Upgrade to kedro 19

.github/ISSUE_TEMPLATE/bug_report.md

@@ -7,31 +7,30 @@ assignees: ''
 
 ---
 
-**_If you like the repo, please give it a :star:_**
+<!-- **_If you like the repo, please give it a :star:_** -->
 
 ## Description
-
-Short description of the problem here.
+<!-- Short description of the problem here. -->
 
 ## Context
 
-How has this bug affected you? What were you trying to accomplish?
+<!-- How has this bug affected you? What were you trying to accomplish? -->
 
 ## Steps to Reproduce
 
-Please provide a detailed description. A Minimal Reproducible Example would really help to solve your issue faster (see this [Stack Overflow thread](https://stackoverflow.com/help/minimal-reproducible-example) to see how to create a good "reprex"). A link to a github repo is even better.
+<!-- Please provide a detailed description. A Minimal Reproducible Example would really help to solve your issue faster (see this [Stack Overflow thread](https://stackoverflow.com/help/minimal-reproducible-example) to see how to create a good "reprex"). A link to a github repo is even better.
 
 1. [First Step]
 2. [Second Step]
-3. [And so on...]
+3. [And so on...] -->
 
 ## Expected Result
 
-Tell us what should happen.
+<!-- Tell us what should happen. -->
 
 ## Actual Result
 
-Tell us what happens instead.
+<!-- Tell us what happens instead. -->
 
 ```
 -- If you received an error, place it here.
@@ -43,20 +42,20 @@ Tell us what happens instead.
 
 ## Your Environment
 
-Include as many relevant details about the environment in which you experienced the bug:
+<!-- Include as many relevant details about the environment in which you experienced the bug: -->
 
 * `kedro` and `kedro-mlflow` version used (`pip show kedro` and `pip show kedro-mlflow`):
 * Python version used (`python -V`):
 * Operating system and version:
 
 ## Does the bug also happen with the last version on master?
 
-The plugin is still in early development and known bugs are fixed as soon as we can. If you are lucky, your bug is already fixed on the `master` branch which is the most up to date. This branch contains our more recent development unpublished on PyPI yet.
+<!-- The plugin is still in early development and known bugs are fixed as soon as we can. If you are lucky, your bug is already fixed on the `master` branch which is the most up to date. This branch contains our more recent development unpublished on PyPI yet.
 
 In your environment, please try:
 
