None:
-            chunk_size = _suggest_json_chunk_size(input_file)
-        if chunk_size is None:
-            df = read_table(input_file)
-            if node_filter_s is not None and "A" in df.columns and "B" in df.columns:
-                df = df[df["A"].isin(node_filter_s) | df["B"].isin(node_filter_s)]
-            write_table(df, output_file, overwrite=overwrite)
-        else:
-            _json_to_parquet_in_chunks(input_file, output_file, chunk_size)
-
-    df = read_table(
-        input_file,
-        boundary_gdf=boundary_gdf,
-        boundary_geocode=boundary_geocode,
-        boundary_file=boundary_file,
-    )
-    if node_filter_s is not None and "A" in df.columns and "B" in df.columns:
-        df = df[df["A"].isin(node_filter_s) | df["B"].isin(node_filter_s)]
-    write_table(df, output_file, overwrite=overwrite)
-
    -
    -
    - -
    - -
    - - -

    - prep_dir(outdir, overwrite=True) - -

    - - -
    - -

    Prepare a directory for writing files.

    - -
    - Source code in network_wrangler/utils/io_table.py - 
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    def prep_dir(outdir: Path, overwrite: bool = True):
-    """Prepare a directory for writing files."""
-    if not overwrite and outdir.exists() and len(list(outdir.iterdir())) > 0:
-        msg = f"Directory {outdir} is not empty and overwrite is False."
-        raise FileExistsError(msg)
-    outdir.mkdir(parents=True, exist_ok=True)
-
-    # clean out existing files
-    for f in outdir.iterdir():
-        if f.is_file():
-            f.unlink()
-
    -
    -
    - -
    - -
    - - -

    - read_table(filename, sub_filename=None, boundary_gdf=None, boundary_geocode=None, boundary_file=None, read_speed=DefaultConfig.CPU.EST_PD_READ_SPEED) - -

    - - -
    - -

    Read file and return a dataframe or geodataframe.

    -

    If filename is a zip file, will unzip to a temporary directory.

    -

    If filename is a geojson or shapefile, will filter the data -to the boundary_gdf, boundary_geocode, or boundary_file if provided. Note that you can only -provide one of these boundary filters.

    -

    If filename is a geoparquet file, will filter the data to the bounding box of the -boundary_gdf, boundary_geocode, or boundary_file if provided. Note that you can only -provide one of these boundary filters.

    -

    NOTE: if you are accessing multiple files from this zip file you will want to unzip it first -and THEN access the table files so you don’t create multiple duplicate unzipped tmp dirs.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    filename - Path - -
    -

    filename to load.

    -
    -     		- required -
    sub_filename - Optional[str] - -
    -

    if the file is a zip, the sub_filename to load.

    -
    -     		- None -
    boundary_gdf - Optional[GeoDataFrame] - -
    -

    GeoDataFrame to filter the input data to. Only used for geographic data. -Defaults to None.

    -
    -     		- None -
    boundary_geocode - Optional[str] - -
    -

    Geocode to filter the input data to. Only used for geographic data. -Defaults to None.

    -
    -     		- None -
    boundary_file - Optional[Path] - -
    -

    File to load as a boundary to filter the input data to. Only used for -geographic data. Defaults to None.

    -
    -     		- None -
    read_speed - dict - -
    -

    dictionary of read speeds for different file types. Defaults to -DefaultConfig.CPU.EST_PD_READ_SPEED.

    -
    -     		- EST_PD_READ_SPEED -
    - -
    - Source code in network_wrangler/utils/io_table.py - 
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    def read_table(
-    filename: Path,
-    sub_filename: Optional[str] = None,
-    boundary_gdf: Optional[gpd.GeoDataFrame] = None,
-    boundary_geocode: Optional[str] = None,
-    boundary_file: Optional[Path] = None,
-    read_speed: dict = DefaultConfig.CPU.EST_PD_READ_SPEED,
-) -> Union[pd.DataFrame, gpd.GeoDataFrame]:
-    """Read file and return a dataframe or geodataframe.
-
-    If filename is a zip file, will unzip to a temporary directory.
-
-    If filename is a geojson or shapefile, will filter the data
-    to the boundary_gdf, boundary_geocode, or boundary_file if provided. Note that you can only
-    provide one of these boundary filters.
-
-    If filename is a geoparquet file, will filter the data to the *bounding box* of the
-    boundary_gdf, boundary_geocode, or boundary_file if provided. Note that you can only
-    provide one of these boundary filters.
-
-    NOTE:  if you are accessing multiple files from this zip file you will want to unzip it first
-    and THEN access the table files so you don't create multiple duplicate unzipped tmp dirs.
-
-    Args:
-        filename (Path): filename to load.
-        sub_filename: if the file is a zip, the sub_filename to load.
-        boundary_gdf: GeoDataFrame to filter the input data to. Only used for geographic data.
-            Defaults to None.
-        boundary_geocode: Geocode to filter the input data to. Only used for geographic data.
-            Defaults to None.
-        boundary_file: File to load as a boundary to filter the input data to. Only used for
-            geographic data. Defaults to None.
-        read_speed: dictionary of read speeds for different file types. Defaults to
-            DefaultConfig.CPU.EST_PD_READ_SPEED.
-    """
-    filename = Path(filename)
-    if not filename.exists():
-        msg = f"Input file {filename} does not exist."
-        raise FileNotFoundError(msg)
-    if filename.stat().st_size == 0:
-        msg = f"File {filename} is empty."
-        raise FileExistsError(msg)
-    if filename.suffix == ".zip":
-        if not sub_filename:
-            msg = "sub_filename must be provided for zip files."
-            raise ValueError(msg)
-        filename = unzip_file(filename) / sub_filename
-    WranglerLogger.debug(
-        f"Estimated read time: {_estimate_read_time_of_file(filename, read_speed)}."
-    )
-
-    # will result in None if no boundary is provided
-    mask_gdf = get_bounding_polygon(
-        boundary_gdf=boundary_gdf,
-        boundary_geocode=boundary_geocode,
-        boundary_file=boundary_file,
-    )
-
-    if any(x in filename.suffix for x in ["geojson", "shp", "csv"]):
-        try:
-            # masking only supported by fiona engine, which is slower.
-            if mask_gdf is None:
-                return gpd.read_file(filename, engine="pyogrio")
-            return gpd.read_file(filename, mask=mask_gdf, engine="fiona")
-        except Exception as err:
-            if "csv" in filename.suffix:
-                return pd.read_csv(filename)
-            raise FileReadError from err
-    elif "parquet" in filename.suffix:
-        return _read_parquet_table(filename, mask_gdf)
-    elif "json" in filename.suffix:
-        with filename.open() as f:
-            return pd.read_json(f, orient="records")
-    msg = f"Filetype {filename.suffix} not implemented."
-    raise NotImplementedError(msg)
-
    -
    -
    - -
    - -
    - - -

    - unzip_file(path) - -

    - - -
    - -

    Unzips a file to a temporary directory and returns the directory path.

    - -
    - Source code in network_wrangler/utils/io_table.py - 
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    def unzip_file(path: Path) -> Path:
-    """Unzips a file to a temporary directory and returns the directory path."""
-    tmpdir = tempfile.mkdtemp()
-    shutil.unpack_archive(path, tmpdir)
-
-    def finalize() -> None:
-        shutil.rmtree(tmpdir)
-
-    # Lazy cleanup
-    weakref.finalize(tmpdir, finalize)
-
-    return Path(tmpdir)
-
    -
    -
    - -
    - -
    - - -

    - write_table(df, filename, overwrite=False, **kwargs) - -

    - - -
    - -

    Write a dataframe or geodataframe to a file.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    df - DataFrame - -
    -

    dataframe to write.

    -
    -     		- required -
    filename - Path - -
    -

    filename to write to.

    -
    -     		- required -
    overwrite - bool - -
    -

    whether to overwrite the file if it exists. Defaults to False.

    -
    -     		- False -
    kwargs - -
    -

    additional arguments to pass to the writer.

    -
    -     		- {} -
    - -
    - Source code in network_wrangler/utils/io_table.py - 
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    def write_table(
-    df: Union[pd.DataFrame, gpd.GeoDataFrame],
-    filename: Path,
-    overwrite: bool = False,
-    **kwargs,
-) -> None:
-    """Write a dataframe or geodataframe to a file.
-
-    Args:
-        df (pd.DataFrame): dataframe to write.
-        filename (Path): filename to write to.
-        overwrite (bool): whether to overwrite the file if it exists. Defaults to False.
-        kwargs: additional arguments to pass to the writer.
-
-    """
-    filename = Path(filename)
-    if filename.exists() and not overwrite:
-        msg = f"File {filename} already exists and overwrite is False."
-        raise FileExistsError(msg)
-
-    if filename.parent.is_dir() and not filename.parent.exists():
-        filename.parent.mkdir(parents=True)
-
-    WranglerLogger.debug(f"Writing to {filename}.")
-
-    if "shp" in filename.suffix:
-        df.to_file(filename, index=False, **kwargs)
-    elif "parquet" in filename.suffix:
-        df.to_parquet(filename, index=False, **kwargs)
-    elif "csv" in filename.suffix or "txt" in filename.suffix:
-        df.to_csv(filename, index=False, date_format="%H:%M:%S", **kwargs)
-    elif "geojson" in filename.suffix:
-        # required due to issues with list-like columns
-        if isinstance(df, gpd.GeoDataFrame):
-            data = df.to_json(drop_id=True)
-        else:
-            data = df.to_json(orient="records", index=False)
-        with filename.open("w", encoding="utf-8") as file:
-            file.write(data)
-    elif "json" in filename.suffix:
-        with filename.open("w") as f:
-            f.write(df.to_json(orient="records"))
-    else:
-        msg = f"Filetype {filename.suffix} not implemented."
-        raise NotImplementedError(msg)
-
    -
    -
    - -
    - - - -
    - -
    - -
    - -
    - - - - -
    - -

    Utility functions for loading dictionaries from files.

    - - - -
    - - - - - - - - - -
    - - -

    - load_dict(path) - -

    - - -
    - -

    Load a dictionary from a file.

    - -
    - Source code in network_wrangler/utils/io_dict.py - 
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    def load_dict(path: Path) -> dict:
-    """Load a dictionary from a file."""
-    path = Path(path)
-    if not path.is_file():
-        msg = f"Specified dict file {path} not found."
-        raise FileNotFoundError(msg)
-
-    if path.suffix.lower() == ".toml":
-        return _load_toml(path)
-    if path.suffix.lower() == ".json":
-        return _load_json(path)
-    if path.suffix.lower() == ".yaml" or path.suffix.lower() == ".yml":
-        return _load_yaml(path)
-    msg = f"Filetype {path.suffix} not implemented."
-    raise NotImplementedError(msg)
-
    -
    -
    - -
    - -
    - - -

    - load_merge_dict(path) - -

    - - -
    - -

    Load and merge multiple dictionaries from files.

    - -
    - Source code in network_wrangler/utils/io_dict.py - 
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    def load_merge_dict(path: Union[Path, list[Path]]) -> dict:
-    """Load and merge multiple dictionaries from files."""
-    if not isinstance(path, list):
-        path = [path]
-    data = load_dict(path[0])
-    for path_item in path[1:]:
-        merge_dicts(data, load_dict(path_item))
-    return data
-
    -
    -
    - -
    - - - -
    - -
    - -
    - -
    - - - - -
    - -

    Helper functions for data models.

    - - - -
    - - - - - - - - -
    - - - -

    - DatamodelDataframeIncompatableError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Raised when a data model and a dataframe are not compatable.

    - -
    - Source code in network_wrangler/utils/models.py - 
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    class DatamodelDataframeIncompatableError(Exception):
-    """Raised when a data model and a dataframe are not compatable."""
-
    -
    - -
    - -
    - -
    - - - -

    - TableValidationError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Raised when a table validation fails.

    - -
    - Source code in network_wrangler/utils/models.py - 
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    class TableValidationError(Exception):
-    """Raised when a table validation fails."""
-
    -
    - -
    - -
    - - -
    - - -

    - coerce_extra_fields_to_type_in_df(data, model, df) - -

    - - -
    - -

    Coerce extra fields in data that aren’t specified in Pydantic model to the type in the df.

    -

    Note: will not coerce lists of submodels, etc.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    data - dict - -
    -

    The data to coerce.

    -
    -     		- required -
    model - BaseModel - -
    -

    The Pydantic model to validate the data against.

    -
    -     		- required -
    df - DataFrame - -
    -

    The DataFrame to coerce the data to.

    -
    -     		- required -
    - -
    - Source code in network_wrangler/utils/models.py - 
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    def coerce_extra_fields_to_type_in_df(
-    data: BaseModel, model: BaseModel, df: pd.DataFrame
-) -> BaseModel:
-    """Coerce extra fields in data that aren't specified in Pydantic model to the type in the df.
-
-    Note: will not coerce lists of submodels, etc.
-
-    Args:
-        data (dict): The data to coerce.
-        model (BaseModel): The Pydantic model to validate the data against.
-        df (pd.DataFrame): The DataFrame to coerce the data to.
-    """
-    out_data = copy.deepcopy(data)
-
-    # Coerce submodels
-    for field in submodel_fields_in_model(model, data):
-        out_data.__dict__[field] = coerce_extra_fields_to_type_in_df(
-            data.__dict__[field], model.__annotations__[field], df
-        )
-
-    for field in extra_attributes_undefined_in_model(data, model):
-        try:
-            v = coerce_val_to_df_types(field, data.model_extra[field], df)
-        except ValueError as err:
-            raise DatamodelDataframeIncompatableError() from err
-        out_data.model_extra[field] = v
-    return out_data
-
    -
    -
    - -
    - -
    - - -

    - default_from_datamodel(data_model, field) - -

    - - -
    - -

    Returns default value from pandera data model for a given field name.

    - -
    - Source code in network_wrangler/utils/models.py - 
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    def default_from_datamodel(data_model: pa.DataFrameModel, field: str):
-    """Returns default value from pandera data model for a given field name."""
-    if field in data_model.__fields__ and hasattr(data_model.__fields__[field][1], "default"):
-        return data_model.__fields__[field][1].default
-    return None
-
    -
    -
    - -
    - -
    - - -

    - empty_df_from_datamodel(model, crs=LAT_LON_CRS) - -

    - - -
    - -

    Create an empty DataFrame or GeoDataFrame with the specified columns.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    model - BaseModel - -
    -

    A pandera data model to create empty [Geo]DataFrame from.

    -
    -     		- required -
    crs - int - -
    -

    if schema has geometry, will use this as the geometry’s crs. Defaults to LAT_LONG_CRS

    -
    -     		- LAT_LON_CRS -
    - - -
    - Source code in network_wrangler/utils/models.py - 
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    def empty_df_from_datamodel(
-    model: DataFrameModel, crs: int = LAT_LON_CRS
-) -> Union[gpd.GeoDataFrame, pd.DataFrame]:
-    """Create an empty DataFrame or GeoDataFrame with the specified columns.
-
-    Args:
-        model (BaseModel): A pandera data model to create empty [Geo]DataFrame from.
-        crs: if schema has geometry, will use this as the geometry's crs. Defaults to LAT_LONG_CRS
-    Returns:
-        An empty [Geo]DataFrame that validates to the specified model.
-    """
-    schema = model.to_schema()
-    data: dict[str, list] = {col: [] for col in schema.columns}
-
-    if "geometry" in data:
-        return model(gpd.GeoDataFrame(data, crs=crs))
-
-    return model(pd.DataFrame(data))
-
    -
    -
    - -
    - -
    - - -

    - extra_attributes_undefined_in_model(instance, model) - -

    - - -
    - -

    Find the extra attributes in a pydantic model that are not defined in the model.

    - -
    - Source code in network_wrangler/utils/models.py - 
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    def extra_attributes_undefined_in_model(instance: BaseModel, model: BaseModel) -> list:
-    """Find the extra attributes in a pydantic model that are not defined in the model."""
-    defined_fields = model.model_fields
-    all_attributes = list(instance.model_dump(exclude_none=True, by_alias=True).keys())
-    extra_attributes = [a for a in all_attributes if a not in defined_fields]
-    return extra_attributes
-
    -
    -
    - -
    - -
    - - -

    - fill_df_with_defaults_from_model(df, model) - -

    - - -
    - -

    Fill a DataFrame with default values from a Pandera DataFrameModel.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    df - -
    -

    DataFrame to fill with default values.

    -
    -     		- required -
    model - -
    -

    Pandera DataFrameModel to get default values from.

    -
    -     		- required -
    - -
    - Source code in network_wrangler/utils/models.py - 
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    def fill_df_with_defaults_from_model(df, model):
-    """Fill a DataFrame with default values from a Pandera DataFrameModel.
-
-    Args:
-        df: DataFrame to fill with default values.
-        model: Pandera DataFrameModel to get default values from.
-    """
-    for c in df.columns:
-        default_value = default_from_datamodel(model, c)
-        if default_value is None:
-            df[c] = df[c].where(pd.notna(df[c]), None)
-        else:
-            df[c] = df[c].fillna(default_value)
-    return df
-
    -
    -
    - -
    - -
    - - -

    - identify_model(data, models) - -

    - - -
    - -

    Identify the model that the input data conforms to.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    data - Union[DataFrame, dict] - -
    -

    The input data to identify.

    -
    -     		- required -
    models - list[DataFrameModel, BaseModel] - -
    -

    A list of models to validate the input -data against.

    -
    -     		- required -
    - -
    - Source code in network_wrangler/utils/models.py - 
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    def identify_model(
-    data: Union[pd.DataFrame, dict], models: list
-) -> Union[DataFrameModel, BaseModel]:
-    """Identify the model that the input data conforms to.
-
-    Args:
-        data (Union[pd.DataFrame, dict]): The input data to identify.
-        models (list[DataFrameModel,BaseModel]): A list of models to validate the input
-          data against.
-    """
-    for m in models:
-        try:
-            if isinstance(data, pd.DataFrame):
-                validate_df_to_model(data, m)
-            else:
-                m(**data)
-            return m
-        except ValidationError:
-            continue
-        except SchemaError:
-            continue
-
-    WranglerLogger.error(
-        f"The input data isn't consistant with any provided data model.\
-                         \nInput data: {data}\
-                         \nData Models: {models}"
-    )
-    msg = "The input data isn't consistant with any provided data model."
-    raise TableValidationError(msg)
-
    -
    -
    - -
    - -
    - - -

    - order_fields_from_data_model(df, model) - -

    - - -
    - -

    Order the fields in a DataFrame to match the order in a Pandera DataFrameModel.

    -

    Will add any fields that are not in the model to the end of the DataFrame. -Will not add any fields that are in the model but not in the DataFrame.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    df - DataFrame - -
    -

    DataFrame to order.

    -
    -     		- required -
    model - DataFrameModel - -
    -

    Pandera DataFrameModel to order the DataFrame to.

    -
    -     		- required -
    - -
    - Source code in network_wrangler/utils/models.py - 
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    def order_fields_from_data_model(df: pd.DataFrame, model: DataFrameModel) -> pd.DataFrame:
-    """Order the fields in a DataFrame to match the order in a Pandera DataFrameModel.
-
-    Will add any fields that are not in the model to the end of the DataFrame.
-    Will not add any fields that are in the model but not in the DataFrame.
-
-    Args:
-        df: DataFrame to order.
-        model: Pandera DataFrameModel to order the DataFrame to.
-    """
-    model_fields = list(model.__fields__.keys())
-    df_model_fields = [f for f in model_fields if f in df.columns]
-    df_additional_fields = [f for f in df.columns if f not in model_fields]
-    return df[df_model_fields + df_additional_fields]
-
    -
    -
    - -
    - -
    - - -

    - submodel_fields_in_model(model, instance=None) - -

    - - -
    - -

    Find the fields in a pydantic model that are submodels.

    - -
    - Source code in network_wrangler/utils/models.py - 
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    def submodel_fields_in_model(model: type, instance: Optional[BaseModel] = None) -> list:
-    """Find the fields in a pydantic model that are submodels."""
-    types = get_type_hints(model)
-    model_type = (ModelMetaclass, BaseModel)
-    submodels = [f for f in model.model_fields if isinstance(types.get(f), model_type)]
-    if instance is not None:
-        defined = list(instance.model_dump(exclude_none=True, by_alias=True).keys())
-        return [f for f in submodels if f in defined]
-    return submodels
-
    -
    -
    - -
    - -
    - - -

    - validate_call_pyd(func) - -

    - - -
    - -

    Decorator to validate the function i/o using Pydantic models without Pandera.

    - -
    - Source code in network_wrangler/utils/models.py - 
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    def validate_call_pyd(func):
-    """Decorator to validate the function i/o using Pydantic models without Pandera."""
-
-    @wraps(func)
-    def wrapper(*args, **kwargs):
-        type_hints = get_type_hints(func)
-        # Modify the type hints to replace pandera DataFrame models with pandas DataFrames
-        modified_type_hints = {
-            key: value
-            for key, value in type_hints.items()
-            if not _is_type_from_type_hint(value, PanderaDataFrame)
-        }
-
-        new_func = func
-        new_func.__annotations__ = modified_type_hints
-        validated_func = validate_call(new_func, config={"arbitrary_types_allowed": True})
-
-        return validated_func(*args, **kwargs)
-
-    return wrapper
-
    -
    -
    - -
    - -
    - - -

    - validate_df_to_model(df, model, output_file=Path('validation_failure_cases.csv')) - -

    - - -
    - -

    Wrapper to validate a DataFrame against a Pandera DataFrameModel with better logging.

    -

    Also copies the attrs from the input DataFrame to the validated DataFrame.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    df - DataFrame - -
    -

    DataFrame to validate.

    -
    -     		- required -
    model - type - -
    -

    Pandera DataFrameModel to validate against.

    -
    -     		- required -
    output_file - Path - -
    -

    Optional file to write validation errors to. Defaults to -validation_failure_cases.csv.

    -
    -     		- Path('validation_failure_cases.csv') -
    - -
    - Source code in network_wrangler/utils/models.py - 
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    @validate_call(config={"arbitrary_types_allowed": True})
-def validate_df_to_model(
-    df: DataFrame, model: type, output_file: Path = Path("validation_failure_cases.csv")
-) -> DataFrame:
-    """Wrapper to validate a DataFrame against a Pandera DataFrameModel with better logging.
-
-    Also copies the attrs from the input DataFrame to the validated DataFrame.
-
-    Args:
-        df: DataFrame to validate.
-        model: Pandera DataFrameModel to validate against.
-        output_file: Optional file to write validation errors to. Defaults to
-            validation_failure_cases.csv.
-    """
-    attrs = copy.deepcopy(df.attrs)
-    err_msg = f"Validation to {model.__name__} failed."
-    try:
-        model_df = model.validate(df, lazy=True)
-        model_df = fill_df_with_defaults_from_model(model_df, model)
-        model_df.attrs = attrs
-        return model_df
-    except (TypeError, ValueError) as e:
-        WranglerLogger.error(f"Validation to {model.__name__} failed.\n{e}")
-        raise TableValidationError(err_msg) from e
-    except SchemaErrors as e:
-        # Log the summary of errors
-        WranglerLogger.error(
-            f"Validation to {model.__name__} failed with {len(e.failure_cases)} \
-            errors: \n{e.failure_cases}"
-        )
-
-        # If there are many errors, save them to a file
-        if len(e.failure_cases) > SMALL_RECS:
-            error_file = output_file
-            e.failure_cases.to_csv(error_file)
-            WranglerLogger.info(f"Detailed error cases written to {error_file}")
-        else:
-            # Otherwise log the errors directly
-            WranglerLogger.error("Detailed failure cases:\n%s", e.failure_cases)
-        raise TableValidationError(err_msg) from e
-    except SchemaError as e:
-        WranglerLogger.error(f"Validation to {model.__name__} failed with error: {e}")
-        WranglerLogger.error(f"Failure Cases:\n{e.failure_cases}")
-        raise TableValidationError(err_msg) from e
-
    -
    -
    - -
    - - - -
    - -
    - -
    - -
    - - - - -
    - -

    Functions to help with network manipulations in dataframes.

    - - - -
    - - - - - - - - - -
    - - - - - -
    - -

    Translates a df with tidy data representing a sequence of points into links.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    point_seq_df - DataFrame - -
    -

    Dataframe with source breadcrumbs

    -
    -     		- required -
    id_field - str - -
    -

    Trace ID

    -
    -     		- required -
    seq_field - str - -
    -

    Order of breadcrumbs within ID_field

    -
    -     		- required -
    node_id_field - str - -
    -

    field denoting the node ID

    -
    -     		- required -
    from_field - str - -
    -

    Field to export from_field to. Defaults to “A”.

    -
    -     		- 'A' -
    to_field - str - -
    -

    Field to export to_field to. Defaults to “B”.

    -
    -     		- 'B' -
    - - -

    Returns:

    - - - - - - - - - - - - - -
    TypeDescription
    - DataFrame - -
    -

    pd.DataFrame: Link records with id_field, from_field, to_field

    -
    -
    - -
    - Source code in network_wrangler/utils/net.py - 
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    def point_seq_to_links(
-    point_seq_df: DataFrame,
-    id_field: str,
-    seq_field: str,
-    node_id_field: str,
-    from_field: str = "A",
-    to_field: str = "B",
-) -> DataFrame:
-    """Translates a df with tidy data representing a sequence of points into links.
-
-    Args:
-        point_seq_df (pd.DataFrame): Dataframe with source breadcrumbs
-        id_field (str): Trace ID
-        seq_field (str): Order of breadcrumbs within ID_field
-        node_id_field (str): field denoting the node ID
-        from_field (str, optional): Field to export from_field to. Defaults to "A".
-        to_field (str, optional): Field to export to_field to. Defaults to "B".
-
-    Returns:
-        pd.DataFrame: Link records with id_field, from_field, to_field
-    """
-    point_seq_df = point_seq_df.sort_values(by=[id_field, seq_field])
-
-    links = point_seq_df.add_suffix(f"_{from_field}").join(
-        point_seq_df.shift(-1).add_suffix(f"_{to_field}")
-    )
-
-    links = links[links[f"{id_field}_{to_field}"] == links[f"{id_field}_{from_field}"]]
-
-    links = links.drop(columns=[f"{id_field}_{to_field}"])
-    links = links.rename(
-        columns={
-            f"{id_field}_{from_field}": id_field,
-            f"{node_id_field}_{from_field}": from_field,
-            f"{node_id_field}_{to_field}": to_field,
-        }
-    )
-
-    links = links.dropna(subset=[from_field, to_field])
-    # Since join with a shift() has some NAs, we need to recast the columns to int
-    _int_cols = [to_field, f"{seq_field}_{to_field}"]
-    links[_int_cols] = links[_int_cols].astype(int)
-    return links
-
    -
    -
    - -
    - - - -
    - -
    - -
    - -
    - - - - -
    - -

    Functions related to parsing and comparing time objects and series.

    -

    Internal function terminology for timespan scopes:

    -
      -
    • matching: a scope that could be applied for a given timespan combination. - This includes the default timespan as well as scopes wholely contained within.
      • -
    • overlapping: a timespan that fully or partially overlaps a given timespan. - This includes the default timespan, all matching timespans and all timespans where - at least one minute overlap.
      • -
    • conflicting: a timespan that is overlapping but not matching. By definition default - scope values are not conflicting.
      • -
    • independent a timespan that is not overlapping.
      • -
    - - - -
    - - - - - - - - -
    - - - -

    - TimespanDfQueryError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Error for timespan query errors.

    - -
    - Source code in network_wrangler/utils/time.py - 
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    class TimespanDfQueryError(Exception):
-    """Error for timespan query errors."""
-
    -
    - -
    - -
    - - -
    - - -

    - calc_overlap_duration_with_query(start_time_s, end_time_s, start_time_q, end_time_q) - -

    - - -
    - -

    Calculate the overlap series of start and end times and a query start and end times.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    start_time_s - Series[datetime] - -
    -

    Series of start times to calculate overlap with.

    -
    -     		- required -
    end_time_s - Series[datetime] - -
    -

    Series of end times to calculate overlap with.

    -
    -     		- required -
    start_time_q - datetime - -
    -

    Query start time to calculate overlap with.

    -
    -     		- required -
    end_time_q - datetime - -
    -

    Query end time to calculate overlap with.

    -
    -     		- required -
    - -
    - Source code in network_wrangler/utils/time.py - 
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    def calc_overlap_duration_with_query(
-    start_time_s: pd.Series[datetime],
-    end_time_s: pd.Series[datetime],
-    start_time_q: datetime,
-    end_time_q: datetime,
-) -> pd.Series[timedelta]:
-    """Calculate the overlap series of start and end times and a query start and end times.
-
-    Args:
-        start_time_s: Series of start times to calculate overlap with.
-        end_time_s: Series of end times to calculate overlap with.
-        start_time_q: Query start time to calculate overlap with.
-        end_time_q: Query end time to calculate overlap with.
-    """
-    overlap_start = start_time_s.combine(start_time_q, max)
-    overlap_end = end_time_s.combine(end_time_q, min)
-    overlap_duration_s = (overlap_end - overlap_start).dt.total_seconds() / 60
-
-    return overlap_duration_s
-
    -
    -
    - -
    - -
    - - -

    - convert_timespan_to_start_end_dt(timespan_s) - -

    - - -
    - -

    Convert a timespan string [‘12:00’,‘14:00] to start_time & end_time datetime cols in df.

    - -
    - Source code in network_wrangler/utils/time.py - 
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    def convert_timespan_to_start_end_dt(timespan_s: pd.Serie[str]) -> pd.DataFrame:
-    """Convert a timespan string ['12:00','14:00] to start_time & end_time datetime cols in df."""
-    start_time = timespan_s.apply(lambda x: str_to_time(x[0]))
-    end_time = timespan_s.apply(lambda x: str_to_time(x[1]))
-    return pd.DataFrame({"start_time": start_time, "end_time": end_time})
-
    -
    -
    - -
    - -
    - - -

    - dt_contains(timespan1, timespan2) - -

    - - -
    - -

    Check timespan1 inclusively contains timespan2.

    -

    If the end time is less than the start time, it is assumed to be the next day.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    timespan1 - list[time] - -
    -

    The first timespan represented as a list containing the start -time and end time.

    -
    -     		- required -
    timespan2 - list[time] - -
    -

    The second timespan represented as a list containing the start -time and end time.

    -
    -     		- required -
    - - -

    Returns:

    - - - - - - - - - - - - - -
    Name TypeDescription
    bool - bool - -
    -

    True if the first timespan contains the second timespan, False otherwise.

    -
    -
    - -
    - Source code in network_wrangler/utils/time.py - 
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    @validate_call
-def dt_contains(timespan1: list[datetime], timespan2: list[datetime]) -> bool:
-    """Check timespan1 inclusively contains timespan2.
-
-    If the end time is less than the start time, it is assumed to be the next day.
-
-    Args:
-        timespan1 (list[time]): The first timespan represented as a list containing the start
-            time and end time.
-        timespan2 (list[time]): The second timespan represented as a list containing the start
-            time and end time.
-
-    Returns:
-        bool: True if the first timespan contains the second timespan, False otherwise.
-    """
-    start_time_dt, end_time_dt = timespan1
-
-    if end_time_dt < start_time_dt:
-        end_time_dt = end_time_dt + timedelta(days=1)
-
-    start_time_dt2, end_time_dt2 = timespan2
-
-    if end_time_dt2 < start_time_dt2:
-        end_time_dt2 = end_time_dt2 + timedelta(days=1)
-
-    return (start_time_dt <= start_time_dt2) and (end_time_dt >= end_time_dt2)
-
    -
    -
    - -
    - -
    - - -

    - dt_list_overlaps(timespans) - -

    - - -
    - -

    Check if any of the timespans overlap.

    -

    overlapping: a timespan that fully or partially overlaps a given timespan. -This includes and all timespans where at least one minute overlap.

    - -
    - Source code in network_wrangler/utils/time.py - 
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    def dt_list_overlaps(timespans: list[list[datetime]]) -> bool:
-    """Check if any of the timespans overlap.
-
-    `overlapping`: a timespan that fully or partially overlaps a given timespan.
-    This includes and all timespans where at least one minute overlap.
-    """
-    return bool(filter_dt_list_to_overlaps(timespans))
-
    -
    -
    - -
    - -
    - - -

    - dt_overlap_duration(timedelta1, timedelta2) - -

    - - -
    - -

    Check if two timespans overlap and return the amount of overlap.

    -

    If the end time is less than the start time, it is assumed to be the next day.

    - -
    - Source code in network_wrangler/utils/time.py - 
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    @validate_call
-def dt_overlap_duration(timedelta1: timedelta, timedelta2: timedelta) -> timedelta:
-    """Check if two timespans overlap and return the amount of overlap.
-
-    If the end time is less than the start time, it is assumed to be the next day.
-    """
-    if timedelta1.end_time < timedelta1.start_time:
-        timedelta1 = timedelta1 + timedelta(days=1)
-    if timedelta2.end_time < timedelta2.start_time:
-        timedelta2 = timedelta2 + timedelta(days=1)
-    overlap_start = max(timedelta1.start_time, timedelta2.start_time)
-    overlap_end = min(timedelta1.end_time, timedelta2.end_time)
-    overlap_duration = max(overlap_end - overlap_start, timedelta(0))
-    return overlap_duration
-
    -
    -
    - -
    - -
    - - -

    - dt_overlaps(timespan1, timespan2) - -

    - - -
    - -

    Check if two timespans overlap.

    -

    If the end time is less than the start time, it is assumed to be the next day.

    -

    overlapping: a timespan that fully or partially overlaps a given timespan. -This includes and all timespans where at least one minute overlap.

    - -
    - Source code in network_wrangler/utils/time.py - 
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    @validate_call(config={"arbitrary_types_allowed": True})
-def dt_overlaps(timespan1: list[datetime], timespan2: list[datetime]) -> bool:
-    """Check if two timespans overlap.
-
-    If the end time is less than the start time, it is assumed to be the next day.
-
-    `overlapping`: a timespan that fully or partially overlaps a given timespan.
-    This includes and all timespans where at least one minute overlap.
-    """
-    time1_start, time1_end = timespan1
-    time2_start, time2_end = timespan2
-
-    if time1_end < time1_start:
-        time1_end += timedelta(days=1)
-    if time2_end < time2_start:
-        time2_end += timedelta(days=1)
-
-    return (time1_start < time2_end) and (time2_start < time1_end)
-
    -
    -
    - -
    - -
    - - -

    - dt_to_seconds_from_midnight(dt) - -

    - - -
    - -

    Convert a datetime object to the number of seconds since midnight.

    - -
    - Source code in network_wrangler/utils/time.py - 
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    @validate_call(config={"arbitrary_types_allowed": True})
-def dt_to_seconds_from_midnight(dt: datetime) -> int:
-    """Convert a datetime object to the number of seconds since midnight."""
-    return round((dt - dt.replace(hour=0, minute=0, second=0, microsecond=0)).total_seconds())
-
    -
    -
    - -
    - -
    - - -

    - duration_dt(start_time_dt, end_time_dt) - -

    - - -
    - -

    Returns a datetime.timedelta object representing the duration of the timespan.

    -

    If end_time is less than start_time, the duration will assume that it crosses over -midnight.

    - -
    - Source code in network_wrangler/utils/time.py - 
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    def duration_dt(start_time_dt: datetime, end_time_dt: datetime) -> timedelta:
-    """Returns a datetime.timedelta object representing the duration of the timespan.
-
-    If end_time is less than start_time, the duration will assume that it crosses over
-    midnight.
-    """
-    if end_time_dt < start_time_dt:
-        return timedelta(
-            hours=24 - start_time_dt.hour + end_time_dt.hour,
-            minutes=end_time_dt.minute - start_time_dt.minute,
-            seconds=end_time_dt.second - start_time_dt.second,
-        )
-    return end_time_dt - start_time_dt
-
    -
    -
    - -
    - -
    - - -

    - filter_df_to_max_overlapping_timespans(orig_df, query_timespan, strict_match=False, min_overlap_minutes=1, keep_max_of_cols=None) - -

    - - -
    - -

    Filters dataframe for entries that have maximum overlap with the given query timespan.

    -

    If the end time is less than the start time, it is assumed to be the next day.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    orig_df - DataFrame - -
    -

    dataframe to query timespans for with start_time and end_time fields.

    -
    -     		- required -
    query_timespan - list[TimeString] - -
    -

    TimespanString of format [‘HH:MM’,’HH:MM’] to query orig_df for overlapping -records.

    -
    -     		- required -
    strict_match - bool - -
    -

    boolean indicating if the returned df should only contain -records that fully contain the query timespan. If set to True, min_overlap_minutes -does not apply. Defaults to False.

    -
    -     		- False -
    min_overlap_minutes - int - -
    -

    minimum number of minutes the timespans need to overlap to keep. -Defaults to 1.

    -
    -     		- 1 -
    keep_max_of_cols - Optional[list[str]] - -
    -

    list of fields to return the maximum value of overlap for. If None, -will return all overlapping time periods. Defaults to ['model_link_id']

    -
    -     		- None -
    - -
    - Source code in network_wrangler/utils/time.py - 
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    @validate_call(config={"arbitrary_types_allowed": True})
-def filter_df_to_max_overlapping_timespans(
-    orig_df: pd.DataFrame,
-    query_timespan: list[TimeString],
-    strict_match: bool = False,
-    min_overlap_minutes: int = 1,
-    keep_max_of_cols: Optional[list[str]] = None,
-) -> pd.DataFrame:
-    """Filters dataframe for entries that have maximum overlap with the given query timespan.
-
-    If the end time is less than the start time, it is assumed to be the next day.
-
-    Args:
-        orig_df: dataframe to query timespans for with `start_time` and `end_time` fields.
-        query_timespan: TimespanString of format ['HH:MM','HH:MM'] to query orig_df for overlapping
-            records.
-        strict_match: boolean indicating if the returned df should only contain
-            records that fully contain the query timespan. If set to True, min_overlap_minutes
-            does not apply. Defaults to False.
-        min_overlap_minutes: minimum number of minutes the timespans need to overlap to keep.
-            Defaults to 1.
-        keep_max_of_cols: list of fields to return the maximum value of overlap for.  If None,
-            will return all overlapping time periods. Defaults to `['model_link_id']`
-    """
-    if keep_max_of_cols is None:
-        keep_max_of_cols = ["model_link_id"]
-    if "start_time" not in orig_df.columns or "end_time" not in orig_df.columns:
-        msg = "DataFrame must have 'start_time' and 'end_time' columns"
-        WranglerLogger.error(msg)
-        raise TimespanDfQueryError(msg)
-    q_start, q_end = str_to_time_list(query_timespan)
-
-    real_end = orig_df["end_time"]
-    real_end.loc[orig_df["end_time"] < orig_df["start_time"]] += pd.Timedelta(days=1)
-
-    orig_df["overlap_duration"] = calc_overlap_duration_with_query(
-        orig_df["start_time"],
-        real_end,
-        q_start,
-        q_end,
-    )
-    if strict_match:
-        overlap_df = orig_df.loc[(orig_df.start_time <= q_start) & (real_end >= q_end)]
-    else:
-        overlap_df = orig_df.loc[orig_df.overlap_duration > min_overlap_minutes]
-    WranglerLogger.debug(f"overlap_df: \n{overlap_df}")
-    if keep_max_of_cols:
-        # keep only the maximum overlap
-        idx = overlap_df.groupby(keep_max_of_cols)["overlap_duration"].idxmax()
-        overlap_df = overlap_df.loc[idx]
-    return overlap_df
-
    -
    -
    - -
    - -
    - - -

    - filter_df_to_overlapping_timespans(orig_df, query_timespans) - -

    - - -
    - -

    Filters dataframe for entries that have any overlap with ANY of the given query timespans.

    -

    If the end time is less than the start time, it is assumed to be the next day.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    orig_df - DataFrame - -
    -

    dataframe to query timespans for with start_time and end_time fields.

    -
    -     		- required -
    query_timespans - list[TimespanString] - -
    -

    List of a list of TimespanStr of format [‘HH:MM’,’HH:MM’] to query orig_df -for overlapping records.

    -
    -     		- required -
    - -
    - Source code in network_wrangler/utils/time.py - 
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    @validate_call(config={"arbitrary_types_allowed": True})
-def filter_df_to_overlapping_timespans(
-    orig_df: pd.DataFrame,
-    query_timespans: list[TimespanString],
-) -> pd.DataFrame:
-    """Filters dataframe for entries that have any overlap with ANY of the given query timespans.
-
-    If the end time is less than the start time, it is assumed to be the next day.
-
-    Args:
-        orig_df: dataframe to query timespans for with `start_time` and `end_time` fields.
-        query_timespans: List of a list of TimespanStr of format ['HH:MM','HH:MM'] to query orig_df
-            for overlapping records.
-    """
-    if "start_time" not in orig_df.columns or "end_time" not in orig_df.columns:
-        msg = "DataFrame must have 'start_time' and 'end_time' columns"
-        WranglerLogger.error(msg)
-        raise TimespanDfQueryError(msg)
-
-    mask = pd.Series([False] * len(orig_df), index=orig_df.index)
-    for query_timespan in query_timespans:
-        q_start_time, q_end_time = str_to_time_list(query_timespan)
-        end_time_s = orig_df["end_time"]
-        end_time_s.loc[orig_df["end_time"] < orig_df["start_time"]] += pd.Timedelta(days=1)
-        this_ts_mask = (orig_df["start_time"] < q_end_time) & (q_start_time < end_time_s)
-        mask |= this_ts_mask
-    return orig_df.loc[mask]
-
    -
    -
    - -
    - -
    - - -

    - filter_dt_list_to_overlaps(timespans) - -

    - - -
    - -

    Filter a list of timespans to only include those that overlap.

    -

    overlapping: a timespan that fully or partially overlaps a given timespan. -This includes and all timespans where at least one minute overlap.

    - -
    - Source code in network_wrangler/utils/time.py - 
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    @validate_call
-def filter_dt_list_to_overlaps(timespans: list[list[datetime]]) -> list[list[datetime]]:
-    """Filter a list of timespans to only include those that overlap.
-
-    `overlapping`: a timespan that fully or partially overlaps a given timespan.
-    This includes and all timespans where at least one minute overlap.
-    """
-    overlaps = []
-    for i in range(len(timespans)):
-        for j in range(i + 1, len(timespans)):
-            if dt_overlaps(timespans[i], timespans[j]):
-                overlaps += [timespans[i], timespans[j]]
-
-    # remove dupes
-    return list(map(list, set(map(tuple, overlaps))))
-
    -
    -
    - -
    - -
    - - -

    - format_seconds_to_legible_str(seconds) - -

    - - -
    - -

    Formats seconds into a human-friendly string for log files.

    - -
    - Source code in network_wrangler/utils/time.py - 
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    def format_seconds_to_legible_str(seconds: int) -> str:
-    """Formats seconds into a human-friendly string for log files."""
-    if seconds < 60:  # noqa: PLR2004
-        return f"{int(seconds)} seconds"
-    if seconds < 3600:  # noqa: PLR2004
-        return f"{int(seconds // 60)} minutes"
-    hours = int(seconds // 3600)
-    minutes = int((seconds % 3600) // 60)
-    return f"{hours} hours and {minutes} minutes"
-
    -
    -
    - -
    - -
    - - -

    - is_increasing(datetimes) - -

    - - -
    - -

    Check if a list of datetime objects is increasing in time.

    - -
    - Source code in network_wrangler/utils/time.py - 
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    def is_increasing(datetimes: list[datetime]) -> bool:
-    """Check if a list of datetime objects is increasing in time."""
-    return all(datetimes[i] <= datetimes[i + 1] for i in range(len(datetimes) - 1))
-
    -
    -
    - -
    - -
    - - -

    - seconds_from_midnight_to_str(seconds) - -

    - - -
    - -

    Convert the number of seconds since midnight to a TimeString (HH:MM).

    - -
    - Source code in network_wrangler/utils/time.py - 
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    @validate_call(config={"arbitrary_types_allowed": True})
-def seconds_from_midnight_to_str(seconds: int) -> TimeString:
-    """Convert the number of seconds since midnight to a TimeString (HH:MM)."""
-    return str(timedelta(seconds=seconds))
-
    -
    -
    - -
    - -
    - - -

    - str_to_seconds_from_midnight(time_str) - -

    - - -
    - -

    Convert a TimeString (HH:MM<:SS>) to the number of seconds since midnight.

    - -
    - Source code in network_wrangler/utils/time.py - 
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    @validate_call(config={"arbitrary_types_allowed": True})
-def str_to_seconds_from_midnight(time_str: TimeString) -> int:
-    """Convert a TimeString (HH:MM<:SS>) to the number of seconds since midnight."""
-    dt = str_to_time(time_str)
-    return dt_to_seconds_from_midnight(dt)
-
    -
    -
    - -
    - -
    - - -

    - str_to_time(time_str, base_date=None) - -

    - - -
    - -

    Convert TimeString (HH:MM<:SS>) to datetime object.

    -

    If HH > 24, will subtract 24 to be within 24 hours. Timespans will be treated as the next day.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    time_str - TimeString - -
    -

    TimeString in HH:MM:SS or HH:MM format.

    -
    -     		- required -
    base_date - Optional[date] - -
    -

    optional date to base the datetime on. Defaults to None. -If not provided, will use today.

    -
    -     		- None -
    - -
    - Source code in network_wrangler/utils/time.py - 
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    @validate_call(config={"arbitrary_types_allowed": True})
-def str_to_time(time_str: TimeString, base_date: Optional[date] = None) -> datetime:
-    """Convert TimeString (HH:MM<:SS>) to datetime object.
-
-    If HH > 24, will subtract 24 to be within 24 hours. Timespans will be treated as the next day.
-
-    Args:
-        time_str: TimeString in HH:MM:SS or HH:MM format.
-        base_date: optional date to base the datetime on. Defaults to None.
-            If not provided, will use today.
-    """
-    # Set the base date to today if not provided
-    if base_date is None:
-        base_date = date.today()
-
-    # Split the time string to extract hours, minutes, and seconds
-    parts = time_str.split(":")
-    hours = int(parts[0])
-    minutes = int(parts[1])
-    seconds = int(parts[2]) if len(parts) == 3 else 0  # noqa: PLR2004
-
-    if hours >= 24:  # noqa: PLR2004
-        add_days = hours // 24
-        base_date += timedelta(days=add_days)
-        hours -= 24 * add_days
-
-    # Create a time object with the adjusted hours, minutes, and seconds
-    adjusted_time = datetime.strptime(f"{hours:02}:{minutes:02}:{seconds:02}", "%H:%M:%S").time()
-
-    # Combine the base date with the adjusted time and add the extra days if needed
-    combined_datetime = datetime.combine(base_date, adjusted_time)
-
-    return combined_datetime
-
    -
    -
    - -
    - -
    - - -

    - str_to_time_list(timespan) - -

    - - -
    - -

    Convert list of TimeStrings (HH:MM<:SS>) to list of datetime.time objects.

    - -
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    @validate_call(config={"arbitrary_types_allowed": True})
-def str_to_time_list(timespan: list[TimeString]) -> list[datetime]:
-    """Convert list of TimeStrings (HH:MM<:SS>) to list of datetime.time objects."""
-    timespan_dt: list[datetime] = list(map(str_to_time, timespan))
-    if not is_increasing(timespan_dt):
-        timespan_dt = [timespan_dt[0], timespan_dt[1] + timedelta(days=1)]
-        WranglerLogger.warning(f"Timespan is not in increasing order: {timespan}.\
-            End time will be treated as next day.")
-    return timespan_dt
-
    -
    -
    - -
    - -
    - - -

    - str_to_time_series(time_str_s, base_date=None) - -

    - - -
    - -

    Convert mixed panda series datetime and TimeString (HH:MM<:SS>) to datetime object.

    -

    If HH > 24, will subtract 24 to be within 24 hours. Timespans will be treated as the next day.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    time_str_s - Series - -
    -

    Pandas Series of TimeStrings in HH:MM:SS or HH:MM format.

    -
    -     		- required -
    base_date - Optional[Union[Series, date]] - -
    -

    optional date to base the datetime on. Defaults to None. -If not provided, will use today. Can be either a single instance or a series of -same length as time_str_s

    -
    -     		- None -
    - -
    - Source code in network_wrangler/utils/time.py - 
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    def str_to_time_series(
-    time_str_s: pd.Series, base_date: Optional[Union[pd.Series, date]] = None
-) -> pd.Series:
-    """Convert mixed panda series datetime and TimeString (HH:MM<:SS>) to datetime object.
-
-    If HH > 24, will subtract 24 to be within 24 hours. Timespans will be treated as the next day.
-
-    Args:
-        time_str_s: Pandas Series of TimeStrings in HH:MM:SS or HH:MM format.
-        base_date: optional date to base the datetime on. Defaults to None.
-            If not provided, will use today. Can be either a single instance or a series of
-            same length as time_str_s
-    """
-    # check strings are in the correct format, leave existing date times alone
-    is_string = time_str_s.apply(lambda x: isinstance(x, str))
-    time_strings = time_str_s[is_string]
-    result = time_str_s.copy()
-    if is_string.any():
-        result[is_string] = _all_str_to_time_series(time_strings, base_date)
-    result = result.astype("datetime64[ns]")
-    return result
-
    -
    -
    - -
    - -
    - - -

    - timespan_str_list_to_dt(timespans) - -

    - - -
    - -

    Convert list of TimespanStrings to list of datetime.time objects.

    - -
    - Source code in network_wrangler/utils/time.py - 
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    @validate_call(config={"arbitrary_types_allowed": True})
-def timespan_str_list_to_dt(timespans: list[TimespanString]) -> list[list[datetime]]:
-    """Convert list of TimespanStrings to list of datetime.time objects."""
-    return [str_to_time_list(ts) for ts in timespans]
-
    -
    -
    - -
    - -
    - - -

    - timespans_overlap(timespan1, timespan2) - -

    - - -
    - -

    Check if two timespan strings overlap.

    -

    overlapping: a timespan that fully or partially overlaps a given timespan. -This includes and all timespans where at least one minute overlap.

    - -
    - Source code in network_wrangler/utils/time.py - 
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    def timespans_overlap(timespan1: list[TimespanString], timespan2: list[TimespanString]) -> bool:
-    """Check if two timespan strings overlap.
-
-    `overlapping`: a timespan that fully or partially overlaps a given timespan.
-    This includes and all timespans where at least one minute overlap.
-    """
-    timespan1 = str_to_time_list(timespan1)
-    timespan2 = str_to_time_list(timespan2)
-    return dt_overlaps(timespan1, timespan2)
-
    -
    -
    - -
    - - - -
    - -
    - -
    - -
    - - - - -
    - -

    Utility functions for pandas data manipulation.

    - - - -
    - - - - - - - - -
    - - - -

    - DataSegmentationError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Raised when there is an error segmenting data.

    - -
    - Source code in network_wrangler/utils/data.py - 
    19
-20
    class DataSegmentationError(Exception):
-    """Raised when there is an error segmenting data."""
-
    -
    - -
    - -
    - -
    - - - -

    - InvalidJoinFieldError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Raised when the join field is not unique.

    - -
    - Source code in network_wrangler/utils/data.py - 
    27
-28
    class InvalidJoinFieldError(Exception):
-    """Raised when the join field is not unique."""
-
    -
    - -
    - -
    - -
    - - - -

    - MissingPropertiesError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Raised when properties are missing from the dataframe.

    - -
    - Source code in network_wrangler/utils/data.py - 
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-24
    class MissingPropertiesError(Exception):
-    """Raised when properties are missing from the dataframe."""
-
    -
    - -
    - -
    - - -
    - - -

    - coerce_dict_to_df_types(d, df, skip_keys=None, return_skipped=False) - -

    - - -
    - -

    Coerce dictionary values to match the type of a dataframe columns matching dict keys.

    -

    Will also coerce a list of values.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    d - dict - -
    -

    dictionary to coerce with singleton or list values

    -
    -     		- required -
    df - DataFrame - -
    -

    dataframe to get types from

    -
    -     		- required -
    skip_keys - Optional[list] - -
    -

    list of dict keys to skip. Defaults to []/

    -
    -     		- None -
    return_skipped - bool - -
    -

    keep the uncoerced, skipped keys/vals in the resulting dict. -Defaults to False.

    -
    -     		- False -
    - - -

    Returns:

    - - - - - - - - - - - - - -
    Name TypeDescription
    dict - dict[str, CoerceTypes] - -
    -

    dict with coerced types

    -
    -
    - -
    - Source code in network_wrangler/utils/data.py - 
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    def coerce_dict_to_df_types(
-    d: dict[str, CoerceTypes],
-    df: pd.DataFrame,
-    skip_keys: Optional[list] = None,
-    return_skipped: bool = False,
-) -> dict[str, CoerceTypes]:
-    """Coerce dictionary values to match the type of a dataframe columns matching dict keys.
-
-    Will also coerce a list of values.
-
-    Args:
-        d (dict): dictionary to coerce with singleton or list values
-        df (pd.DataFrame): dataframe to get types from
-        skip_keys: list of dict keys to skip. Defaults to []/
-        return_skipped: keep the uncoerced, skipped keys/vals in the resulting dict.
-            Defaults to False.
-
-    Returns:
-        dict: dict with coerced types
-    """
-    if skip_keys is None:
-        skip_keys = []
-    coerced_dict: dict[str, CoerceTypes] = {}
-    for k, vals in d.items():
-        if k in skip_keys:
-            if return_skipped:
-                coerced_dict[k] = vals
-            continue
-        if k not in df.columns:
-            msg = f"Key {k} not in dataframe columns."
-            raise ValueError(msg)
-        if pd.api.types.infer_dtype(df[k]) == "integer":
-            if isinstance(vals, list):
-                coerced_v: CoerceTypes = [int(float(v)) for v in vals]
-            else:
-                coerced_v = int(float(vals))
-        elif pd.api.types.infer_dtype(df[k]) == "floating":
-            coerced_v = [float(v) for v in vals] if isinstance(vals, list) else float(vals)
-        elif pd.api.types.infer_dtype(df[k]) == "boolean":
-            coerced_v = [bool(v) for v in vals] if isinstance(vals, list) else bool(vals)
-        elif isinstance(vals, list):
-            coerced_v = [str(v) for v in vals]
-        else:
-            coerced_v = str(vals)
-        coerced_dict[k] = coerced_v
-    return coerced_dict
-
    -
    -
    - -
    - -
    - - -

    - coerce_gdf(df, geometry=None, in_crs=LAT_LON_CRS) - -

    - - -
    - -

    Coerce a DataFrame to a GeoDataFrame, optionally with a new geometry.

    - -
    - Source code in network_wrangler/utils/data.py - 
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    def coerce_gdf(
-    df: pd.DataFrame, geometry: GeoSeries = None, in_crs: int = LAT_LON_CRS
-) -> GeoDataFrame:
-    """Coerce a DataFrame to a GeoDataFrame, optionally with a new geometry."""
-    if isinstance(df, GeoDataFrame):
-        if df.crs is None:
-            df.crs = in_crs
-        return df
-    p = None
-
-    if "geometry" not in df and geometry is None:
-        msg = "Must give geometry argument if don't have Geometry in dataframe"
-        raise ValueError(msg)
-
-    geometry = geometry if geometry is not None else df["geometry"]
-    if not isinstance(geometry, GeoSeries):
-        try:
-            geometry = GeoSeries(geometry)
-        except Exception:
-            geometry = geometry.apply(wkt.loads)
-    df = GeoDataFrame(df, geometry=geometry, crs=in_crs)
-
-    return df
-
    -
    -
    - -
    - -
    - - -

    - coerce_val_to_df_types(field, val, df) - -

    - - -
    - -

    Coerce field value to match the type of a matching dataframe columns.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    field - str - -
    -

    field to lookup

    -
    -     		- required -
    val - CoerceTypes - -
    -

    value or list of values to coerce

    -
    -     		- required -
    df - DataFrame - -
    -

    dataframe to get types from

    -
    -     		- required -
    - - -
    - Source code in network_wrangler/utils/data.py - 
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    def coerce_val_to_df_types(  # noqa: PLR0911
-    field: str,
-    val: CoerceTypes,
-    df: pd.DataFrame,
-) -> CoerceTypes:
-    """Coerce field value to match the type of a matching dataframe columns.
-
-    Args:
-        field: field to lookup
-        val: value or list of values to coerce
-        df (pd.DataFrame): dataframe to get types from
-
-    Returns: coerced value or list of values
-    """
-    if field not in df.columns:
-        msg = f"Field {field} not in dataframe columns."
-        raise ValueError(msg)
-    if pd.api.types.infer_dtype(df[field]) == "integer":
-        if isinstance(val, list):
-            return [int(float(v)) for v in val]
-        return int(float(val))
-    if pd.api.types.infer_dtype(df[field]) == "floating":
-        if isinstance(val, list):
-            return [float(v) for v in val]
-        return float(val)
-    if pd.api.types.infer_dtype(df[field]) == "boolean":
-        if isinstance(val, list):
-            return [bool(v) for v in val]
-        return bool(val)
-    if isinstance(val, list):
-        return [str(v) for v in val]
-    return str(val)
-
    -
    -
    - -
    - -
    - - -

    - coerce_val_to_series_type(val, s) - -

    - - -
    - -

    Coerces a value to match type of pandas series.

    -

    Will try not to fail so if you give it a value that can’t convert to a number, it will -return a string.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    val - -
    -

    Any type of singleton value

    -
    -     		- required -
    s - Series - -
    -

    series to match the type to

    -
    -     		- required -
    - -
    - Source code in network_wrangler/utils/data.py - 
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    def coerce_val_to_series_type(val, s: pd.Series) -> Union[float, str, bool]:
-    """Coerces a value to match type of pandas series.
-
-    Will try not to fail so if you give it a value that can't convert to a number, it will
-    return a string.
-
-    Args:
-        val: Any type of singleton value
-        s (pd.Series): series to match the type to
-    """
-    # WranglerLogger.debug(f"Input val: {val} of type {type(val)} to match with series type \
-    #    {pd.api.types.infer_dtype(s)}.")
-    if pd.api.types.infer_dtype(s) in ["integer", "floating"]:
-        try:
-            v: Union[float, str, bool] = float(val)
-        except:
-            v = str(val)
-    elif pd.api.types.infer_dtype(s) == "boolean":
-        v = bool(val)
-    else:
-        v = str(val)
-    # WranglerLogger.debug(f"Return value: {v}")
-    return v
-
    -
    -
    - -
    - -
    - - -

    - compare_df_values(df1, df2, join_col=None, ignore=None, atol=1e-05) - -

    - - -
    - -

    Compare overlapping part of dataframes and returns where there are differences.

    - -
    - Source code in network_wrangler/utils/data.py - 
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    def compare_df_values(
-    df1, df2, join_col: Optional[str] = None, ignore: Optional[list[str]] = None, atol=1e-5
-):
-    """Compare overlapping part of dataframes and returns where there are differences."""
-    if ignore is None:
-        ignore = []
-    comp_c = [
-        c
-        for c in df1.columns
-        if c in df2.columns and c not in ignore and not isinstance(df1[c], GeoSeries)
-    ]
-    if join_col is None:
-        comp_df = df1[comp_c].merge(
-            df2[comp_c],
-            how="inner",
-            right_index=True,
-            left_index=True,
-            suffixes=["_a", "_b"],
-        )
-    else:
-        comp_df = df1[comp_c].merge(df2[comp_c], how="inner", on=join_col, suffixes=["_a", "_b"])
-
-    # Filter columns by data type
-    numeric_cols = [col for col in comp_c if np.issubdtype(df1[col].dtype, np.number)]
-    ll_cols = list(set(list_like_columns(df1) + list_like_columns(df2)))
-    other_cols = [col for col in comp_c if col not in numeric_cols and col not in ll_cols]
-
-    # For numeric columns, use np.isclose
-    if numeric_cols:
-        numeric_a = comp_df[[f"{col}_a" for col in numeric_cols]]
-        numeric_b = comp_df[[f"{col}_b" for col in numeric_cols]]
-        is_close = np.isclose(numeric_a, numeric_b, atol=atol, equal_nan=True)
-        comp_df[numeric_cols] = ~is_close
-
-    if ll_cols:
-        for ll_c in ll_cols:
-            comp_df[ll_c] = diff_list_like_series(comp_df[ll_c + "_a"], comp_df[ll_c + "_b"])
-
-    # For non-numeric columns, use direct comparison
-    if other_cols:
-        for col in other_cols:
-            comp_df[col] = (comp_df[f"{col}_a"] != comp_df[f"{col}_b"]) & ~(
-                comp_df[f"{col}_a"].isna() & comp_df[f"{col}_b"].isna()
-            )
-
-    # Filter columns and rows where no differences
-    cols_w_diffs = [col for col in comp_c if comp_df[col].any()]
-    out_cols = [col for subcol in cols_w_diffs for col in (f"{subcol}_a", f"{subcol}_b", subcol)]
-    comp_df = comp_df[out_cols]
-    comp_df = comp_df.loc[comp_df[cols_w_diffs].any(axis=1)]
-
-    return comp_df
-
    -
    -
    - -
    - -
    - - -

    - compare_lists(list1, list2) - -

    - - -
    - -

    Compare two lists.

    - -
    - Source code in network_wrangler/utils/data.py - 
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    def compare_lists(list1, list2) -> bool:
-    """Compare two lists."""
-    list1 = convert_numpy_to_list(list1)
-    list2 = convert_numpy_to_list(list1)
-    return list1 != list2
-
    -
    -
    - -
    - -
    - - -

    - concat_with_attr(dfs, **kwargs) - -

    - - -
    - -

    Concatenate a list of dataframes and retain the attributes of the first dataframe.

    - -
    - Source code in network_wrangler/utils/data.py - 
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    def concat_with_attr(dfs: list[pd.DataFrame], **kwargs) -> pd.DataFrame:
-    """Concatenate a list of dataframes and retain the attributes of the first dataframe."""
-    import copy
-
-    if not dfs:
-        msg = "No dataframes to concatenate."
-        raise ValueError(msg)
-    attrs = copy.deepcopy(dfs[0].attrs)
-    df = pd.concat(dfs, **kwargs)
-    df.attrs = attrs
-    return df
-
    -
    -
    - -
    - -
    - - -

    - convert_numpy_to_list(item) - -

    - - -
    - -

    Function to recursively convert numpy arrays to lists.

    - -
    - Source code in network_wrangler/utils/data.py - 
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    def convert_numpy_to_list(item):
-    """Function to recursively convert numpy arrays to lists."""
-    if isinstance(item, np.ndarray):
-        return item.tolist()
-    if isinstance(item, list):
-        return [convert_numpy_to_list(sub_item) for sub_item in item]
-    if isinstance(item, dict):
-        return {key: convert_numpy_to_list(value) for key, value in item.items()}
-    return item
-
    -
    -
    - -
    - -
    - - -

    - dict_fields_in_df(d, df) - -

    - - -
    - -

    Check if all fields in dict are in dataframe.

    - -
    - Source code in network_wrangler/utils/data.py - 
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    def dict_fields_in_df(d: dict, df: pd.DataFrame) -> bool:
-    """Check if all fields in dict are in dataframe."""
-    missing_fields = [f for f in d if f not in df.columns]
-    if missing_fields:
-        msg = f"Fields in dictionary missing from dataframe: {missing_fields}."
-        WranglerLogger.error(msg)
-        raise ValueError(msg)
-    return True
-
    -
    -
    - -
    - -
    - - -

    - dict_to_query(selection_dict) - -

    - - -
    - -

    Generates the query of from selection_dict.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    selection_dict - Mapping[str, Any] - -
    -

    selection dictionary

    -
    -     		- required -
    - - -

    Returns:

    - - - - - - - - - - - - - -
    Name TypeDescription
    _type_ - str - -
    -

    Query value

    -
    -
    - -
    - Source code in network_wrangler/utils/data.py - 
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    def dict_to_query(
-    selection_dict: Mapping[str, Any],
-) -> str:
-    """Generates the query of from selection_dict.
-
-    Args:
-        selection_dict: selection dictionary
-
-    Returns:
-        _type_: Query value
-    """
-    WranglerLogger.debug("Building selection query")
-
-    def _kv_to_query_part(k, v, _q_part=""):
-        if isinstance(v, list):
-            _q_part += "(" + " or ".join([_kv_to_query_part(k, i) for i in v]) + ")"
-            return _q_part
-        if isinstance(v, str):
-            return k + '.str.contains("' + v + '")'
-        return k + "==" + str(v)
-
-    query = "(" + " and ".join([_kv_to_query_part(k, v) for k, v in selection_dict.items()]) + ")"
-    WranglerLogger.debug(f"Selection query: \n{query}")
-    return query
-
    -
    -
    - -
    - -
    - - -

    - diff_dfs(df1, df2, ignore=None) - -

    - - -
    - -

    Returns True if two dataframes are different and log differences.

    - -
    - Source code in network_wrangler/utils/data.py - 
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    def diff_dfs(df1, df2, ignore: Optional[list[str]] = None) -> bool:
-    """Returns True if two dataframes are different and log differences."""
-    if ignore is None:
-        ignore = []
-    diff = False
-    if set(df1.columns) != set(df2.columns):
-        WranglerLogger.warning(
-            f" Columns are different 1vs2 \n    {set(df1.columns) ^ set(df2.columns)}"
-        )
-        common_cols = [col for col in df1.columns if col in df2.columns]
-        df1 = df1[common_cols]
-        df2 = df2[common_cols]
-        diff = True
-
-    cols_to_compare = [col for col in df1.columns if col not in ignore]
-    df1 = df1[cols_to_compare]
-    df2 = df2[cols_to_compare]
-
-    if len(df1) != len(df2):
-        WranglerLogger.warning(
-            f" Length is different /" f"DF1: {len(df1)} vs /" f"DF2: {len(df2)}\n /"
-        )
-        diff = True
-
-    diff_df = compare_df_values(df1, df2)
-
-    if not diff_df.empty:
-        WranglerLogger.error(f"!!! Differences dfs: \n{diff_df}")
-        return True
-
-    if not diff:
-        WranglerLogger.info("...no differences in df found.")
-    return diff
-
    -
    -
    - -
    - -
    - - -

    - diff_list_like_series(s1, s2) - -

    - - -
    - -

    Compare two series that contain list-like items as strings.

    - -
    - Source code in network_wrangler/utils/data.py - 
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    def diff_list_like_series(s1, s2) -> bool:
-    """Compare two series that contain list-like items as strings."""
-    diff_df = concat_with_attr([s1, s2], axis=1, keys=["s1", "s2"])
-    # diff_df["diff"] = diff_df.apply(lambda x: str(x["s1"]) != str(x["s2"]), axis=1)
-    diff_df["diff"] = diff_df.apply(lambda x: compare_lists(x["s1"], x["s2"]), axis=1)
-    if diff_df["diff"].any():
-        WranglerLogger.info("List-Like differences:")
-        WranglerLogger.info(diff_df)
-        return True
-    return False
-
    -
    -
    - -
    - -
    - - -

    - fk_in_pk(pk, fk, ignore_nan=True) - -

    - - -
    - -

    Check if all foreign keys are in the primary keys, optionally ignoring NaN.

    - -
    - Source code in network_wrangler/utils/data.py - 
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    def fk_in_pk(
-    pk: Union[pd.Series, list], fk: Union[pd.Series, list], ignore_nan: bool = True
-) -> tuple[bool, list]:
-    """Check if all foreign keys are in the primary keys, optionally ignoring NaN."""
-    if isinstance(fk, list):
-        fk = pd.Series(fk)
-
-    if ignore_nan:
-        fk = fk.dropna()
-
-    missing_flag = ~fk.isin(pk)
-
-    if missing_flag.any():
-        WranglerLogger.warning(
-            f"Following keys referenced in {fk.name} but missing in\
-            primary key table: \n{fk[missing_flag]} "
-        )
-        return False, fk[missing_flag].tolist()
-
-    return True, []
-
    -
    -
    - -
    - -
    - - -

    - isin_dict(df, d, ignore_missing=True, strict_str=False) - -

    - - -
    - -

    Filter the dataframe using a dictionary - faster than using isin.

    -

    Uses merge to filter the dataframe by the dictionary keys and values.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    df - DataFrame - -
    -

    dataframe to filter

    -
    -     		- required -
    d - dict - -
    -

    dictionary with keys as column names and values as values to filter by

    -
    -     		- required -
    ignore_missing - bool - -
    -

    if True, will ignore missing values in the selection dict.

    -
    -     		- True -
    strict_str - bool - -
    -

    if True, will not allow partial string matches and will force case-matching. -Defaults to False. If False, will be overridden if key is in STRICT_MATCH_FIELDS or if -ignore_missing is False.

    -
    -     		- False -
    - -
    - Source code in network_wrangler/utils/data.py - 
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    def isin_dict(
-    df: pd.DataFrame, d: dict, ignore_missing: bool = True, strict_str: bool = False
-) -> pd.DataFrame:
-    """Filter the dataframe using a dictionary - faster than using isin.
-
-    Uses merge to filter the dataframe by the dictionary keys and values.
-
-    Args:
-        df: dataframe to filter
-        d: dictionary with keys as column names and values as values to filter by
-        ignore_missing: if True, will ignore missing values in the selection dict.
-        strict_str: if True, will not allow partial string matches and will force case-matching.
-            Defaults to False. If False, will be overridden if key is in STRICT_MATCH_FIELDS or if
-            ignore_missing is False.
-    """
-    sel_links_mask = np.zeros(len(df), dtype=bool)
-    missing = {}
-    for col, vals in d.items():
-        if vals is None:
-            continue
-        if col not in df.columns:
-            msg = f"Key {col} not in dataframe columns."
-            raise DataframeSelectionError(msg)
-        _strict_str = strict_str or col in STRICT_MATCH_FIELDS or not ignore_missing
-        vals_list = [vals] if not isinstance(vals, list) else vals
-
-        index_name = df.index.name if df.index.name is not None else "index"
-        _df = df[[col]].reset_index(names=index_name)
-
-        if isinstance(vals_list[0], str) and not _strict_str:
-            vals_list = [val.lower() for val in vals_list]
-            _df[col] = _df[col].str.lower()
-
-            # Use str.contains for partial matching
-            mask = np.zeros(len(_df), dtype=bool)
-            for val in vals_list:
-                mask |= _df[col].str.contains(val, case=False, na=False)
-            selected = _df[mask].set_index(index_name)
-        else:
-            vals_df = pd.DataFrame({col: vals_list}, index=range(len(vals_list)))
-            merged_df = _df.merge(vals_df, on=col, how="outer", indicator=True)
-            selected = merged_df[merged_df["_merge"] == "both"].set_index(index_name)
-            _missing_vals = merged_df[merged_df["_merge"] == "right_only"][col].tolist()
-            if _missing_vals:
-                missing[col] = _missing_vals
-                WranglerLogger.warning(f"Missing values in selection dict for {col}: {missing}")
-
-        sel_links_mask |= df.index.isin(selected.index)
-
-    if not ignore_missing and any(missing):
-        msg = "Missing values in selection dict."
-        raise DataframeSelectionError(msg)
-
-    return df.loc[sel_links_mask]
-
    -
    -
    - -
    - -
    - - -

    - list_like_columns(df, item_type=None) - -

    - - -
    - -

    Find columns in a dataframe that contain list-like items that can’t be json-serialized.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    df - -
    -

    dataframe to check

    -
    -     		- required -
    item_type - Optional[type] - -
    -

    if not None, will only return columns where all items are of this type by -checking only the first item in the column. Defaults to None.

    -
    -     		- None -
    - -
    - Source code in network_wrangler/utils/data.py - 
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    def list_like_columns(df, item_type: Optional[type] = None) -> list[str]:
-    """Find columns in a dataframe that contain list-like items that can't be json-serialized.
-
-    Args:
-        df: dataframe to check
-        item_type: if not None, will only return columns where all items are of this type by
-            checking **only** the first item in the column.  Defaults to None.
-    """
-    list_like_columns = []
-
-    for column in df.columns:
-        if df[column].apply(lambda x: isinstance(x, (list, ndarray))).any():
-            if item_type is not None and not isinstance(df[column].iloc[0], item_type):
-                continue
-            list_like_columns.append(column)
-    return list_like_columns
-
    -
    -
    - -
    - -
    - - -

    - segment_data_by_selection(item_list, data, field=None, end_val=0) - -

    - - -
    - -

    Segment a dataframe or series into before, middle, and end segments based on item_list.

    -

    selected segment = everything from the first to last item in item_list inclusive of the first - and last items. -Before segment = everything before -After segment = everything after

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    item_list - list - -
    -

    List of items to segment data by. If longer than two, will only -use the first and last items.

    -
    -     		- required -
    data - Union[Series, DataFrame] - -
    -

    Data to segment into before, middle, and after.

    -
    -     		- required -
    field - str - -
    -

    If a dataframe, specifies which field to reference. -Defaults to None.

    -
    -     		- None -
    end_val - int - -
    -

    Notation for util the end or from the begining. Defaults to 0.

    -
    -     		- 0 -
    - - -

    Raises:

    - - - - - - - - - - - - - -
    TypeDescription
    - DataSegmentationError - -
    -

    If item list isn’t found in data in correct order.

    -
    -
    - - -

    Returns:

    - - - - - - - - - - - - - -
    Name TypeDescription
    tuple - tuple[Union[Series, list, DataFrame], Union[Series, list, DataFrame], Union[Series, list, DataFrame]] - -
    -

    data broken out by beofore, selected segment, and after.

    -
    -
    - -
    - Source code in network_wrangler/utils/data.py - 
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    def segment_data_by_selection(
-    item_list: list,
-    data: Union[list, pd.DataFrame, pd.Series],
-    field: Optional[str] = None,
-    end_val=0,
-) -> tuple[
-    Union[pd.Series, list, pd.DataFrame],
-    Union[pd.Series, list, pd.DataFrame],
-    Union[pd.Series, list, pd.DataFrame],
-]:
-    """Segment a dataframe or series into before, middle, and end segments based on item_list.
-
-    selected segment = everything from the first to last item in item_list inclusive of the first
-        and last items.
-    Before segment = everything before
-    After segment = everything after
-
-    Args:
-        item_list (list): List of items to segment data by. If longer than two, will only
-            use the first and last items.
-        data (Union[pd.Series, pd.DataFrame]): Data to segment into before, middle, and after.
-        field (str, optional): If a dataframe, specifies which field to reference.
-            Defaults to None.
-        end_val (int, optional): Notation for util the end or from the begining. Defaults to 0.
-
-    Raises:
-        DataSegmentationError: If item list isn't found in data in correct order.
-
-    Returns:
-        tuple: data broken out by beofore, selected segment, and after.
-    """
-    ref_data = data
-    if isinstance(data, pd.DataFrame):
-        ref_data = data[field].tolist()
-    elif isinstance(data, pd.Series):
-        ref_data = data.tolist()
-
-    # ------- Replace "to the end" indicators with first or last value --------
-    start_item, end_item = item_list[0], item_list[-1]
-    if start_item == end_val:
-        start_item = ref_data[0]
-    if end_item == end_val:
-        end_item = ref_data[-1]
-
-    # --------Find the start and end indices -----------------------------------
-    start_idxs = list({i for i, item in enumerate(ref_data) if item == start_item})
-    if not start_idxs:
-        msg = f"Segment start item: {start_item} not in data."
-        raise DataSegmentationError(msg)
-    if len(start_idxs) > 1:
-        WranglerLogger.warning(
-            f"Found multiple starting locations for data segment: {start_item}.\
-                                Choosing first ... largest segment being selected."
-        )
-    start_idx = min(start_idxs)
-
-    # find the end node starting from the start index.
-    end_idxs = [i + start_idx for i, item in enumerate(ref_data[start_idx:]) if item == end_item]
-    # WranglerLogger.debug(f"End indexes: {end_idxs}")
-    if not end_idxs:
-        msg = f"Segment end item: {end_item} not in data after starting idx."
-        raise DataSegmentationError(msg)
-    if len(end_idxs) > 1:
-        WranglerLogger.warning(
-            f"Found multiple ending locations for data segment: {end_item}.\
-                                Choosing last ... largest segment being selected."
-        )
-    end_idx = max(end_idxs) + 1
-    # WranglerLogger.debug(
-    # f"Segmenting data fr {start_item} idx:{start_idx} to {end_item} idx:{end_idx}.\n{ref_data}")
-    # -------- Extract the segments --------------------------------------------
-    if isinstance(data, pd.DataFrame):
-        before_segment = data.iloc[:start_idx]
-        selected_segment = data.iloc[start_idx:end_idx]
-        after_segment = data.iloc[end_idx:]
-    else:
-        before_segment = data[:start_idx]
-        selected_segment = data[start_idx:end_idx]
-        after_segment = data[end_idx:]
-
-    if isinstance(data, (pd.DataFrame, pd.Series)):
-        before_segment = before_segment.reset_index(drop=True)
-        selected_segment = selected_segment.reset_index(drop=True)
-        after_segment = after_segment.reset_index(drop=True)
-
-    # WranglerLogger.debug(f"Segmented data into before, selected, and after.\n \
-    #    Before:\n{before_segment}\nSelected:\n{selected_segment}\nAfter:\n{after_segment}")
-
-    return before_segment, selected_segment, after_segment
-
    -
    -
    - -
    - -
    - - -

    - segment_data_by_selection_min_overlap(selection_list, data, field, replacements_list, end_val=0) - -

    - - -
    - -

    Segments data based on item_list reducing overlap with replacement list.

    -

    selected segment: everything from the first to last item in item_list inclusive of the first - and last items but not if first and last items overlap with replacement list. -Before segment = everything before -After segment = everything after

    -

    Example: -selection_list = [2,5] -data = pd.DataFrame({“i”:[1,2,3,4,5,6]}) -field = “i” -replacements_list = [2,22,33]

    - - -

    Returns:

    - - - - - - - - - - - - - - - - - -
    TypeDescription
    - list - -
    -

    [22,33]

    -
    -
    - tuple[Union[Series, DataFrame], Union[Series, DataFrame], Union[Series, DataFrame]] - -
    -

    [1], [2,3,4,5], [6]

    -
    -
    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    selection_list - list - -
    -

    List of items to segment data by. If longer than two, will only -use the first and last items.

    -
    -     		- required -
    data - Union[Series, DataFrame] - -
    -

    Data to segment into before, middle, and after.

    -
    -     		- required -
    field - str - -
    -

    Specifies which field to reference.

    -
    -     		- required -
    replacements_list - list - -
    -

    List of items to eventually replace the selected segment with.

    -
    -     		- required -
    end_val - int - -
    -

    Notation for util the end or from the begining. Defaults to 0.

    -
    -     		- 0 -
    - - -

    tuple containing:

    - - - - - - - - - - - - - - - - - -
    TypeDescription
    - list - -
    -
      -
    • updated replacement_list
      • -
    -
    -
    - tuple[Union[Series, DataFrame], Union[Series, DataFrame], Union[Series, DataFrame]] - -
    -
      -
    • tuple of before, selected segment, and after data
      • -
    -
    -
    - -
    - Source code in network_wrangler/utils/data.py - 
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    def segment_data_by_selection_min_overlap(
-    selection_list: list,
-    data: pd.DataFrame,
-    field: str,
-    replacements_list: list,
-    end_val=0,
-) -> tuple[
-    list,
-    tuple[
-        Union[pd.Series, pd.DataFrame],
-        Union[pd.Series, pd.DataFrame],
-        Union[pd.Series, pd.DataFrame],
-    ],
-]:
-    """Segments data based on item_list reducing overlap with replacement list.
-
-    *selected segment*: everything from the first to last item in item_list inclusive of the first
-        and last items but not if first and last items overlap with replacement list.
-    Before segment = everything before
-    After segment = everything after
-
-    Example:
-    selection_list = [2,5]
-    data = pd.DataFrame({"i":[1,2,3,4,5,6]})
-    field = "i"
-    replacements_list = [2,22,33]
-
-    returns:
-        [22,33]
-        [1], [2,3,4,5], [6]
-
-    Args:
-        selection_list (list): List of items to segment data by. If longer than two, will only
-            use the first and last items.
-        data (Union[pd.Series, pd.DataFrame]): Data to segment into before, middle, and after.
-        field (str): Specifies which field to reference.
-        replacements_list (list): List of items to eventually replace the selected segment with.
-        end_val (int, optional): Notation for util the end or from the begining. Defaults to 0.
-
-    Returns: tuple containing:
-        - updated replacement_list
-        - tuple of before, selected segment, and after data
-    """
-    before_segment, segment_df, after_segment = segment_data_by_selection(
-        selection_list, data, field=field, end_val=end_val
-    )
-    if not isinstance(segment_df, pd.DataFrame):
-        msg = "segment_df should be a DataFrame - something is wrong."
-        raise ValueError(msg)
-
-    if replacements_list and replacements_list[0] == segment_df[field].iat[0]:
-        # move first item from selected segment to the before_segment df
-        replacements_list = replacements_list[1:]
-        before_segment = concat_with_attr(
-            [before_segment, segment_df.iloc[:1]], ignore_index=True, sort=False
-        )
-        segment_df = segment_df.iloc[1:]
-        # WranglerLogger.debug(f"item start overlaps with replacement. Repl: {replacements_list}")
-    if replacements_list and replacements_list[-1] == data[field].iat[-1]:
-        # move last item from selected segment to the after_segment df
-        replacements_list = replacements_list[:-1]
-        after_segment = concat_with_attr(
-            [data.iloc[-1:], after_segment], ignore_index=True, sort=False
-        )
-        segment_df = segment_df.iloc[:-1]
-        # WranglerLogger.debug(f"item end overlaps with replacement. Repl: {replacements_list}")
-
-    return replacements_list, (before_segment, segment_df, after_segment)
-
    -
    -
    - -
    - -
    - - -

    - update_df_by_col_value(destination_df, source_df, join_col, properties=None, fail_if_missing=True) - -

    - - -
    - -

    Updates destination_df with ALL values in source_df for specified props with same join_col.

    -

    Source_df can contain a subset of IDs of destination_df. -If fail_if_missing is true, destination_df must have all -the IDS in source DF - ensuring all source_df values are contained in resulting df.

    -
    >> destination_df
-trip_id  property1  property2
-1         10      100
-2         20      200
-3         30      300
-4         40      400
-
->> source_df
-trip_id  property1  property2
-2         25      250
-3         35      350
-
->> updated_df
-trip_id  property1  property2
-0        1       10      100
-1        2       25      250
-2        3       35      350
-3        4       40      400
-
    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    destination_df - DataFrame - -
    -

    Dataframe to modify.

    -
    -     		- required -
    source_df - DataFrame - -
    -

    Dataframe with updated columns

    -
    -     		- required -
    join_col - str - -
    -

    column to join on

    -
    -     		- required -
    properties - list[str] - -
    -

    List of properties to use. If None, will default to all -in source_df.