 ```bash
 pip install --upgrade git+https://github.com/Galileo-Galilei/kedro-mlflow
 ```
 
-And check if you can to reproduce the error. If you can't, just wait for the next release or use the master branch at your own risk!
+And check if you can to reproduce the error. If you can't, just wait for the next release or use the master branch at your own risk! -->

.github/ISSUE_TEMPLATE/feature_request.md

@@ -6,16 +6,16 @@ labels: 'Issue: Feature Request'
 assignees: ''
 ---
 
-*If you like the repo, please give it a :star:*
+<!-- **_If you like the repo, please give it a :star:_** -->
 
 ## Description
-A clear and concise description of what you want to achieve. An image or a code example is worth thousand words!
+<!-- A clear and concise description of what you want to achieve. An image or a code example is worth thousand words! -->
 
 ## Context
-Why is this change important to you? How would you use it? How can it benefit other users?
+<!-- Why is this change important to you? How would you use it? How can it benefit other users? -->
 
 ## Possible Implementation
-(Optional) Suggest an idea for implementing the addition or change.
+<!-- (Optional) Suggest an idea for implementing the addition or change. -->
 
 ## Possible Alternatives
-(Optional) Describe any alternative solutions or features you've considered.
+<!-- (Optional) Describe any alternative solutions or features you've considered. -->

.pre-commit-config.yaml

@@ -1,7 +1,7 @@
 exclude: ^kedro_mlflow/template/project/run.py$
 repos:
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.1.3
+    rev: v0.1.8
     hooks:
       - id: ruff
         args: [--fix, --exit-non-zero-on-fix]

CHANGELOG.md

@@ -6,10 +6,12 @@
 
 - :sparkles: Add support for python 3.11 ([#450, rxm7706](https://github.com/Galileo-Galilei/kedro-mlflow/pull/450))
 - :sparkles: :arrow_up: Add support for pydantic v2 ([#476](https://github.com/Galileo-Galilei/kedro-mlflow/pull/476))
+- :sparkles: :arrow_up: Add support for ``kedro==0.19.X`` ([#](https://github.com/Galileo-Galilei/kedro-mlflow/pull/))
 
 ### Changed
 
-- :boom: :sparkles: Change default ``copy_mode``  to ``"assign"`` in ``KedroPipelineModel`` because this is the most efficient setup (and usually the desired one) when serving a Kedro ``Pipeline`` as a Mlflow model. This is different from Kedro's default which is to deepcopy the dataset ([#463, ShubhamZoro](https://github.com/Galileo-Galilei/kedro-mlflow/pull/463)).
+- :boom: ::arrow_up:: Drop support for ``kedro==0.18.X`` series.
+- :boom: :sparkles: Change default ``copy_mode``  to ``"assign"`` in ``KedroPipelineModel`` because this is the most efficient setup (and usually the desired one) when serving a Kedro ``Pipeline`` as a Mlflow model. This is different from Kedro's default which is to deepcopy the dataset ([#463](https://github.com/Galileo-Galilei/kedro-mlflow/pull/463)).
 - :boom: :recycle: ``MlflowArtifactDataset.__init__`` method ``data_set`` argument is renamed ``dataset`` to match new Kedro conventions ([#391](https://github.com/Galileo-Galilei/kedro-mlflow/pull/391)).
 - :boom: :recycle: Rename the following ``DataSets`` with the ``Dataset`` suffix (without capitalized ``S``) to match new kedro conventions from ``kedro>=0.19`` and onwards ([#439, ShubhamZoro](https://github.com/Galileo-Galilei/kedro-mlflow/pull/439)):
   - ``MlflowArtifactDataSet``->``MlflowArtifactDataset``
@@ -26,7 +28,7 @@
 
 ### Fixed
 
--   :bug: Avoid error when using kedro==0.18.1 with `TemplatedConfigLoader` and no `mlflow.yml` configuration file ([#452, sami-sweng](https://github.com/Galileo-Galilei/kedro-mlflow/issues/452))
+-   :bug: Avoid error when using ``kedro==0.18.1`` with `TemplatedConfigLoader` and no `mlflow.yml` configuration file ([#452, sami-sweng](https://github.com/Galileo-Galilei/kedro-mlflow/issues/452))
 
 ## [0.11.9] - 2023-07-23
 

docs/source/03_getting_started/01_example_project.md

@@ -12,7 +12,7 @@ pip install kedro-mlflow==0.11.10
 
 ## Install the toy project
 
-For this end to end example, we will use the [kedro starter](https://kedro.readthedocs.io/en/stable/get_started/starters.html) with the [iris dataset](https://github.com/quantumblacklabs/kedro-starter-pandas-iris).