    -
    -     		- None -
    fail_if_missing - bool - -
    -

    If True, will raise an error if there are missing IDs in -destination_df that exist in source_df.

    -
    -     		- True -
    - -
    - Source code in network_wrangler/utils/data.py - 
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    def update_df_by_col_value(
-    destination_df: pd.DataFrame,
-    source_df: pd.DataFrame,
-    join_col: str,
-    properties: Optional[list[str]] = None,
-    fail_if_missing: bool = True,
-) -> pd.DataFrame:
-    """Updates destination_df with ALL values in source_df for specified props with same join_col.
-
-    Source_df can contain a subset of IDs of destination_df.
-    If fail_if_missing is true, destination_df must have all
-    the IDS in source DF - ensuring all source_df values are contained in resulting df.
-
-    ```
-    >> destination_df
-    trip_id  property1  property2
-    1         10      100
-    2         20      200
-    3         30      300
-    4         40      400
-
-    >> source_df
-    trip_id  property1  property2
-    2         25      250
-    3         35      350
-
-    >> updated_df
-    trip_id  property1  property2
-    0        1       10      100
-    1        2       25      250
-    2        3       35      350
-    3        4       40      400
-    ```
-
-    Args:
-        destination_df (pd.DataFrame): Dataframe to modify.
-        source_df (pd.DataFrame): Dataframe with updated columns
-        join_col (str): column to join on
-        properties (list[str]): List of properties to use. If None, will default to all
-            in source_df.
-        fail_if_missing (bool): If True, will raise an error if there are missing IDs in
-            destination_df that exist in source_df.
-    """
-    # 1. Identify which properties should be updated; and if they exist in both DFs.
-    if properties is None:
-        properties = [
-            c for c in source_df.columns if c in destination_df.columns and c != join_col
-        ]
-    else:
-        _dest_miss = _df_missing_cols(destination_df, [*properties, join_col])
-        if _dest_miss:
-            msg = f"Properties missing from destination_df: {_dest_miss}"
-            raise MissingPropertiesError(msg)
-        _source_miss = _df_missing_cols(source_df, [*properties, join_col])
-        if _source_miss:
-            msg = f"Properties missing from source_df: {_source_miss}"
-            raise MissingPropertiesError(msg)
-
-    # 2. Identify if there are IDs missing from destination_df that exist in source_df
-    if fail_if_missing:
-        missing_ids = set(source_df[join_col]) - set(destination_df[join_col])
-        if missing_ids:
-            msg = f"IDs missing from source_df: \n{missing_ids}"
-            raise InvalidJoinFieldError(msg)
-
-    WranglerLogger.debug(f"Updating properties for {len(source_df)} records: {properties}.")
-
-    if not source_df[join_col].is_unique:
-        msg = f"Can't join from source_df when join_col: {join_col} is not unique."
-        raise InvalidJoinFieldError(msg)
-
-    if not destination_df[join_col].is_unique:
-        return _update_props_from_one_to_many(destination_df, source_df, join_col, properties)
-
-    return _update_props_for_common_idx(destination_df, source_df, join_col, properties)
-
    -
    -
    - -
    - -
    - - -

    - validate_existing_value_in_df(df, idx, field, expected_value) - -

    - - -
    - -

    Validate if df[field]==expected_value for all indices in idx.

    - -
    - Source code in network_wrangler/utils/data.py - 
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    def validate_existing_value_in_df(df: pd.DataFrame, idx: list[int], field: str, expected_value):
-    """Validate if df[field]==expected_value for all indices in idx."""
-    if field not in df.columns:
-        WranglerLogger.warning(f"!! {field} Not an existing field.")
-        return False
-    if not df.loc[idx, field].eq(expected_value).all():
-        WranglerLogger.warning(
-            f"Existing value defined for {field} in project card \
-            does not match the value in the selection links. \n\
-            Specified Existing: {expected_value}\n\
-            Actual Existing: \n {df.loc[idx, field]}."
-        )
-        return False
-    return True
-
    -
    -
    - -
    - - - -
    - -
    - -
    - -
    - - - - -
    - -

    Helper geographic manipulation functions.

    - - - -
    - - - - - - - - -
    - - - -

    - InvalidCRSError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Raised when a point is not valid for a given coordinate reference system.

    - -
    - Source code in network_wrangler/utils/geo.py - 
    31
-32
    class InvalidCRSError(Exception):
-    """Raised when a point is not valid for a given coordinate reference system."""
-
    -
    - -
    - -
    - - -
    - - -

    - check_point_valid_for_crs(point, crs) - -

    - - -
    - -

    Check if a point is valid for a given coordinate reference system.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    point - Point - -
    -

    Shapely Point

    -
    -     		- required -
    crs - int - -
    -

    coordinate reference system in ESPG code

    -
    -     		- required -
    - - -
    - Source code in network_wrangler/utils/geo.py - 
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    def check_point_valid_for_crs(point: Point, crs: int):
-    """Check if a point is valid for a given coordinate reference system.
-
-    Args:
-        point: Shapely Point
-        crs: coordinate reference system in ESPG code
-
-    raises: InvalidCRSError if point is not valid for the given crs
-    """
-    crs = CRS.from_user_input(crs)
-    minx, miny, maxx, maxy = crs.area_of_use.bounds
-    ok_bounds = True
-    if not minx <= point.x <= maxx:
-        WranglerLogger.error(f"Invalid X coordinate for CRS {crs}: {point.x}")
-        ok_bounds = False
-    if not miny <= point.y <= maxy:
-        WranglerLogger.error(f"Invalid Y coordinate for CRS {crs}: {point.y}")
-        ok_bounds = False
-
-    if not ok_bounds:
-        msg = f"Invalid coordinate for CRS {crs}: {point.x}, {point.y}"
-        raise InvalidCRSError(msg)
-
    -
    -
    - -
    - -
    - - -

    - get_bearing(lat1, lon1, lat2, lon2) - -

    - - -
    - -

    Calculate the bearing (forward azimuth) b/w the two points.

    -

    returns: bearing in radians

    - -
    - Source code in network_wrangler/utils/geo.py - 
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    def get_bearing(lat1, lon1, lat2, lon2):
-    """Calculate the bearing (forward azimuth) b/w the two points.
-
-    returns: bearing in radians
-    """
-    # bearing in degrees
-    brng = Geodesic.WGS84.Inverse(lat1, lon1, lat2, lon2)["azi1"]
-
-    # convert bearing to radians
-    brng = math.radians(brng)
-
-    return brng
-
    -
    -
    - -
    - -
    - - -

    - get_bounding_polygon(boundary_geocode=None, boundary_file=None, boundary_gdf=None, crs=LAT_LON_CRS) - -

    - - -
    - -

    Get the bounding polygon for a given boundary.

    -

    Will return None if no arguments given. Will raise a ValueError if more than one given.

    -

    This function retrieves the bounding polygon for a given boundary. The boundary can be provided -as a GeoDataFrame, a geocode string or dictionary, or a boundary file. The resulting polygon -geometry is returned as a GeoSeries.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    boundary_geocode - Union[str, dict] - -
    -

    A geocode string or dictionary -representing the boundary. Defaults to None.

    -
    -     		- None -
    boundary_file - Union[str, Path] - -
    -

    A path to the boundary file. Only used if -boundary_geocode is None. Defaults to None.

    -
    -     		- None -
    boundary_gdf - GeoDataFrame - -
    -

    A GeoDataFrame representing the boundary. -Only used if boundary_geocode and boundary_file are None. Defaults to None.

    -
    -     		- None -
    crs - int - -
    -

    The coordinate reference system (CRS) code. Defaults to 4326 (WGS84).

    -
    -     		- LAT_LON_CRS -
    - - -

    Returns:

    - - - - - - - - - - - - - -
    TypeDescription
    - GeoSeries - -
    -

    gpd.GeoSeries: The polygon geometry representing the bounding polygon.

    -
    -
    - -
    - Source code in network_wrangler/utils/geo.py - 
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    def get_bounding_polygon(
-    boundary_geocode: Optional[Union[str, dict]] = None,
-    boundary_file: Optional[Union[str, Path]] = None,
-    boundary_gdf: Optional[gpd.GeoDataFrame] = None,
-    crs: int = LAT_LON_CRS,  # WGS84
-) -> gpd.GeoSeries:
-    """Get the bounding polygon for a given boundary.
-
-    Will return None if no arguments given. Will raise a ValueError if more than one given.
-
-    This function retrieves the bounding polygon for a given boundary. The boundary can be provided
-    as a GeoDataFrame, a geocode string or dictionary, or a boundary file. The resulting polygon
-    geometry is returned as a GeoSeries.
-
-    Args:
-        boundary_geocode (Union[str, dict], optional): A geocode string or dictionary
-            representing the boundary. Defaults to None.
-        boundary_file (Union[str, Path], optional): A path to the boundary file. Only used if
-            boundary_geocode is None. Defaults to None.
-        boundary_gdf (gpd.GeoDataFrame, optional): A GeoDataFrame representing the boundary.
-            Only used if boundary_geocode and boundary_file are None. Defaults to None.
-        crs (int, optional): The coordinate reference system (CRS) code. Defaults to 4326 (WGS84).
-
-    Returns:
-        gpd.GeoSeries: The polygon geometry representing the bounding polygon.
-    """
-    import osmnx as ox
-
-    nargs = sum(x is not None for x in [boundary_gdf, boundary_geocode, boundary_file])
-    if nargs == 0:
-        return None
-    if nargs != 1:
-        msg = "Exactly one of boundary_gdf, boundary_geocode, or boundary_file must be provided."
-        raise ValueError(msg)
-
-    OK_BOUNDARY_SUFF = [".shp", ".geojson", ".parquet"]
-
-    if boundary_geocode is not None:
-        boundary_gdf = ox.geocode_to_gdf(boundary_geocode)
-    elif boundary_file is not None:
-        boundary_file = Path(boundary_file)
-        if boundary_file.suffix not in OK_BOUNDARY_SUFF:
-            msg = "Boundary file must have one of the following suffixes: {OK_BOUNDARY_SUFF}"
-            raise ValueError(msg)
-        if not boundary_file.exists():
-            msg = f"Boundary file {boundary_file} does not exist"
-            raise FileNotFoundError(msg)
-        if boundary_file.suffix == ".parquet":
-            boundary_gdf = gpd.read_parquet(boundary_file)
-        else:
-            boundary_gdf = gpd.read_file(boundary_file)
-            if boundary_file.suffix == ".geojson":  # geojson standard is WGS84
-                boundary_gdf.crs = crs
-
-    if boundary_gdf is None:
-        msg = "One of boundary_gdf, boundary_geocode or boundary_file must be provided."
-        raise ValueError(msg)
-
-    if boundary_gdf.crs is not None:
-        boundary_gdf = boundary_gdf.to_crs(crs)
-    # make sure boundary_gdf is a polygon
-    if len(boundary_gdf.geom_type[boundary_gdf.geom_type != "Polygon"]) > 0:
-        msg = "boundary_gdf must all be Polygons"
-        raise ValueError(msg)
-    # get the boundary as a single polygon
-    boundary_gs = gpd.GeoSeries([boundary_gdf.geometry.union_all()], crs=crs)
-
-    return boundary_gs
-
    -
    -
    - -
    - -
    - - -

    - get_point_geometry_from_linestring(polyline_geometry, pos=0) - -

    - - -
    - -

    Get a point geometry from a linestring geometry.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    polyline_geometry - -
    -

    shapely LineString instance

    -
    -     		- required -
    pos - int - -
    -

    position in the linestring to get the point from. Defaults to 0.

    -
    -     		- 0 -
    - -
    - Source code in network_wrangler/utils/geo.py - 
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    def get_point_geometry_from_linestring(polyline_geometry, pos: int = 0):
-    """Get a point geometry from a linestring geometry.
-
-    Args:
-        polyline_geometry: shapely LineString instance
-        pos: position in the linestring to get the point from. Defaults to 0.
-    """
-    # WranglerLogger.debug(
-    #    f"get_point_geometry_from_linestring.polyline_geometry.coords[0]: \
-    #    {polyline_geometry.coords[0]}."
-    # )
-
-    # Note: when upgrading to shapely 2.0, will need to use following command
-    # _point_coords = get_coordinates(polyline_geometry).tolist()[pos]
-    return point_from_xy(*polyline_geometry.coords[pos])
-
    -
    -
    - -
    - -
    - - -

    - length_of_linestring_miles(gdf) - -

    - - -
    - -

    Returns a Series with the linestring length in miles.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    gdf - Union[GeoSeries, GeoDataFrame] - -
    -

    GeoDataFrame with linestring geometry. If given a GeoSeries will attempt to convert -to a GeoDataFrame.

    -
    -     		- required -
    - -
    - Source code in network_wrangler/utils/geo.py - 
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    def length_of_linestring_miles(gdf: Union[gpd.GeoSeries, gpd.GeoDataFrame]) -> pd.Series:
-    """Returns a Series with the linestring length in miles.
-
-    Args:
-        gdf: GeoDataFrame with linestring geometry.  If given a GeoSeries will attempt to convert
-            to a GeoDataFrame.
-    """
-    # WranglerLogger.debug(f"length_of_linestring_miles.gdf input:\n{gdf}.")
-    if isinstance(gdf, gpd.GeoSeries):
-        gdf = gpd.GeoDataFrame(geometry=gdf)
-
-    p_crs = gdf.estimate_utm_crs()
-    gdf = gdf.to_crs(p_crs)
-    METERS_IN_MILES = 1609.34
-    length_miles = gdf.geometry.length / METERS_IN_MILES
-    length_s = pd.Series(length_miles, index=gdf.index)
-
-    return length_s
-
    -
    -
    - -
    - -
    - - -

    - linestring_from_lats_lons(df, lat_fields, lon_fields) - -

    - - -
    - -

    Create a LineString geometry from a DataFrame with lon/lat fields.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    df - -
    -

    DataFrame with columns for lon/lat fields.

    -
    -     		- required -
    lat_fields - -
    -

    list of column names for the lat fields.

    -
    -     		- required -
    lon_fields - -
    -

    list of column names for the lon fields.

    -
    -     		- required -
    - -
    - Source code in network_wrangler/utils/geo.py - 
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    def linestring_from_lats_lons(df, lat_fields, lon_fields) -> gpd.GeoSeries:
-    """Create a LineString geometry from a DataFrame with lon/lat fields.
-
-    Args:
-        df: DataFrame with columns for lon/lat fields.
-        lat_fields: list of column names for the lat fields.
-        lon_fields: list of column names for the lon fields.
-    """
-    if len(lon_fields) != len(lat_fields):
-        msg = "lon_fields and lat_fields lists must have the same length"
-        raise ValueError(msg)
-
-    line_geometries = gpd.GeoSeries(
-        [
-            LineString([(row[lon], row[lat]) for lon, lat in zip(lon_fields, lat_fields)])
-            for _, row in df.iterrows()
-        ]
-    )
-
-    return gpd.GeoSeries(line_geometries)
-
    -
    -
    - -
    - -
    - - -

    - linestring_from_nodes(links_df, nodes_df, from_node='A', to_node='B', node_pk='model_node_id') - -

    - - -
    - -

    Creates a LineString geometry GeoSeries from a DataFrame of links and a DataFrame of nodes.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    links_df - DataFrame - -
    -

    DataFrame with columns for from_node and to_node.

    -
    -     		- required -
    nodes_df - GeoDataFrame - -
    -

    GeoDataFrame with geometry column.

    -
    -     		- required -
    from_node - str - -
    -

    column name in links_df for the from node. Defaults to “A”.

    -
    -     		- 'A' -
    to_node - str - -
    -

    column name in links_df for the to node. Defaults to “B”.

    -
    -     		- 'B' -
    node_pk - str - -
    -

    primary key column name in nodes_df. Defaults to “model_node_id”.

    -
    -     		- 'model_node_id' -
    - -
    - Source code in network_wrangler/utils/geo.py - 
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    def linestring_from_nodes(
-    links_df: pd.DataFrame,
-    nodes_df: gpd.GeoDataFrame,
-    from_node: str = "A",
-    to_node: str = "B",
-    node_pk: str = "model_node_id",
-) -> gpd.GeoSeries:
-    """Creates a LineString geometry GeoSeries from a DataFrame of links and a DataFrame of nodes.
-
-    Args:
-        links_df: DataFrame with columns for from_node and to_node.
-        nodes_df: GeoDataFrame with geometry column.
-        from_node: column name in links_df for the from node. Defaults to "A".
-        to_node: column name in links_df for the to node. Defaults to "B".
-        node_pk: primary key column name in nodes_df. Defaults to "model_node_id".
-    """
-    assert "geometry" in nodes_df.columns, "nodes_df must have a 'geometry' column"
-
-    idx_name = "index" if links_df.index.name is None else links_df.index.name
-    # WranglerLogger.debug(f"Index name: {idx_name}")
-    required_link_cols = [from_node, to_node]
-
-    if not all(col in links_df.columns for col in required_link_cols):
-        WranglerLogger.error(
-            f"links_df.columns missing required columns.\n\
-                            links_df.columns: {links_df.columns}\n\
-                            required_link_cols: {required_link_cols}"
-        )
-        msg = "links_df must have columns {required_link_cols} to create linestring from nodes"
-        raise ValueError(msg)
-
-    links_geo_df = copy.deepcopy(links_df[required_link_cols])
-    # need to continuously reset the index to make sure the index is the same as the link index
-    links_geo_df = (
-        links_geo_df.reset_index()
-        .merge(
-            nodes_df[[node_pk, "geometry"]],
-            left_on=from_node,
-            right_on=node_pk,
-            how="left",
-        )
-        .set_index(idx_name)
-    )
-
-    links_geo_df = links_geo_df.rename(columns={"geometry": "geometry_A"})
-
-    links_geo_df = (
-        links_geo_df.reset_index()
-        .merge(
-            nodes_df[[node_pk, "geometry"]],
-            left_on=to_node,
-            right_on=node_pk,
-            how="left",
-        )
-        .set_index(idx_name)
-    )
-
-    links_geo_df = links_geo_df.rename(columns={"geometry": "geometry_B"})
-
-    # makes sure all nodes exist
-    _missing_geo_links_df = links_geo_df[
-        links_geo_df["geometry_A"].isnull() | links_geo_df["geometry_B"].isnull()
-    ]
-    if not _missing_geo_links_df.empty:
-        missing_nodes = _missing_geo_links_df[[from_node, to_node]].values
-        WranglerLogger.error(
-            f"Cannot create link geometry from nodes because the nodes are\
-                             missing from the network. Missing nodes: {missing_nodes}"
-        )
-        msg = "Cannot create link geometry from nodes because the nodes are missing from the network."
-        raise MissingNodesError(msg)
-
-    # create geometry from points
-    links_geo_df["geometry"] = links_geo_df.apply(
-        lambda row: LineString([row["geometry_A"], row["geometry_B"]]), axis=1
-    )
-
-    # convert to GeoDataFrame
-    links_gdf = gpd.GeoDataFrame(links_geo_df["geometry"], geometry=links_geo_df["geometry"])
-    return links_gdf["geometry"]
-
    -
    -
    - -
    - -
    - - -

    - location_ref_from_point(geometry, sequence=1, bearing=None, distance_to_next_ref=None) - -

    - - -
    - -

    Generates a shared street point location reference.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    geometry - Point - -
    -

    Point shapely geometry

    -
    -     		- required -
    sequence - int - -
    -

    Sequence if part of polyline. Defaults to None.

    -
    -     		- 1 -
    bearing - float - -
    -

    Direction of line if part of polyline. Defaults to None.

    -
    -     		- None -
    distance_to_next_ref - float - -
    -

    Distnce to next point if part of polyline. -Defaults to None.

    -
    -     		- None -
    - - -

    Returns:

    - - - - - - - - - - - - - -
    Name TypeDescription
    LocationReference - LocationReference - -
    -

    As defined by sharedStreets.io schema

    -
    -
    - -
    - Source code in network_wrangler/utils/geo.py - 
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    def location_ref_from_point(
-    geometry: Point,
-    sequence: int = 1,
-    bearing: Optional[float] = None,
-    distance_to_next_ref: Optional[float] = None,
-) -> LocationReference:
-    """Generates a shared street point location reference.
-
-    Args:
-        geometry (Point): Point shapely geometry
-        sequence (int, optional): Sequence if part of polyline. Defaults to None.
-        bearing (float, optional): Direction of line if part of polyline. Defaults to None.
-        distance_to_next_ref (float, optional): Distnce to next point if part of polyline.
-            Defaults to None.
-
-    Returns:
-        LocationReference: As defined by sharedStreets.io schema
-    """
-    lr = {
-        "point": LatLongCoordinates(geometry.coords[0]),
-    }
-
-    for arg in ["sequence", "bearing", "distance_to_next_ref"]:
-        if locals()[arg] is not None:
-            lr[arg] = locals()[arg]
-
-    return LocationReference(**lr)
-
    -
    -
    - -
    - -
    - - -

    - location_refs_from_linestring(geometry) - -

    - - -
    - -

    Generates a shared street location reference from linestring.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    geometry - LineString - -
    -

    Shapely LineString instance

    -
    -     		- required -
    - - -

    Returns:

    - - - - - - - - - - - - - -
    Name TypeDescription
    LocationReferences - list[LocationReference] - -
    -

    As defined by sharedStreets.io schema

    -
    -
    - -
    - Source code in network_wrangler/utils/geo.py - 
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    def location_refs_from_linestring(geometry: LineString) -> list[LocationReference]:
-    """Generates a shared street location reference from linestring.
-
-    Args:
-        geometry (LineString): Shapely LineString instance
-
-    Returns:
-        LocationReferences: As defined by sharedStreets.io schema
-    """
-    return [
-        location_ref_from_point(
-            point,
-            sequence=i + 1,
-            distance_to_next_ref=point.distance(geometry.coords[i + 1]),
-            bearing=get_bearing(*point.coords[0], *geometry.coords[i + 1]),
-        )
-        for i, point in enumerate(geometry.coords[:-1])
-    ]
-
    -
    -
    - -
    - -
    - - -

    - offset_geometry_meters(geo_s, offset_distance_meters) - -

    - - -
    - -

    Offset a GeoSeries of LineStrings by a given distance in meters.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    geo_s - GeoSeries - -
    -

    GeoSeries of LineStrings to offset.

    -
    -     		- required -
    offset_distance_meters - float - -
    -

    distance in meters to offset the LineStrings.

    -
    -     		- required -
    - -
    - Source code in network_wrangler/utils/geo.py - 
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    def offset_geometry_meters(geo_s: gpd.GeoSeries, offset_distance_meters: float) -> gpd.GeoSeries:
-    """Offset a GeoSeries of LineStrings by a given distance in meters.
-
-    Args:
-        geo_s: GeoSeries of LineStrings to offset.
-        offset_distance_meters: distance in meters to offset the LineStrings.
-    """
-    if geo_s.empty:
-        return geo_s
-    og_crs = geo_s.crs
-    meters_crs = _id_utm_crs(geo_s)
-    geo_s = geo_s.to_crs(meters_crs)
-    offset_geo = geo_s.apply(lambda x: x.offset_curve(offset_distance_meters))
-    offset_geo = gpd.GeoSeries(offset_geo)
-    return offset_geo.to_crs(og_crs)
-
    -
    -
    - -
    - -
    - - -

    - offset_point_with_distance_and_bearing(lon, lat, distance, bearing) - -

    - - -
    - -

    Get the new lon-lat (in degrees) given current point (lon-lat), distance and bearing.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    lon - float - -
    -

    longitude of original point

    -
    -     		- required -
    lat - float - -
    -

    latitude of original point

    -
    -     		- required -
    distance - float - -
    -

    distance in meters to offset point by

    -
    -     		- required -
    bearing - float - -
    -

    direction to offset point to in radians

    -
    -     		- required -
    - - -
    - Source code in network_wrangler/utils/geo.py - 
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    def offset_point_with_distance_and_bearing(
-    lon: float, lat: float, distance: float, bearing: float
-) -> list[float]:
-    """Get the new lon-lat (in degrees) given current point (lon-lat), distance and bearing.
-
-    Args:
-        lon: longitude of original point
-        lat: latitude of original point
-        distance: distance in meters to offset point by
-        bearing: direction to offset point to in radians
-
-    returns: list of new offset lon-lat
-    """
-    # Earth's radius in meters
-    radius = 6378137
-
-    # convert the lat long from degree to radians
-    lat_radians = math.radians(lat)
-    lon_radians = math.radians(lon)
-
-    # calculate the new lat long in radians
-    out_lat_radians = math.asin(
-        math.sin(lat_radians) * math.cos(distance / radius)
-        + math.cos(lat_radians) * math.sin(distance / radius) * math.cos(bearing)
-    )
-
-    out_lon_radians = lon_radians + math.atan2(
-        math.sin(bearing) * math.sin(distance / radius) * math.cos(lat_radians),
-        math.cos(distance / radius) - math.sin(lat_radians) * math.sin(lat_radians),
-    )
-    # convert the new lat long back to degree
-    out_lat = math.degrees(out_lat_radians)
-    out_lon = math.degrees(out_lon_radians)
-
-    return [out_lon, out_lat]
-
    -
    -
    - -
    - -
    - - -

    - point_from_xy(x, y, xy_crs=LAT_LON_CRS, point_crs=LAT_LON_CRS) - -

    - - -
    - -

    Creates point geometry from x and y coordinates.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    x - -
    -

    x coordinate, in xy_crs

    -
    -     		- required -
    y - -
    -

    y coordinate, in xy_crs

    -
    -     		- required -
    xy_crs - int - -
    -

    coordinate reference system in ESPG code for x/y inputs. Defaults to 4326 (WGS84)

    -
    -     		- LAT_LON_CRS -
    point_crs - int - -
    -

    coordinate reference system in ESPG code for point output. -Defaults to 4326 (WGS84)

    -
    -     		- LAT_LON_CRS -
    - - -
    - Source code in network_wrangler/utils/geo.py - 
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    def point_from_xy(x, y, xy_crs: int = LAT_LON_CRS, point_crs: int = LAT_LON_CRS):
-    """Creates point geometry from x and y coordinates.
-
-    Args:
-        x: x coordinate, in xy_crs
-        y: y coordinate, in xy_crs
-        xy_crs: coordinate reference system in ESPG code for x/y inputs. Defaults to 4326 (WGS84)
-        point_crs: coordinate reference system in ESPG code for point output.
-            Defaults to 4326 (WGS84)
-
-    Returns: Shapely Point in point_crs
-    """
-    point = Point(x, y)
-
-    if xy_crs == point_crs:
-        check_point_valid_for_crs(point, point_crs)
-        return point
-
-    if (xy_crs, point_crs) not in transformers:
-        # store transformers in dictionary because they are an "expensive" operation
-        transformers[(xy_crs, point_crs)] = Transformer.from_proj(
-            Proj(init="epsg:" + str(xy_crs)),
-            Proj(init="epsg:" + str(point_crs)),
-            always_xy=True,  # required b/c Proj v6+ uses lon/lat instead of x/y
-        )
-
-    return transform(transformers[(xy_crs, point_crs)].transform, point)
-
    -
    -
    - -
    - -
    - - -

    - to_points_gdf(table, ref_nodes_df=None, ref_road_net=None) - -

    - - -
    - -

    Convert a table to a GeoDataFrame.

    -

    If the table is already a GeoDataFrame, return it as is. Otherwise, attempt to convert the -table to a GeoDataFrame using the following methods: -1. If the table has a ‘geometry’ column, return a GeoDataFrame using that column. -2. If the table has ‘lat’ and ‘lon’ columns, return a GeoDataFrame using those columns. -3. If the table has a ‘*model_node_id’ or ‘stop_id’ column, return a GeoDataFrame using that column and the - nodes_df provided. -If none of the above, raise a ValueError.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    table - DataFrame - -
    -

    DataFrame to convert to GeoDataFrame.

    -
    -     		- required -
    ref_nodes_df - Optional[GeoDataFrame] - -
    -

    GeoDataFrame of nodes to use to convert model_node_id to geometry.

    -
    -     		- None -
    ref_road_net - Optional[RoadwayNetwork] - -
    -

    RoadwayNetwork object to use to convert model_node_id to geometry.

    -
    -     		- None -
    - - -

    Returns:

    - - - - - - - - - - - - - -
    Name TypeDescription
    GeoDataFrame - GeoDataFrame - -
    -

    GeoDataFrame representation of the table.

    -
    -
    - -
    - Source code in network_wrangler/utils/geo.py - 
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    def to_points_gdf(
-    table: pd.DataFrame,
-    ref_nodes_df: Optional[gpd.GeoDataFrame] = None,
-    ref_road_net: Optional[RoadwayNetwork] = None,
-) -> gpd.GeoDataFrame:
-    """Convert a table to a GeoDataFrame.
-
-    If the table is already a GeoDataFrame, return it as is. Otherwise, attempt to convert the
-    table to a GeoDataFrame using the following methods:
-    1. If the table has a 'geometry' column, return a GeoDataFrame using that column.
-    2. If the table has 'lat' and 'lon' columns, return a GeoDataFrame using those columns.
-    3. If the table has a '*model_node_id' or 'stop_id' column, return a GeoDataFrame using that column and the
-         nodes_df provided.
-    If none of the above, raise a ValueError.
-
-    Args:
-        table: DataFrame to convert to GeoDataFrame.
-        ref_nodes_df: GeoDataFrame of nodes to use to convert model_node_id to geometry.
-        ref_road_net: RoadwayNetwork object to use to convert model_node_id to geometry.
-
-    Returns:
-        GeoDataFrame: GeoDataFrame representation of the table.
-    """
-    if table is gpd.GeoDataFrame:
-        return table
-
-    WranglerLogger.debug("Converting GTFS table to GeoDataFrame")
-    if "geometry" in table.columns:
-        return gpd.GeoDataFrame(table, geometry="geometry")
-
-    lat_cols = list(filter(lambda col: "lat" in col, table.columns))
-    lon_cols = list(filter(lambda col: "lon" in col, table.columns))
-    model_node_id_cols = [
-        c for c in ["model_node_id", "stop_id", "shape_model_node_id"] if c in table.columns
-    ]
-
-    if not (lat_cols and lon_cols) or not model_node_id_cols:
-        WranglerLogger.error(
-            "Needed either lat/long or *model_node_id columns to convert \
-            to GeoDataFrame. Columns found: {table.columns}"
-        )
-        if not (lat_cols and lon_cols):
-            WranglerLogger.error("No lat/long cols found.")
-        if not model_node_id_cols:
-            WranglerLogger.error("No *model_node_id cols found.")
-        msg = "Could not find lat/long, geometry columns or *model_node_id column in \
-                         table necessary to convert to GeoDataFrame"
-        raise ValueError(msg)
-
-    if lat_cols and lon_cols:
-        # using first found lat and lon columns
-        return gpd.GeoDataFrame(
-            table,
-            geometry=gpd.points_from_xy(table[lon_cols[0]], table[lat_cols[0]]),
-            crs="EPSG:4326",
-        )
-
-    if model_node_id_cols:
-        node_id_col = model_node_id_cols[0]
-
-        if ref_nodes_df is None:
-            if ref_road_net is None:
-                msg = "Must provide either nodes_df or road_net to convert \
-                                 model_node_id to geometry"
-                raise ValueError(msg)
-            ref_nodes_df = ref_road_net.nodes_df
-
-        WranglerLogger.debug("Converting table to GeoDataFrame using model_node_id")
-
-        _table = table.merge(
-            ref_nodes_df[["model_node_id", "geometry"]],
-            left_on=node_id_col,
-            right_on="model_node_id",
-        )
-        return gpd.GeoDataFrame(_table, geometry="geometry")
-    msg = "Could not find lat/long, geometry columns or *model_node_id column in table \
-                        necessary to convert to GeoDataFrame"
-    raise ValueError(msg)
-
    -
    -
    - -
    - -
    - - -

    - update_nodes_in_linestring_geometry(original_df, updated_nodes_df, position) - -

    - - -
    - -

    Updates the nodes in a linestring geometry and returns updated geometry.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    original_df - GeoDataFrame - -
    -

    GeoDataFrame with the model_node_id and linestring geometry

    -
    -     		- required -
    updated_nodes_df - GeoDataFrame - -
    -

    GeoDataFrame with updated node geometries.

    -
    -     		- required -
    position - int - -
    -

    position in the linestring to update with the node.

    -
    -     		- required -
    - -
    - Source code in network_wrangler/utils/geo.py - 
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    def update_nodes_in_linestring_geometry(
-    original_df: gpd.GeoDataFrame,
-    updated_nodes_df: gpd.GeoDataFrame,
-    position: int,
-) -> gpd.GeoSeries:
-    """Updates the nodes in a linestring geometry and returns updated geometry.
-
-    Args:
-        original_df: GeoDataFrame with the `model_node_id` and linestring geometry
-        updated_nodes_df: GeoDataFrame with updated node geometries.
-        position: position in the linestring to update with the node.
-    """
-    LINK_FK_NODE = ["A", "B"]
-    original_index = original_df.index
-
-    updated_df = original_df.reset_index().merge(
-        updated_nodes_df[["model_node_id", "geometry"]],
-        left_on=LINK_FK_NODE[position],
-        right_on="model_node_id",
-        suffixes=("", "_node"),
-    )
-
-    updated_df["geometry"] = updated_df.apply(
-        lambda row: update_points_in_linestring(
-            row["geometry"], row["geometry_node"].coords[0], position
-        ),
-        axis=1,
-    )
-
-    updated_df = updated_df.reset_index().set_index(original_index.names)
-
-    WranglerLogger.debug(f"updated_df - AFTER: \n {updated_df.geometry}")
-    return updated_df["geometry"]
-
    -
    -
    - -
    - -
    - - -

    - update_point_geometry(df, ref_point_df, lon_field='X', lat_field='Y', id_field='model_node_id', ref_lon_field='X', ref_lat_field='Y', ref_id_field='model_node_id') - -

    - - -
    - -

    Returns copy of df with lat and long fields updated with geometry from ref_point_df.

    -

    NOTE: does not update “geometry” field if it exists.

    - -
    - Source code in network_wrangler/utils/geo.py - 
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    def update_point_geometry(
-    df: pd.DataFrame,
-    ref_point_df: pd.DataFrame,
-    lon_field: str = "X",
-    lat_field: str = "Y",
-    id_field: str = "model_node_id",
-    ref_lon_field: str = "X",
-    ref_lat_field: str = "Y",
-    ref_id_field: str = "model_node_id",
-) -> pd.DataFrame:
-    """Returns copy of df with lat and long fields updated with geometry from ref_point_df.
-
-    NOTE: does not update "geometry" field if it exists.
-    """
-    df = copy.deepcopy(df)
-
-    ref_df = ref_point_df.rename(
-        columns={
-            ref_lon_field: lon_field,
-            ref_lat_field: lat_field,
-            ref_id_field: id_field,
-        }
-    )
-
-    updated_df = update_df_by_col_value(
-        df,
-        ref_df[[id_field, lon_field, lat_field]],
-        id_field,
-        properties=[lat_field, lon_field],
-        fail_if_missing=False,
-    )
-    return updated_df
-
    -
    -
    - -
    - -
    - - -

    - update_points_in_linestring(linestring, updated_coords, position) - -

    - - -
    - -

    Replaces a point in a linestring with a new point.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    linestring - LineString - -
    -

    original_linestring

    -
    -     		- required -
    updated_coords - List[float] - -
    -

    updated poimt coordinates

    -
    -     		- required -
    position - int - -
    -

    position in the linestring to update

    -
    -     		- required -
    - -
    - Source code in network_wrangler/utils/geo.py - 
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    def update_points_in_linestring(
-    linestring: LineString, updated_coords: list[float], position: int
-):
-    """Replaces a point in a linestring with a new point.
-
-    Args:
-        linestring (LineString): original_linestring
-        updated_coords (List[float]): updated poimt coordinates
-        position (int): position in the linestring to update
-    """
-    coords = [c for c in linestring.coords]
-    coords[position] = updated_coords
-    return LineString(coords)
-
    -
    -
    - -
    - - - -
    - -
    - -
    - -
    - - - - -
    - -

    Dataframe accessors that allow functions to be called directly on the dataframe.

    - - - -
    - - - - - - - - -
    - - - -

    - DictQueryAccessor - - -

    - - -
    - - -

    Query link, node and shape dataframes using project selection dictionary.

    -

    Will overlook any keys which are not columns in the dataframe.

    -

    Usage:

    -
    selection_dict = {
-    "lanes": [1, 2, 3],
-    "name": ["6th", "Sixth", "sixth"],
-    "drive_access": 1,
-}
-selected_links_df = links_df.dict_query(selection_dict)
-
    - -
    - Source code in network_wrangler/utils/df_accessors.py - 
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    @pd.api.extensions.register_dataframe_accessor("dict_query")
-class DictQueryAccessor:
-    """Query link, node and shape dataframes using project selection dictionary.
-
-    Will overlook any keys which are not columns in the dataframe.
-
-    Usage:
-
-    ```
-    selection_dict = {
-        "lanes": [1, 2, 3],
-        "name": ["6th", "Sixth", "sixth"],
-        "drive_access": 1,
-    }
-    selected_links_df = links_df.dict_query(selection_dict)
-    ```
-
-    """
-
-    def __init__(self, pandas_obj):
-        """Initialization function for the dictionary query accessor."""
-        self._obj = pandas_obj
-
-    def __call__(self, selection_dict: dict, return_all_if_none: bool = False):
-        """Queries the dataframe using the selection dictionary.
-
-        Args:
-            selection_dict (dict): _description_
-            return_all_if_none (bool, optional): If True, will return entire df if dict has
-                 no values. Defaults to False.
-        """
-        _not_selection_keys = ["modes", "all", "ignore_missing"]
-        _selection_dict = {
-            k: v
-            for k, v in selection_dict.items()
-            if k not in _not_selection_keys and v is not None
-        }
-        missing_columns = [k for k in _selection_dict if k not in self._obj.columns]
-        if missing_columns:
-            msg = f"Selection fields not found in dataframe: {missing_columns}"
-            raise SelectionError(msg)
-
-        if not _selection_dict:
-            if return_all_if_none:
-                return self._obj
-            msg = f"Relevant part of selection dictionary is empty: {selection_dict}"
-            raise SelectionError(msg)
-
-        _sel_query = dict_to_query(_selection_dict)
-        # WranglerLogger.debug(f"_sel_query: \n   {_sel_query}")
-        _df = self._obj.query(_sel_query, engine="python")
-
-        if len(_df) == 0:
-            WranglerLogger.warning(
-                f"No records found in df \
-                  using selection: {selection_dict}"
-            )
-        return _df
-
    -
    - - - -
    - - - - - - - - - -
    - - -

    - __call__(selection_dict, return_all_if_none=False) - -

    - - -
    - -

    Queries the dataframe using the selection dictionary.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    selection_dict - dict - -
    -

    description

    -
    -     		- required -
    return_all_if_none - bool - -
    -

    If True, will return entire df if dict has - no values. Defaults to False.

    -
    -     		- False -
    - -
    - Source code in network_wrangler/utils/df_accessors.py - 
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    def __call__(self, selection_dict: dict, return_all_if_none: bool = False):
-    """Queries the dataframe using the selection dictionary.
-
-    Args:
-        selection_dict (dict): _description_
-        return_all_if_none (bool, optional): If True, will return entire df if dict has
-             no values. Defaults to False.
-    """
-    _not_selection_keys = ["modes", "all", "ignore_missing"]
-    _selection_dict = {
-        k: v
-        for k, v in selection_dict.items()
-        if k not in _not_selection_keys and v is not None
-    }
-    missing_columns = [k for k in _selection_dict if k not in self._obj.columns]
-    if missing_columns:
-        msg = f"Selection fields not found in dataframe: {missing_columns}"
-        raise SelectionError(msg)
-
-    if not _selection_dict:
-        if return_all_if_none:
-            return self._obj
-        msg = f"Relevant part of selection dictionary is empty: {selection_dict}"
-        raise SelectionError(msg)
-
-    _sel_query = dict_to_query(_selection_dict)
-    # WranglerLogger.debug(f"_sel_query: \n   {_sel_query}")
-    _df = self._obj.query(_sel_query, engine="python")
-
-    if len(_df) == 0:
-        WranglerLogger.warning(
-            f"No records found in df \
-              using selection: {selection_dict}"
-        )
-    return _df
-
    -
    -
    - -
    - -
    - - -

    - __init__(pandas_obj) - -

    - - -
    - -

    Initialization function for the dictionary query accessor.

    - -
    - Source code in network_wrangler/utils/df_accessors.py - 
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    def __init__(self, pandas_obj):
-    """Initialization function for the dictionary query accessor."""
-    self._obj = pandas_obj
-
    -
    -
    - -
    - - - -
    - -
    - -
    - -
    - - - -

    - Isin_dict - - -

    - - -
    - - -

    Faster implimentation of isin for querying dataframes with dictionary.

    - -
    - Source code in network_wrangler/utils/df_accessors.py - 
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    @pd.api.extensions.register_dataframe_accessor("isin_dict")
-class Isin_dict:
-    """Faster implimentation of isin for querying dataframes with dictionary."""
-
-    def __init__(self, pandas_obj):
-        """Initialization function for the dataframe hash."""
-        self._obj = pandas_obj
-
-    def __call__(self, d: dict, **kwargs) -> pd.DataFrame:
-        """Function to perform the faster dictionary isin()."""
-        return isin_dict(self._obj, d, **kwargs)
-
    -
    - - - -
    - - - - - - - - - -
    - - -

    - __call__(d, **kwargs) - -

    - - -
    - -

    Function to perform the faster dictionary isin().

    - -
    - Source code in network_wrangler/utils/df_accessors.py - 
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    def __call__(self, d: dict, **kwargs) -> pd.DataFrame:
-    """Function to perform the faster dictionary isin()."""
-    return isin_dict(self._obj, d, **kwargs)
-
    -
    -
    - -
    - -
    - - -

    - __init__(pandas_obj) - -

    - - -
    - -

    Initialization function for the dataframe hash.

    - -
    - Source code in network_wrangler/utils/df_accessors.py - 
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    def __init__(self, pandas_obj):
-    """Initialization function for the dataframe hash."""
-    self._obj = pandas_obj
-
    -
    -
    - -
    - - - -
    - -
    - -
    - -
    - - - -

    - dfHash - - -

    - - -
    - - -

    Creates a dataframe hash that is compatable with geopandas and various metadata.

    -

    Definitely not the fastest, but she seems to work where others have failed.

    - -
    - Source code in network_wrangler/utils/df_accessors.py - 
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    @pd.api.extensions.register_dataframe_accessor("df_hash")
-class dfHash:
-    """Creates a dataframe hash that is compatable with geopandas and various metadata.
-
-    Definitely not the fastest, but she seems to work where others have failed.
-    """
-
-    def __init__(self, pandas_obj):
-        """Initialization function for the dataframe hash."""
-        self._obj = pandas_obj
-
-    def __call__(self):
-        """Function to hash the dataframe."""
-        _value = str(self._obj.values).encode()
-        hash = hashlib.sha1(_value).hexdigest()
-        return hash
-
    -
    - - - -
    - - - - - - - - - -
    - - -

    - __call__() - -

    - - -
    - -

    Function to hash the dataframe.

    - -
    - Source code in network_wrangler/utils/df_accessors.py - 
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    def __call__(self):
-    """Function to hash the dataframe."""
-    _value = str(self._obj.values).encode()
-    hash = hashlib.sha1(_value).hexdigest()
-    return hash
-
    -
    -
    - -
    - -
    - - -

    - __init__(pandas_obj) - -

    - - -
    - -

    Initialization function for the dataframe hash.

    - -
    - Source code in network_wrangler/utils/df_accessors.py - 
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    def __init__(self, pandas_obj):
-    """Initialization function for the dataframe hash."""
-    self._obj = pandas_obj
-
    -
    -
    - -
    - - - -
    - -
    - -
    - - - - -
    - -
    - -
    - -
    - - - - -
    - -

    Logging utilities for Network Wrangler.

    - - - -
    - - - - - - - - - -
    - - -

    - setup_logging(info_log_filename=None, debug_log_filename=None, std_out_level='info') - -

    - - -
    - -

    Sets up the WranglerLogger w.r.t. the debug file location and if logging to console.

    -

    Called by the test_logging fixture in conftest.py and can be called by the user to setup -logging for their session. If called multiple times, the logger will be reset.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    info_log_filename - Optional[Path] - -
    -

    the location of the log file that will get created to add the INFO log. -The INFO Log is terse, just gives the bare minimum of details. -Defaults to file in cwd() wrangler_[datetime].log. To turn off logging to a file, -use log_filename = None.

    -
    -     		- None -
    debug_log_filename - Optional[Path] - -
    -

    the location of the log file that will get created to add the DEBUG log -The DEBUG log is very noisy, for debugging. Defaults to file in cwd() -wrangler_[datetime].log. To turn off logging to a file, use log_filename = None.

    -
    -     		- None -
    std_out_level - str - -
    -

    the level of logging to the console. One of “info”, “warning”, “debug”. -Defaults to “info” but will be set to ERROR if nothing provided matches.

    -
    -     		- 'info' -
    - -
    - Source code in network_wrangler/logger.py - 
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    def setup_logging(
-    info_log_filename: Optional[Path] = None,
-    debug_log_filename: Optional[Path] = None,
-    std_out_level: str = "info",
-):
-    """Sets up the WranglerLogger w.r.t. the debug file location and if logging to console.
-
-    Called by the test_logging fixture in conftest.py and can be called by the user to setup
-    logging for their session. If called multiple times, the logger will be reset.
-
-    Args:
-        info_log_filename: the location of the log file that will get created to add the INFO log.
-            The INFO Log is terse, just gives the bare minimum of details.
-            Defaults to file in cwd() `wrangler_[datetime].log`. To turn off logging to a file,
-            use log_filename = None.
-        debug_log_filename: the location of the log file that will get created to add the DEBUG log
-            The DEBUG log is very noisy, for debugging. Defaults to file in cwd()
-            `wrangler_[datetime].log`. To turn off logging to a file, use log_filename = None.
-        std_out_level: the level of logging to the console. One of "info", "warning", "debug".
-            Defaults to "info" but will be set to ERROR if nothing provided matches.
-    """
-    # add function variable so that we know if logging has been called
-    setup_logging.called = True
-
-    DEFAULT_LOG_PATH = Path(f"wrangler_{datetime.now().strftime('%Y_%m_%d__%H_%M_%S')}.debug.log")
-    debug_log_filename = debug_log_filename if debug_log_filename else DEFAULT_LOG_PATH
-
-    # Clear handles if any exist already
-    WranglerLogger.handlers = []
-
-    WranglerLogger.setLevel(logging.DEBUG)
-
-    FORMAT = logging.Formatter(
-        "%(asctime)-15s %(levelname)s: %(message)s", datefmt="%Y-%m-%d %H:%M:%S,"
-    )
-    default_info_f = f"network_wrangler_{datetime.now().strftime('%Y_%m_%d__%H_%M_%S')}.info.log"
-    info_log_filename = info_log_filename or Path.cwd() / default_info_f
-
-    info_file_handler = logging.FileHandler(Path(info_log_filename))
-    info_file_handler.setLevel(logging.INFO)
-    info_file_handler.setFormatter(FORMAT)
-    WranglerLogger.addHandler(info_file_handler)
-
-    # create debug file only when debug_log_filename is provided
-    if debug_log_filename:
-        debug_log_handler = logging.FileHandler(Path(debug_log_filename))
-        debug_log_handler.setLevel(logging.DEBUG)
-        debug_log_handler.setFormatter(FORMAT)
-        WranglerLogger.addHandler(debug_log_handler)
-
-    console_handler = logging.StreamHandler(sys.stdout)
-    console_handler.setLevel(logging.DEBUG)
-    console_handler.setFormatter(FORMAT)
-    WranglerLogger.addHandler(console_handler)
-    if std_out_level in ("debug", "info"):
-        console_handler.setLevel(logging.DEBUG)
-    elif std_out_level == "warning":
-        console_handler.setLevel(logging.WARNING)
-    else:
-        console_handler.setLevel(logging.ERROR)
-
    -
    -
    - -
    - - - -
    - -
    - -
    - -
    - - - - -
    - -

    Configuration utilities.

    - - - -
    - - - - - - - - -
    - - - -

    - ConfigItem - - -

    - - -
    - - -

    Base class to add partial dict-like interface to configuration.

    -

    Allow use of .items() [“X”] and .get(“X”) .to_dict() from configuration.

    -

    Not to be constructed directly. To be used a mixin for dataclasses -representing config schema. -Do not use “get” “to_dict”, or “items” for key names.

    - -
    - Source code in network_wrangler/configs/utils.py - 
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    class ConfigItem:
-    """Base class to add partial dict-like interface to  configuration.
-
-    Allow use of .items() ["X"] and .get("X") .to_dict() from configuration.
-
-    Not to be constructed directly. To be used a mixin for dataclasses
-    representing config schema.
-    Do not use "get" "to_dict", or "items" for key names.
-    """
-
-    base_path: Optional[Path] = None
-
-    def __getitem__(self, key):
-        """Return the value for key if key is in the dictionary, else default."""
-        return getattr(self, key)
-
-    def items(self):
-        """A set-like object providing a view on D's items."""
-        return self.__dict__.items()
-
-    def to_dict(self):
-        """Convert the configuration to a dictionary."""
-        result = {}
-        for key, value in self.__dict__.items():
-            if isinstance(value, ConfigItem):
-                result[key] = value.to_dict()
-            else:
-                result[key] = value
-        return result
-
-    def get(self, key, default=None):
-        """Return the value for key if key is in the dictionary, else default."""
-        return self.__dict__.get(key, default)
-
-    def update(self, data: Union[Path, list[Path], dict]):
-        """Update the configuration with a dictionary of new values."""
-        if not isinstance(data, dict):
-            WranglerLogger.info(f"Updating configuration with {data}.")
-            data = load_merge_dict(data)
-
-        self.__dict__.update(data)
-        return self
-
-    def resolve_paths(self, base_path):
-        """Resolve relative paths in the configuration."""
-        base_path = Path(base_path)
-        for key, value in self.__dict__.items():
-            if isinstance(value, ConfigItem):
-                value.resolve_paths(base_path)
-            elif isinstance(value, str) and value.startswith("."):
-                resolved_path = (base_path / value).resolve()
-                setattr(self, key, str(resolved_path))
-
    -
    - - - -
    - - - - - - - - - -
    - - -

    - __getitem__(key) - -

    - - -
    - -

    Return the value for key if key is in the dictionary, else default.

    - -
    - Source code in network_wrangler/configs/utils.py - 
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    def __getitem__(self, key):
-    """Return the value for key if key is in the dictionary, else default."""
-    return getattr(self, key)
-
    -
    -
    - -
    - -
    - - -

    - get(key, default=None) - -

    - - -
    - -

    Return the value for key if key is in the dictionary, else default.

    - -
    - Source code in network_wrangler/configs/utils.py - 
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    def get(self, key, default=None):
-    """Return the value for key if key is in the dictionary, else default."""
-    return self.__dict__.get(key, default)
-
    -
    -
    - -
    - -
    - - -

    - items() - -

    - - -
    - -

    A set-like object providing a view on D’s items.

    - -
    - Source code in network_wrangler/configs/utils.py - 
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-31
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    def items(self):
-    """A set-like object providing a view on D's items."""
-    return self.__dict__.items()
-
    -
    -
    - -
    - -
    - - -

    - resolve_paths(base_path) - -

    - - -
    - -

    Resolve relative paths in the configuration.

    - -
    - Source code in network_wrangler/configs/utils.py - 
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    def resolve_paths(self, base_path):
-    """Resolve relative paths in the configuration."""
-    base_path = Path(base_path)
-    for key, value in self.__dict__.items():
-        if isinstance(value, ConfigItem):
-            value.resolve_paths(base_path)
-        elif isinstance(value, str) and value.startswith("."):
-            resolved_path = (base_path / value).resolve()
-            setattr(self, key, str(resolved_path))
-
    -
    -
    - -
    - -
    - - -

    - to_dict() - -

    - - -
    - -

    Convert the configuration to a dictionary.

    - -
    - Source code in network_wrangler/configs/utils.py - 
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    def to_dict(self):
-    """Convert the configuration to a dictionary."""
-    result = {}
-    for key, value in self.__dict__.items():
-        if isinstance(value, ConfigItem):
-            result[key] = value.to_dict()
-        else:
-            result[key] = value
-    return result
-
    -
    -
    - -
    - -
    - - -

    - update(data) - -

    - - -
    - -

    Update the configuration with a dictionary of new values.

    - -
    - Source code in network_wrangler/configs/utils.py - 
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    def update(self, data: Union[Path, list[Path], dict]):
-    """Update the configuration with a dictionary of new values."""
-    if not isinstance(data, dict):
-        WranglerLogger.info(f"Updating configuration with {data}.")
-        data = load_merge_dict(data)
-
-    self.__dict__.update(data)
-    return self
-
    -
    -
    - -
    - - - -
    - -
    - -
    - - -
    - - -

    - find_configs_in_dir(dir, config_type) - -

    - - -
    - -

    Find configuration files in the directory that match *config<ext>.

    - -
    - Source code in network_wrangler/configs/utils.py - 
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    def find_configs_in_dir(dir: Union[Path, list[Path]], config_type) -> list[Path]:
-    """Find configuration files in the directory that match `*config<ext>`."""
-    config_files: list[Path] = []
-    if isinstance(dir, list):
-        for d in dir:
-            config_files.extend(find_configs_in_dir(d, config_type))
-    elif dir.is_dir():
-        dir = Path(dir)
-        for ext in SUPPORTED_CONFIG_EXTENSIONS:
-            config_like_files = list(dir.glob(f"*config{ext}"))
-            config_files.extend(find_configs_in_dir(config_like_files, config_type))
-    elif dir.is_file():
-        try:
-            config_type(load_dict(dir))
-        except ValidationError:
-            return config_files
-        config_files.append(dir)
-
-    if config_files:
-        return [Path(config_file) for config_file in config_files]
-    return []
-
    -
    -
    - -
    - - - -
    - -
    - -
    - -
    - - - - -
    - -

    Module for time and timespan objects.

    - - - -
    - - - - - - - - -
    - - - -

    - Time - - -

    - - -
    - - -

    Represents a time object.

    -

    This class provides methods to initialize and manipulate time objects.

    - - -

    Attributes:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescription
    datetime - datetime - -
    -

    The underlying datetime object representing the time.

    -
    -
    time_str - str - -
    -

    The time string representation in HH:MM:SS format.

    -
    -
    time_sec - int - -
    -

    The time in seconds since midnight.

    -
    -
    _raw_time_in - TimeType - -
    -

    The raw input value used to initialize the Time object.

    -
    -
    - -
    - Source code in network_wrangler/time.py - 
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    class Time:
-    """Represents a time object.
-
-    This class provides methods to initialize and manipulate time objects.
-
-    Attributes:
-        datetime (datetime): The underlying datetime object representing the time.
-        time_str (str): The time string representation in HH:MM:SS format.
-        time_sec (int): The time in seconds since midnight.
-
-        _raw_time_in (TimeType): The raw input value used to initialize the Time object.
-
-    """
-
-    def __init__(self, value: TimeType):
-        """Initializes a Time object.
-
-        Args:
-            value (TimeType): A time object, string in HH:MM[:SS] format, or seconds since
-                midnight.
-
-        Raises:
-            TimeFormatError: If the value is not a valid time format.
-
-        """
-        if isinstance(value, datetime):
-            self.datetime: datetime = value
-        elif isinstance(value, time):
-            self.datetime = datetime.combine(datetime.today(), value)
-        elif isinstance(value, str):
-            self.datetime = str_to_time(value)
-        elif isinstance(value, int):
-            self.datetime = datetime.datetime.fromtimestamp(value).time()
-        else:
-            msg = "time must be a string, int, or time object"
-            raise TimeFormatError(msg)
-
-        self._raw_time_in = value
-
-    def __getitem__(self, item: Any) -> str:
-        """Get the time string representation.
-
-        Args:
-            item (Any): Not used.
-
-        Returns:
-            str: The time string representation in HH:MM:SS format.
-        """
-        return self.time_str
-
-    @property
-    def time_str(self):
-        """Get the time string representation.
-
-        Returns:
-            str: The time string representation in HH:MM:SS format.
-        """
-        return self.datetime.strftime("%H:%M:%S")
-
-    @property
-    def time_sec(self):
-        """Get the time in seconds since midnight.
-
-        Returns:
-            int: The time in seconds since midnight.
-        """
-        return self.datetime.hour * 3600 + self.datetime.minute * 60 + self.datetime.second
-
-    def __str__(self) -> str:
-        """Get the string representation of the Time object.
-
-        Returns:
-            str: The time string representation in HH:MM:SS format.
-        """
-        return self.time_str
-
-    def __hash__(self) -> int:
-        """Get the hash value of the Time object.
-
-        Returns:
-            int: The hash value of the Time object.
-        """
-        return hash(str(self))
-
    -
    - - - -
    - - - - - - - -
    - - - -

    - time_sec - - - property - - -

    - - -
    - -

    Get the time in seconds since midnight.

    - - -

    Returns:

    - - - - - - - - - - - - - -
    Name TypeDescription
    int - -
    -

    The time in seconds since midnight.

    -
    -
    -
    - -
    - -
    - - - -

    - time_str - - - property - - -

    - - -
    - -

    Get the time string representation.

    - - -

    Returns:

    - - - - - - - - - - - - - -
    Name TypeDescription
    str - -
    -

    The time string representation in HH:MM:SS format.

    -
    -
    -
    - -
    - - - -
    - - -

    - __getitem__(item) - -

    - - -
    - -

    Get the time string representation.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    item - Any - -
    -

    Not used.

    -
    -     		- required -
    - - -

    Returns:

    - - - - - - - - - - - - - -
    Name TypeDescription
    str - str - -
    -

    The time string representation in HH:MM:SS format.

    -
    -
    - -
    - Source code in network_wrangler/time.py - 
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    def __getitem__(self, item: Any) -> str:
-    """Get the time string representation.
-
-    Args:
-        item (Any): Not used.
-
-    Returns:
-        str: The time string representation in HH:MM:SS format.
-    """
-    return self.time_str
-
    -
    -
    - -
    - -
    - - -

    - __hash__() - -

    - - -
    - -

    Get the hash value of the Time object.

    - - -

    Returns:

    - - - - - - - - - - - - - -
    Name TypeDescription
    int - int - -
    -

    The hash value of the Time object.

    -
    -
    - -
    - Source code in network_wrangler/time.py - 
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    def __hash__(self) -> int:
-    """Get the hash value of the Time object.
-
-    Returns:
-        int: The hash value of the Time object.
-    """
-    return hash(str(self))
-
    -
    -
    - -
    - -
    - - -

    - __init__(value) - -

    - - -
    - -

    Initializes a Time object.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    value - TimeType - -
    -

    A time object, string in HH:MM[:SS] format, or seconds since -midnight.

    -
    -     		- required -
    - - -

    Raises:

    - - - - - - - - - - - - - -
    TypeDescription
    - TimeFormatError - -
    -

    If the value is not a valid time format.

    -
    -
    - -
    - Source code in network_wrangler/time.py - 
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    def __init__(self, value: TimeType):
-    """Initializes a Time object.
-
-    Args:
-        value (TimeType): A time object, string in HH:MM[:SS] format, or seconds since
-            midnight.
-
-    Raises:
-        TimeFormatError: If the value is not a valid time format.
-
-    """
-    if isinstance(value, datetime):
-        self.datetime: datetime = value
-    elif isinstance(value, time):
-        self.datetime = datetime.combine(datetime.today(), value)
-    elif isinstance(value, str):
-        self.datetime = str_to_time(value)
-    elif isinstance(value, int):
-        self.datetime = datetime.datetime.fromtimestamp(value).time()
-    else:
-        msg = "time must be a string, int, or time object"
-        raise TimeFormatError(msg)
-
-    self._raw_time_in = value
-
    -
    -
    - -
    - -
    - - -

    - __str__() - -

    - - -
    - -

    Get the string representation of the Time object.

    - - -

    Returns:

    - - - - - - - - - - - - - -
    Name TypeDescription
    str - str - -
    -

    The time string representation in HH:MM:SS format.

    -
    -
    - -
    - Source code in network_wrangler/time.py - 
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    def __str__(self) -> str:
-    """Get the string representation of the Time object.
-
-    Returns:
-        str: The time string representation in HH:MM:SS format.
-    """
-    return self.time_str
-
    -
    -
    - -
    - - - -
    - -
    - -
    - -
    - - - -

    - Timespan - - -

    - - -
    - - -

    Timespan object.

    -

    This class provides methods to initialize and manipulate time objects.

    -

    If the end_time is less than the start_time, the duration will assume that it crosses - over midnight.

    - - -

    Attributes:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescription
    start_time - time - -
    -

    The start time of the timespan.

    -
    -
    end_time - time - -
    -

    The end time of the timespan.

    -
    -
    timespan_str_list - str - -
    -

    A list of start time and end time in HH:MM:SS format.

    -
    -
    start_time_sec - int - -
    -

    The start time in seconds since midnight.

    -
    -
    end_time_sec - int - -
    -

    The end time in seconds since midnight.

    -
    -
    duration - timedelta - -
    -

    The duration of the timespan.

    -
    -
    duration_sec - int - -
    -

    The duration of the timespan in seconds.

    -
    -
    _raw_timespan_in - Any - -
    -

    The raw input value used to initialize the Timespan object.

    -
    -
    - -
    - Source code in network_wrangler/time.py - 
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    class Timespan:
-    """Timespan object.
-
-    This class provides methods to initialize and manipulate time objects.
-
-    If the end_time is less than the start_time, the duration will assume that it crosses
-        over midnight.
-
-    Attributes:
-        start_time (datetime.time): The start time of the timespan.
-        end_time (datetime.time): The end time of the timespan.
-        timespan_str_list (str): A list of start time and end time in HH:MM:SS format.
-        start_time_sec (int): The start time in seconds since midnight.
-        end_time_sec (int): The end time in seconds since midnight.
-        duration (datetime.timedelta): The duration of the timespan.
-        duration_sec (int): The duration of the timespan in seconds.
-
-        _raw_timespan_in (Any): The raw input value used to initialize the Timespan object.
-
-    """
-
-    def __init__(self, value: list[TimeType]):
-        """Constructor for the Timespan object.
-
-        If the value is a list of two time strings, datetime objects, Time, or seconds from
-        midnight, the start_time and end_time attributes will be set accordingly.
-
-        Args:
-            value (time): a list of two time strings, datetime objects, Time, or seconds from
-              midnight.
-        """
-        if len(value) != 2:  # noqa: PLR2004
-            msg = "timespan must be a list of 2 time strings, datetime objs, Time, or sec from midnight."
-            raise TimespanFormatError(msg)
-
-        self.start_time, self.end_time = (Time(t) for t in value)
-        self._raw_timespan_in = value
-
-    @property
-    def timespan_str_list(self):
-        """Get the timespan string representation."""
-        return [self.start_time.time_str, self.end_time.time_str]
-
-    @property
-    def start_time_sec(self):
-        """Start time in seconds since midnight."""
-        return self.start_time.time_sec
-
-    @property
-    def end_time_sec(self):
-        """End time in seconds since midnight."""
-        return self.end_time.time_sec
-
-    @property
-    def duration(self):
-        """Duration of timespan as a timedelta object."""
-        return duration_dt(self.start_time, self.end_time)
-
-    @property
-    def duration_sec(self):
-        """Duration of timespan in seconds.
-
-        If end_time is less than start_time, the duration will assume that it crosses over
-        midnight.
-        """
-        if self.end_time_sec < self.start_time_sec:
-            return (24 * 3600) - self.start_time_sec + self.end_time_sec
-        return self.end_time_sec - self.start_time_sec
-
-    def __str__(self) -> str:
-        """String representation of the Timespan object."""
-        return str(self.timespan_str)
-
-    def __hash__(self) -> int:
-        """Hash value of the Timespan object."""
-        return hash(str(self))
-
-    def overlaps(self, other: Timespan) -> bool:
-        """Check if two timespans overlap.
-
-        If the start time is greater than the end time, the timespan is assumed to cross over
-        midnight.
-
-        Args:
-            other (Timespan): The other timespan to compare.
-
-        Returns:
-            bool: True if the two timespans overlap, False otherwise.
-        """
-        real_end_time = self.end_time.datetime
-        if self.end_time.datetime > self.start_time.datetime:
-            real_end_time = self.end_time.datetime + datetime.timedelta(days=1)
-
-        real_other_end_time = other.end_time.datetime
-        if other.end_time.datetime > other.start_time.datetime:
-            real_other_end_time = other.end_time.datetime + datetime.timedelta(days=1)
-        return (
-            self.start_time.datetime <= real_other_end_time
-            and real_end_time >= other.start_time.datetime
-        )
-
    -
    - - - -
    - - - - - - - -
    - - - -

    - duration - - - property - - -

    - - -
    - -

    Duration of timespan as a timedelta object.

    -
    - -
    - -
    - - - -

    - duration_sec - - - property - - -

    - - -
    - -

    Duration of timespan in seconds.

    -

    If end_time is less than start_time, the duration will assume that it crosses over -midnight.

    -
    - -
    - -
    - - - -

    - end_time_sec - - - property - - -

    - - -
    - -

    End time in seconds since midnight.

    -
    - -
    - -
    - - - -

    - start_time_sec - - - property - - -

    - - -
    - -

    Start time in seconds since midnight.

    -
    - -
    - -
    - - - -

    - timespan_str_list - - - property - - -

    - - -
    - -

    Get the timespan string representation.

    -
    - -
    - - - -
    - - -

    - __hash__() - -

    - - -
    - -

    Hash value of the Timespan object.

    - -
    - Source code in network_wrangler/time.py - 
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    def __hash__(self) -> int:
-    """Hash value of the Timespan object."""
-    return hash(str(self))
-
    -
    -
    - -
    - -
    - - -

    - __init__(value) - -

    - - -
    - -

    Constructor for the Timespan object.

    -

    If the value is a list of two time strings, datetime objects, Time, or seconds from -midnight, the start_time and end_time attributes will be set accordingly.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    value - time - -
    -

    a list of two time strings, datetime objects, Time, or seconds from -midnight.

    -
    -     		- required -
    - -
    - Source code in network_wrangler/time.py - 
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    def __init__(self, value: list[TimeType]):
-    """Constructor for the Timespan object.
-
-    If the value is a list of two time strings, datetime objects, Time, or seconds from
-    midnight, the start_time and end_time attributes will be set accordingly.
-
-    Args:
-        value (time): a list of two time strings, datetime objects, Time, or seconds from
-          midnight.
-    """
-    if len(value) != 2:  # noqa: PLR2004
-        msg = "timespan must be a list of 2 time strings, datetime objs, Time, or sec from midnight."
-        raise TimespanFormatError(msg)
-
-    self.start_time, self.end_time = (Time(t) for t in value)
-    self._raw_timespan_in = value
-
    -
    -
    - -
    - -
    - - -

    - __str__() - -

    - - -
    - -

    String representation of the Timespan object.

    - -
    - Source code in network_wrangler/time.py - 
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    def __str__(self) -> str:
-    """String representation of the Timespan object."""
-    return str(self.timespan_str)
-
    -
    -
    - -
    - -
    - - -

    - overlaps(other) - -

    - - -
    - -

    Check if two timespans overlap.

    -

    If the start time is greater than the end time, the timespan is assumed to cross over -midnight.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    other - Timespan - -
    -

    The other timespan to compare.

    -
    -     		- required -
    - - -

    Returns:

    - - - - - - - - - - - - - -
    Name TypeDescription
    bool - bool - -
    -

    True if the two timespans overlap, False otherwise.

    -
    -
    - -
    - Source code in network_wrangler/time.py - 
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    def overlaps(self, other: Timespan) -> bool:
-    """Check if two timespans overlap.
-
-    If the start time is greater than the end time, the timespan is assumed to cross over
-    midnight.
-
-    Args:
-        other (Timespan): The other timespan to compare.
-
-    Returns:
-        bool: True if the two timespans overlap, False otherwise.
-    """
-    real_end_time = self.end_time.datetime
-    if self.end_time.datetime > self.start_time.datetime:
-        real_end_time = self.end_time.datetime + datetime.timedelta(days=1)
-
-    real_other_end_time = other.end_time.datetime
-    if other.end_time.datetime > other.start_time.datetime:
-        real_other_end_time = other.end_time.datetime + datetime.timedelta(days=1)
-    return (
-        self.start_time.datetime <= real_other_end_time
-        and real_end_time >= other.start_time.datetime
-    )
-
    -
    -
    - -
    - - - -
    - -
    - -
    - - - - -
    - -
    - -
    - -
    - - - - -
    - -

    Module for visualizing roadway and transit networks using Mapbox tiles.

    -

    This module provides a function net_to_mapbox that creates and serves Mapbox tiles on a local web server based on roadway and transit networks.

    - - -
    - Example usage -

    net_to_mapbox(roadway, transit)

    -
    - - -
    - - - - - - - - -
    - - - -

    - MissingMapboxTokenError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Raised when MAPBOX_ACCESS_TOKEN is not found in environment variables.

    - -
    - Source code in network_wrangler/viz.py - 
    20
-21
    class MissingMapboxTokenError(Exception):
-    """Raised when MAPBOX_ACCESS_TOKEN is not found in environment variables."""
-
    -
    - -
    - -
    - - -
    - - -

    - net_to_mapbox(roadway=None, transit=None, roadway_geojson_out=Path('roadway_shapes.geojson'), transit_geojson_out=Path('transit_shapes.geojson'), mbtiles_out=Path('network.mbtiles'), overwrite=True, port='9000') - -

    - - -
    - -

    Creates and serves mapbox tiles on local web server based on roadway and transit networks.

    - - -

    Parameters:

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    NameTypeDescriptionDefault
    roadway - Optional[Union[RoadwayNetwork, GeoDataFrame, str, Path]] - -
    -

    a RoadwayNetwork instance, geodataframe with roadway linetrings, or path to a -geojson file. Defaults to empty GeoDataFrame.

    -
    -     		- None -
    transit - Optional[Union[TransitNetwork, GeoDataFrame]] - -
    -

    a TransitNetwork instance or a geodataframe with roadway linetrings, or path to a -geojson file. Defaults to empty GeoDataFrame.

    -
    -     		- None -
    roadway_geojson_out - Path - -
    -

    file path for roadway geojson which gets created if roadway is not -a path to a geojson file. Defaults to roadway_shapes.geojson.

    -
    -     		- Path('roadway_shapes.geojson') -
    transit_geojson_out - Path - -
    -

    file path for transit geojson which gets created if transit is not -a path to a geojson file. Defaults to transit_shapes.geojson.

    -
    -     		- Path('transit_shapes.geojson') -
    mbtiles_out - Path - -
    -

    path to output mapbox tiles. Defaults to network.mbtiles

    -
    -     		- Path('network.mbtiles') -
    overwrite - bool - -
    -

    boolean indicating if can overwrite mbtiles_out and roadway_geojson_out and -transit_geojson_out. Defaults to True.

    -
    -     		- True -
    port - str - -
    -

    port to serve resulting tiles on. Defaults to 9000.

    -
    -     		- '9000' -
    - -
    - Source code in network_wrangler/viz.py - 
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    def net_to_mapbox(
-    roadway: Optional[Union[RoadwayNetwork, gpd.GeoDataFrame, str, Path]] = None,
-    transit: Optional[Union[TransitNetwork, gpd.GeoDataFrame]] = None,
-    roadway_geojson_out: Path = Path("roadway_shapes.geojson"),
-    transit_geojson_out: Path = Path("transit_shapes.geojson"),
-    mbtiles_out: Path = Path("network.mbtiles"),
-    overwrite: bool = True,
-    port: str = "9000",
-):
-    """Creates and serves mapbox tiles on local web server based on roadway and transit networks.
-
-    Args:
-        roadway: a RoadwayNetwork instance, geodataframe with roadway linetrings, or path to a
-            geojson file. Defaults to empty GeoDataFrame.
-        transit: a TransitNetwork instance or a geodataframe with roadway linetrings, or path to a
-            geojson file. Defaults to empty GeoDataFrame.
-        roadway_geojson_out: file path for roadway geojson which gets created if roadway is not
-            a path to a geojson file. Defaults to roadway_shapes.geojson.
-        transit_geojson_out: file path for transit geojson which gets created if transit is not
-            a path to a geojson file. Defaults to transit_shapes.geojson.
-        mbtiles_out: path to output mapbox tiles. Defaults to network.mbtiles
-        overwrite: boolean indicating if can overwrite mbtiles_out and roadway_geojson_out and
-            transit_geojson_out. Defaults to True.
-        port: port to serve resulting tiles on. Defaults to 9000.
-    """
-    import subprocess
-
-    if roadway is None:
-        roadway = gpd.GeoDataFrame()
-    if transit is None:
-        transit = gpd.GeoDataFrame()
-    # test for mapbox token
-    try:
-        os.getenv("MAPBOX_ACCESS_TOKEN")
-    except Exception as err:
-        WranglerLogger.error(
-            "NEED TO SET MAPBOX ACCESS TOKEN IN ENVIRONMENT VARIABLES/n \
-                In command line: >>export MAPBOX_ACCESS_TOKEN='pk.0000.1111' # \
-                replace value with your mapbox public access token"
-        )
-        raise MissingMapboxTokenError() from err
-
-    if isinstance(transit, TransitNetwork):
-        transit = transit.shape_links_gdf
-        transit.to_file(transit_geojson_out, driver="GeoJSON")
-    elif Path(transit).exists():
-        transit_geojson_out = transit
-    else:
-        msg = f"Don't understand transit input: {transit}"
-        raise ValueError(msg)
-
-    if isinstance(roadway, RoadwayNetwork):
-        roadway = roadway.link_shapes_df
-        roadway.to_file(roadway_geojson_out, driver="GeoJSON")
-    elif Path(roadway).exists():
-        roadway_geojson_out = Path(roadway)
-    else:
-        msg = "Don't understand roadway input: {roadway}"
-        raise ValueError(msg)
-
-    tippe_options_list: list[str] = ["-zg", "-o", str(mbtiles_out)]
-    if overwrite:
-        tippe_options_list.append("--force")
-    # tippe_options_list.append("--drop-densest-as-needed")
-    tippe_options_list.append(str(roadway_geojson_out))
-    tippe_options_list.append(str(transit_geojson_out))
-
-    try:
-        WranglerLogger.info(
-            f"Running tippecanoe with following options: {' '.join(tippe_options_list)}"
-        )
-        subprocess.run(["tippecanoe", *tippe_options_list], check=False)
-    except Exception as err:
-        WranglerLogger.error(
-            "If tippecanoe isn't installed, try `brew install tippecanoe` or \
-                visit https://github.com/mapbox/tippecanoe"
-        )
-        raise ImportError() from err
-
-    try:
-        WranglerLogger.info(
-            "Running mbview with following options: {}".format(" ".join(tippe_options_list))
-        )
-        subprocess.run(["mbview", "--port", port, f", /{mbtiles_out}"], check=False)
-    except Exception as err:
-        WranglerLogger.error(
-            "If mbview isn't installed, try `npm install -g @mapbox/mbview` or \
-                visit https://github.com/mapbox/mbview"
-        )
-        raise ImportError(msg) from err
-
    -
    -
    - -
    - - - -
    - -
    - -
    - -
    - - - - -
    - -

    All network wrangler errors.

    - - - -
    - - - - - - - - -
    - - - -

    - DataframeSelectionError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Raised when there is an issue with a selection from a dataframe.

    - -
    - Source code in network_wrangler/errors.py - 
    120
-121
    class DataframeSelectionError(Exception):
-    """Raised when there is an issue with a selection from a dataframe."""
-
    -
    - -
    - -
    - -
    - - - -

    - FeedReadError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Raised when there is an error reading a transit feed.

    - -
    - Source code in network_wrangler/errors.py - 
    4
-5
    class FeedReadError(Exception):
-    """Raised when there is an error reading a transit feed."""
-
    -
    - -
    - -
    - -
    - - - -

    - FeedValidationError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Raised when there is an issue with the validation of the GTFS data.

    - -
    - Source code in network_wrangler/errors.py - 
    8
-9
    class FeedValidationError(Exception):
-    """Raised when there is an issue with the validation of the GTFS data."""
-
    -
    - -
    - -
    - -
    - - - -

    - InvalidScopedLinkValue - - -

    - - -
    -

    - Bases: Exception

    - - -

    Raised when there is an issue with a scoped link value.

    - -
    - Source code in network_wrangler/errors.py - 
    12
-13
    class InvalidScopedLinkValue(Exception):
-    """Raised when there is an issue with a scoped link value."""
-
    -
    - -
    - -
    - -
    - - - -

    - LinkAddError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Raised when there is an issue with adding links.

    - -
    - Source code in network_wrangler/errors.py - 
    16
-17
    class LinkAddError(Exception):
-    """Raised when there is an issue with adding links."""
-
    -
    - -
    - -
    - -
    - - - -

    - LinkChangeError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Raised when there is an error in changing a link property.

    - -
    - Source code in network_wrangler/errors.py - 
    20
-21
    class LinkChangeError(Exception):
-    """Raised when there is an error in changing a link property."""
-
    -
    - -
    - -
    - -
    - - - -

    - LinkCreationError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Raised when there is an issue with creating links.

    - -
    - Source code in network_wrangler/errors.py - 
    24
-25
    class LinkCreationError(Exception):
-    """Raised when there is an issue with creating links."""
-
    -
    - -
    - -
    - -
    - - - -

    - LinkDeletionError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Raised when there is an issue with deleting links.

    - -
    - Source code in network_wrangler/errors.py - 
    28
-29
    class LinkDeletionError(Exception):
-    """Raised when there is an issue with deleting links."""
-
    -
    - -
    - -
    - -
    - - - -

    - LinkNotFoundError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Raised when a link is not found in the links table.

    - -
    - Source code in network_wrangler/errors.py - 
    32
-33
    class LinkNotFoundError(Exception):
-    """Raised when a link is not found in the links table."""
-
    -
    - -
    - -
    - -
    - - - -

    - ManagedLaneAccessEgressError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Raised when there is an issue with access/egress points to managed lanes.

    - -
    - Source code in network_wrangler/errors.py - 
    36
-37
    class ManagedLaneAccessEgressError(Exception):
-    """Raised when there is an issue with access/egress points to managed lanes."""
-
    -
    - -
    - -
    - -
    - - - -

    - MissingNodesError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Raised when referenced nodes are missing from the network.

    - -
    - Source code in network_wrangler/errors.py - 
    40
-41
    class MissingNodesError(Exception):
-    """Raised when referenced nodes are missing from the network."""
-
    -
    - -
    - -
    - -
    - - - -

    - NewRoadwayError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Raised when there is an issue with applying a new roadway.

    - -
    - Source code in network_wrangler/errors.py - 
    44
-45
    class NewRoadwayError(Exception):
-    """Raised when there is an issue with applying a new roadway."""
-
    -
    - -
    - -
    - -
    - - - -

    - NodeAddError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Raised when there is an issue with adding nodes.

    - -
    - Source code in network_wrangler/errors.py - 
    48
-49
    class NodeAddError(Exception):
-    """Raised when there is an issue with adding nodes."""
-
    -
    - -
    - -
    - -
    - - - -

    - NodeChangeError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Raised when there is an issue with applying a node change.

    - -
    - Source code in network_wrangler/errors.py - 
    52
-53
    class NodeChangeError(Exception):
-    """Raised when there is an issue with applying a node change."""
-
    -
    - -
    - -
    - -
    - - - -

    - NodeDeletionError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Raised when there is an issue with deleting nodes.

    - -
    - Source code in network_wrangler/errors.py - 
    56
-57
    class NodeDeletionError(Exception):
-    """Raised when there is an issue with deleting nodes."""
-
    -
    - -
    - -
    - -
    - - - -

    - NodeNotFoundError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Raised when a node is not found in the nodes table.

    - -
    - Source code in network_wrangler/errors.py - 
    64
-65
    class NodeNotFoundError(Exception):
-    """Raised when a node is not found in the nodes table."""
-
    -
    - -
    - -
    - -
    - - - -

    - NodesInLinksMissingError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Raised when there is an issue with validating links and nodes.

    - -
    - Source code in network_wrangler/errors.py - 
    60
-61
    class NodesInLinksMissingError(Exception):
-    """Raised when there is an issue with validating links and nodes."""
-
    -
    - -
    - -
    - -
    - - - -

    - NotLinksError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Raised when a dataframe is not a RoadLinksTable.

    - -
    - Source code in network_wrangler/errors.py - 
    68
-69
    class NotLinksError(Exception):
-    """Raised when a dataframe is not a RoadLinksTable."""
-
    -
    - -
    - -
    - -
    - - - -

    - NotNodesError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Raised when a dataframe is not a RoadNodesTable.

    - -
    - Source code in network_wrangler/errors.py - 
    72
-73
    class NotNodesError(Exception):
-    """Raised when a dataframe is not a RoadNodesTable."""
-
    -
    - -
    - -
    - -
    - - - -

    - ProjectCardError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Raised when a project card is not valid.

    - -
    - Source code in network_wrangler/errors.py - 
    76
-77
    class ProjectCardError(Exception):
-    """Raised when a project card is not valid."""
-
    -
    - -
    - -
    - -
    - - - -

    - RoadwayDeletionError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Raised when there is an issue with applying a roadway deletion.

    - -
    - Source code in network_wrangler/errors.py - 
    80
-81
    class RoadwayDeletionError(Exception):
-    """Raised when there is an issue with applying a roadway deletion."""
-
    -
    - -
    - -
    - -
    - - - -

    - RoadwayPropertyChangeError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Raised when there is an issue with applying a roadway property change.

    - -
    - Source code in network_wrangler/errors.py - 
    84
-85
    class RoadwayPropertyChangeError(Exception):
-    """Raised when there is an issue with applying a roadway property change."""
-
    -
    - -
    - -
    - -
    - - - -

    - ScenarioConflictError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Raised when a conflict is detected.

    - -
    - Source code in network_wrangler/errors.py - 
    88
-89
    class ScenarioConflictError(Exception):
-    """Raised when a conflict is detected."""
-
    -
    - -
    - -
    - -
    - - - -

    - ScenarioCorequisiteError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Raised when a co-requisite is not satisfied.

    - -
    - Source code in network_wrangler/errors.py - 
    92
-93
    class ScenarioCorequisiteError(Exception):
-    """Raised when a co-requisite is not satisfied."""
-
    -
    - -
    - -
    - -
    - - - -

    - ScenarioPrerequisiteError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Raised when a pre-requisite is not satisfied.

    - -
    - Source code in network_wrangler/errors.py - 
    96
-97
    class ScenarioPrerequisiteError(Exception):
-    """Raised when a pre-requisite is not satisfied."""
-
    -
    - -
    - -
    - -
    - - - -

    - ScopeConflictError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Raised when there is a scope conflict in a list of ScopedPropertySetItems.