+For this end to end example, we will use the [kedro starter](https://docs.kedro.org/en/stable/starters/starters.html#official-kedro-starters) with the [iris dataset](https://github.com/quantumblacklabs/kedro-starter-pandas-iris).
 
 We use this project because:
 

docs/source/04_experimentation_tracking/06_mlflow_ui.md

@@ -6,7 +6,7 @@ Mlflow offers a user interface (UI) that enable to browse the run history.
 
 ## The ``kedro-mlflow`` helper
 
-When you use a local storage for kedro mlflow, you can call a [mlflow cli command](https://www.mlflow.org/docs/latest/quickstart.html#viewing-the-tracking-ui) to launch the UI if you do not have a [mlflow tracking server configured](https://www.mlflow.org/docs/latest/tracking.html#tracking-ui).
+When you use a local storage for kedro mlflow, you can call a [mlflow cli command](https://www.mlflow.org/docs/latest/tracking.html#tracking-ui) to launch the UI if you do not have a [mlflow tracking server configured](https://www.mlflow.org/docs/latest/tracking.html#mlflow-tracking-server-optional).
 
 To ensure this UI is linked to the tracking uri specified configuration, ``kedro-mlflow`` offers the following command:
 

kedro_mlflow/framework/hooks/mlflow_hook.py

@@ -66,7 +66,7 @@ def after_context_created(
                     {"mlflow": ["mlflow*", "mlflow*/**", "**/mlflow*"]}
                 )
             conf_mlflow_yml = context.config_loader["mlflow"]
-        except (MissingConfigException, AttributeError):
+        except MissingConfigException:
             LOGGER.warning(
                 "No 'mlflow.yml' config file found in environment. Default configuration will be used. Use ``kedro mlflow init`` command in CLI to customize the configuration."
             )

kedro_mlflow/io/artifacts/mlflow_artifact_dataset.py

@@ -1,10 +1,9 @@
 import shutil
-from inspect import isclass
 from pathlib import Path
 from typing import Any, Dict, Union
 
 import mlflow
-from kedro.io import AbstractDataset, AbstractVersionedDataset
+from kedro.io import AbstractVersionedDataset
 from kedro.io.core import parse_dataset_definition
 from mlflow.tracking import MlflowClient
 
@@ -21,9 +20,6 @@ def __new__(
         artifact_path: str = None,
         credentials: Dict[str, Any] = None,
     ):
-        if isclass(dataset["type"]) and issubclass(dataset["type"], AbstractDataset):
-            # parse_dataset_definition needs type to be a string, not the class itself
-            dataset["type"] = f"{dataset['type'].__module__}.{dataset['type'].__name__}"
         dataset_obj, dataset_args = parse_dataset_definition(config=dataset)
 
         # fake inheritance : this mlflow class should be a mother class which wraps

kedro_mlflow/io/metrics/__init__.py

@@ -1,6 +1,6 @@
 from .mlflow_metric_dataset import MlflowMetricDataset
 from .mlflow_metric_history_dataset import MlflowMetricHistoryDataset
-from .mlflow_metrics_dataset import MlflowMetricsHistoryDataset
+from .mlflow_metrics_history_dataset import MlflowMetricsHistoryDataset
 
 __all__ = [
     "MlflowMetricDataset",

kedro_mlflow/io/models/mlflow_abstract_model_dataset.py

@@ -7,9 +7,9 @@
 from kedro.io.core import DatasetError
 
 
-class MlflowModelRegistryDataset(AbstractVersionedDataset):
+class MlflowAbstractModelDataSet(AbstractVersionedDataset):
     """
-    Absract mother class for model datasets.
+    Abstract mother class for model datasets.
     """
 
     def __init__(
@@ -21,7 +21,7 @@ def __init__(
         save_args: Dict[str, Any] = None,
         version: Version = None,
     ) -> None:
-        """Initialize the Kedro MlflowModelDataSet.
+        """Initialize the Kedro MlflowAbstractModelDataSet.
 
         Parameters are passed from the Data Catalog.
 

kedro_mlflow/io/models/mlflow_model_local_filesystem_dataset.py

@@ -5,11 +5,11 @@
 from kedro.io import Version
 
 from kedro_mlflow.io.models.mlflow_abstract_model_dataset import (
-    MlflowModelRegistryDataset,
+    MlflowAbstractModelDataSet,
 )
 
 
-class MlflowModelLocalFileSystemDataset(MlflowModelRegistryDataset):
+class MlflowModelLocalFileSystemDataset(MlflowAbstractModelDataSet):
     """Wrapper for saving, logging and loading for all MLflow model flavor."""
 