    - -
    - Source code in network_wrangler/errors.py - 
    100
-101
    class ScopeConflictError(Exception):
-    """Raised when there is a scope conflict in a list of ScopedPropertySetItems."""
-
    -
    - -
    - -
    - -
    - - - -

    - ScopeLinkValueError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Raised when there is an issue with ScopedLinkValueList.

    - -
    - Source code in network_wrangler/errors.py - 
    104
-105
    class ScopeLinkValueError(Exception):
-    """Raised when there is an issue with ScopedLinkValueList."""
-
    -
    - -
    - -
    - -
    - - - -

    - SegmentFormatError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Error in segment format.

    - -
    - Source code in network_wrangler/errors.py - 
    108
-109
    class SegmentFormatError(Exception):
-    """Error in segment format."""
-
    -
    - -
    - -
    - -
    - - - -

    - SegmentSelectionError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Error in segment selection.

    - -
    - Source code in network_wrangler/errors.py - 
    112
-113
    class SegmentSelectionError(Exception):
-    """Error in segment selection."""
-
    -
    - -
    - -
    - -
    - - - -

    - SelectionError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Raised when there is an issue with a selection.

    - -
    - Source code in network_wrangler/errors.py - 
    116
-117
    class SelectionError(Exception):
-    """Raised when there is an issue with a selection."""
-
    -
    - -
    - -
    - -
    - - - -

    - ShapeAddError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Raised when there is an issue with adding shapes.

    - -
    - Source code in network_wrangler/errors.py - 
    124
-125
    class ShapeAddError(Exception):
-    """Raised when there is an issue with adding shapes."""
-
    -
    - -
    - -
    - -
    - - - -

    - ShapeDeletionError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Raised when there is an issue with deleting shapes from a network.

    - -
    - Source code in network_wrangler/errors.py - 
    128
-129
    class ShapeDeletionError(Exception):
-    """Raised when there is an issue with deleting shapes from a network."""
-
    -
    - -
    - -
    - -
    - - - -

    - SubnetCreationError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Raised when a subnet can’t be created.

    - -
    - Source code in network_wrangler/errors.py - 
    136
-137
    class SubnetCreationError(Exception):
-    """Raised when a subnet can't be created."""
-
    -
    - -
    - -
    - -
    - - - -

    - SubnetExpansionError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Raised when a subnet can’t be expanded to include a node or set of nodes.

    - -
    - Source code in network_wrangler/errors.py - 
    132
-133
    class SubnetExpansionError(Exception):
-    """Raised when a subnet can't be expanded to include a node or set of nodes."""
-
    -
    - -
    - -
    - -
    - - - -

    - TimeFormatError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Time format error exception.

    - -
    - Source code in network_wrangler/errors.py - 
    140
-141
    class TimeFormatError(Exception):
-    """Time format error exception."""
-
    -
    - -
    - -
    - -
    - - - -

    - TimespanFormatError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Timespan format error exception.

    - -
    - Source code in network_wrangler/errors.py - 
    144
-145
    class TimespanFormatError(Exception):
-    """Timespan format error exception."""
-
    -
    - -
    - -
    - -
    - - - -

    - TransitPropertyChangeError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Error raised when applying transit property changes.

    - -
    - Source code in network_wrangler/errors.py - 
    148
-149
    class TransitPropertyChangeError(Exception):
-    """Error raised when applying transit property changes."""
-
    -
    - -
    - -
    - -
    - - - -

    - TransitRoadwayConsistencyError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Error raised when transit network is inconsistent with roadway network.

    - -
    - Source code in network_wrangler/errors.py - 
    172
-173
    class TransitRoadwayConsistencyError(Exception):
-    """Error raised when transit network is inconsistent with roadway network."""
-
    -
    - -
    - -
    - -
    - - - -

    - TransitRouteAddError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Error raised when applying add transit route.

    - -
    - Source code in network_wrangler/errors.py - 
    152
-153
    class TransitRouteAddError(Exception):
-    """Error raised when applying add transit route."""
-
    -
    - -
    - -
    - -
    - - - -

    - TransitRoutingChangeError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Raised when there is an error in the transit routing change.

    - -
    - Source code in network_wrangler/errors.py - 
    156
-157
    class TransitRoutingChangeError(Exception):
-    """Raised when there is an error in the transit routing change."""
-
    -
    - -
    - -
    - -
    - - - -

    - TransitSelectionEmptyError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Error for when no transit trips are selected.

    - -
    - Source code in network_wrangler/errors.py - 
    164
-165
    class TransitSelectionEmptyError(Exception):
-    """Error for when no transit trips are selected."""
-
    -
    - -
    - -
    - -
    - - - -

    - TransitSelectionError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Base error for transit selection errors.

    - -
    - Source code in network_wrangler/errors.py - 
    160
-161
    class TransitSelectionError(Exception):
-    """Base error for transit selection errors."""
-
    -
    - -
    - -
    - -
    - - - -

    - TransitSelectionNetworkConsistencyError - - -

    - - -
    -

    - Bases: TransitSelectionError

    - - -

    Error for when transit selection dictionary is not consistent with transit network.

    - -
    - Source code in network_wrangler/errors.py - 
    168
-169
    class TransitSelectionNetworkConsistencyError(TransitSelectionError):
-    """Error for when transit selection dictionary is not consistent with transit network."""
-
    -
    - -
    - -
    - -
    - - - -

    - TransitValidationError - - -

    - - -
    -

    - Bases: Exception

    - - -

    Error raised when transit network doesn’t have expected values.

    - -
    - Source code in network_wrangler/errors.py - 
    176
-177
    class TransitValidationError(Exception):
-    """Error raised when transit network doesn't have expected values."""
-
    -
    - -
    - -
    - - - - -
    - -
    - -
    - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    -
    -
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circle{fill:var(--md-mermaid-label-bg-color)}.actor{fill:var(--md-mermaid-sequence-actor-bg-color);stroke:var(--md-mermaid-sequence-actor-border-color)}text.actor>tspan{fill:var(--md-mermaid-sequence-actor-fg-color);font-family:var(--md-mermaid-font-family)}line{stroke:var(--md-mermaid-sequence-actor-line-color)}.actor-man circle,.actor-man line{fill:var(--md-mermaid-sequence-actorman-bg-color);stroke:var(--md-mermaid-sequence-actorman-line-color)}.messageLine0,.messageLine1{stroke:var(--md-mermaid-sequence-message-line-color)}.note{fill:var(--md-mermaid-sequence-note-bg-color);stroke:var(--md-mermaid-sequence-note-border-color)}.loopText,.loopText>tspan,.messageText,.noteText>tspan{stroke:none;font-family:var(--md-mermaid-font-family)!important}.messageText{fill:var(--md-mermaid-sequence-message-fg-color)}.loopText,.loopText>tspan{fill:var(--md-mermaid-sequence-loop-fg-color)}.noteText>tspan{fill:var(--md-mermaid-sequence-note-fg-color)}#arrowhead 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I(...e).pipe(oe(o=>d(o,"change").pipe(m(()=>o))),Q(e[r]),m(o=>({index:e.indexOf(o),color:{media:o.getAttribute("data-md-color-media"),scheme:o.getAttribute("data-md-color-scheme"),primary:o.getAttribute("data-md-color-primary"),accent:o.getAttribute("data-md-color-accent")}})),B(1))}function Kn(e){let t=$("input",e),r=E("meta",{name:"theme-color"});document.head.appendChild(r);let o=E("meta",{name:"color-scheme"});document.head.appendChild(o);let n=$t("(prefers-color-scheme: light)");return C(()=>{let i=new g;return i.subscribe(a=>{if(document.body.setAttribute("data-md-color-switching",""),a.color.media==="(prefers-color-scheme)"){let s=matchMedia("(prefers-color-scheme: light)"),p=document.querySelector(s.matches?"[data-md-color-media='(prefers-color-scheme: light)']":"[data-md-color-media='(prefers-color-scheme: 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Gr=Vt(Yr());function Ga(e){e.setAttribute("data-md-copying","");let t=e.closest("[data-copy]"),r=t?t.getAttribute("data-copy"):e.innerText;return e.removeAttribute("data-md-copying"),r.trimEnd()}function Bn({alert$:e}){Gr.default.isSupported()&&new F(t=>{new Gr.default("[data-clipboard-target], [data-clipboard-text]",{text:r=>r.getAttribute("data-clipboard-text")||Ga(P(r.getAttribute("data-clipboard-target")))}).on("success",r=>t.next(r))}).pipe(y(t=>{t.trigger.focus()}),m(()=>ye("clipboard.copied"))).subscribe(e)}function Gn(e,t){return e.protocol=t.protocol,e.hostname=t.hostname,e}function Ja(e,t){let r=new Map;for(let o of $("url",e)){let n=P("loc",o),i=[Gn(new URL(n.textContent),t)];r.set(`${i[0]}`,i);for(let a of $("[rel=alternate]",o)){let s=a.getAttribute("href");s!=null&&i.push(Gn(new URL(s),t))}}return r}function ur(e){return mn(new URL("sitemap.xml",e)).pipe(m(t=>Ja(t,new URL(e))),ve(()=>I(new Map)))}function Xa(e,t){if(!(e.target instanceof Element))return M;let 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g,o=r.pipe(X(),ne(!0));z([t.pipe(Ae(It)),r],(i,a)=>a).pipe(Z("value")).subscribe(({value:i})=>t.next({type:2,data:i})),r.pipe(Z("focus")).subscribe(({focus:i})=>{i&&Je("search",i)}),d(e.form,"reset").pipe(U(o)).subscribe(()=>e.focus());let n=P("header [for=__search]");return d(n,"click").subscribe(()=>e.focus()),ns(e,{worker$:t}).pipe(y(i=>r.next(i)),L(()=>r.complete()),m(i=>R({ref:e},i)),B(1))}function si(e,{worker$:t,query$:r}){let o=new g,n=tn(e.parentElement).pipe(b(Boolean)),i=e.parentElement,a=P(":scope > :first-child",e),s=P(":scope > :last-child",e);Ve("search").subscribe(l=>s.setAttribute("role",l?"list":"presentation")),o.pipe(ee(r),Ur(t.pipe(Ae(It)))).subscribe(([{items:l},{value:f}])=>{switch(l.length){case 0:a.textContent=f.length?ye("search.result.none"):ye("search.result.placeholder");break;case 1:a.textContent=ye("search.result.one");break;default:let u=sr(l.length);a.textContent=ye("search.result.other",u)}});let p=o.pipe(y(()=>s.innerHTML=""),v(({items:l})=>S(I(...l.slice(0,10)),I(...l.slice(10)).pipe(Ye(4),Vr(n),v(([f])=>f)))),m(Tn),pe());return p.subscribe(l=>s.appendChild(l)),p.pipe(oe(l=>{let f=fe("details",l);return typeof f=="undefined"?M:d(f,"toggle").pipe(U(o),m(()=>f))})).subscribe(l=>{l.open===!1&&l.offsetTop<=i.scrollTop&&i.scrollTo({top:l.offsetTop})}),t.pipe(b(dr),m(({data:l})=>l)).pipe(y(l=>o.next(l)),L(()=>o.complete()),m(l=>R({ref:e},l)))}function is(e,{query$:t}){return t.pipe(m(({value:r})=>{let o=xe();return o.hash="",r=r.replace(/\s+/g,"+").replace(/&/g,"%26").replace(/=/g,"%3D"),o.search=`q=${r}`,{url:o}}))}function ci(e,t){let r=new g,o=r.pipe(X(),ne(!0));return r.subscribe(({url:n})=>{e.setAttribute("data-clipboard-text",e.href),e.href=`${n}`}),d(e,"click").pipe(U(o)).subscribe(n=>n.preventDefault()),is(e,t).pipe(y(n=>r.next(n)),L(()=>r.complete()),m(n=>R({ref:e},n)))}function pi(e,{worker$:t,keyboard$:r}){let o=new g,n=Se("search-query"),i=S(d(n,"keydown"),d(n,"focus")).pipe(be(se),m(()=>n.value),K());return o.pipe(We(i),m(([{suggest:s},p])=>{let c=p.split(/([\s-]+)/);if(s!=null&&s.length&&c[c.length-1]){let l=s[s.length-1];l.startsWith(c[c.length-1])&&(c[c.length-1]=l)}else c.length=0;return c})).subscribe(s=>e.innerHTML=s.join("").replace(/\s/g," ")),r.pipe(b(({mode:s})=>s==="search")).subscribe(s=>{switch(s.type){case"ArrowRight":e.innerText.length&&n.selectionStart===n.value.length&&(n.value=e.innerText);break}}),t.pipe(b(dr),m(({data:s})=>s)).pipe(y(s=>o.next(s)),L(()=>o.complete()),m(()=>({ref:e})))}function li(e,{index$:t,keyboard$:r}){let o=Te();try{let n=ni(o.search,t),i=Se("search-query",e),a=Se("search-result",e);d(e,"click").pipe(b(({target:p})=>p instanceof Element&&!!p.closest("a"))).subscribe(()=>Je("search",!1)),r.pipe(b(({mode:p})=>p==="search")).subscribe(p=>{let c=Re();switch(p.type){case"Enter":if(c===i){let l=new Map;for(let f of $(":first-child [href]",a)){let 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z([t,r.pipe(Q(xe()),b(o=>!!o.searchParams.get("h")))]).pipe(m(([o,n])=>oi(o.config)(n.searchParams.get("h"))),m(o=>{var a;let n=new Map,i=document.createNodeIterator(e,NodeFilter.SHOW_TEXT);for(let s=i.nextNode();s;s=i.nextNode())if((a=s.parentElement)!=null&&a.offsetHeight){let p=s.textContent,c=o(p);c.length>p.length&&n.set(s,c)}for(let[s,p]of n){let{childNodes:c}=E("span",null,p);s.replaceWith(...Array.from(c))}return{ref:e,nodes:n}}))}function as(e,{viewport$:t,main$:r}){let o=e.closest(".md-grid"),n=o.offsetTop-o.parentElement.offsetTop;return z([r,t]).pipe(m(([{offset:i,height:a},{offset:{y:s}}])=>(a=a+Math.min(n,Math.max(0,s-i))-n,{height:a,locked:s>=i+n})),K((i,a)=>i.height===a.height&&i.locked===a.locked))}function Jr(e,o){var n=o,{header$:t}=n,r=io(n,["header$"]);let i=P(".md-sidebar__scrollwrap",e),{y:a}=Ue(i);return C(()=>{let s=new g,p=s.pipe(X(),ne(!0)),c=s.pipe(Le(0,me));return c.pipe(ee(t)).subscribe({next([{height:l},{height:f}]){i.style.height=`${l-2*a}px`,e.style.top=`${f}px`},complete(){i.style.height="",e.style.top=""}}),c.pipe(Ae()).subscribe(()=>{for(let l of $(".md-nav__link--active[href]",e)){if(!l.clientHeight)continue;let f=l.closest(".md-sidebar__scrollwrap");if(typeof f!="undefined"){let u=l.offsetTop-f.offsetTop,{height:h}=ce(f);f.scrollTo({top:u-h/2})}}}),ue($("label[tabindex]",e)).pipe(oe(l=>d(l,"click").pipe(be(se),m(()=>l),U(p)))).subscribe(l=>{let f=P(`[id="${l.htmlFor}"]`);P(`[aria-labelledby="${l.id}"]`).setAttribute("aria-expanded",`${f.checked}`)}),as(e,r).pipe(y(l=>s.next(l)),L(()=>s.complete()),m(l=>R({ref:e},l)))})}function fi(e,t){if(typeof t!="undefined"){let r=`https://api.github.com/repos/${e}/${t}`;return Ct(Ne(`${r}/releases/latest`).pipe(ve(()=>M),m(o=>({version:o.tag_name})),Be({})),Ne(r).pipe(ve(()=>M),m(o=>({stars:o.stargazers_count,forks:o.forks_count})),Be({}))).pipe(m(([o,n])=>R(R({},o),n)))}else{let 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"src/templates/assets/javascripts/patches/scrollfix/index.ts", "src/templates/assets/javascripts/patches/scrolllock/index.ts", "src/templates/assets/javascripts/polyfills/index.ts"], - "sourcesContent": ["(function (global, factory) {\n typeof exports === 'object' && typeof module !== 'undefined' ? factory() :\n typeof define === 'function' && define.amd ? define(factory) :\n (factory());\n}(this, (function () { 'use strict';\n\n /**\n * Applies the :focus-visible polyfill at the given scope.\n * A scope in this case is either the top-level Document or a Shadow Root.\n *\n * @param {(Document|ShadowRoot)} scope\n * @see https://github.com/WICG/focus-visible\n */\n function applyFocusVisiblePolyfill(scope) {\n var hadKeyboardEvent = true;\n var hadFocusVisibleRecently = false;\n var hadFocusVisibleRecentlyTimeout = null;\n\n var inputTypesAllowlist = {\n text: true,\n search: true,\n url: true,\n tel: true,\n email: true,\n password: true,\n number: true,\n date: true,\n month: true,\n week: true,\n time: true,\n datetime: true,\n 'datetime-local': true\n };\n\n /**\n * Helper function for legacy browsers and iframes which sometimes focus\n * elements like document, body, and non-interactive SVG.\n * @param {Element} el\n */\n function isValidFocusTarget(el) {\n if (\n el &&\n el !== document &&\n el.nodeName !== 'HTML' &&\n el.nodeName !== 'BODY' &&\n 'classList' in el &&\n 'contains' in el.classList\n ) {\n return true;\n }\n return false;\n }\n\n /**\n * Computes whether the given element should automatically trigger the\n * `focus-visible` class being added, i.e. whether it should always match\n * `:focus-visible` when focused.\n * @param {Element} el\n * @return {boolean}\n */\n function focusTriggersKeyboardModality(el) {\n var type = el.type;\n var tagName = el.tagName;\n\n if (tagName === 'INPUT' && inputTypesAllowlist[type] && !el.readOnly) {\n return true;\n }\n\n if (tagName === 'TEXTAREA' && !el.readOnly) {\n return true;\n }\n\n if (el.isContentEditable) {\n return true;\n }\n\n return false;\n }\n\n /**\n * Add the `focus-visible` class to the given element if it was not added by\n * the author.\n * @param {Element} el\n */\n function addFocusVisibleClass(el) {\n if (el.classList.contains('focus-visible')) {\n return;\n }\n el.classList.add('focus-visible');\n el.setAttribute('data-focus-visible-added', '');\n }\n\n /**\n * Remove the `focus-visible` class from the given element if it was not\n * originally added by the author.\n * @param {Element} el\n */\n function removeFocusVisibleClass(el) {\n if (!el.hasAttribute('data-focus-visible-added')) {\n return;\n }\n el.classList.remove('focus-visible');\n el.removeAttribute('data-focus-visible-added');\n }\n\n /**\n * If the most recent user interaction was via the keyboard;\n * and the key press did not include a meta, alt/option, or control key;\n * then the modality is keyboard. Otherwise, the modality is not keyboard.\n * Apply `focus-visible` to any current active element and keep track\n * of our keyboard modality state with `hadKeyboardEvent`.\n * @param {KeyboardEvent} e\n */\n function onKeyDown(e) {\n if (e.metaKey || e.altKey || e.ctrlKey) {\n return;\n }\n\n if (isValidFocusTarget(scope.activeElement)) {\n addFocusVisibleClass(scope.activeElement);\n }\n\n hadKeyboardEvent = true;\n }\n\n /**\n * If at any point a user clicks with a pointing device, ensure that we change\n * the modality away from keyboard.\n * This avoids the situation where a user presses a key on an already focused\n * element, and then clicks on a different element, focusing it with a\n * pointing device, while we still think we're in keyboard modality.\n * @param {Event} e\n */\n function onPointerDown(e) {\n hadKeyboardEvent = false;\n }\n\n /**\n * On `focus`, add the `focus-visible` class to the target if:\n * - the target received focus as a result of keyboard navigation, or\n * - the event target is an element that will likely require interaction\n * via the keyboard (e.g. a text box)\n * @param {Event} e\n */\n function onFocus(e) {\n // Prevent IE from focusing the document or HTML element.\n if (!isValidFocusTarget(e.target)) {\n return;\n }\n\n if (hadKeyboardEvent || focusTriggersKeyboardModality(e.target)) {\n addFocusVisibleClass(e.target);\n }\n }\n\n /**\n * On `blur`, remove the `focus-visible` class from the target.\n * @param {Event} e\n */\n function onBlur(e) {\n if (!isValidFocusTarget(e.target)) {\n return;\n }\n\n if (\n e.target.classList.contains('focus-visible') ||\n e.target.hasAttribute('data-focus-visible-added')\n ) {\n // To detect a tab/window switch, we look for a blur event followed\n // rapidly by a visibility change.\n // If we don't see a visibility change within 100ms, it's probably a\n // regular focus change.\n hadFocusVisibleRecently = true;\n window.clearTimeout(hadFocusVisibleRecentlyTimeout);\n hadFocusVisibleRecentlyTimeout = window.setTimeout(function() {\n hadFocusVisibleRecently = false;\n }, 100);\n removeFocusVisibleClass(e.target);\n }\n }\n\n /**\n * If the user changes tabs, keep track of whether or not the previously\n * focused element had .focus-visible.\n * @param {Event} e\n */\n function onVisibilityChange(e) {\n if (document.visibilityState === 'hidden') {\n // If the tab becomes active again, the browser will handle calling focus\n // on the element (Safari actually calls it twice).\n // If this tab change caused a blur on an element with focus-visible,\n // re-apply the class when the user switches back to the tab.\n if (hadFocusVisibleRecently) {\n hadKeyboardEvent = true;\n }\n addInitialPointerMoveListeners();\n }\n }\n\n /**\n * Add a group of listeners to detect usage of any pointing devices.\n * These listeners will be added when the polyfill first loads, and anytime\n * the window is blurred, so that they are active when the window regains\n * focus.\n */\n function addInitialPointerMoveListeners() {\n document.addEventListener('mousemove', onInitialPointerMove);\n document.addEventListener('mousedown', onInitialPointerMove);\n document.addEventListener('mouseup', onInitialPointerMove);\n document.addEventListener('pointermove', onInitialPointerMove);\n document.addEventListener('pointerdown', onInitialPointerMove);\n document.addEventListener('pointerup', onInitialPointerMove);\n document.addEventListener('touchmove', onInitialPointerMove);\n document.addEventListener('touchstart', onInitialPointerMove);\n document.addEventListener('touchend', onInitialPointerMove);\n }\n\n function removeInitialPointerMoveListeners() {\n document.removeEventListener('mousemove', onInitialPointerMove);\n document.removeEventListener('mousedown', onInitialPointerMove);\n document.removeEventListener('mouseup', onInitialPointerMove);\n document.removeEventListener('pointermove', onInitialPointerMove);\n document.removeEventListener('pointerdown', onInitialPointerMove);\n document.removeEventListener('pointerup', onInitialPointerMove);\n document.removeEventListener('touchmove', onInitialPointerMove);\n document.removeEventListener('touchstart', onInitialPointerMove);\n document.removeEventListener('touchend', onInitialPointerMove);\n }\n\n /**\n * When the polfyill first loads, assume the user is in keyboard modality.\n * If any event is received from a pointing device (e.g. mouse, pointer,\n * touch), turn off keyboard modality.\n * This accounts for situations where focus enters the page from the URL bar.\n * @param {Event} e\n */\n function onInitialPointerMove(e) {\n // Work around a Safari quirk that fires a mousemove on whenever the\n // window blurs, even if you're tabbing out of the page. \u00AF\\_(\u30C4)_/\u00AF\n if (e.target.nodeName && e.target.nodeName.toLowerCase() === 'html') {\n return;\n }\n\n hadKeyboardEvent = false;\n removeInitialPointerMoveListeners();\n }\n\n // For some kinds of state, we are interested in changes at the global scope\n // only. For example, global pointer input, global key presses and global\n // visibility change should affect the state at every scope:\n document.addEventListener('keydown', onKeyDown, true);\n document.addEventListener('mousedown', onPointerDown, true);\n document.addEventListener('pointerdown', onPointerDown, true);\n document.addEventListener('touchstart', onPointerDown, true);\n document.addEventListener('visibilitychange', onVisibilityChange, true);\n\n addInitialPointerMoveListeners();\n\n // For focus and blur, we specifically care about state changes in the local\n // scope. This is because focus / blur events that originate from within a\n // shadow root are not re-dispatched from the host element if it was already\n // the active element in its own scope:\n scope.addEventListener('focus', onFocus, true);\n scope.addEventListener('blur', onBlur, true);\n\n // We detect that a node is a ShadowRoot by ensuring that it is a\n // DocumentFragment and also has a host property. This check covers native\n // implementation and polyfill implementation transparently. If we only cared\n // about the native implementation, we could just check if the scope was\n // an instance of a ShadowRoot.\n if (scope.nodeType === Node.DOCUMENT_FRAGMENT_NODE && scope.host) {\n // Since a ShadowRoot is a special kind of DocumentFragment, it does not\n // have a root element to add a class to. So, we add this attribute to the\n // host element instead:\n scope.host.setAttribute('data-js-focus-visible', '');\n } else if (scope.nodeType === Node.DOCUMENT_NODE) {\n document.documentElement.classList.add('js-focus-visible');\n document.documentElement.setAttribute('data-js-focus-visible', '');\n }\n }\n\n // It is important to wrap all references to global window and document in\n // these checks to support server-side rendering use cases\n // @see https://github.com/WICG/focus-visible/issues/199\n if (typeof window !== 'undefined' && typeof document !== 'undefined') {\n // Make the polyfill helper globally available. This can be used as a signal\n // to interested libraries that wish to coordinate with the polyfill for e.g.,\n // applying the polyfill to a shadow root:\n window.applyFocusVisiblePolyfill = applyFocusVisiblePolyfill;\n\n // Notify interested libraries of the polyfill's presence, in case the\n // polyfill was loaded lazily:\n var event;\n\n try {\n event = new CustomEvent('focus-visible-polyfill-ready');\n } catch (error) {\n // IE11 does not support using CustomEvent as a constructor directly:\n event = document.createEvent('CustomEvent');\n event.initCustomEvent('focus-visible-polyfill-ready', false, false, {});\n }\n\n window.dispatchEvent(event);\n }\n\n if (typeof document !== 'undefined') {\n // Apply the polyfill to the global document, so that no JavaScript\n // coordination is required to use the polyfill in the top-level document:\n applyFocusVisiblePolyfill(document);\n }\n\n})));\n", "/*!\n * clipboard.js v2.0.11\n * https://clipboardjs.com/\n *\n * Licensed MIT \u00A9 Zeno Rocha\n */\n(function webpackUniversalModuleDefinition(root, factory) {\n\tif(typeof exports === 'object' && typeof module === 'object')\n\t\tmodule.exports = factory();\n\telse if(typeof define === 'function' && define.amd)\n\t\tdefine([], factory);\n\telse if(typeof exports === 'object')\n\t\texports[\"ClipboardJS\"] = factory();\n\telse\n\t\troot[\"ClipboardJS\"] = factory();\n})(this, function() {\nreturn /******/ (function() { // webpackBootstrap\n/******/ \tvar __webpack_modules__ = ({\n\n/***/ 686:\n/***/ (function(__unused_webpack_module, __webpack_exports__, __webpack_require__) {\n\n\"use strict\";\n\n// EXPORTS\n__webpack_require__.d(__webpack_exports__, {\n \"default\": function() { return /* binding */ clipboard; }\n});\n\n// EXTERNAL MODULE: ./node_modules/tiny-emitter/index.js\nvar tiny_emitter = __webpack_require__(279);\nvar tiny_emitter_default = /*#__PURE__*/__webpack_require__.n(tiny_emitter);\n// EXTERNAL MODULE: ./node_modules/good-listener/src/listen.js\nvar listen = __webpack_require__(370);\nvar listen_default = /*#__PURE__*/__webpack_require__.n(listen);\n// EXTERNAL MODULE: ./node_modules/select/src/select.js\nvar src_select = __webpack_require__(817);\nvar select_default = /*#__PURE__*/__webpack_require__.n(src_select);\n;// CONCATENATED MODULE: ./src/common/command.js\n/**\n * Executes a given operation type.\n * @param {String} type\n * @return {Boolean}\n */\nfunction command(type) {\n try {\n return document.execCommand(type);\n } catch (err) {\n return false;\n }\n}\n;// CONCATENATED MODULE: ./src/actions/cut.js\n\n\n/**\n * Cut action wrapper.\n * @param {String|HTMLElement} target\n * @return {String}\n */\n\nvar ClipboardActionCut = function ClipboardActionCut(target) {\n var selectedText = select_default()(target);\n command('cut');\n return selectedText;\n};\n\n/* harmony default export */ var actions_cut = (ClipboardActionCut);\n;// CONCATENATED MODULE: ./src/common/create-fake-element.js\n/**\n * Creates a fake textarea element with a value.\n * @param {String} value\n * @return {HTMLElement}\n */\nfunction createFakeElement(value) {\n var isRTL = document.documentElement.getAttribute('dir') === 'rtl';\n var fakeElement = document.createElement('textarea'); // Prevent zooming on iOS\n\n fakeElement.style.fontSize = '12pt'; // Reset box model\n\n fakeElement.style.border = '0';\n fakeElement.style.padding = '0';\n fakeElement.style.margin = '0'; // Move element out of screen horizontally\n\n fakeElement.style.position = 'absolute';\n fakeElement.style[isRTL ? 'right' : 'left'] = '-9999px'; // Move element to the same position vertically\n\n var yPosition = window.pageYOffset || document.documentElement.scrollTop;\n fakeElement.style.top = \"\".concat(yPosition, \"px\");\n fakeElement.setAttribute('readonly', '');\n fakeElement.value = value;\n return fakeElement;\n}\n;// CONCATENATED MODULE: ./src/actions/copy.js\n\n\n\n/**\n * Create fake copy action wrapper using a fake element.\n * @param {String} target\n * @param {Object} options\n * @return {String}\n */\n\nvar fakeCopyAction = function fakeCopyAction(value, options) {\n var fakeElement = createFakeElement(value);\n options.container.appendChild(fakeElement);\n var selectedText = select_default()(fakeElement);\n command('copy');\n fakeElement.remove();\n return selectedText;\n};\n/**\n * Copy action wrapper.\n * @param {String|HTMLElement} target\n * @param {Object} options\n * @return {String}\n */\n\n\nvar ClipboardActionCopy = function ClipboardActionCopy(target) {\n var options = arguments.length > 1 && arguments[1] !== undefined ? arguments[1] : {\n container: document.body\n };\n var selectedText = '';\n\n if (typeof target === 'string') {\n selectedText = fakeCopyAction(target, options);\n } else if (target instanceof HTMLInputElement && !['text', 'search', 'url', 'tel', 'password'].includes(target === null || target === void 0 ? void 0 : target.type)) {\n // If input type doesn't support `setSelectionRange`. Simulate it. https://developer.mozilla.org/en-US/docs/Web/API/HTMLInputElement/setSelectionRange\n selectedText = fakeCopyAction(target.value, options);\n } else {\n selectedText = select_default()(target);\n command('copy');\n }\n\n return selectedText;\n};\n\n/* harmony default export */ var actions_copy = (ClipboardActionCopy);\n;// CONCATENATED MODULE: ./src/actions/default.js\nfunction _typeof(obj) { \"@babel/helpers - typeof\"; if (typeof Symbol === \"function\" && typeof Symbol.iterator === \"symbol\") { _typeof = function _typeof(obj) { return typeof obj; }; } else { _typeof = function _typeof(obj) { return obj && typeof Symbol === \"function\" && obj.constructor === Symbol && obj !== Symbol.prototype ? \"symbol\" : typeof obj; }; } return _typeof(obj); }\n\n\n\n/**\n * Inner function which performs selection from either `text` or `target`\n * properties and then executes copy or cut operations.\n * @param {Object} options\n */\n\nvar ClipboardActionDefault = function ClipboardActionDefault() {\n var options = arguments.length > 0 && arguments[0] !== undefined ? arguments[0] : {};\n // Defines base properties passed from constructor.\n var _options$action = options.action,\n action = _options$action === void 0 ? 'copy' : _options$action,\n container = options.container,\n target = options.target,\n text = options.text; // Sets the `action` to be performed which can be either 'copy' or 'cut'.\n\n if (action !== 'copy' && action !== 'cut') {\n throw new Error('Invalid \"action\" value, use either \"copy\" or \"cut\"');\n } // Sets the `target` property using an element that will be have its content copied.\n\n\n if (target !== undefined) {\n if (target && _typeof(target) === 'object' && target.nodeType === 1) {\n if (action === 'copy' && target.hasAttribute('disabled')) {\n throw new Error('Invalid \"target\" attribute. Please use \"readonly\" instead of \"disabled\" attribute');\n }\n\n if (action === 'cut' && (target.hasAttribute('readonly') || target.hasAttribute('disabled'))) {\n throw new Error('Invalid \"target\" attribute. You can\\'t cut text from elements with \"readonly\" or \"disabled\" attributes');\n }\n } else {\n throw new Error('Invalid \"target\" value, use a valid Element');\n }\n } // Define selection strategy based on `text` property.\n\n\n if (text) {\n return actions_copy(text, {\n container: container\n });\n } // Defines which selection strategy based on `target` property.\n\n\n if (target) {\n return action === 'cut' ? actions_cut(target) : actions_copy(target, {\n container: container\n });\n }\n};\n\n/* harmony default export */ var actions_default = (ClipboardActionDefault);\n;// CONCATENATED MODULE: ./src/clipboard.js\nfunction clipboard_typeof(obj) { \"@babel/helpers - typeof\"; if (typeof Symbol === \"function\" && typeof Symbol.iterator === \"symbol\") { clipboard_typeof = function _typeof(obj) { return typeof obj; }; } else { clipboard_typeof = function _typeof(obj) { return obj && typeof Symbol === \"function\" && obj.constructor === Symbol && obj !== Symbol.prototype ? \"symbol\" : typeof obj; }; } return clipboard_typeof(obj); }\n\nfunction _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError(\"Cannot call a class as a function\"); } }\n\nfunction _defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if (\"value\" in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } }\n\nfunction _createClass(Constructor, protoProps, staticProps) { if (protoProps) _defineProperties(Constructor.prototype, protoProps); if (staticProps) _defineProperties(Constructor, staticProps); return Constructor; }\n\nfunction _inherits(subClass, superClass) { if (typeof superClass !== \"function\" && superClass !== null) { throw new TypeError(\"Super expression must either be null or a function\"); } subClass.prototype = Object.create(superClass && superClass.prototype, { constructor: { value: subClass, writable: true, configurable: true } }); if (superClass) _setPrototypeOf(subClass, superClass); }\n\nfunction _setPrototypeOf(o, p) { _setPrototypeOf = Object.setPrototypeOf || function _setPrototypeOf(o, p) { o.__proto__ = p; return o; }; return _setPrototypeOf(o, p); }\n\nfunction _createSuper(Derived) { var hasNativeReflectConstruct = _isNativeReflectConstruct(); return function _createSuperInternal() { var Super = _getPrototypeOf(Derived), result; if (hasNativeReflectConstruct) { var NewTarget = _getPrototypeOf(this).constructor; result = Reflect.construct(Super, arguments, NewTarget); } else { result = Super.apply(this, arguments); } return _possibleConstructorReturn(this, result); }; }\n\nfunction _possibleConstructorReturn(self, call) { if (call && (clipboard_typeof(call) === \"object\" || typeof call === \"function\")) { return call; } return _assertThisInitialized(self); }\n\nfunction _assertThisInitialized(self) { if (self === void 0) { throw new ReferenceError(\"this hasn't been initialised - super() hasn't been called\"); } return self; }\n\nfunction _isNativeReflectConstruct() { if (typeof Reflect === \"undefined\" || !Reflect.construct) return false; if (Reflect.construct.sham) return false; if (typeof Proxy === \"function\") return true; try { Date.prototype.toString.call(Reflect.construct(Date, [], function () {})); return true; } catch (e) { return false; } }\n\nfunction _getPrototypeOf(o) { _getPrototypeOf = Object.setPrototypeOf ? Object.getPrototypeOf : function _getPrototypeOf(o) { return o.__proto__ || Object.getPrototypeOf(o); }; return _getPrototypeOf(o); }\n\n\n\n\n\n\n/**\n * Helper function to retrieve attribute value.\n * @param {String} suffix\n * @param {Element} element\n */\n\nfunction getAttributeValue(suffix, element) {\n var attribute = \"data-clipboard-\".concat(suffix);\n\n if (!element.hasAttribute(attribute)) {\n return;\n }\n\n return element.getAttribute(attribute);\n}\n/**\n * Base class which takes one or more elements, adds event listeners to them,\n * and instantiates a new `ClipboardAction` on each click.\n */\n\n\nvar Clipboard = /*#__PURE__*/function (_Emitter) {\n _inherits(Clipboard, _Emitter);\n\n var _super = _createSuper(Clipboard);\n\n /**\n * @param {String|HTMLElement|HTMLCollection|NodeList} trigger\n * @param {Object} options\n */\n function Clipboard(trigger, options) {\n var _this;\n\n _classCallCheck(this, Clipboard);\n\n _this = _super.call(this);\n\n _this.resolveOptions(options);\n\n _this.listenClick(trigger);\n\n return _this;\n }\n /**\n * Defines if attributes would be resolved using internal setter functions\n * or custom functions that were passed in the constructor.\n * @param {Object} options\n */\n\n\n _createClass(Clipboard, [{\n key: \"resolveOptions\",\n value: function resolveOptions() {\n var options = arguments.length > 0 && arguments[0] !== undefined ? arguments[0] : {};\n this.action = typeof options.action === 'function' ? options.action : this.defaultAction;\n this.target = typeof options.target === 'function' ? options.target : this.defaultTarget;\n this.text = typeof options.text === 'function' ? options.text : this.defaultText;\n this.container = clipboard_typeof(options.container) === 'object' ? options.container : document.body;\n }\n /**\n * Adds a click event listener to the passed trigger.\n * @param {String|HTMLElement|HTMLCollection|NodeList} trigger\n */\n\n }, {\n key: \"listenClick\",\n value: function listenClick(trigger) {\n var _this2 = this;\n\n this.listener = listen_default()(trigger, 'click', function (e) {\n return _this2.onClick(e);\n });\n }\n /**\n * Defines a new `ClipboardAction` on each click event.\n * @param {Event} e\n */\n\n }, {\n key: \"onClick\",\n value: function onClick(e) {\n var trigger = e.delegateTarget || e.currentTarget;\n var action = this.action(trigger) || 'copy';\n var text = actions_default({\n action: action,\n container: this.container,\n target: this.target(trigger),\n text: this.text(trigger)\n }); // Fires an event based on the copy operation result.\n\n this.emit(text ? 'success' : 'error', {\n action: action,\n text: text,\n trigger: trigger,\n clearSelection: function clearSelection() {\n if (trigger) {\n trigger.focus();\n }\n\n window.getSelection().removeAllRanges();\n }\n });\n }\n /**\n * Default `action` lookup function.\n * @param {Element} trigger\n */\n\n }, {\n key: \"defaultAction\",\n value: function defaultAction(trigger) {\n return getAttributeValue('action', trigger);\n }\n /**\n * Default `target` lookup function.\n * @param {Element} trigger\n */\n\n }, {\n key: \"defaultTarget\",\n value: function defaultTarget(trigger) {\n var selector = getAttributeValue('target', trigger);\n\n if (selector) {\n return document.querySelector(selector);\n }\n }\n /**\n * Allow fire programmatically a copy action\n * @param {String|HTMLElement} target\n * @param {Object} options\n * @returns Text copied.\n */\n\n }, {\n key: \"defaultText\",\n\n /**\n * Default `text` lookup function.\n * @param {Element} trigger\n */\n value: function defaultText(trigger) {\n return getAttributeValue('text', trigger);\n }\n /**\n * Destroy lifecycle.\n */\n\n }, {\n key: \"destroy\",\n value: function destroy() {\n this.listener.destroy();\n }\n }], [{\n key: \"copy\",\n value: function copy(target) {\n var options = arguments.length > 1 && arguments[1] !== undefined ? arguments[1] : {\n container: document.body\n };\n return actions_copy(target, options);\n }\n /**\n * Allow fire programmatically a cut action\n * @param {String|HTMLElement} target\n * @returns Text cutted.\n */\n\n }, {\n key: \"cut\",\n value: function cut(target) {\n return actions_cut(target);\n }\n /**\n * Returns the support of the given action, or all actions if no action is\n * given.\n * @param {String} [action]\n */\n\n }, {\n key: \"isSupported\",\n value: function isSupported() {\n var action = arguments.length > 0 && arguments[0] !== undefined ? arguments[0] : ['copy', 'cut'];\n var actions = typeof action === 'string' ? [action] : action;\n var support = !!document.queryCommandSupported;\n actions.forEach(function (action) {\n support = support && !!document.queryCommandSupported(action);\n });\n return support;\n }\n }]);\n\n return Clipboard;\n}((tiny_emitter_default()));\n\n/* harmony default export */ var clipboard = (Clipboard);\n\n/***/ }),\n\n/***/ 828:\n/***/ (function(module) {\n\nvar DOCUMENT_NODE_TYPE = 9;\n\n/**\n * A polyfill for Element.matches()\n */\nif (typeof Element !== 'undefined' && !Element.prototype.matches) {\n var proto = Element.prototype;\n\n proto.matches = proto.matchesSelector ||\n proto.mozMatchesSelector ||\n proto.msMatchesSelector ||\n proto.oMatchesSelector ||\n proto.webkitMatchesSelector;\n}\n\n/**\n * Finds the closest parent that matches a selector.\n *\n * @param {Element} element\n * @param {String} selector\n * @return {Function}\n */\nfunction closest (element, selector) {\n while (element && element.nodeType !== DOCUMENT_NODE_TYPE) {\n if (typeof element.matches === 'function' &&\n element.matches(selector)) {\n return element;\n }\n element = element.parentNode;\n }\n}\n\nmodule.exports = closest;\n\n\n/***/ }),\n\n/***/ 438:\n/***/ (function(module, __unused_webpack_exports, __webpack_require__) {\n\nvar closest = __webpack_require__(828);\n\n/**\n * Delegates event to a selector.\n *\n * @param {Element} element\n * @param {String} selector\n * @param {String} type\n * @param {Function} callback\n * @param {Boolean} useCapture\n * @return {Object}\n */\nfunction _delegate(element, selector, type, callback, useCapture) {\n var listenerFn = listener.apply(this, arguments);\n\n element.addEventListener(type, listenerFn, useCapture);\n\n return {\n destroy: function() {\n element.removeEventListener(type, listenerFn, useCapture);\n }\n }\n}\n\n/**\n * Delegates event to a selector.\n *\n * @param {Element|String|Array} [elements]\n * @param {String} selector\n * @param {String} type\n * @param {Function} callback\n * @param {Boolean} useCapture\n * @return {Object}\n */\nfunction delegate(elements, selector, type, callback, useCapture) {\n // Handle the regular Element usage\n if (typeof elements.addEventListener === 'function') {\n return _delegate.apply(null, arguments);\n }\n\n // Handle Element-less usage, it defaults to global delegation\n if (typeof type === 'function') {\n // Use `document` as the first parameter, then apply arguments\n // This is a short way to .unshift `arguments` without running into deoptimizations\n return _delegate.bind(null, document).apply(null, arguments);\n }\n\n // Handle Selector-based usage\n if (typeof elements === 'string') {\n elements = document.querySelectorAll(elements);\n }\n\n // Handle Array-like based usage\n return Array.prototype.map.call(elements, function (element) {\n return _delegate(element, selector, type, callback, useCapture);\n });\n}\n\n/**\n * Finds closest match and invokes callback.\n *\n * @param {Element} element\n * @param {String} selector\n * @param {String} type\n * @param {Function} callback\n * @return {Function}\n */\nfunction listener(element, selector, type, callback) {\n return function(e) {\n e.delegateTarget = closest(e.target, selector);\n\n if (e.delegateTarget) {\n callback.call(element, e);\n }\n }\n}\n\nmodule.exports = delegate;\n\n\n/***/ }),\n\n/***/ 879:\n/***/ (function(__unused_webpack_module, exports) {\n\n/**\n * Check if argument is a HTML element.\n *\n * @param {Object} value\n * @return {Boolean}\n */\nexports.node = function(value) {\n return value !== undefined\n && value instanceof HTMLElement\n && value.nodeType === 1;\n};\n\n/**\n * Check if argument is a list of HTML elements.\n *\n * @param {Object} value\n * @return {Boolean}\n */\nexports.nodeList = function(value) {\n var type = Object.prototype.toString.call(value);\n\n return value !== undefined\n && (type === '[object NodeList]' || type === '[object HTMLCollection]')\n && ('length' in value)\n && (value.length === 0 || exports.node(value[0]));\n};\n\n/**\n * Check if argument is a string.\n *\n * @param {Object} value\n * @return {Boolean}\n */\nexports.string = function(value) {\n return typeof value === 'string'\n || value instanceof String;\n};\n\n/**\n * Check if argument is a function.\n *\n * @param {Object} value\n * @return {Boolean}\n */\nexports.fn = function(value) {\n var type = Object.prototype.toString.call(value);\n\n return type === '[object Function]';\n};\n\n\n/***/ }),\n\n/***/ 370:\n/***/ (function(module, __unused_webpack_exports, __webpack_require__) {\n\nvar is = __webpack_require__(879);\nvar delegate = __webpack_require__(438);\n\n/**\n * Validates all params and calls the right\n * listener function based on its target type.\n *\n * @param {String|HTMLElement|HTMLCollection|NodeList} target\n * @param {String} type\n * @param {Function} callback\n * @return {Object}\n */\nfunction listen(target, type, callback) {\n if (!target && !type && !callback) {\n throw new Error('Missing required arguments');\n }\n\n if (!is.string(type)) {\n throw new TypeError('Second argument must be a String');\n }\n\n if (!is.fn(callback)) {\n throw new TypeError('Third argument must be a Function');\n }\n\n if (is.node(target)) {\n return listenNode(target, type, callback);\n }\n else if (is.nodeList(target)) {\n return listenNodeList(target, type, callback);\n }\n else if (is.string(target)) {\n return listenSelector(target, type, callback);\n }\n else {\n throw new TypeError('First argument must be a String, HTMLElement, HTMLCollection, or NodeList');\n }\n}\n\n/**\n * Adds an event listener to a HTML element\n * and returns a remove listener function.\n *\n * @param {HTMLElement} node\n * @param {String} type\n * @param {Function} callback\n * @return {Object}\n */\nfunction listenNode(node, type, callback) {\n node.addEventListener(type, callback);\n\n return {\n destroy: function() {\n node.removeEventListener(type, callback);\n }\n }\n}\n\n/**\n * Add an event listener to a list of HTML elements\n * and returns a remove listener function.\n *\n * @param {NodeList|HTMLCollection} nodeList\n * @param {String} type\n * @param {Function} callback\n * @return {Object}\n */\nfunction listenNodeList(nodeList, type, callback) {\n Array.prototype.forEach.call(nodeList, function(node) {\n node.addEventListener(type, callback);\n });\n\n return {\n destroy: function() {\n Array.prototype.forEach.call(nodeList, function(node) {\n node.removeEventListener(type, callback);\n });\n }\n }\n}\n\n/**\n * Add an event listener to a selector\n * and returns a remove listener function.\n *\n * @param {String} selector\n * @param {String} type\n * @param {Function} callback\n * @return {Object}\n */\nfunction listenSelector(selector, type, callback) {\n return delegate(document.body, selector, type, callback);\n}\n\nmodule.exports = listen;\n\n\n/***/ }),\n\n/***/ 817:\n/***/ (function(module) {\n\nfunction select(element) {\n var selectedText;\n\n if (element.nodeName === 'SELECT') {\n element.focus();\n\n selectedText = element.value;\n }\n else if (element.nodeName === 'INPUT' || element.nodeName === 'TEXTAREA') {\n var isReadOnly = element.hasAttribute('readonly');\n\n if (!isReadOnly) {\n element.setAttribute('readonly', '');\n }\n\n element.select();\n element.setSelectionRange(0, element.value.length);\n\n if (!isReadOnly) {\n element.removeAttribute('readonly');\n }\n\n selectedText = element.value;\n }\n else {\n if (element.hasAttribute('contenteditable')) {\n element.focus();\n }\n\n var selection = window.getSelection();\n var range = document.createRange();\n\n range.selectNodeContents(element);\n selection.removeAllRanges();\n selection.addRange(range);\n\n selectedText = selection.toString();\n }\n\n return selectedText;\n}\n\nmodule.exports = select;\n\n\n/***/ }),\n\n/***/ 279:\n/***/ (function(module) {\n\nfunction E () {\n // Keep this empty so it's easier to inherit from\n // (via https://github.com/lipsmack from https://github.com/scottcorgan/tiny-emitter/issues/3)\n}\n\nE.prototype = {\n on: function (name, callback, ctx) {\n var e = this.e || (this.e = {});\n\n (e[name] || (e[name] = [])).push({\n fn: callback,\n ctx: ctx\n });\n\n return this;\n },\n\n once: function (name, callback, ctx) {\n var self = this;\n function listener () {\n self.off(name, listener);\n callback.apply(ctx, arguments);\n };\n\n listener._ = callback\n return this.on(name, listener, ctx);\n },\n\n emit: function (name) {\n var data = [].slice.call(arguments, 1);\n var evtArr = ((this.e || (this.e = {}))[name] || []).slice();\n var i = 0;\n var len = evtArr.length;\n\n for (i; i < len; i++) {\n evtArr[i].fn.apply(evtArr[i].ctx, data);\n }\n\n return this;\n },\n\n off: function (name, callback) {\n var e = this.e || (this.e = {});\n var evts = e[name];\n var liveEvents = [];\n\n if (evts && callback) {\n for (var i = 0, len = evts.length; i < len; i++) {\n if (evts[i].fn !== callback && evts[i].fn._ !== callback)\n liveEvents.push(evts[i]);\n }\n }\n\n // Remove event from queue to prevent memory leak\n // Suggested by https://github.com/lazd\n // Ref: https://github.com/scottcorgan/tiny-emitter/commit/c6ebfaa9bc973b33d110a84a307742b7cf94c953#commitcomment-5024910\n\n (liveEvents.length)\n ? e[name] = liveEvents\n : delete e[name];\n\n return this;\n }\n};\n\nmodule.exports = E;\nmodule.exports.TinyEmitter = E;\n\n\n/***/ })\n\n/******/ \t});\n/************************************************************************/\n/******/ \t// The module cache\n/******/ \tvar __webpack_module_cache__ = {};\n/******/ \t\n/******/ \t// The require function\n/******/ \tfunction __webpack_require__(moduleId) {\n/******/ \t\t// Check if module is in cache\n/******/ \t\tif(__webpack_module_cache__[moduleId]) {\n/******/ \t\t\treturn __webpack_module_cache__[moduleId].exports;\n/******/ \t\t}\n/******/ \t\t// Create a new module (and put it into the cache)\n/******/ \t\tvar module = __webpack_module_cache__[moduleId] = {\n/******/ \t\t\t// no module.id needed\n/******/ \t\t\t// no module.loaded needed\n/******/ \t\t\texports: {}\n/******/ \t\t};\n/******/ \t\n/******/ \t\t// Execute the module function\n/******/ \t\t__webpack_modules__[moduleId](module, module.exports, __webpack_require__);\n/******/ \t\n/******/ \t\t// Return the exports of the module\n/******/ \t\treturn module.exports;\n/******/ \t}\n/******/ \t\n/************************************************************************/\n/******/ \t/* webpack/runtime/compat get default export */\n/******/ \t!function() {\n/******/ \t\t// getDefaultExport function for compatibility with non-harmony modules\n/******/ \t\t__webpack_require__.n = function(module) {\n/******/ \t\t\tvar getter = module && module.__esModule ?\n/******/ \t\t\t\tfunction() { return module['default']; } :\n/******/ \t\t\t\tfunction() { return module; };\n/******/ \t\t\t__webpack_require__.d(getter, { a: getter });\n/******/ \t\t\treturn getter;\n/******/ \t\t};\n/******/ \t}();\n/******/ \t\n/******/ \t/* webpack/runtime/define property getters */\n/******/ \t!function() {\n/******/ \t\t// define getter functions for harmony exports\n/******/ \t\t__webpack_require__.d = function(exports, definition) {\n/******/ \t\t\tfor(var key in definition) {\n/******/ \t\t\t\tif(__webpack_require__.o(definition, key) && !__webpack_require__.o(exports, key)) {\n/******/ \t\t\t\t\tObject.defineProperty(exports, key, { enumerable: true, get: definition[key] });\n/******/ \t\t\t\t}\n/******/ \t\t\t}\n/******/ \t\t};\n/******/ \t}();\n/******/ \t\n/******/ \t/* webpack/runtime/hasOwnProperty shorthand */\n/******/ \t!function() {\n/******/ \t\t__webpack_require__.o = function(obj, prop) { return Object.prototype.hasOwnProperty.call(obj, prop); }\n/******/ \t}();\n/******/ \t\n/************************************************************************/\n/******/ \t// module exports must be returned from runtime so entry inlining is disabled\n/******/ \t// startup\n/******/ \t// Load entry module and return exports\n/******/ \treturn __webpack_require__(686);\n/******/ })()\n.default;\n});", "/*!\n * escape-html\n * Copyright(c) 2012-2013 TJ Holowaychuk\n * Copyright(c) 2015 Andreas Lubbe\n * Copyright(c) 2015 Tiancheng \"Timothy\" Gu\n * MIT Licensed\n */\n\n'use strict';\n\n/**\n * Module variables.\n * @private\n */\n\nvar matchHtmlRegExp = /[\"'&<>]/;\n\n/**\n * Module exports.\n * @public\n */\n\nmodule.exports = escapeHtml;\n\n/**\n * Escape special characters in the given string of html.\n *\n * @param {string} string The string to escape for inserting into HTML\n * @return {string}\n * @public\n */\n\nfunction escapeHtml(string) {\n var str = '' + string;\n var match = matchHtmlRegExp.exec(str);\n\n if (!match) {\n return str;\n }\n\n var escape;\n var html = '';\n var index = 0;\n var lastIndex = 0;\n\n for (index = match.index; index < str.length; index++) {\n switch (str.charCodeAt(index)) {\n case 34: // \"\n escape = '"';\n break;\n case 38: // &\n escape = '&';\n break;\n case 39: // '\n escape = ''';\n break;\n case 60: // <\n escape = '<';\n break;\n case 62: // >\n escape = '>';\n break;\n default:\n continue;\n }\n\n if (lastIndex !== index) {\n html += str.substring(lastIndex, index);\n }\n\n lastIndex = index + 1;\n html += escape;\n }\n\n return lastIndex !== index\n ? html + str.substring(lastIndex, index)\n : html;\n}\n", "/*\n * Copyright (c) 2016-2024 Martin Donath \n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport \"focus-visible\"\n\nimport {\n EMPTY,\n NEVER,\n Observable,\n Subject,\n defer,\n delay,\n filter,\n map,\n merge,\n mergeWith,\n shareReplay,\n switchMap\n} from \"rxjs\"\n\nimport { configuration, feature } from \"./_\"\nimport {\n at,\n getActiveElement,\n getOptionalElement,\n requestJSON,\n setLocation,\n setToggle,\n watchDocument,\n watchKeyboard,\n watchLocation,\n watchLocationTarget,\n watchMedia,\n watchPrint,\n watchScript,\n watchViewport\n} from \"./browser\"\nimport {\n getComponentElement,\n getComponentElements,\n mountAnnounce,\n mountBackToTop,\n mountConsent,\n mountContent,\n mountDialog,\n mountHeader,\n mountHeaderTitle,\n mountPalette,\n mountProgress,\n mountSearch,\n mountSearchHiglight,\n mountSidebar,\n mountSource,\n mountTableOfContents,\n mountTabs,\n watchHeader,\n watchMain\n} from \"./components\"\nimport {\n SearchIndex,\n setupClipboardJS,\n setupInstantNavigation,\n setupVersionSelector\n} from \"./integrations\"\nimport {\n patchEllipsis,\n patchIndeterminate,\n patchScrollfix,\n patchScrolllock\n} from \"./patches\"\nimport \"./polyfills\"\n\n/* ----------------------------------------------------------------------------\n * Functions - @todo refactor\n * ------------------------------------------------------------------------- */\n\n/**\n * Fetch search index\n *\n * @returns Search index observable\n */\nfunction fetchSearchIndex(): Observable {\n if (location.protocol === \"file:\") {\n return watchScript(\n `${new URL(\"search/search_index.js\", config.base)}`\n )\n .pipe(\n // @ts-ignore - @todo fix typings\n map(() => __index),\n shareReplay(1)\n )\n } else {\n return requestJSON(\n new URL(\"search/search_index.json\", config.base)\n )\n }\n}\n\n/* ----------------------------------------------------------------------------\n * Application\n * ------------------------------------------------------------------------- */\n\n/* Yay, JavaScript is available */\ndocument.documentElement.classList.remove(\"no-js\")\ndocument.documentElement.classList.add(\"js\")\n\n/* Set up navigation observables and subjects */\nconst document$ = watchDocument()\nconst location$ = watchLocation()\nconst target$ = watchLocationTarget(location$)\nconst keyboard$ = watchKeyboard()\n\n/* Set up media observables */\nconst viewport$ = watchViewport()\nconst tablet$ = watchMedia(\"(min-width: 960px)\")\nconst screen$ = watchMedia(\"(min-width: 1220px)\")\nconst print$ = watchPrint()\n\n/* Retrieve search index, if search is enabled */\nconst config = configuration()\nconst index$ = document.forms.namedItem(\"search\")\n ? fetchSearchIndex()\n : NEVER\n\n/* Set up Clipboard.js integration */\nconst alert$ = new Subject()\nsetupClipboardJS({ alert$ })\n\n/* Set up progress indicator */\nconst progress$ = new Subject()\n\n/* Set up instant navigation, if enabled */\nif (feature(\"navigation.instant\"))\n setupInstantNavigation({ location$, viewport$, progress$ })\n .subscribe(document$)\n\n/* Set up version selector */\nif (config.version?.provider === \"mike\")\n setupVersionSelector({ document$ })\n\n/* Always close drawer and search on navigation */\nmerge(location$, target$)\n .pipe(\n delay(125)\n )\n .subscribe(() => {\n setToggle(\"drawer\", false)\n setToggle(\"search\", false)\n })\n\n/* Set up global keyboard handlers */\nkeyboard$\n .pipe(\n filter(({ mode }) => mode === \"global\")\n )\n .subscribe(key => {\n switch (key.type) {\n\n /* Go to previous page */\n case \"p\":\n case \",\":\n const prev = getOptionalElement(\"link[rel=prev]\")\n if (typeof prev !== \"undefined\")\n setLocation(prev)\n break\n\n /* Go to next page */\n case \"n\":\n case \".\":\n const next = getOptionalElement(\"link[rel=next]\")\n if (typeof next !== \"undefined\")\n setLocation(next)\n break\n\n /* Expand navigation, see https://bit.ly/3ZjG5io */\n case \"Enter\":\n const active = getActiveElement()\n if (active instanceof HTMLLabelElement)\n active.click()\n }\n })\n\n/* Set up patches */\npatchEllipsis({ viewport$, document$ })\npatchIndeterminate({ document$, tablet$ })\npatchScrollfix({ document$ })\npatchScrolllock({ viewport$, tablet$ })\n\n/* Set up header and main area observable */\nconst header$ = watchHeader(getComponentElement(\"header\"), { viewport$ })\nconst main$ = document$\n .pipe(\n map(() => getComponentElement(\"main\")),\n switchMap(el => watchMain(el, { viewport$, header$ })),\n shareReplay(1)\n )\n\n/* Set up control component observables */\nconst control$ = merge(\n\n /* Consent */\n ...getComponentElements(\"consent\")\n .map(el => mountConsent(el, { target$ })),\n\n /* Dialog */\n ...getComponentElements(\"dialog\")\n .map(el => mountDialog(el, { alert$ })),\n\n /* Header */\n ...getComponentElements(\"header\")\n .map(el => mountHeader(el, { viewport$, header$, main$ })),\n\n /* Color palette */\n ...getComponentElements(\"palette\")\n .map(el => mountPalette(el)),\n\n /* Progress bar */\n ...getComponentElements(\"progress\")\n .map(el => mountProgress(el, { progress$ })),\n\n /* Search */\n ...getComponentElements(\"search\")\n .map(el => mountSearch(el, { index$, keyboard$ })),\n\n /* Repository information */\n ...getComponentElements(\"source\")\n .map(el => mountSource(el))\n)\n\n/* Set up content component observables */\nconst content$ = defer(() => merge(\n\n /* Announcement bar */\n ...getComponentElements(\"announce\")\n .map(el => mountAnnounce(el)),\n\n /* Content */\n ...getComponentElements(\"content\")\n .map(el => mountContent(el, { viewport$, target$, print$ })),\n\n /* Search highlighting */\n ...getComponentElements(\"content\")\n .map(el => feature(\"search.highlight\")\n ? mountSearchHiglight(el, { index$, location$ })\n : EMPTY\n ),\n\n /* Header title */\n ...getComponentElements(\"header-title\")\n .map(el => mountHeaderTitle(el, { viewport$, header$ })),\n\n /* Sidebar */\n ...getComponentElements(\"sidebar\")\n .map(el => el.getAttribute(\"data-md-type\") === \"navigation\"\n ? at(screen$, () => mountSidebar(el, { viewport$, header$, main$ }))\n : at(tablet$, () => mountSidebar(el, { viewport$, header$, main$ }))\n ),\n\n /* Navigation tabs */\n ...getComponentElements(\"tabs\")\n .map(el => mountTabs(el, { viewport$, header$ })),\n\n /* Table of contents */\n ...getComponentElements(\"toc\")\n .map(el => mountTableOfContents(el, {\n viewport$, header$, main$, target$\n })),\n\n /* Back-to-top button */\n ...getComponentElements(\"top\")\n .map(el => mountBackToTop(el, { viewport$, header$, main$, target$ }))\n))\n\n/* Set up component observables */\nconst component$ = document$\n .pipe(\n switchMap(() => content$),\n mergeWith(control$),\n shareReplay(1)\n )\n\n/* Subscribe to all components */\ncomponent$.subscribe()\n\n/* ----------------------------------------------------------------------------\n * Exports\n * ------------------------------------------------------------------------- */\n\nwindow.document$ = document$ /* Document observable */\nwindow.location$ = location$ /* Location subject */\nwindow.target$ = target$ /* Location target observable */\nwindow.keyboard$ = keyboard$ /* Keyboard observable */\nwindow.viewport$ = viewport$ /* Viewport observable */\nwindow.tablet$ = tablet$ /* Media tablet observable */\nwindow.screen$ = screen$ /* Media screen observable */\nwindow.print$ = print$ /* Media print observable */\nwindow.alert$ = alert$ /* Alert subject */\nwindow.progress$ = progress$ /* Progress indicator subject */\nwindow.component$ = component$ /* Component observable */\n", "/*! *****************************************************************************\r\nCopyright (c) Microsoft Corporation.