     def __init__(

kedro_mlflow/io/models/mlflow_model_registry_dataset.py

@@ -1,11 +1,11 @@
 from typing import Any, Dict, Optional, Union
 
 from kedro_mlflow.io.models.mlflow_abstract_model_dataset import (
-    MlflowModelRegistryDataset,
+    MlflowAbstractModelDataSet,
 )
 
 
-class MlflowModelRegistryDataset(MlflowModelRegistryDataset):
+class MlflowModelRegistryDataset(MlflowAbstractModelDataSet):
     """Wrapper for saving, logging and loading for all MLflow model flavor."""
 
     def __init__(

kedro_mlflow/io/models/mlflow_model_tracking_dataset.py

@@ -4,11 +4,11 @@
 from kedro.io.core import DatasetError
 
 from kedro_mlflow.io.models.mlflow_abstract_model_dataset import (
-    MlflowModelRegistryDataset,
+    MlflowAbstractModelDataSet,
 )
 
 
-class MlflowModelTrackingDataset(MlflowModelRegistryDataset):
+class MlflowModelTrackingDataset(MlflowAbstractModelDataSet):
     """Wrapper for saving, logging and loading for all MLflow model flavor."""
 
     def __init__(

pyproject.toml

@@ -1,12 +1,3 @@
-[tool.black]
-exclude = "/template/"
-
-[tool.isort]
-profile = "black"
-sections=["FUTURE","STDLIB","THIRDPARTY","FIRSTPARTY","LOCALFOLDER"]
-known_first_party=["kedro_mlflow"]
-known_third_party=["anyconfig","black","click","cookiecutter","flake8","isort","jinja2","kedro","mlflow","pandas","pytest","pytest_lazyfixture","setuptools","sklearn","yaml"]
-
 [tool.ruff]
 select = [
     "F",  # Pyflakes

requirements.txt

@@ -1,4 +1,4 @@
-kedro>=0.18.1, <0.19.0
+kedro>=0.19.0, <0.20.0
 kedro_datasets
 mlflow>=1.0.0, <3.0.0
 pydantic>=1.0.0, <3.0.0

tests/config/test_get_mlflow_config.py

@@ -63,7 +63,7 @@ def test_mlflow_config_default(kedro_project):
 def test_mlflow_config_in_uninitialized_project(kedro_project, package_name):
     # config_with_base_mlflow_conf is a pytest.fixture in conftest
     bootstrap_project(kedro_project)
-    session = KedroSession.create(project_path=kedro_project, package_name=package_name)
+    session = KedroSession.create(project_path=kedro_project)
     context = session.load_context()
     assert context.mlflow.dict() == dict(
         server=dict(
@@ -90,9 +90,7 @@ def test_mlflow_config_with_no_experiment_name(kedro_project):
     open((kedro_project / "conf" / "base" / "mlflow.yml").as_posix(), mode="w").close()
 
     bootstrap_project(kedro_project)
-    session = KedroSession.create(
-        project_path=kedro_project, package_name="fake_project"
-    )
+    session = KedroSession.create(project_path=kedro_project)
     context = session.load_context()
     assert context.mlflow.dict() == dict(
         server=dict(
@@ -203,9 +201,7 @@ def fake_project(tmp_path, local_logging_config):
 )
 def test_mlflow_config_correctly_set(kedro_project, project_settings):
     bootstrap_project(kedro_project)
-    session = KedroSession.create(
-        project_path=kedro_project, package_name="fake_project"
-    )
+    session = KedroSession.create(project_path=kedro_project)
     context = session.load_context()
     assert context.mlflow.dict(exclude={"project_path"}) == dict(
         server=dict(
@@ -229,7 +225,7 @@ def test_mlflow_config_correctly_set(kedro_project, project_settings):
 
 # TODO: when OmegaConfigLoader will support templating with globals, add a similar test
 @pytest.mark.usefixtures("mock_settings_omega_config_loader_class")
-def test_mlflow_config_interpolated_with_globals_resolver(fake_project):
+def test_mlflow_config_interpolated_with_globals_resolver(monkeypatch, fake_project):
     dict_config = dict(
         server=dict(
             mlflow_tracking_uri="${globals: mlflow_tracking_uri}",
@@ -266,7 +262,7 @@ def test_mlflow_config_interpolated_with_globals_resolver(fake_project):
     ).as_uri()
 
     bootstrap_project(fake_project)
-    with KedroSession.create("fake_package", fake_project) as session:
+    with KedroSession.create(fake_project) as session:
         context = session.load_context()
         assert context.mlflow.dict(exclude={"project_path"}) == expected
 
@@ -323,7 +319,7 @@ def request_headers(self):
     _write_yaml(fake_project / "conf" / "local" / "mlflow.yml", dict_config)
 