\r\n\r\nPermission to use, copy, modify, and/or distribute this software for any\r\npurpose with or without fee is hereby granted.\r\n\r\nTHE SOFTWARE IS PROVIDED \"AS IS\" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH\r\nREGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY\r\nAND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT,\r\nINDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM\r\nLOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR\r\nOTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR\r\nPERFORMANCE OF THIS SOFTWARE.\r\n***************************************************************************** */\r\n/* global Reflect, Promise */\r\n\r\nvar extendStatics = function(d, b) {\r\n extendStatics = Object.setPrototypeOf ||\r\n ({ __proto__: [] } instanceof Array && function (d, b) { d.__proto__ = b; }) ||\r\n function (d, b) { for (var p in b) if (Object.prototype.hasOwnProperty.call(b, p)) d[p] = b[p]; };\r\n return extendStatics(d, b);\r\n};\r\n\r\nexport function __extends(d, b) {\r\n if (typeof b !== \"function\" && b !== null)\r\n throw new TypeError(\"Class extends value \" + String(b) + \" is not a constructor or null\");\r\n extendStatics(d, b);\r\n function __() { this.constructor = d; }\r\n d.prototype = b === null ? Object.create(b) : (__.prototype = b.prototype, new __());\r\n}\r\n\r\nexport var __assign = function() {\r\n __assign = Object.assign || function __assign(t) {\r\n for (var s, i = 1, n = arguments.length; i < n; i++) {\r\n s = arguments[i];\r\n for (var p in s) if (Object.prototype.hasOwnProperty.call(s, p)) t[p] = s[p];\r\n }\r\n return t;\r\n }\r\n return __assign.apply(this, arguments);\r\n}\r\n\r\nexport function __rest(s, e) {\r\n var t = {};\r\n for (var p in s) if (Object.prototype.hasOwnProperty.call(s, p) && e.indexOf(p) < 0)\r\n t[p] = s[p];\r\n if (s != null && typeof Object.getOwnPropertySymbols === \"function\")\r\n for (var i = 0, p = Object.getOwnPropertySymbols(s); i < p.length; i++) {\r\n if (e.indexOf(p[i]) < 0 && Object.prototype.propertyIsEnumerable.call(s, p[i]))\r\n t[p[i]] = s[p[i]];\r\n }\r\n return t;\r\n}\r\n\r\nexport function __decorate(decorators, target, key, desc) {\r\n var c = arguments.length, r = c < 3 ? target : desc === null ? desc = Object.getOwnPropertyDescriptor(target, key) : desc, d;\r\n if (typeof Reflect === \"object\" && typeof Reflect.decorate === \"function\") r = Reflect.decorate(decorators, target, key, desc);\r\n else for (var i = decorators.length - 1; i >= 0; i--) if (d = decorators[i]) r = (c < 3 ? d(r) : c > 3 ? d(target, key, r) : d(target, key)) || r;\r\n return c > 3 && r && Object.defineProperty(target, key, r), r;\r\n}\r\n\r\nexport function __param(paramIndex, decorator) {\r\n return function (target, key) { decorator(target, key, paramIndex); }\r\n}\r\n\r\nexport function __metadata(metadataKey, metadataValue) {\r\n if (typeof Reflect === \"object\" && typeof Reflect.metadata === \"function\") return Reflect.metadata(metadataKey, metadataValue);\r\n}\r\n\r\nexport function __awaiter(thisArg, _arguments, P, generator) {\r\n function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }\r\n return new (P || (P = Promise))(function (resolve, reject) {\r\n function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }\r\n function rejected(value) { try { step(generator[\"throw\"](value)); } catch (e) { reject(e); } }\r\n function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }\r\n step((generator = generator.apply(thisArg, _arguments || [])).next());\r\n });\r\n}\r\n\r\nexport function __generator(thisArg, body) {\r\n var _ = { label: 0, sent: function() { if (t[0] & 1) throw t[1]; return t[1]; }, trys: [], ops: [] }, f, y, t, g;\r\n return g = { next: verb(0), \"throw\": verb(1), \"return\": verb(2) }, typeof Symbol === \"function\" && (g[Symbol.iterator] = function() { return this; }), g;\r\n function verb(n) { return function (v) { return step([n, v]); }; }\r\n function step(op) {\r\n if (f) throw new TypeError(\"Generator is already executing.\");\r\n while (_) try {\r\n if (f = 1, y && (t = op[0] & 2 ? y[\"return\"] : op[0] ? y[\"throw\"] || ((t = y[\"return\"]) && t.call(y), 0) : y.next) && !(t = t.call(y, op[1])).done) return t;\r\n if (y = 0, t) op = [op[0] & 2, t.value];\r\n switch (op[0]) {\r\n case 0: case 1: t = op; break;\r\n case 4: _.label++; return { value: op[1], done: false };\r\n case 5: _.label++; y = op[1]; op = [0]; continue;\r\n case 7: op = _.ops.pop(); _.trys.pop(); continue;\r\n default:\r\n if (!(t = _.trys, t = t.length > 0 && t[t.length - 1]) && (op[0] === 6 || op[0] === 2)) { _ = 0; continue; }\r\n if (op[0] === 3 && (!t || (op[1] > t[0] && op[1] < t[3]))) { _.label = op[1]; break; }\r\n if (op[0] === 6 && _.label < t[1]) { _.label = t[1]; t = op; break; }\r\n if (t && _.label < t[2]) { _.label = t[2]; _.ops.push(op); break; }\r\n if (t[2]) _.ops.pop();\r\n _.trys.pop(); continue;\r\n }\r\n op = body.call(thisArg, _);\r\n } catch (e) { op = [6, e]; y = 0; } finally { f = t = 0; }\r\n if (op[0] & 5) throw op[1]; return { value: op[0] ? op[1] : void 0, done: true };\r\n }\r\n}\r\n\r\nexport var __createBinding = Object.create ? (function(o, m, k, k2) {\r\n if (k2 === undefined) k2 = k;\r\n Object.defineProperty(o, k2, { enumerable: true, get: function() { return m[k]; } });\r\n}) : (function(o, m, k, k2) {\r\n if (k2 === undefined) k2 = k;\r\n o[k2] = m[k];\r\n});\r\n\r\nexport function __exportStar(m, o) {\r\n for (var p in m) if (p !== \"default\" && !Object.prototype.hasOwnProperty.call(o, p)) __createBinding(o, m, p);\r\n}\r\n\r\nexport function __values(o) {\r\n var s = typeof Symbol === \"function\" && Symbol.iterator, m = s && o[s], i = 0;\r\n if (m) return m.call(o);\r\n if (o && typeof o.length === \"number\") return {\r\n next: function () {\r\n if (o && i >= o.length) o = void 0;\r\n return { value: o && o[i++], done: !o };\r\n }\r\n };\r\n throw new TypeError(s ? \"Object is not iterable.\" : \"Symbol.iterator is not defined.\");\r\n}\r\n\r\nexport function __read(o, n) {\r\n var m = typeof Symbol === \"function\" && o[Symbol.iterator];\r\n if (!m) return o;\r\n var i = m.call(o), r, ar = [], e;\r\n try {\r\n while ((n === void 0 || n-- > 0) && !(r = i.next()).done) ar.push(r.value);\r\n }\r\n catch (error) { e = { error: error }; }\r\n finally {\r\n try {\r\n if (r && !r.done && (m = i[\"return\"])) m.call(i);\r\n }\r\n finally { if (e) throw e.error; }\r\n }\r\n return ar;\r\n}\r\n\r\n/** @deprecated */\r\nexport function __spread() {\r\n for (var ar = [], i = 0; i < arguments.length; i++)\r\n ar = ar.concat(__read(arguments[i]));\r\n return ar;\r\n}\r\n\r\n/** @deprecated */\r\nexport function __spreadArrays() {\r\n for (var s = 0, i = 0, il = arguments.length; i < il; i++) s += arguments[i].length;\r\n for (var r = Array(s), k = 0, i = 0; i < il; i++)\r\n for (var a = arguments[i], j = 0, jl = a.length; j < jl; j++, k++)\r\n r[k] = a[j];\r\n return r;\r\n}\r\n\r\nexport function __spreadArray(to, from, pack) {\r\n if (pack || arguments.length === 2) for (var i = 0, l = from.length, ar; i < l; i++) {\r\n if (ar || !(i in from)) {\r\n if (!ar) ar = Array.prototype.slice.call(from, 0, i);\r\n ar[i] = from[i];\r\n }\r\n }\r\n return to.concat(ar || Array.prototype.slice.call(from));\r\n}\r\n\r\nexport function __await(v) {\r\n return this instanceof __await ? (this.v = v, this) : new __await(v);\r\n}\r\n\r\nexport function __asyncGenerator(thisArg, _arguments, generator) {\r\n if (!Symbol.asyncIterator) throw new TypeError(\"Symbol.asyncIterator is not defined.\");\r\n var g = generator.apply(thisArg, _arguments || []), i, q = [];\r\n return i = {}, verb(\"next\"), verb(\"throw\"), verb(\"return\"), i[Symbol.asyncIterator] = function () { return this; }, i;\r\n function verb(n) { if (g[n]) i[n] = function (v) { return new Promise(function (a, b) { q.push([n, v, a, b]) > 1 || resume(n, v); }); }; }\r\n function resume(n, v) { try { step(g[n](v)); } catch (e) { settle(q[0][3], e); } }\r\n function step(r) { r.value instanceof __await ? Promise.resolve(r.value.v).then(fulfill, reject) : settle(q[0][2], r); }\r\n function fulfill(value) { resume(\"next\", value); }\r\n function reject(value) { resume(\"throw\", value); }\r\n function settle(f, v) { if (f(v), q.shift(), q.length) resume(q[0][0], q[0][1]); }\r\n}\r\n\r\nexport function __asyncDelegator(o) {\r\n var i, p;\r\n return i = {}, verb(\"next\"), verb(\"throw\", function (e) { throw e; }), verb(\"return\"), i[Symbol.iterator] = function () { return this; }, i;\r\n function verb(n, f) { i[n] = o[n] ? function (v) { return (p = !p) ? { value: __await(o[n](v)), done: n === \"return\" } : f ? f(v) : v; } : f; }\r\n}\r\n\r\nexport function __asyncValues(o) {\r\n if (!Symbol.asyncIterator) throw new TypeError(\"Symbol.asyncIterator is not defined.\");\r\n var m = o[Symbol.asyncIterator], i;\r\n return m ? m.call(o) : (o = typeof __values === \"function\" ? __values(o) : o[Symbol.iterator](), i = {}, verb(\"next\"), verb(\"throw\"), verb(\"return\"), i[Symbol.asyncIterator] = function () { return this; }, i);\r\n function verb(n) { i[n] = o[n] && function (v) { return new Promise(function (resolve, reject) { v = o[n](v), settle(resolve, reject, v.done, v.value); }); }; }\r\n function settle(resolve, reject, d, v) { Promise.resolve(v).then(function(v) { resolve({ value: v, done: d }); }, reject); }\r\n}\r\n\r\nexport function __makeTemplateObject(cooked, raw) {\r\n if (Object.defineProperty) { Object.defineProperty(cooked, \"raw\", { value: raw }); } else { cooked.raw = raw; }\r\n return cooked;\r\n};\r\n\r\nvar __setModuleDefault = Object.create ? (function(o, v) {\r\n Object.defineProperty(o, \"default\", { enumerable: true, value: v });\r\n}) : function(o, v) {\r\n o[\"default\"] = v;\r\n};\r\n\r\nexport function __importStar(mod) {\r\n if (mod && mod.__esModule) return mod;\r\n var result = {};\r\n if (mod != null) for (var k in mod) if (k !== \"default\" && Object.prototype.hasOwnProperty.call(mod, k)) __createBinding(result, mod, k);\r\n __setModuleDefault(result, mod);\r\n return result;\r\n}\r\n\r\nexport function __importDefault(mod) {\r\n return (mod && mod.__esModule) ? mod : { default: mod };\r\n}\r\n\r\nexport function __classPrivateFieldGet(receiver, state, kind, f) {\r\n if (kind === \"a\" && !f) throw new TypeError(\"Private accessor was defined without a getter\");\r\n if (typeof state === \"function\" ? receiver !== state || !f : !state.has(receiver)) throw new TypeError(\"Cannot read private member from an object whose class did not declare it\");\r\n return kind === \"m\" ? f : kind === \"a\" ? f.call(receiver) : f ? f.value : state.get(receiver);\r\n}\r\n\r\nexport function __classPrivateFieldSet(receiver, state, value, kind, f) {\r\n if (kind === \"m\") throw new TypeError(\"Private method is not writable\");\r\n if (kind === \"a\" && !f) throw new TypeError(\"Private accessor was defined without a setter\");\r\n if (typeof state === \"function\" ? receiver !== state || !f : !state.has(receiver)) throw new TypeError(\"Cannot write private member to an object whose class did not declare it\");\r\n return (kind === \"a\" ? f.call(receiver, value) : f ? f.value = value : state.set(receiver, value)), value;\r\n}\r\n", "/**\n * Returns true if the object is a function.\n * @param value The value to check\n */\nexport function isFunction(value: any): value is (...args: any[]) => any {\n return typeof value === 'function';\n}\n", "/**\n * Used to create Error subclasses until the community moves away from ES5.\n *\n * This is because compiling from TypeScript down to ES5 has issues with subclassing Errors\n * as well as other built-in types: https://github.com/Microsoft/TypeScript/issues/12123\n *\n * @param createImpl A factory function to create the actual constructor implementation. The returned\n * function should be a named function that calls `_super` internally.\n */\nexport function createErrorClass(createImpl: (_super: any) => any): T {\n const _super = (instance: any) => {\n Error.call(instance);\n instance.stack = new Error().stack;\n };\n\n const ctorFunc = createImpl(_super);\n ctorFunc.prototype = Object.create(Error.prototype);\n ctorFunc.prototype.constructor = ctorFunc;\n return ctorFunc;\n}\n", "import { createErrorClass } from './createErrorClass';\n\nexport interface UnsubscriptionError extends Error {\n readonly errors: any[];\n}\n\nexport interface UnsubscriptionErrorCtor {\n /**\n * @deprecated Internal implementation detail. Do not construct error instances.\n * Cannot be tagged as internal: https://github.com/ReactiveX/rxjs/issues/6269\n */\n new (errors: any[]): UnsubscriptionError;\n}\n\n/**\n * An error thrown when one or more errors have occurred during the\n * `unsubscribe` of a {@link Subscription}.\n */\nexport const UnsubscriptionError: UnsubscriptionErrorCtor = createErrorClass(\n (_super) =>\n function UnsubscriptionErrorImpl(this: any, errors: (Error | string)[]) {\n _super(this);\n this.message = errors\n ? `${errors.length} errors occurred during unsubscription:\n${errors.map((err, i) => `${i + 1}) ${err.toString()}`).join('\\n ')}`\n : '';\n this.name = 'UnsubscriptionError';\n this.errors = errors;\n }\n);\n", "/**\n * Removes an item from an array, mutating it.\n * @param arr The array to remove the item from\n * @param item The item to remove\n */\nexport function arrRemove(arr: T[] | undefined | null, item: T) {\n if (arr) {\n const index = arr.indexOf(item);\n 0 <= index && arr.splice(index, 1);\n }\n}\n", "import { isFunction } from './util/isFunction';\nimport { UnsubscriptionError } from './util/UnsubscriptionError';\nimport { SubscriptionLike, TeardownLogic, Unsubscribable } from './types';\nimport { arrRemove } from './util/arrRemove';\n\n/**\n * Represents a disposable resource, such as the execution of an Observable. A\n * Subscription has one important method, `unsubscribe`, that takes no argument\n * and just disposes the resource held by the subscription.\n *\n * Additionally, subscriptions may be grouped together through the `add()`\n * method, which will attach a child Subscription to the current Subscription.\n * When a Subscription is unsubscribed, all its children (and its grandchildren)\n * will be unsubscribed as well.\n *\n * @class Subscription\n */\nexport class Subscription implements SubscriptionLike {\n /** @nocollapse */\n public static EMPTY = (() => {\n const empty = new Subscription();\n empty.closed = true;\n return empty;\n })();\n\n /**\n * A flag to indicate whether this Subscription has already been unsubscribed.\n */\n public closed = false;\n\n private _parentage: Subscription[] | Subscription | null = null;\n\n /**\n * The list of registered finalizers to execute upon unsubscription. Adding and removing from this\n * list occurs in the {@link #add} and {@link #remove} methods.\n */\n private _finalizers: Exclude[] | null = null;\n\n /**\n * @param initialTeardown A function executed first as part of the finalization\n * process that is kicked off when {@link #unsubscribe} is called.\n */\n constructor(private initialTeardown?: () => void) {}\n\n /**\n * Disposes the resources held by the subscription. May, for instance, cancel\n * an ongoing Observable execution or cancel any other type of work that\n * started when the Subscription was created.\n * @return {void}\n */\n unsubscribe(): void {\n let errors: any[] | undefined;\n\n if (!this.closed) {\n this.closed = true;\n\n // Remove this from it's parents.\n const { _parentage } = this;\n if (_parentage) {\n this._parentage = null;\n if (Array.isArray(_parentage)) {\n for (const parent of _parentage) {\n parent.remove(this);\n }\n } else {\n _parentage.remove(this);\n }\n }\n\n const { initialTeardown: initialFinalizer } = this;\n if (isFunction(initialFinalizer)) {\n try {\n initialFinalizer();\n } catch (e) {\n errors = e instanceof UnsubscriptionError ? e.errors : [e];\n }\n }\n\n const { _finalizers } = this;\n if (_finalizers) {\n this._finalizers = null;\n for (const finalizer of _finalizers) {\n try {\n execFinalizer(finalizer);\n } catch (err) {\n errors = errors ?? [];\n if (err instanceof UnsubscriptionError) {\n errors = [...errors, ...err.errors];\n } else {\n errors.push(err);\n }\n }\n }\n }\n\n if (errors) {\n throw new UnsubscriptionError(errors);\n }\n }\n }\n\n /**\n * Adds a finalizer to this subscription, so that finalization will be unsubscribed/called\n * when this subscription is unsubscribed. If this subscription is already {@link #closed},\n * because it has already been unsubscribed, then whatever finalizer is passed to it\n * will automatically be executed (unless the finalizer itself is also a closed subscription).\n *\n * Closed Subscriptions cannot be added as finalizers to any subscription. Adding a closed\n * subscription to a any subscription will result in no operation. (A noop).\n *\n * Adding a subscription to itself, or adding `null` or `undefined` will not perform any\n * operation at all. (A noop).\n *\n * `Subscription` instances that are added to this instance will automatically remove themselves\n * if they are unsubscribed. Functions and {@link Unsubscribable} objects that you wish to remove\n * will need to be removed manually with {@link #remove}\n *\n * @param teardown The finalization logic to add to this subscription.\n */\n add(teardown: TeardownLogic): void {\n // Only add the finalizer if it's not undefined\n // and don't add a subscription to itself.\n if (teardown && teardown !== this) {\n if (this.closed) {\n // If this subscription is already closed,\n // execute whatever finalizer is handed to it automatically.\n execFinalizer(teardown);\n } else {\n if (teardown instanceof Subscription) {\n // We don't add closed subscriptions, and we don't add the same subscription\n // twice. Subscription unsubscribe is idempotent.\n if (teardown.closed || teardown._hasParent(this)) {\n return;\n }\n teardown._addParent(this);\n }\n (this._finalizers = this._finalizers ?? []).push(teardown);\n }\n }\n }\n\n /**\n * Checks to see if a this subscription already has a particular parent.\n * This will signal that this subscription has already been added to the parent in question.\n * @param parent the parent to check for\n */\n private _hasParent(parent: Subscription) {\n const { _parentage } = this;\n return _parentage === parent || (Array.isArray(_parentage) && _parentage.includes(parent));\n }\n\n /**\n * Adds a parent to this subscription so it can be removed from the parent if it\n * unsubscribes on it's own.\n *\n * NOTE: THIS ASSUMES THAT {@link _hasParent} HAS ALREADY BEEN CHECKED.\n * @param parent The parent subscription to add\n */\n private _addParent(parent: Subscription) {\n const { _parentage } = this;\n this._parentage = Array.isArray(_parentage) ? (_parentage.push(parent), _parentage) : _parentage ? [_parentage, parent] : parent;\n }\n\n /**\n * Called on a child when it is removed via {@link #remove}.\n * @param parent The parent to remove\n */\n private _removeParent(parent: Subscription) {\n const { _parentage } = this;\n if (_parentage === parent) {\n this._parentage = null;\n } else if (Array.isArray(_parentage)) {\n arrRemove(_parentage, parent);\n }\n }\n\n /**\n * Removes a finalizer from this subscription that was previously added with the {@link #add} method.\n *\n * Note that `Subscription` instances, when unsubscribed, will automatically remove themselves\n * from every other `Subscription` they have been added to. This means that using the `remove` method\n * is not a common thing and should be used thoughtfully.\n *\n * If you add the same finalizer instance of a function or an unsubscribable object to a `Subscription` instance\n * more than once, you will need to call `remove` the same number of times to remove all instances.\n *\n * All finalizer instances are removed to free up memory upon unsubscription.\n *\n * @param teardown The finalizer to remove from this subscription\n */\n remove(teardown: Exclude): void {\n const { _finalizers } = this;\n _finalizers && arrRemove(_finalizers, teardown);\n\n if (teardown instanceof Subscription) {\n teardown._removeParent(this);\n }\n }\n}\n\nexport const EMPTY_SUBSCRIPTION = Subscription.EMPTY;\n\nexport function isSubscription(value: any): value is Subscription {\n return (\n value instanceof Subscription ||\n (value && 'closed' in value && isFunction(value.remove) && isFunction(value.add) && isFunction(value.unsubscribe))\n );\n}\n\nfunction execFinalizer(finalizer: Unsubscribable | (() => void)) {\n if (isFunction(finalizer)) {\n finalizer();\n } else {\n finalizer.unsubscribe();\n }\n}\n", "import { Subscriber } from './Subscriber';\nimport { ObservableNotification } from './types';\n\n/**\n * The {@link GlobalConfig} object for RxJS. It is used to configure things\n * like how to react on unhandled errors.\n */\nexport const config: GlobalConfig = {\n onUnhandledError: null,\n onStoppedNotification: null,\n Promise: undefined,\n useDeprecatedSynchronousErrorHandling: false,\n useDeprecatedNextContext: false,\n};\n\n/**\n * The global configuration object for RxJS, used to configure things\n * like how to react on unhandled errors. Accessible via {@link config}\n * object.\n */\nexport interface GlobalConfig {\n /**\n * A registration point for unhandled errors from RxJS. These are errors that\n * cannot were not handled by consuming code in the usual subscription path. For\n * example, if you have this configured, and you subscribe to an observable without\n * providing an error handler, errors from that subscription will end up here. This\n * will _always_ be called asynchronously on another job in the runtime. This is because\n * we do not want errors thrown in this user-configured handler to interfere with the\n * behavior of the library.\n */\n onUnhandledError: ((err: any) => void) | null;\n\n /**\n * A registration point for notifications that cannot be sent to subscribers because they\n * have completed, errored or have been explicitly unsubscribed. By default, next, complete\n * and error notifications sent to stopped subscribers are noops. However, sometimes callers\n * might want a different behavior. For example, with sources that attempt to report errors\n * to stopped subscribers, a caller can configure RxJS to throw an unhandled error instead.\n * This will _always_ be called asynchronously on another job in the runtime. This is because\n * we do not want errors thrown in this user-configured handler to interfere with the\n * behavior of the library.\n */\n onStoppedNotification: ((notification: ObservableNotification, subscriber: Subscriber) => void) | null;\n\n /**\n * The promise constructor used by default for {@link Observable#toPromise toPromise} and {@link Observable#forEach forEach}\n * methods.\n *\n * @deprecated As of version 8, RxJS will no longer support this sort of injection of a\n * Promise constructor. If you need a Promise implementation other than native promises,\n * please polyfill/patch Promise as you see appropriate. Will be removed in v8.\n */\n Promise?: PromiseConstructorLike;\n\n /**\n * If true, turns on synchronous error rethrowing, which is a deprecated behavior\n * in v6 and higher. This behavior enables bad patterns like wrapping a subscribe\n * call in a try/catch block. It also enables producer interference, a nasty bug\n * where a multicast can be broken for all observers by a downstream consumer with\n * an unhandled error. DO NOT USE THIS FLAG UNLESS IT'S NEEDED TO BUY TIME\n * FOR MIGRATION REASONS.\n *\n * @deprecated As of version 8, RxJS will no longer support synchronous throwing\n * of unhandled errors. All errors will be thrown on a separate call stack to prevent bad\n * behaviors described above. Will be removed in v8.\n */\n useDeprecatedSynchronousErrorHandling: boolean;\n\n /**\n * If true, enables an as-of-yet undocumented feature from v5: The ability to access\n * `unsubscribe()` via `this` context in `next` functions created in observers passed\n * to `subscribe`.\n *\n * This is being removed because the performance was severely problematic, and it could also cause\n * issues when types other than POJOs are passed to subscribe as subscribers, as they will likely have\n * their `this` context overwritten.\n *\n * @deprecated As of version 8, RxJS will no longer support altering the\n * context of next functions provided as part of an observer to Subscribe. Instead,\n * you will have access to a subscription or a signal or token that will allow you to do things like\n * unsubscribe and test closed status. Will be removed in v8.\n */\n useDeprecatedNextContext: boolean;\n}\n", "import type { TimerHandle } from './timerHandle';\ntype SetTimeoutFunction = (handler: () => void, timeout?: number, ...args: any[]) => TimerHandle;\ntype ClearTimeoutFunction = (handle: TimerHandle) => void;\n\ninterface TimeoutProvider {\n setTimeout: SetTimeoutFunction;\n clearTimeout: ClearTimeoutFunction;\n delegate:\n | {\n setTimeout: SetTimeoutFunction;\n clearTimeout: ClearTimeoutFunction;\n }\n | undefined;\n}\n\nexport const timeoutProvider: TimeoutProvider = {\n // When accessing the delegate, use the variable rather than `this` so that\n // the functions can be called without being bound to the provider.\n setTimeout(handler: () => void, timeout?: number, ...args) {\n const { delegate } = timeoutProvider;\n if (delegate?.setTimeout) {\n return delegate.setTimeout(handler, timeout, ...args);\n }\n return setTimeout(handler, timeout, ...args);\n },\n clearTimeout(handle) {\n const { delegate } = timeoutProvider;\n return (delegate?.clearTimeout || clearTimeout)(handle as any);\n },\n delegate: undefined,\n};\n", "import { config } from '../config';\nimport { timeoutProvider } from '../scheduler/timeoutProvider';\n\n/**\n * Handles an error on another job either with the user-configured {@link onUnhandledError},\n * or by throwing it on that new job so it can be picked up by `window.onerror`, `process.on('error')`, etc.\n *\n * This should be called whenever there is an error that is out-of-band with the subscription\n * or when an error hits a terminal boundary of the subscription and no error handler was provided.\n *\n * @param err the error to report\n */\nexport function reportUnhandledError(err: any) {\n timeoutProvider.setTimeout(() => {\n const { onUnhandledError } = config;\n if (onUnhandledError) {\n // Execute the user-configured error handler.\n onUnhandledError(err);\n } else {\n // Throw so it is picked up by the runtime's uncaught error mechanism.\n throw err;\n }\n });\n}\n", "/* tslint:disable:no-empty */\nexport function noop() { }\n", "import { CompleteNotification, NextNotification, ErrorNotification } from './types';\n\n/**\n * A completion object optimized for memory use and created to be the\n * same \"shape\" as other notifications in v8.\n * @internal\n */\nexport const COMPLETE_NOTIFICATION = (() => createNotification('C', undefined, undefined) as CompleteNotification)();\n\n/**\n * Internal use only. Creates an optimized error notification that is the same \"shape\"\n * as other notifications.\n * @internal\n */\nexport function errorNotification(error: any): ErrorNotification {\n return createNotification('E', undefined, error) as any;\n}\n\n/**\n * Internal use only. Creates an optimized next notification that is the same \"shape\"\n * as other notifications.\n * @internal\n */\nexport function nextNotification(value: T) {\n return createNotification('N', value, undefined) as NextNotification;\n}\n\n/**\n * Ensures that all notifications created internally have the same \"shape\" in v8.\n *\n * TODO: This is only exported to support a crazy legacy test in `groupBy`.\n * @internal\n */\nexport function createNotification(kind: 'N' | 'E' | 'C', value: any, error: any) {\n return {\n kind,\n value,\n error,\n };\n}\n", "import { config } from '../config';\n\nlet context: { errorThrown: boolean; error: any } | null = null;\n\n/**\n * Handles dealing with errors for super-gross mode. Creates a context, in which\n * any synchronously thrown errors will be passed to {@link captureError}. Which\n * will record the error such that it will be rethrown after the call back is complete.\n * TODO: Remove in v8\n * @param cb An immediately executed function.\n */\nexport function errorContext(cb: () => void) {\n if (config.useDeprecatedSynchronousErrorHandling) {\n const isRoot = !context;\n if (isRoot) {\n context = { errorThrown: false, error: null };\n }\n cb();\n if (isRoot) {\n const { errorThrown, error } = context!;\n context = null;\n if (errorThrown) {\n throw error;\n }\n }\n } else {\n // This is the general non-deprecated path for everyone that\n // isn't crazy enough to use super-gross mode (useDeprecatedSynchronousErrorHandling)\n cb();\n }\n}\n\n/**\n * Captures errors only in super-gross mode.\n * @param err the error to capture\n */\nexport function captureError(err: any) {\n if (config.useDeprecatedSynchronousErrorHandling && context) {\n context.errorThrown = true;\n context.error = err;\n }\n}\n", "import { isFunction } from './util/isFunction';\nimport { Observer, ObservableNotification } from './types';\nimport { isSubscription, Subscription } from './Subscription';\nimport { config } from './config';\nimport { reportUnhandledError } from './util/reportUnhandledError';\nimport { noop } from './util/noop';\nimport { nextNotification, errorNotification, COMPLETE_NOTIFICATION } from './NotificationFactories';\nimport { timeoutProvider } from './scheduler/timeoutProvider';\nimport { captureError } from './util/errorContext';\n\n/**\n * Implements the {@link Observer} interface and extends the\n * {@link Subscription} class. While the {@link Observer} is the public API for\n * consuming the values of an {@link Observable}, all Observers get converted to\n * a Subscriber, in order to provide Subscription-like capabilities such as\n * `unsubscribe`. Subscriber is a common type in RxJS, and crucial for\n * implementing operators, but it is rarely used as a public API.\n *\n * @class Subscriber\n */\nexport class Subscriber extends Subscription implements Observer {\n /**\n * A static factory for a Subscriber, given a (potentially partial) definition\n * of an Observer.\n * @param next The `next` callback of an Observer.\n * @param error The `error` callback of an\n * Observer.\n * @param complete The `complete` callback of an\n * Observer.\n * @return A Subscriber wrapping the (partially defined)\n * Observer represented by the given arguments.\n * @nocollapse\n * @deprecated Do not use. Will be removed in v8. There is no replacement for this\n * method, and there is no reason to be creating instances of `Subscriber` directly.\n * If you have a specific use case, please file an issue.\n */\n static create(next?: (x?: T) => void, error?: (e?: any) => void, complete?: () => void): Subscriber {\n return new SafeSubscriber(next, error, complete);\n }\n\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n protected isStopped: boolean = false;\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n protected destination: Subscriber | Observer; // this `any` is the escape hatch to erase extra type param (e.g. R)\n\n /**\n * @deprecated Internal implementation detail, do not use directly. Will be made internal in v8.\n * There is no reason to directly create an instance of Subscriber. This type is exported for typings reasons.\n */\n constructor(destination?: Subscriber | Observer) {\n super();\n if (destination) {\n this.destination = destination;\n // Automatically chain subscriptions together here.\n // if destination is a Subscription, then it is a Subscriber.\n if (isSubscription(destination)) {\n destination.add(this);\n }\n } else {\n this.destination = EMPTY_OBSERVER;\n }\n }\n\n /**\n * The {@link Observer} callback to receive notifications of type `next` from\n * the Observable, with a value. The Observable may call this method 0 or more\n * times.\n * @param {T} [value] The `next` value.\n * @return {void}\n */\n next(value?: T): void {\n if (this.isStopped) {\n handleStoppedNotification(nextNotification(value), this);\n } else {\n this._next(value!);\n }\n }\n\n /**\n * The {@link Observer} callback to receive notifications of type `error` from\n * the Observable, with an attached `Error`. Notifies the Observer that\n * the Observable has experienced an error condition.\n * @param {any} [err] The `error` exception.\n * @return {void}\n */\n error(err?: any): void {\n if (this.isStopped) {\n handleStoppedNotification(errorNotification(err), this);\n } else {\n this.isStopped = true;\n this._error(err);\n }\n }\n\n /**\n * The {@link Observer} callback to receive a valueless notification of type\n * `complete` from the Observable. Notifies the Observer that the Observable\n * has finished sending push-based notifications.\n * @return {void}\n */\n complete(): void {\n if (this.isStopped) {\n handleStoppedNotification(COMPLETE_NOTIFICATION, this);\n } else {\n this.isStopped = true;\n this._complete();\n }\n }\n\n unsubscribe(): void {\n if (!this.closed) {\n this.isStopped = true;\n super.unsubscribe();\n this.destination = null!;\n }\n }\n\n protected _next(value: T): void {\n this.destination.next(value);\n }\n\n protected _error(err: any): void {\n try {\n this.destination.error(err);\n } finally {\n this.unsubscribe();\n }\n }\n\n protected _complete(): void {\n try {\n this.destination.complete();\n } finally {\n this.unsubscribe();\n }\n }\n}\n\n/**\n * This bind is captured here because we want to be able to have\n * compatibility with monoid libraries that tend to use a method named\n * `bind`. In particular, a library called Monio requires this.\n */\nconst _bind = Function.prototype.bind;\n\nfunction bind any>(fn: Fn, thisArg: any): Fn {\n return _bind.call(fn, thisArg);\n}\n\n/**\n * Internal optimization only, DO NOT EXPOSE.\n * @internal\n */\nclass ConsumerObserver implements Observer {\n constructor(private partialObserver: Partial>) {}\n\n next(value: T): void {\n const { partialObserver } = this;\n if (partialObserver.next) {\n try {\n partialObserver.next(value);\n } catch (error) {\n handleUnhandledError(error);\n }\n }\n }\n\n error(err: any): void {\n const { partialObserver } = this;\n if (partialObserver.error) {\n try {\n partialObserver.error(err);\n } catch (error) {\n handleUnhandledError(error);\n }\n } else {\n handleUnhandledError(err);\n }\n }\n\n complete(): void {\n const { partialObserver } = this;\n if (partialObserver.complete) {\n try {\n partialObserver.complete();\n } catch (error) {\n handleUnhandledError(error);\n }\n }\n }\n}\n\nexport class SafeSubscriber extends Subscriber {\n constructor(\n observerOrNext?: Partial> | ((value: T) => void) | null,\n error?: ((e?: any) => void) | null,\n complete?: (() => void) | null\n ) {\n super();\n\n let partialObserver: Partial>;\n if (isFunction(observerOrNext) || !observerOrNext) {\n // The first argument is a function, not an observer. The next\n // two arguments *could* be observers, or they could be empty.\n partialObserver = {\n next: (observerOrNext ?? undefined) as (((value: T) => void) | undefined),\n error: error ?? undefined,\n complete: complete ?? undefined,\n };\n } else {\n // The first argument is a partial observer.\n let context: any;\n if (this && config.useDeprecatedNextContext) {\n // This is a deprecated path that made `this.unsubscribe()` available in\n // next handler functions passed to subscribe. This only exists behind a flag\n // now, as it is *very* slow.\n context = Object.create(observerOrNext);\n context.unsubscribe = () => this.unsubscribe();\n partialObserver = {\n next: observerOrNext.next && bind(observerOrNext.next, context),\n error: observerOrNext.error && bind(observerOrNext.error, context),\n complete: observerOrNext.complete && bind(observerOrNext.complete, context),\n };\n } else {\n // The \"normal\" path. Just use the partial observer directly.\n partialObserver = observerOrNext;\n }\n }\n\n // Wrap the partial observer to ensure it's a full observer, and\n // make sure proper error handling is accounted for.\n this.destination = new ConsumerObserver(partialObserver);\n }\n}\n\nfunction handleUnhandledError(error: any) {\n if (config.useDeprecatedSynchronousErrorHandling) {\n captureError(error);\n } else {\n // Ideal path, we report this as an unhandled error,\n // which is thrown on a new call stack.\n reportUnhandledError(error);\n }\n}\n\n/**\n * An error handler used when no error handler was supplied\n * to the SafeSubscriber -- meaning no error handler was supplied\n * do the `subscribe` call on our observable.\n * @param err The error to handle\n */\nfunction defaultErrorHandler(err: any) {\n throw err;\n}\n\n/**\n * A handler for notifications that cannot be sent to a stopped subscriber.\n * @param notification The notification being sent\n * @param subscriber The stopped subscriber\n */\nfunction handleStoppedNotification(notification: ObservableNotification, subscriber: Subscriber) {\n const { onStoppedNotification } = config;\n onStoppedNotification && timeoutProvider.setTimeout(() => onStoppedNotification(notification, subscriber));\n}\n\n/**\n * The observer used as a stub for subscriptions where the user did not\n * pass any arguments to `subscribe`. Comes with the default error handling\n * behavior.\n */\nexport const EMPTY_OBSERVER: Readonly> & { closed: true } = {\n closed: true,\n next: noop,\n error: defaultErrorHandler,\n complete: noop,\n};\n", "/**\n * Symbol.observable or a string \"@@observable\". Used for interop\n *\n * @deprecated We will no longer be exporting this symbol in upcoming versions of RxJS.\n * Instead polyfill and use Symbol.observable directly *or* use https://www.npmjs.com/package/symbol-observable\n */\nexport const observable: string | symbol = (() => (typeof Symbol === 'function' && Symbol.observable) || '@@observable')();\n", "/**\n * This function takes one parameter and just returns it. Simply put,\n * this is like `(x: T): T => x`.\n *\n * ## Examples\n *\n * This is useful in some cases when using things like `mergeMap`\n *\n * ```ts\n * import { interval, take, map, range, mergeMap, identity } from 'rxjs';\n *\n * const source$ = interval(1000).pipe(take(5));\n *\n * const result$ = source$.pipe(\n * map(i => range(i)),\n * mergeMap(identity) // same as mergeMap(x => x)\n * );\n *\n * result$.subscribe({\n * next: console.log\n * });\n * ```\n *\n * Or when you want to selectively apply an operator\n *\n * ```ts\n * import { interval, take, identity } from 'rxjs';\n *\n * const shouldLimit = () => Math.random() < 0.5;\n *\n * const source$ = interval(1000);\n *\n * const result$ = source$.pipe(shouldLimit() ? take(5) : identity);\n *\n * result$.subscribe({\n * next: console.log\n * });\n * ```\n *\n * @param x Any value that is returned by this function\n * @returns The value passed as the first parameter to this function\n */\nexport function identity(x: T): T {\n return x;\n}\n", "import { identity } from './identity';\nimport { UnaryFunction } from '../types';\n\nexport function pipe(): typeof identity;\nexport function pipe(fn1: UnaryFunction): UnaryFunction;\nexport function pipe(fn1: UnaryFunction, fn2: UnaryFunction): UnaryFunction;\nexport function pipe(fn1: UnaryFunction, fn2: UnaryFunction, fn3: UnaryFunction): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction\n): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction,\n fn5: UnaryFunction\n): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction,\n fn5: UnaryFunction,\n fn6: UnaryFunction\n): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction,\n fn5: UnaryFunction,\n fn6: UnaryFunction,\n fn7: UnaryFunction\n): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction,\n fn5: UnaryFunction,\n fn6: UnaryFunction,\n fn7: UnaryFunction,\n fn8: UnaryFunction\n): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction,\n fn5: UnaryFunction,\n fn6: UnaryFunction,\n fn7: UnaryFunction,\n fn8: UnaryFunction,\n fn9: UnaryFunction\n): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction,\n fn5: UnaryFunction,\n fn6: UnaryFunction,\n fn7: UnaryFunction,\n fn8: UnaryFunction,\n fn9: UnaryFunction,\n ...fns: UnaryFunction[]\n): UnaryFunction;\n\n/**\n * pipe() can be called on one or more functions, each of which can take one argument (\"UnaryFunction\")\n * and uses it to return a value.\n * It returns a function that takes one argument, passes it to the first UnaryFunction, and then\n * passes the result to the next one, passes that result to the next one, and so on. \n */\nexport function pipe(...fns: Array>): UnaryFunction {\n return pipeFromArray(fns);\n}\n\n/** @internal */\nexport function pipeFromArray(fns: Array>): UnaryFunction {\n if (fns.length === 0) {\n return identity as UnaryFunction;\n }\n\n if (fns.length === 1) {\n return fns[0];\n }\n\n return function piped(input: T): R {\n return fns.reduce((prev: any, fn: UnaryFunction) => fn(prev), input as any);\n };\n}\n", "import { Operator } from './Operator';\nimport { SafeSubscriber, Subscriber } from './Subscriber';\nimport { isSubscription, Subscription } from './Subscription';\nimport { TeardownLogic, OperatorFunction, Subscribable, Observer } from './types';\nimport { observable as Symbol_observable } from './symbol/observable';\nimport { pipeFromArray } from './util/pipe';\nimport { config } from './config';\nimport { isFunction } from './util/isFunction';\nimport { errorContext } from './util/errorContext';\n\n/**\n * A representation of any set of values over any amount of time. This is the most basic building block\n * of RxJS.\n *\n * @class Observable\n */\nexport class Observable implements Subscribable {\n /**\n * @deprecated Internal implementation detail, do not use directly. Will be made internal in v8.\n */\n source: Observable | undefined;\n\n /**\n * @deprecated Internal implementation detail, do not use directly. Will be made internal in v8.\n */\n operator: Operator | undefined;\n\n /**\n * @constructor\n * @param {Function} subscribe the function that is called when the Observable is\n * initially subscribed to. This function is given a Subscriber, to which new values\n * can be `next`ed, or an `error` method can be called to raise an error, or\n * `complete` can be called to notify of a successful completion.\n */\n constructor(subscribe?: (this: Observable, subscriber: Subscriber) => TeardownLogic) {\n if (subscribe) {\n this._subscribe = subscribe;\n }\n }\n\n // HACK: Since TypeScript inherits static properties too, we have to\n // fight against TypeScript here so Subject can have a different static create signature\n /**\n * Creates a new Observable by calling the Observable constructor\n * @owner Observable\n * @method create\n * @param {Function} subscribe? the subscriber function to be passed to the Observable constructor\n * @return {Observable} a new observable\n * @nocollapse\n * @deprecated Use `new Observable()` instead. Will be removed in v8.\n */\n static create: (...args: any[]) => any = (subscribe?: (subscriber: Subscriber) => TeardownLogic) => {\n return new Observable(subscribe);\n };\n\n /**\n * Creates a new Observable, with this Observable instance as the source, and the passed\n * operator defined as the new observable's operator.\n * @method lift\n * @param operator the operator defining the operation to take on the observable\n * @return a new observable with the Operator applied\n * @deprecated Internal implementation detail, do not use directly. Will be made internal in v8.\n * If you have implemented an operator using `lift`, it is recommended that you create an\n * operator by simply returning `new Observable()` directly. See \"Creating new operators from\n * scratch\" section here: https://rxjs.dev/guide/operators\n */\n lift(operator?: Operator): Observable {\n const observable = new Observable();\n observable.source = this;\n observable.operator = operator;\n return observable;\n }\n\n subscribe(observerOrNext?: Partial> | ((value: T) => void)): Subscription;\n /** @deprecated Instead of passing separate callback arguments, use an observer argument. Signatures taking separate callback arguments will be removed in v8. Details: https://rxjs.dev/deprecations/subscribe-arguments */\n subscribe(next?: ((value: T) => void) | null, error?: ((error: any) => void) | null, complete?: (() => void) | null): Subscription;\n /**\n * Invokes an execution of an Observable and registers Observer handlers for notifications it will emit.\n *\n * Use it when you have all these Observables, but still nothing is happening.\n *\n * `subscribe` is not a regular operator, but a method that calls Observable's internal `subscribe` function. It\n * might be for example a function that you passed to Observable's constructor, but most of the time it is\n * a library implementation, which defines what will be emitted by an Observable, and when it be will emitted. This means\n * that calling `subscribe` is actually the moment when Observable starts its work, not when it is created, as it is often\n * the thought.\n *\n * Apart from starting the execution of an Observable, this method allows you to listen for values\n * that an Observable emits, as well as for when it completes or errors. You can achieve this in two\n * of the following ways.\n *\n * The first way is creating an object that implements {@link Observer} interface. It should have methods\n * defined by that interface, but note that it should be just a regular JavaScript object, which you can create\n * yourself in any way you want (ES6 class, classic function constructor, object literal etc.). In particular, do\n * not attempt to use any RxJS implementation details to create Observers - you don't need them. Remember also\n * that your object does not have to implement all methods. If you find yourself creating a method that doesn't\n * do anything, you can simply omit it. Note however, if the `error` method is not provided and an error happens,\n * it will be thrown asynchronously. Errors thrown asynchronously cannot be caught using `try`/`catch`. Instead,\n * use the {@link onUnhandledError} configuration option or use a runtime handler (like `window.onerror` or\n * `process.on('error)`) to be notified of unhandled errors. Because of this, it's recommended that you provide\n * an `error` method to avoid missing thrown errors.\n *\n * The second way is to give up on Observer object altogether and simply provide callback functions in place of its methods.\n * This means you can provide three functions as arguments to `subscribe`, where the first function is equivalent\n * of a `next` method, the second of an `error` method and the third of a `complete` method. Just as in case of an Observer,\n * if you do not need to listen for something, you can omit a function by passing `undefined` or `null`,\n * since `subscribe` recognizes these functions by where they were placed in function call. When it comes\n * to the `error` function, as with an Observer, if not provided, errors emitted by an Observable will be thrown asynchronously.\n *\n * You can, however, subscribe with no parameters at all. This may be the case where you're not interested in terminal events\n * and you also handled emissions internally by using operators (e.g. using `tap`).\n *\n * Whichever style of calling `subscribe` you use, in both cases it returns a Subscription object.\n * This object allows you to call `unsubscribe` on it, which in turn will stop the work that an Observable does and will clean\n * up all resources that an Observable used. Note that cancelling a subscription will not call `complete` callback\n * provided to `subscribe` function, which is reserved for a regular completion signal that comes from an Observable.\n *\n * Remember that callbacks provided to `subscribe` are not guaranteed to be called asynchronously.\n * It is an Observable itself that decides when these functions will be called. For example {@link of}\n * by default emits all its values synchronously. Always check documentation for how given Observable\n * will behave when subscribed and if its default behavior can be modified with a `scheduler`.\n *\n * #### Examples\n *\n * Subscribe with an {@link guide/observer Observer}\n *\n * ```ts\n * import { of } from 'rxjs';\n *\n * const sumObserver = {\n * sum: 0,\n * next(value) {\n * console.log('Adding: ' + value);\n * this.sum = this.sum + value;\n * },\n * error() {\n * // We actually could just remove this method,\n * // since we do not really care about errors right now.\n * },\n * complete() {\n * console.log('Sum equals: ' + this.sum);\n * }\n * };\n *\n * of(1, 2, 3) // Synchronously emits 1, 2, 3 and then completes.\n * .subscribe(sumObserver);\n *\n * // Logs:\n * // 'Adding: 1'\n * // 'Adding: 2'\n * // 'Adding: 3'\n * // 'Sum equals: 6'\n * ```\n *\n * Subscribe with functions ({@link deprecations/subscribe-arguments deprecated})\n *\n * ```ts\n * import { of } from 'rxjs'\n *\n * let sum = 0;\n *\n * of(1, 2, 3).subscribe(\n * value => {\n * console.log('Adding: ' + value);\n * sum = sum + value;\n * },\n * undefined,\n * () => console.log('Sum equals: ' + sum)\n * );\n *\n * // Logs:\n * // 'Adding: 1'\n * // 'Adding: 2'\n * // 'Adding: 3'\n * // 'Sum equals: 6'\n * ```\n *\n * Cancel a subscription\n *\n * ```ts\n * import { interval } from 'rxjs';\n *\n * const subscription = interval(1000).subscribe({\n * next(num) {\n * console.log(num)\n * },\n * complete() {\n * // Will not be called, even when cancelling subscription.\n * console.log('completed!');\n * }\n * });\n *\n * setTimeout(() => {\n * subscription.unsubscribe();\n * console.log('unsubscribed!');\n * }, 2500);\n *\n * // Logs:\n * // 0 after 1s\n * // 1 after 2s\n * // 'unsubscribed!' after 2.5s\n * ```\n *\n * @param {Observer|Function} observerOrNext (optional) Either an observer with methods to be called,\n * or the first of three possible handlers, which is the handler for each value emitted from the subscribed\n * Observable.\n * @param {Function} error (optional) A handler for a terminal event resulting from an error. If no error handler is provided,\n * the error will be thrown asynchronously as unhandled.\n * @param {Function} complete (optional) A handler for a terminal event resulting from successful completion.\n * @return {Subscription} a subscription reference to the registered handlers\n * @method subscribe\n */\n subscribe(\n observerOrNext?: Partial> | ((value: T) => void) | null,\n error?: ((error: any) => void) | null,\n complete?: (() => void) | null\n ): Subscription {\n const subscriber = isSubscriber(observerOrNext) ? observerOrNext : new SafeSubscriber(observerOrNext, error, complete);\n\n errorContext(() => {\n const { operator, source } = this;\n subscriber.add(\n operator\n ? // We're dealing with a subscription in the\n // operator chain to one of our lifted operators.\n operator.call(subscriber, source)\n : source\n ? // If `source` has a value, but `operator` does not, something that\n // had intimate knowledge of our API, like our `Subject`, must have\n // set it. We're going to just call `_subscribe` directly.\n this._subscribe(subscriber)\n : // In all other cases, we're likely wrapping a user-provided initializer\n // function, so we need to catch errors and handle them appropriately.\n this._trySubscribe(subscriber)\n );\n });\n\n return subscriber;\n }\n\n /** @internal */\n protected _trySubscribe(sink: Subscriber): TeardownLogic {\n try {\n return this._subscribe(sink);\n } catch (err) {\n // We don't need to return anything in this case,\n // because it's just going to try to `add()` to a subscription\n // above.\n sink.error(err);\n }\n }\n\n /**\n * Used as a NON-CANCELLABLE means of subscribing to an observable, for use with\n * APIs that expect promises, like `async/await`. You cannot unsubscribe from this.\n *\n * **WARNING**: Only use this with observables you *know* will complete. If the source\n * observable does not complete, you will end up with a promise that is hung up, and\n * potentially all of the state of an async function hanging out in memory. To avoid\n * this situation, look into adding something like {@link timeout}, {@link take},\n * {@link takeWhile}, or {@link takeUntil} amongst others.