     bootstrap_project(fake_project)
-    with KedroSession.create("fake_package", fake_project) as session:
+    with KedroSession.create(project_path=fake_project) as session:
         session.load_context()  # trigger setup and request_header_provider registration
 
         assert (
@@ -382,7 +378,7 @@ def request_headers(self):
     _write_yaml(fake_project / "conf" / "local" / "mlflow.yml", dict_config)
 
     bootstrap_project(fake_project)
-    with KedroSession.create("fake_package", fake_project) as session:
+    with KedroSession.create(project_path=fake_project) as session:
         session.load_context()  # trigger setup and request_header_provider registration
 
         assert (
@@ -445,7 +441,7 @@ def request_headers(self):
     _write_yaml(fake_project / "conf" / "local" / "mlflow.yml", dict_config)
 
     bootstrap_project(fake_project)
-    with KedroSession.create("fake_package", fake_project) as session:
+    with KedroSession.create(project_path=fake_project) as session:
         session.load_context()  # trigger setup and request_header_provider registration
 
     assert (
@@ -500,7 +496,7 @@ def request_headers(self):
     _write_yaml(fake_project / "conf" / "local" / "mlflow.yml", dict_config)
 
     bootstrap_project(fake_project)
-    with KedroSession.create("fake_package", fake_project) as session:
+    with KedroSession.create(project_path=fake_project) as session:
         with pytest.raises(ValueError, match=r"should be a sublass of"):
             session.load_context()  # trigger setup and request_header_provider registration
 

tests/framework/cli/test_cli.py

@@ -104,9 +104,7 @@ def test_cli_init_existing_config(
     monkeypatch.chdir(kedro_project_with_mlflow_conf)
     bootstrap_project(kedro_project_with_mlflow_conf)
 
-    with KedroSession.create(
-        "fake_project", project_path=kedro_project_with_mlflow_conf
-    ) as session:
+    with KedroSession.create(project_path=kedro_project_with_mlflow_conf) as session:
         # emulate first call by writing a mlflow.yml file
         yaml_str = yaml.dump(dict(server=dict(mlflow_tracking_uri="toto")))
         (

tests/framework/hooks/test_hook_deactivate_tracking.py

@@ -115,9 +115,9 @@ def config_dir(
     payload = {
         "tool": {
             "kedro": {
-                "project_version": kedro_version,
                 "project_name": MOCK_PACKAGE_NAME,
                 "package_name": MOCK_PACKAGE_NAME,
+                "kedro_init_version": kedro_version,
             }
         }
     }
@@ -221,7 +221,7 @@ def mock_session(mocker, mock_settings_with_mlflow_hooks, kedro_project_path):
     )  # prevent registering the one of the plugins which are already installed
 
     configure_project(MOCK_PACKAGE_NAME)
-    return KedroSession.create(MOCK_PACKAGE_NAME, kedro_project_path)
+    return KedroSession.create(kedro_project_path)
 
 
 def test_deactivated_tracking_but_not_for_given_pipeline(mock_session):

tests/framework/hooks/test_hook_log_metrics.py

@@ -106,7 +106,7 @@ def dummy_catalog(tmp_path):
             "raw_data": MemoryDataset(pd.DataFrame(data=[1], columns=["a"])),
             "params:unused_param": MemoryDataset("blah"),
             "data": MemoryDataset(),
-            "model": PickleDataset((tmp_path / "model.csv").as_posix()),
+            "model": PickleDataset(filepath=(tmp_path / "model.csv").as_posix()),
             "my_metrics": MlflowMetricsHistoryDataset(),
             "another_metrics": MlflowMetricsHistoryDataset(prefix="foo"),
             "my_metric": MlflowMetricDataset(),
@@ -181,7 +181,9 @@ def test_mlflow_hook_metrics_dataset_with_run_id(
                 "params:unused_param": MemoryDataset("blah"),
                 "data": MemoryDataset(),
                 "model": PickleDataset(
-                    (kedro_project_with_mlflow_conf / "data" / "model.csv").as_posix()
+                    filepath=(
+                        kedro_project_with_mlflow_conf / "data" / "model.csv"
+                    ).as_posix()
                 ),
                 "my_metrics": MlflowMetricsHistoryDataset(run_id=existing_run_id),
                 "another_metrics": MlflowMetricsHistoryDataset(