\n *\n * #### Example\n *\n * ```ts\n * import { interval, take } from 'rxjs';\n *\n * const source$ = interval(1000).pipe(take(4));\n *\n * async function getTotal() {\n * let total = 0;\n *\n * await source$.forEach(value => {\n * total += value;\n * console.log('observable -> ' + value);\n * });\n *\n * return total;\n * }\n *\n * getTotal().then(\n * total => console.log('Total: ' + total)\n * );\n *\n * // Expected:\n * // 'observable -> 0'\n * // 'observable -> 1'\n * // 'observable -> 2'\n * // 'observable -> 3'\n * // 'Total: 6'\n * ```\n *\n * @param next a handler for each value emitted by the observable\n * @return a promise that either resolves on observable completion or\n * rejects with the handled error\n */\n forEach(next: (value: T) => void): Promise;\n\n /**\n * @param next a handler for each value emitted by the observable\n * @param promiseCtor a constructor function used to instantiate the Promise\n * @return a promise that either resolves on observable completion or\n * rejects with the handled error\n * @deprecated Passing a Promise constructor will no longer be available\n * in upcoming versions of RxJS. This is because it adds weight to the library, for very\n * little benefit. If you need this functionality, it is recommended that you either\n * polyfill Promise, or you create an adapter to convert the returned native promise\n * to whatever promise implementation you wanted. Will be removed in v8.\n */\n forEach(next: (value: T) => void, promiseCtor: PromiseConstructorLike): Promise;\n\n forEach(next: (value: T) => void, promiseCtor?: PromiseConstructorLike): Promise {\n promiseCtor = getPromiseCtor(promiseCtor);\n\n return new promiseCtor((resolve, reject) => {\n const subscriber = new SafeSubscriber({\n next: (value) => {\n try {\n next(value);\n } catch (err) {\n reject(err);\n subscriber.unsubscribe();\n }\n },\n error: reject,\n complete: resolve,\n });\n this.subscribe(subscriber);\n }) as Promise;\n }\n\n /** @internal */\n protected _subscribe(subscriber: Subscriber): TeardownLogic {\n return this.source?.subscribe(subscriber);\n }\n\n /**\n * An interop point defined by the es7-observable spec https://github.com/zenparsing/es-observable\n * @method Symbol.observable\n * @return {Observable} this instance of the observable\n */\n [Symbol_observable]() {\n return this;\n }\n\n /* tslint:disable:max-line-length */\n pipe(): Observable;\n pipe(op1: OperatorFunction): Observable;\n pipe(op1: OperatorFunction, op2: OperatorFunction): Observable;\n pipe(op1: OperatorFunction, op2: OperatorFunction, op3: OperatorFunction): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction\n ): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction,\n op5: OperatorFunction\n ): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction,\n op5: OperatorFunction,\n op6: OperatorFunction\n ): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction,\n op5: OperatorFunction,\n op6: OperatorFunction,\n op7: OperatorFunction\n ): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction,\n op5: OperatorFunction,\n op6: OperatorFunction,\n op7: OperatorFunction,\n op8: OperatorFunction\n ): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction,\n op5: OperatorFunction,\n op6: OperatorFunction,\n op7: OperatorFunction,\n op8: OperatorFunction,\n op9: OperatorFunction\n ): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction,\n op5: OperatorFunction,\n op6: OperatorFunction,\n op7: OperatorFunction,\n op8: OperatorFunction,\n op9: OperatorFunction,\n ...operations: OperatorFunction[]\n ): Observable;\n /* tslint:enable:max-line-length */\n\n /**\n * Used to stitch together functional operators into a chain.\n * @method pipe\n * @return {Observable} the Observable result of all of the operators having\n * been called in the order they were passed in.\n *\n * ## Example\n *\n * ```ts\n * import { interval, filter, map, scan } from 'rxjs';\n *\n * interval(1000)\n * .pipe(\n * filter(x => x % 2 === 0),\n * map(x => x + x),\n * scan((acc, x) => acc + x)\n * )\n * .subscribe(x => console.log(x));\n * ```\n */\n pipe(...operations: OperatorFunction[]): Observable {\n return pipeFromArray(operations)(this);\n }\n\n /* tslint:disable:max-line-length */\n /** @deprecated Replaced with {@link firstValueFrom} and {@link lastValueFrom}. Will be removed in v8. Details: https://rxjs.dev/deprecations/to-promise */\n toPromise(): Promise;\n /** @deprecated Replaced with {@link firstValueFrom} and {@link lastValueFrom}. Will be removed in v8. Details: https://rxjs.dev/deprecations/to-promise */\n toPromise(PromiseCtor: typeof Promise): Promise;\n /** @deprecated Replaced with {@link firstValueFrom} and {@link lastValueFrom}. Will be removed in v8. Details: https://rxjs.dev/deprecations/to-promise */\n toPromise(PromiseCtor: PromiseConstructorLike): Promise;\n /* tslint:enable:max-line-length */\n\n /**\n * Subscribe to this Observable and get a Promise resolving on\n * `complete` with the last emission (if any).\n *\n * **WARNING**: Only use this with observables you *know* will complete. If the source\n * observable does not complete, you will end up with a promise that is hung up, and\n * potentially all of the state of an async function hanging out in memory. To avoid\n * this situation, look into adding something like {@link timeout}, {@link take},\n * {@link takeWhile}, or {@link takeUntil} amongst others.\n *\n * @method toPromise\n * @param [promiseCtor] a constructor function used to instantiate\n * the Promise\n * @return A Promise that resolves with the last value emit, or\n * rejects on an error. If there were no emissions, Promise\n * resolves with undefined.\n * @deprecated Replaced with {@link firstValueFrom} and {@link lastValueFrom}. Will be removed in v8. Details: https://rxjs.dev/deprecations/to-promise\n */\n toPromise(promiseCtor?: PromiseConstructorLike): Promise {\n promiseCtor = getPromiseCtor(promiseCtor);\n\n return new promiseCtor((resolve, reject) => {\n let value: T | undefined;\n this.subscribe(\n (x: T) => (value = x),\n (err: any) => reject(err),\n () => resolve(value)\n );\n }) as Promise;\n }\n}\n\n/**\n * Decides between a passed promise constructor from consuming code,\n * A default configured promise constructor, and the native promise\n * constructor and returns it. If nothing can be found, it will throw\n * an error.\n * @param promiseCtor The optional promise constructor to passed by consuming code\n */\nfunction getPromiseCtor(promiseCtor: PromiseConstructorLike | undefined) {\n return promiseCtor ?? config.Promise ?? Promise;\n}\n\nfunction isObserver(value: any): value is Observer {\n return value && isFunction(value.next) && isFunction(value.error) && isFunction(value.complete);\n}\n\nfunction isSubscriber(value: any): value is Subscriber {\n return (value && value instanceof Subscriber) || (isObserver(value) && isSubscription(value));\n}\n", "import { Observable } from '../Observable';\nimport { Subscriber } from '../Subscriber';\nimport { OperatorFunction } from '../types';\nimport { isFunction } from './isFunction';\n\n/**\n * Used to determine if an object is an Observable with a lift function.\n */\nexport function hasLift(source: any): source is { lift: InstanceType['lift'] } {\n return isFunction(source?.lift);\n}\n\n/**\n * Creates an `OperatorFunction`. Used to define operators throughout the library in a concise way.\n * @param init The logic to connect the liftedSource to the subscriber at the moment of subscription.\n */\nexport function operate(\n init: (liftedSource: Observable, subscriber: Subscriber) => (() => void) | void\n): OperatorFunction {\n return (source: Observable) => {\n if (hasLift(source)) {\n return source.lift(function (this: Subscriber, liftedSource: Observable) {\n try {\n return init(liftedSource, this);\n } catch (err) {\n this.error(err);\n }\n });\n }\n throw new TypeError('Unable to lift unknown Observable type');\n };\n}\n", "import { Subscriber } from '../Subscriber';\n\n/**\n * Creates an instance of an `OperatorSubscriber`.\n * @param destination The downstream subscriber.\n * @param onNext Handles next values, only called if this subscriber is not stopped or closed. Any\n * error that occurs in this function is caught and sent to the `error` method of this subscriber.\n * @param onError Handles errors from the subscription, any errors that occur in this handler are caught\n * and send to the `destination` error handler.\n * @param onComplete Handles completion notification from the subscription. Any errors that occur in\n * this handler are sent to the `destination` error handler.\n * @param onFinalize Additional teardown logic here. This will only be called on teardown if the\n * subscriber itself is not already closed. This is called after all other teardown logic is executed.\n */\nexport function createOperatorSubscriber(\n destination: Subscriber,\n onNext?: (value: T) => void,\n onComplete?: () => void,\n onError?: (err: any) => void,\n onFinalize?: () => void\n): Subscriber {\n return new OperatorSubscriber(destination, onNext, onComplete, onError, onFinalize);\n}\n\n/**\n * A generic helper for allowing operators to be created with a Subscriber and\n * use closures to capture necessary state from the operator function itself.\n */\nexport class OperatorSubscriber extends Subscriber {\n /**\n * Creates an instance of an `OperatorSubscriber`.\n * @param destination The downstream subscriber.\n * @param onNext Handles next values, only called if this subscriber is not stopped or closed. Any\n * error that occurs in this function is caught and sent to the `error` method of this subscriber.\n * @param onError Handles errors from the subscription, any errors that occur in this handler are caught\n * and send to the `destination` error handler.\n * @param onComplete Handles completion notification from the subscription. Any errors that occur in\n * this handler are sent to the `destination` error handler.\n * @param onFinalize Additional finalization logic here. This will only be called on finalization if the\n * subscriber itself is not already closed. This is called after all other finalization logic is executed.\n * @param shouldUnsubscribe An optional check to see if an unsubscribe call should truly unsubscribe.\n * NOTE: This currently **ONLY** exists to support the strange behavior of {@link groupBy}, where unsubscription\n * to the resulting observable does not actually disconnect from the source if there are active subscriptions\n * to any grouped observable. (DO NOT EXPOSE OR USE EXTERNALLY!!!)\n */\n constructor(\n destination: Subscriber,\n onNext?: (value: T) => void,\n onComplete?: () => void,\n onError?: (err: any) => void,\n private onFinalize?: () => void,\n private shouldUnsubscribe?: () => boolean\n ) {\n // It's important - for performance reasons - that all of this class's\n // members are initialized and that they are always initialized in the same\n // order. This will ensure that all OperatorSubscriber instances have the\n // same hidden class in V8. This, in turn, will help keep the number of\n // hidden classes involved in property accesses within the base class as\n // low as possible. If the number of hidden classes involved exceeds four,\n // the property accesses will become megamorphic and performance penalties\n // will be incurred - i.e. inline caches won't be used.\n //\n // The reasons for ensuring all instances have the same hidden class are\n // further discussed in this blog post from Benedikt Meurer:\n // https://benediktmeurer.de/2018/03/23/impact-of-polymorphism-on-component-based-frameworks-like-react/\n super(destination);\n this._next = onNext\n ? function (this: OperatorSubscriber, value: T) {\n try {\n onNext(value);\n } catch (err) {\n destination.error(err);\n }\n }\n : super._next;\n this._error = onError\n ? function (this: OperatorSubscriber, err: any) {\n try {\n onError(err);\n } catch (err) {\n // Send any errors that occur down stream.\n destination.error(err);\n } finally {\n // Ensure finalization.\n this.unsubscribe();\n }\n }\n : super._error;\n this._complete = onComplete\n ? function (this: OperatorSubscriber) {\n try {\n onComplete();\n } catch (err) {\n // Send any errors that occur down stream.\n destination.error(err);\n } finally {\n // Ensure finalization.\n this.unsubscribe();\n }\n }\n : super._complete;\n }\n\n unsubscribe() {\n if (!this.shouldUnsubscribe || this.shouldUnsubscribe()) {\n const { closed } = this;\n super.unsubscribe();\n // Execute additional teardown if we have any and we didn't already do so.\n !closed && this.onFinalize?.();\n }\n }\n}\n", "import { Subscription } from '../Subscription';\n\ninterface AnimationFrameProvider {\n schedule(callback: FrameRequestCallback): Subscription;\n requestAnimationFrame: typeof requestAnimationFrame;\n cancelAnimationFrame: typeof cancelAnimationFrame;\n delegate:\n | {\n requestAnimationFrame: typeof requestAnimationFrame;\n cancelAnimationFrame: typeof cancelAnimationFrame;\n }\n | undefined;\n}\n\nexport const animationFrameProvider: AnimationFrameProvider = {\n // When accessing the delegate, use the variable rather than `this` so that\n // the functions can be called without being bound to the provider.\n schedule(callback) {\n let request = requestAnimationFrame;\n let cancel: typeof cancelAnimationFrame | undefined = cancelAnimationFrame;\n const { delegate } = animationFrameProvider;\n if (delegate) {\n request = delegate.requestAnimationFrame;\n cancel = delegate.cancelAnimationFrame;\n }\n const handle = request((timestamp) => {\n // Clear the cancel function. The request has been fulfilled, so\n // attempting to cancel the request upon unsubscription would be\n // pointless.\n cancel = undefined;\n callback(timestamp);\n });\n return new Subscription(() => cancel?.(handle));\n },\n requestAnimationFrame(...args) {\n const { delegate } = animationFrameProvider;\n return (delegate?.requestAnimationFrame || requestAnimationFrame)(...args);\n },\n cancelAnimationFrame(...args) {\n const { delegate } = animationFrameProvider;\n return (delegate?.cancelAnimationFrame || cancelAnimationFrame)(...args);\n },\n delegate: undefined,\n};\n", "import { createErrorClass } from './createErrorClass';\n\nexport interface ObjectUnsubscribedError extends Error {}\n\nexport interface ObjectUnsubscribedErrorCtor {\n /**\n * @deprecated Internal implementation detail. Do not construct error instances.\n * Cannot be tagged as internal: https://github.com/ReactiveX/rxjs/issues/6269\n */\n new (): ObjectUnsubscribedError;\n}\n\n/**\n * An error thrown when an action is invalid because the object has been\n * unsubscribed.\n *\n * @see {@link Subject}\n * @see {@link BehaviorSubject}\n *\n * @class ObjectUnsubscribedError\n */\nexport const ObjectUnsubscribedError: ObjectUnsubscribedErrorCtor = createErrorClass(\n (_super) =>\n function ObjectUnsubscribedErrorImpl(this: any) {\n _super(this);\n this.name = 'ObjectUnsubscribedError';\n this.message = 'object unsubscribed';\n }\n);\n", "import { Operator } from './Operator';\nimport { Observable } from './Observable';\nimport { Subscriber } from './Subscriber';\nimport { Subscription, EMPTY_SUBSCRIPTION } from './Subscription';\nimport { Observer, SubscriptionLike, TeardownLogic } from './types';\nimport { ObjectUnsubscribedError } from './util/ObjectUnsubscribedError';\nimport { arrRemove } from './util/arrRemove';\nimport { errorContext } from './util/errorContext';\n\n/**\n * A Subject is a special type of Observable that allows values to be\n * multicasted to many Observers. Subjects are like EventEmitters.\n *\n * Every Subject is an Observable and an Observer. You can subscribe to a\n * Subject, and you can call next to feed values as well as error and complete.\n */\nexport class Subject extends Observable implements SubscriptionLike {\n closed = false;\n\n private currentObservers: Observer[] | null = null;\n\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n observers: Observer[] = [];\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n isStopped = false;\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n hasError = false;\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n thrownError: any = null;\n\n /**\n * Creates a \"subject\" by basically gluing an observer to an observable.\n *\n * @nocollapse\n * @deprecated Recommended you do not use. Will be removed at some point in the future. Plans for replacement still under discussion.\n */\n static create: (...args: any[]) => any = (destination: Observer, source: Observable): AnonymousSubject => {\n return new AnonymousSubject(destination, source);\n };\n\n constructor() {\n // NOTE: This must be here to obscure Observable's constructor.\n super();\n }\n\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n lift(operator: Operator): Observable {\n const subject = new AnonymousSubject(this, this);\n subject.operator = operator as any;\n return subject as any;\n }\n\n /** @internal */\n protected _throwIfClosed() {\n if (this.closed) {\n throw new ObjectUnsubscribedError();\n }\n }\n\n next(value: T) {\n errorContext(() => {\n this._throwIfClosed();\n if (!this.isStopped) {\n if (!this.currentObservers) {\n this.currentObservers = Array.from(this.observers);\n }\n for (const observer of this.currentObservers) {\n observer.next(value);\n }\n }\n });\n }\n\n error(err: any) {\n errorContext(() => {\n this._throwIfClosed();\n if (!this.isStopped) {\n this.hasError = this.isStopped = true;\n this.thrownError = err;\n const { observers } = this;\n while (observers.length) {\n observers.shift()!.error(err);\n }\n }\n });\n }\n\n complete() {\n errorContext(() => {\n this._throwIfClosed();\n if (!this.isStopped) {\n this.isStopped = true;\n const { observers } = this;\n while (observers.length) {\n observers.shift()!.complete();\n }\n }\n });\n }\n\n unsubscribe() {\n this.isStopped = this.closed = true;\n this.observers = this.currentObservers = null!;\n }\n\n get observed() {\n return this.observers?.length > 0;\n }\n\n /** @internal */\n protected _trySubscribe(subscriber: Subscriber): TeardownLogic {\n this._throwIfClosed();\n return super._trySubscribe(subscriber);\n }\n\n /** @internal */\n protected _subscribe(subscriber: Subscriber): Subscription {\n this._throwIfClosed();\n this._checkFinalizedStatuses(subscriber);\n return this._innerSubscribe(subscriber);\n }\n\n /** @internal */\n protected _innerSubscribe(subscriber: Subscriber) {\n const { hasError, isStopped, observers } = this;\n if (hasError || isStopped) {\n return EMPTY_SUBSCRIPTION;\n }\n this.currentObservers = null;\n observers.push(subscriber);\n return new Subscription(() => {\n this.currentObservers = null;\n arrRemove(observers, subscriber);\n });\n }\n\n /** @internal */\n protected _checkFinalizedStatuses(subscriber: Subscriber) {\n const { hasError, thrownError, isStopped } = this;\n if (hasError) {\n subscriber.error(thrownError);\n } else if (isStopped) {\n subscriber.complete();\n }\n }\n\n /**\n * Creates a new Observable with this Subject as the source. You can do this\n * to create custom Observer-side logic of the Subject and conceal it from\n * code that uses the Observable.\n * @return {Observable} Observable that the Subject casts to\n */\n asObservable(): Observable {\n const observable: any = new Observable();\n observable.source = this;\n return observable;\n }\n}\n\n/**\n * @class AnonymousSubject\n */\nexport class AnonymousSubject extends Subject {\n constructor(\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n public destination?: Observer,\n source?: Observable\n ) {\n super();\n this.source = source;\n }\n\n next(value: T) {\n this.destination?.next?.(value);\n }\n\n error(err: any) {\n this.destination?.error?.(err);\n }\n\n complete() {\n this.destination?.complete?.();\n }\n\n /** @internal */\n protected _subscribe(subscriber: Subscriber): Subscription {\n return this.source?.subscribe(subscriber) ?? EMPTY_SUBSCRIPTION;\n }\n}\n", "import { Subject } from './Subject';\nimport { Subscriber } from './Subscriber';\nimport { Subscription } from './Subscription';\n\n/**\n * A variant of Subject that requires an initial value and emits its current\n * value whenever it is subscribed to.\n *\n * @class BehaviorSubject\n */\nexport class BehaviorSubject extends Subject {\n constructor(private _value: T) {\n super();\n }\n\n get value(): T {\n return this.getValue();\n }\n\n /** @internal */\n protected _subscribe(subscriber: Subscriber): Subscription {\n const subscription = super._subscribe(subscriber);\n !subscription.closed && subscriber.next(this._value);\n return subscription;\n }\n\n getValue(): T {\n const { hasError, thrownError, _value } = this;\n if (hasError) {\n throw thrownError;\n }\n this._throwIfClosed();\n return _value;\n }\n\n next(value: T): void {\n super.next((this._value = value));\n }\n}\n", "import { TimestampProvider } from '../types';\n\ninterface DateTimestampProvider extends TimestampProvider {\n delegate: TimestampProvider | undefined;\n}\n\nexport const dateTimestampProvider: DateTimestampProvider = {\n now() {\n // Use the variable rather than `this` so that the function can be called\n // without being bound to the provider.\n return (dateTimestampProvider.delegate || Date).now();\n },\n delegate: undefined,\n};\n", "import { Subject } from './Subject';\nimport { TimestampProvider } from './types';\nimport { Subscriber } from './Subscriber';\nimport { Subscription } from './Subscription';\nimport { dateTimestampProvider } from './scheduler/dateTimestampProvider';\n\n/**\n * A variant of {@link Subject} that \"replays\" old values to new subscribers by emitting them when they first subscribe.\n *\n * `ReplaySubject` has an internal buffer that will store a specified number of values that it has observed. Like `Subject`,\n * `ReplaySubject` \"observes\" values by having them passed to its `next` method. When it observes a value, it will store that\n * value for a time determined by the configuration of the `ReplaySubject`, as passed to its constructor.\n *\n * When a new subscriber subscribes to the `ReplaySubject` instance, it will synchronously emit all values in its buffer in\n * a First-In-First-Out (FIFO) manner. The `ReplaySubject` will also complete, if it has observed completion; and it will\n * error if it has observed an error.\n *\n * There are two main configuration items to be concerned with:\n *\n * 1. `bufferSize` - This will determine how many items are stored in the buffer, defaults to infinite.\n * 2. `windowTime` - The amount of time to hold a value in the buffer before removing it from the buffer.\n *\n * Both configurations may exist simultaneously. So if you would like to buffer a maximum of 3 values, as long as the values\n * are less than 2 seconds old, you could do so with a `new ReplaySubject(3, 2000)`.\n *\n * ### Differences with BehaviorSubject\n *\n * `BehaviorSubject` is similar to `new ReplaySubject(1)`, with a couple of exceptions:\n *\n * 1. `BehaviorSubject` comes \"primed\" with a single value upon construction.\n * 2. `ReplaySubject` will replay values, even after observing an error, where `BehaviorSubject` will not.\n *\n * @see {@link Subject}\n * @see {@link BehaviorSubject}\n * @see {@link shareReplay}\n */\nexport class ReplaySubject extends Subject {\n private _buffer: (T | number)[] = [];\n private _infiniteTimeWindow = true;\n\n /**\n * @param bufferSize The size of the buffer to replay on subscription\n * @param windowTime The amount of time the buffered items will stay buffered\n * @param timestampProvider An object with a `now()` method that provides the current timestamp. This is used to\n * calculate the amount of time something has been buffered.\n */\n constructor(\n private _bufferSize = Infinity,\n private _windowTime = Infinity,\n private _timestampProvider: TimestampProvider = dateTimestampProvider\n ) {\n super();\n this._infiniteTimeWindow = _windowTime === Infinity;\n this._bufferSize = Math.max(1, _bufferSize);\n this._windowTime = Math.max(1, _windowTime);\n }\n\n next(value: T): void {\n const { isStopped, _buffer, _infiniteTimeWindow, _timestampProvider, _windowTime } = this;\n if (!isStopped) {\n _buffer.push(value);\n !_infiniteTimeWindow && _buffer.push(_timestampProvider.now() + _windowTime);\n }\n this._trimBuffer();\n super.next(value);\n }\n\n /** @internal */\n protected _subscribe(subscriber: Subscriber): Subscription {\n this._throwIfClosed();\n this._trimBuffer();\n\n const subscription = this._innerSubscribe(subscriber);\n\n const { _infiniteTimeWindow, _buffer } = this;\n // We use a copy here, so reentrant code does not mutate our array while we're\n // emitting it to a new subscriber.\n const copy = _buffer.slice();\n for (let i = 0; i < copy.length && !subscriber.closed; i += _infiniteTimeWindow ? 1 : 2) {\n subscriber.next(copy[i] as T);\n }\n\n this._checkFinalizedStatuses(subscriber);\n\n return subscription;\n }\n\n private _trimBuffer() {\n const { _bufferSize, _timestampProvider, _buffer, _infiniteTimeWindow } = this;\n // If we don't have an infinite buffer size, and we're over the length,\n // use splice to truncate the old buffer values off. Note that we have to\n // double the size for instances where we're not using an infinite time window\n // because we're storing the values and the timestamps in the same array.\n const adjustedBufferSize = (_infiniteTimeWindow ? 1 : 2) * _bufferSize;\n _bufferSize < Infinity && adjustedBufferSize < _buffer.length && _buffer.splice(0, _buffer.length - adjustedBufferSize);\n\n // Now, if we're not in an infinite time window, remove all values where the time is\n // older than what is allowed.\n if (!_infiniteTimeWindow) {\n const now = _timestampProvider.now();\n let last = 0;\n // Search the array for the first timestamp that isn't expired and\n // truncate the buffer up to that point.\n for (let i = 1; i < _buffer.length && (_buffer[i] as number) <= now; i += 2) {\n last = i;\n }\n last && _buffer.splice(0, last + 1);\n }\n }\n}\n", "import { Scheduler } from '../Scheduler';\nimport { Subscription } from '../Subscription';\nimport { SchedulerAction } from '../types';\n\n/**\n * A unit of work to be executed in a `scheduler`. An action is typically\n * created from within a {@link SchedulerLike} and an RxJS user does not need to concern\n * themselves about creating and manipulating an Action.\n *\n * ```ts\n * class Action extends Subscription {\n * new (scheduler: Scheduler, work: (state?: T) => void);\n * schedule(state?: T, delay: number = 0): Subscription;\n * }\n * ```\n *\n * @class Action\n */\nexport class Action extends Subscription {\n constructor(scheduler: Scheduler, work: (this: SchedulerAction, state?: T) => void) {\n super();\n }\n /**\n * Schedules this action on its parent {@link SchedulerLike} for execution. May be passed\n * some context object, `state`. May happen at some point in the future,\n * according to the `delay` parameter, if specified.\n * @param {T} [state] Some contextual data that the `work` function uses when\n * called by the Scheduler.\n * @param {number} [delay] Time to wait before executing the work, where the\n * time unit is implicit and defined by the Scheduler.\n * @return {void}\n */\n public schedule(state?: T, delay: number = 0): Subscription {\n return this;\n }\n}\n", "import type { TimerHandle } from './timerHandle';\ntype SetIntervalFunction = (handler: () => void, timeout?: number, ...args: any[]) => TimerHandle;\ntype ClearIntervalFunction = (handle: TimerHandle) => void;\n\ninterface IntervalProvider {\n setInterval: SetIntervalFunction;\n clearInterval: ClearIntervalFunction;\n delegate:\n | {\n setInterval: SetIntervalFunction;\n clearInterval: ClearIntervalFunction;\n }\n | undefined;\n}\n\nexport const intervalProvider: IntervalProvider = {\n // When accessing the delegate, use the variable rather than `this` so that\n // the functions can be called without being bound to the provider.\n setInterval(handler: () => void, timeout?: number, ...args) {\n const { delegate } = intervalProvider;\n if (delegate?.setInterval) {\n return delegate.setInterval(handler, timeout, ...args);\n }\n return setInterval(handler, timeout, ...args);\n },\n clearInterval(handle) {\n const { delegate } = intervalProvider;\n return (delegate?.clearInterval || clearInterval)(handle as any);\n },\n delegate: undefined,\n};\n", "import { Action } from './Action';\nimport { SchedulerAction } from '../types';\nimport { Subscription } from '../Subscription';\nimport { AsyncScheduler } from './AsyncScheduler';\nimport { intervalProvider } from './intervalProvider';\nimport { arrRemove } from '../util/arrRemove';\nimport { TimerHandle } from './timerHandle';\n\nexport class AsyncAction extends Action {\n public id: TimerHandle | undefined;\n public state?: T;\n // @ts-ignore: Property has no initializer and is not definitely assigned\n public delay: number;\n protected pending: boolean = false;\n\n constructor(protected scheduler: AsyncScheduler, protected work: (this: SchedulerAction, state?: T) => void) {\n super(scheduler, work);\n }\n\n public schedule(state?: T, delay: number = 0): Subscription {\n if (this.closed) {\n return this;\n }\n\n // Always replace the current state with the new state.\n this.state = state;\n\n const id = this.id;\n const scheduler = this.scheduler;\n\n //\n // Important implementation note:\n //\n // Actions only execute once by default, unless rescheduled from within the\n // scheduled callback. This allows us to implement single and repeat\n // actions via the same code path, without adding API surface area, as well\n // as mimic traditional recursion but across asynchronous boundaries.\n //\n // However, JS runtimes and timers distinguish between intervals achieved by\n // serial `setTimeout` calls vs. a single `setInterval` call. An interval of\n // serial `setTimeout` calls can be individually delayed, which delays\n // scheduling the next `setTimeout`, and so on. `setInterval` attempts to\n // guarantee the interval callback will be invoked more precisely to the\n // interval period, regardless of load.\n //\n // Therefore, we use `setInterval` to schedule single and repeat actions.\n // If the action reschedules itself with the same delay, the interval is not\n // canceled. If the action doesn't reschedule, or reschedules with a\n // different delay, the interval will be canceled after scheduled callback\n // execution.\n //\n if (id != null) {\n this.id = this.recycleAsyncId(scheduler, id, delay);\n }\n\n // Set the pending flag indicating that this action has been scheduled, or\n // has recursively rescheduled itself.\n this.pending = true;\n\n this.delay = delay;\n // If this action has already an async Id, don't request a new one.\n this.id = this.id ?? this.requestAsyncId(scheduler, this.id, delay);\n\n return this;\n }\n\n protected requestAsyncId(scheduler: AsyncScheduler, _id?: TimerHandle, delay: number = 0): TimerHandle {\n return intervalProvider.setInterval(scheduler.flush.bind(scheduler, this), delay);\n }\n\n protected recycleAsyncId(_scheduler: AsyncScheduler, id?: TimerHandle, delay: number | null = 0): TimerHandle | undefined {\n // If this action is rescheduled with the same delay time, don't clear the interval id.\n if (delay != null && this.delay === delay && this.pending === false) {\n return id;\n }\n // Otherwise, if the action's delay time is different from the current delay,\n // or the action has been rescheduled before it's executed, clear the interval id\n if (id != null) {\n intervalProvider.clearInterval(id);\n }\n\n return undefined;\n }\n\n /**\n * Immediately executes this action and the `work` it contains.\n * @return {any}\n */\n public execute(state: T, delay: number): any {\n if (this.closed) {\n return new Error('executing a cancelled action');\n }\n\n this.pending = false;\n const error = this._execute(state, delay);\n if (error) {\n return error;\n } else if (this.pending === false && this.id != null) {\n // Dequeue if the action didn't reschedule itself. Don't call\n // unsubscribe(), because the action could reschedule later.\n // For example:\n // ```\n // scheduler.schedule(function doWork(counter) {\n // /* ... I'm a busy worker bee ... */\n // var originalAction = this;\n // /* wait 100ms before rescheduling the action */\n // setTimeout(function () {\n // originalAction.schedule(counter + 1);\n // }, 100);\n // }, 1000);\n // ```\n this.id = this.recycleAsyncId(this.scheduler, this.id, null);\n }\n }\n\n protected _execute(state: T, _delay: number): any {\n let errored: boolean = false;\n let errorValue: any;\n try {\n this.work(state);\n } catch (e) {\n errored = true;\n // HACK: Since code elsewhere is relying on the \"truthiness\" of the\n // return here, we can't have it return \"\" or 0 or false.\n // TODO: Clean this up when we refactor schedulers mid-version-8 or so.\n errorValue = e ? e : new Error('Scheduled action threw falsy error');\n }\n if (errored) {\n this.unsubscribe();\n return errorValue;\n }\n }\n\n unsubscribe() {\n if (!this.closed) {\n const { id, scheduler } = this;\n const { actions } = scheduler;\n\n this.work = this.state = this.scheduler = null!;\n this.pending = false;\n\n arrRemove(actions, this);\n if (id != null) {\n this.id = this.recycleAsyncId(scheduler, id, null);\n }\n\n this.delay = null!;\n super.unsubscribe();\n }\n }\n}\n", "import { Action } from './scheduler/Action';\nimport { Subscription } from './Subscription';\nimport { SchedulerLike, SchedulerAction } from './types';\nimport { dateTimestampProvider } from './scheduler/dateTimestampProvider';\n\n/**\n * An execution context and a data structure to order tasks and schedule their\n * execution. Provides a notion of (potentially virtual) time, through the\n * `now()` getter method.\n *\n * Each unit of work in a Scheduler is called an `Action`.\n *\n * ```ts\n * class Scheduler {\n * now(): number;\n * schedule(work, delay?, state?): Subscription;\n * }\n * ```\n *\n * @class Scheduler\n * @deprecated Scheduler is an internal implementation detail of RxJS, and\n * should not be used directly. Rather, create your own class and implement\n * {@link SchedulerLike}. Will be made internal in v8.\n */\nexport class Scheduler implements SchedulerLike {\n public static now: () => number = dateTimestampProvider.now;\n\n constructor(private schedulerActionCtor: typeof Action, now: () => number = Scheduler.now) {\n this.now = now;\n }\n\n /**\n * A getter method that returns a number representing the current time\n * (at the time this function was called) according to the scheduler's own\n * internal clock.\n * @return {number} A number that represents the current time. May or may not\n * have a relation to wall-clock time. May or may not refer to a time unit\n * (e.g. milliseconds).\n */\n public now: () => number;\n\n /**\n * Schedules a function, `work`, for execution. May happen at some point in\n * the future, according to the `delay` parameter, if specified. May be passed\n * some context object, `state`, which will be passed to the `work` function.\n *\n * The given arguments will be processed an stored as an Action object in a\n * queue of actions.\n *\n * @param {function(state: ?T): ?Subscription} work A function representing a\n * task, or some unit of work to be executed by the Scheduler.\n * @param {number} [delay] Time to wait before executing the work, where the\n * time unit is implicit and defined by the Scheduler itself.\n * @param {T} [state] Some contextual data that the `work` function uses when\n * called by the Scheduler.\n * @return {Subscription} A subscription in order to be able to unsubscribe\n * the scheduled work.\n */\n public schedule(work: (this: SchedulerAction, state?: T) => void, delay: number = 0, state?: T): Subscription {\n return new this.schedulerActionCtor(this, work).schedule(state, delay);\n }\n}\n", "import { Scheduler } from '../Scheduler';\nimport { Action } from './Action';\nimport { AsyncAction } from './AsyncAction';\nimport { TimerHandle } from './timerHandle';\n\nexport class AsyncScheduler extends Scheduler {\n public actions: Array> = [];\n /**\n * A flag to indicate whether the Scheduler is currently executing a batch of\n * queued actions.\n * @type {boolean}\n * @internal\n */\n public _active: boolean = false;\n /**\n * An internal ID used to track the latest asynchronous task such as those\n * coming from `setTimeout`, `setInterval`, `requestAnimationFrame`, and\n * others.\n * @type {any}\n * @internal\n */\n public _scheduled: TimerHandle | undefined;\n\n constructor(SchedulerAction: typeof Action, now: () => number = Scheduler.now) {\n super(SchedulerAction, now);\n }\n\n public flush(action: AsyncAction): void {\n const { actions } = this;\n\n if (this._active) {\n actions.push(action);\n return;\n }\n\n let error: any;\n this._active = true;\n\n do {\n if ((error = action.execute(action.state, action.delay))) {\n break;\n }\n } while ((action = actions.shift()!)); // exhaust the scheduler queue\n\n this._active = false;\n\n if (error) {\n while ((action = actions.shift()!)) {\n action.unsubscribe();\n }\n throw error;\n }\n }\n}\n", "import { AsyncAction } from './AsyncAction';\nimport { AsyncScheduler } from './AsyncScheduler';\n\n/**\n *\n * Async Scheduler\n *\n * Schedule task as if you used setTimeout(task, duration)\n *\n * `async` scheduler schedules tasks asynchronously, by putting them on the JavaScript\n * event loop queue. It is best used to delay tasks in time or to schedule tasks repeating\n * in intervals.\n *\n * If you just want to \"defer\" task, that is to perform it right after currently\n * executing synchronous code ends (commonly achieved by `setTimeout(deferredTask, 0)`),\n * better choice will be the {@link asapScheduler} scheduler.\n *\n * ## Examples\n * Use async scheduler to delay task\n * ```ts\n * import { asyncScheduler } from 'rxjs';\n *\n * const task = () => console.log('it works!');\n *\n * asyncScheduler.schedule(task, 2000);\n *\n * // After 2 seconds logs:\n * // \"it works!\"\n * ```\n *\n * Use async scheduler to repeat task in intervals\n * ```ts\n * import { asyncScheduler } from 'rxjs';\n *\n * function task(state) {\n * console.log(state);\n * this.schedule(state + 1, 1000); // `this` references currently executing Action,\n * // which we reschedule with new state and delay\n * }\n *\n * asyncScheduler.schedule(task, 3000, 0);\n *\n * // Logs:\n * // 0 after 3s\n * // 1 after 4s\n * // 2 after 5s\n * // 3 after 6s\n * ```\n */\n\nexport const asyncScheduler = new AsyncScheduler(AsyncAction);\n\n/**\n * @deprecated Renamed to {@link asyncScheduler}. Will be removed in v8.\n */\nexport const async = asyncScheduler;\n", "import { AsyncAction } from './AsyncAction';\nimport { Subscription } from '../Subscription';\nimport { QueueScheduler } from './QueueScheduler';\nimport { SchedulerAction } from '../types';\nimport { TimerHandle } from './timerHandle';\n\nexport class QueueAction extends AsyncAction {\n constructor(protected scheduler: QueueScheduler, protected work: (this: SchedulerAction, state?: T) => void) {\n super(scheduler, work);\n }\n\n public schedule(state?: T, delay: number = 0): Subscription {\n if (delay > 0) {\n return super.schedule(state, delay);\n }\n this.delay = delay;\n this.state = state;\n this.scheduler.flush(this);\n return this;\n }\n\n public execute(state: T, delay: number): any {\n return delay > 0 || this.closed ? super.execute(state, delay) : this._execute(state, delay);\n }\n\n protected requestAsyncId(scheduler: QueueScheduler, id?: TimerHandle, delay: number = 0): TimerHandle {\n // If delay exists and is greater than 0, or if the delay is null (the\n // action wasn't rescheduled) but was originally scheduled as an async\n // action, then recycle as an async action.\n\n if ((delay != null && delay > 0) || (delay == null && this.delay > 0)) {\n return super.requestAsyncId(scheduler, id, delay);\n }\n\n // Otherwise flush the scheduler starting with this action.\n scheduler.flush(this);\n\n // HACK: In the past, this was returning `void`. However, `void` isn't a valid\n // `TimerHandle`, and generally the return value here isn't really used. So the\n // compromise is to return `0` which is both \"falsy\" and a valid `TimerHandle`,\n // as opposed to refactoring every other instanceo of `requestAsyncId`.\n return 0;\n }\n}\n", "import { AsyncScheduler } from './AsyncScheduler';\n\nexport class QueueScheduler extends AsyncScheduler {\n}\n", "import { QueueAction } from './QueueAction';\nimport { QueueScheduler } from './QueueScheduler';\n\n/**\n *\n * Queue Scheduler\n *\n * Put every next task on a queue, instead of executing it immediately\n *\n * `queue` scheduler, when used with delay, behaves the same as {@link asyncScheduler} scheduler.\n *\n * When used without delay, it schedules given task synchronously - executes it right when\n * it is scheduled. However when called recursively, that is when inside the scheduled task,\n * another task is scheduled with queue scheduler, instead of executing immediately as well,\n * that task will be put on a queue and wait for current one to finish.\n *\n * This means that when you execute task with `queue` scheduler, you are sure it will end\n * before any other task scheduled with that scheduler will start.\n *\n * ## Examples\n * Schedule recursively first, then do something\n * ```ts\n * import { queueScheduler } from 'rxjs';\n *\n * queueScheduler.schedule(() => {\n * queueScheduler.schedule(() => console.log('second')); // will not happen now, but will be put on a queue\n *\n * console.log('first');\n * });\n *\n * // Logs:\n * // \"first\"\n * // \"second\"\n * ```\n *\n * Reschedule itself recursively\n * ```ts\n * import { queueScheduler } from 'rxjs';\n *\n * queueScheduler.schedule(function(state) {\n * if (state !== 0) {\n * console.log('before', state);\n * this.schedule(state - 1); // `this` references currently executing Action,\n * // which we reschedule with new state\n * console.log('after', state);\n * }\n * }, 0, 3);\n *\n * // In scheduler that runs recursively, you would expect:\n * // \"before\", 3\n * // \"before\", 2\n * // \"before\", 1\n * // \"after\", 1\n * // \"after\", 2\n * // \"after\", 3\n *\n * // But with queue it logs:\n * // \"before\", 3\n * // \"after\", 3\n * // \"before\", 2\n * // \"after\", 2\n * // \"before\", 1\n * // \"after\", 1\n * ```\n */\n\nexport const queueScheduler = new QueueScheduler(QueueAction);\n\n/**\n * @deprecated Renamed to {@link queueScheduler}. Will be removed in v8.\n */\nexport const queue = queueScheduler;\n", "import { AsyncAction } from './AsyncAction';\nimport { AnimationFrameScheduler } from './AnimationFrameScheduler';\nimport { SchedulerAction } from '../types';\nimport { animationFrameProvider } from './animationFrameProvider';\nimport { TimerHandle } from './timerHandle';\n\nexport class AnimationFrameAction extends AsyncAction {\n constructor(protected scheduler: AnimationFrameScheduler, protected work: (this: SchedulerAction, state?: T) => void) {\n super(scheduler, work);\n }\n\n protected requestAsyncId(scheduler: AnimationFrameScheduler, id?: TimerHandle, delay: number = 0): TimerHandle {\n // If delay is greater than 0, request as an async action.\n if (delay !== null && delay > 0) {\n return super.requestAsyncId(scheduler, id, delay);\n }\n // Push the action to the end of the scheduler queue.\n scheduler.actions.push(this);\n // If an animation frame has already been requested, don't request another\n // one. If an animation frame hasn't been requested yet, request one. Return\n // the current animation frame request id.\n return scheduler._scheduled || (scheduler._scheduled = animationFrameProvider.requestAnimationFrame(() => scheduler.flush(undefined)));\n }\n\n protected recycleAsyncId(scheduler: AnimationFrameScheduler, id?: TimerHandle, delay: number = 0): TimerHandle | undefined {\n // If delay exists and is greater than 0, or if the delay is null (the\n // action wasn't rescheduled) but was originally scheduled as an async\n // action, then recycle as an async action.\n if (delay != null ? delay > 0 : this.delay > 0) {\n return super.recycleAsyncId(scheduler, id, delay);\n }\n // If the scheduler queue has no remaining actions with the same async id,\n // cancel the requested animation frame and set the scheduled flag to\n // undefined so the next AnimationFrameAction will request its own.\n const { actions } = scheduler;\n if (id != null && actions[actions.length - 1]?.id !== id) {\n animationFrameProvider.cancelAnimationFrame(id as number);\n scheduler._scheduled = undefined;\n }\n // Return undefined so the action knows to request a new async id if it's rescheduled.\n return undefined;\n }\n}\n", "import { AsyncAction } from './AsyncAction';\nimport { AsyncScheduler } from './AsyncScheduler';\n\nexport class AnimationFrameScheduler extends AsyncScheduler {\n public flush(action?: AsyncAction): void {\n this._active = true;\n // The async id that effects a call to flush is stored in _scheduled.\n // Before executing an action, it's necessary to check the action's async\n // id to determine whether it's supposed to be executed in the current\n // flush.\n // Previous implementations of this method used a count to determine this,\n // but that was unsound, as actions that are unsubscribed - i.e. cancelled -\n // are removed from the actions array and that can shift actions that are\n // scheduled to be executed in a subsequent flush into positions at which\n // they are executed within the current flush.\n const flushId = this._scheduled;\n this._scheduled = undefined;\n\n const { actions } = this;\n let error: any;\n action = action || actions.shift()!;\n\n do {\n if ((error = action.execute(action.state, action.delay))) {\n break;\n }\n } while ((action = actions[0]) && action.id === flushId && actions.shift());\n\n this._active = false;\n\n if (error) {\n while ((action = actions[0]) && action.id === flushId && actions.shift()) {\n action.unsubscribe();\n }\n throw error;\n }\n }\n}\n", "import { AnimationFrameAction } from './AnimationFrameAction';\nimport { AnimationFrameScheduler } from './AnimationFrameScheduler';\n\n/**\n *\n * Animation Frame Scheduler\n *\n * Perform task when `window.requestAnimationFrame` would fire\n *\n * When `animationFrame` scheduler is used with delay, it will fall back to {@link asyncScheduler} scheduler\n * behaviour.\n *\n * Without delay, `animationFrame` scheduler can be used to create smooth browser animations.\n * It makes sure scheduled task will happen just before next browser content repaint,\n * thus performing animations as efficiently as possible.\n *\n * ## Example\n * Schedule div height animation\n * ```ts\n * // html:
    \n * import { animationFrameScheduler } from 'rxjs';\n *\n * const div = document.querySelector('div');\n *\n * animationFrameScheduler.schedule(function(height) {\n * div.style.height = height + \"px\";\n *\n * this.schedule(height + 1); // `this` references currently executing Action,\n * // which we reschedule with new state\n * }, 0, 0);\n *\n * // You will see a div element growing in height\n * ```\n */\n\nexport const animationFrameScheduler = new AnimationFrameScheduler(AnimationFrameAction);\n\n/**\n * @deprecated Renamed to {@link animationFrameScheduler}. Will be removed in v8.\n */\nexport const animationFrame = animationFrameScheduler;\n", "import { Observable } from '../Observable';\nimport { SchedulerLike } from '../types';\n\n/**\n * A simple Observable that emits no items to the Observer and immediately\n * emits a complete notification.\n *\n * Just emits 'complete', and nothing else.\n *\n * ![](empty.png)\n *\n * A simple Observable that only emits the complete notification. It can be used\n * for composing with other Observables, such as in a {@link mergeMap}.\n *\n * ## Examples\n *\n * Log complete notification\n *\n * ```ts\n * import { EMPTY } from 'rxjs';\n *\n * EMPTY.subscribe({\n * next: () => console.log('Next'),\n * complete: () => console.log('Complete!')\n * });\n *\n * // Outputs\n * // Complete!\n * ```\n *\n * Emit the number 7, then complete\n *\n * ```ts\n * import { EMPTY, startWith } from 'rxjs';\n *\n * const result = EMPTY.pipe(startWith(7));\n * result.subscribe(x => console.log(x));\n *\n * // Outputs\n * // 7\n * ```\n *\n * Map and flatten only odd numbers to the sequence `'a'`, `'b'`, `'c'`\n *\n * ```ts\n * import { interval, mergeMap, of, EMPTY } from 'rxjs';\n *\n * const interval$ = interval(1000);\n * const result = interval$.pipe(\n * mergeMap(x => x % 2 === 1 ? of('a', 'b', 'c') : EMPTY),\n * );\n * result.subscribe(x => console.log(x));\n *\n * // Results in the following to the console:\n * // x is equal to the count on the interval, e.g. (0, 1, 2, 3, ...)\n * // x will occur every 1000ms\n * // if x % 2 is equal to 1, print a, b, c (each on its own)\n * // if x % 2 is not equal to 1, nothing will be output\n * ```\n *\n * @see {@link Observable}\n * @see {@link NEVER}\n * @see {@link of}\n * @see {@link throwError}\n */\nexport const EMPTY = new Observable((subscriber) => subscriber.complete());\n\n/**\n * @param scheduler A {@link SchedulerLike} to use for scheduling\n * the emission of the complete notification.\n * @deprecated Replaced with the {@link EMPTY} constant or {@link scheduled} (e.g. `scheduled([], scheduler)`). Will be removed in v8.\n */\nexport function empty(scheduler?: SchedulerLike) {\n return scheduler ? emptyScheduled(scheduler) : EMPTY;\n}\n\nfunction emptyScheduled(scheduler: SchedulerLike) {\n return new Observable((subscriber) => scheduler.schedule(() => subscriber.complete()));\n}\n", "import { SchedulerLike } from '../types';\nimport { isFunction } from './isFunction';\n\nexport function isScheduler(value: any): value is SchedulerLike {\n return value && isFunction(value.schedule);\n}\n", "import { SchedulerLike } from '../types';\nimport { isFunction } from './isFunction';\nimport { isScheduler } from './isScheduler';\n\nfunction last(arr: T[]): T | undefined {\n return arr[arr.length - 1];\n}\n\nexport function popResultSelector(args: any[]): ((...args: unknown[]) => unknown) | undefined {\n return isFunction(last(args)) ? args.pop() : undefined;\n}\n\nexport function popScheduler(args: any[]): SchedulerLike | undefined {\n return isScheduler(last(args)) ? args.pop() : undefined;\n}\n\nexport function popNumber(args: any[], defaultValue: number): number {\n return typeof last(args) === 'number' ? args.pop()! : defaultValue;\n}\n", "export const isArrayLike = ((x: any): x is ArrayLike => x && typeof x.length === 'number' && typeof x !== 'function');", "import { isFunction } from \"./isFunction\";\n\n/**\n * Tests to see if the object is \"thennable\".\n * @param value the object to test\n */\nexport function isPromise(value: any): value is PromiseLike {\n return isFunction(value?.then);\n}\n", "import { InteropObservable } from '../types';\nimport { observable as Symbol_observable } from '../symbol/observable';\nimport { isFunction } from './isFunction';\n\n/** Identifies an input as being Observable (but not necessary an Rx Observable) */\nexport function isInteropObservable(input: any): input is InteropObservable {\n return isFunction(input[Symbol_observable]);\n}\n", "import { isFunction } from './isFunction';\n\nexport function isAsyncIterable(obj: any): obj is AsyncIterable {\n return Symbol.asyncIterator && isFunction(obj?.[Symbol.asyncIterator]);\n}\n", "/**\n * Creates the TypeError to throw if an invalid object is passed to `from` or `scheduled`.\n * @param input The object that was passed.\n */\nexport function createInvalidObservableTypeError(input: any) {\n // TODO: We should create error codes that can be looked up, so this can be less verbose.\n return new TypeError(\n `You provided ${\n input !== null && typeof input === 'object' ? 'an invalid object' : `'${input}'`\n } where a stream was expected. You can provide an Observable, Promise, ReadableStream, Array, AsyncIterable, or Iterable.`\n );\n}\n", "export function getSymbolIterator(): symbol {\n if (typeof Symbol !== 'function' || !Symbol.iterator) {\n return '@@iterator' as any;\n }\n\n return Symbol.iterator;\n}\n\nexport const iterator = getSymbolIterator();\n", "import { iterator as Symbol_iterator } from '../symbol/iterator';\nimport { isFunction } from './isFunction';\n\n/** Identifies an input as being an Iterable */\nexport function isIterable(input: any): input is Iterable {\n return isFunction(input?.[Symbol_iterator]);\n}\n", "import { ReadableStreamLike } from '../types';\nimport { isFunction } from './isFunction';\n\nexport async function* readableStreamLikeToAsyncGenerator(readableStream: ReadableStreamLike): AsyncGenerator {\n const reader = readableStream.getReader();\n try {\n while (true) {\n const { value, done } = await reader.read();\n if (done) {\n return;\n }\n yield value!;\n }\n } finally {\n reader.releaseLock();\n }\n}\n\nexport function isReadableStreamLike(obj: any): obj is ReadableStreamLike {\n // We don't want to use instanceof checks because they would return\n // false for instances from another Realm, like an