Rebase...

lib/galaxy/tool_util/parameters/__init__.py

@@ -4,7 +4,7 @@
     dereference,
     encode,
     encode_test,
-    fill_defaults,
+    fill_static_defaults,
 )
 from .factory import (
     from_input_source,
@@ -138,7 +138,7 @@
     "decode",
     "encode",
     "encode_test",
-    "fill_defaults",
+    "fill_static_defaults",
     "dereference",
     "WorkflowStepToolState",
     "WorkflowStepLinkedToolState",

lib/galaxy/tool_util/parameters/convert.py

@@ -240,8 +240,8 @@ def encode_callback(parameter: ToolParameterT, value: Any):
     return request_state
 
 
-def fill_defaults(
-    tool_state: Dict[str, Any], input_models: ToolParameterBundle, partial: bool = True
+def fill_static_defaults(
+    tool_state: Dict[str, Any], input_models: ToolParameterBundle, profile: str, partial: bool = True
 ) -> Dict[str, Any]:
     """If additional defaults might stem from Galaxy runtime, partial should be true.
 
@@ -269,7 +269,8 @@ def _fill_default_for(tool_state: Dict[str, Any], parameter: ToolParameterT) ->
             # even optional parameters default to false if not in the body of the request :_(
             # see test_tools.py -> expression_null_handling_boolean or test cases for gx_boolean_optional.xml
             tool_state[parameter_name] = boolean.value or False
-    if parameter_type in ["gx_integer", "gx_float", "gx_hidden", "gx_data_column"]:
+
+    if parameter_type in ["gx_integer", "gx_float", "gx_hidden"]:
         has_value_parameter = cast(
             Union[
                 IntegerParameterModel,

lib/galaxy/tool_util/parameters/factory.py

@@ -14,6 +14,7 @@
     PagesSource,
     ToolSource,
 )
+from galaxy.tool_util.parser.util import parse_profile_version
 from galaxy.util import string_as_bool
 from .models import (
     BaseUrlParameterModel,
@@ -64,7 +65,7 @@ def get_color_value(input_source: InputSource) -> str:
     return input_source.get("value", "#000000")
 
 
-def _from_input_source_galaxy(input_source: InputSource) -> ToolParameterT:
+def _from_input_source_galaxy(input_source: InputSource, profile: float) -> ToolParameterT:
     input_type = input_source.parse_input_type()
     if input_type == "param":
         param_type = input_source.get("type")
@@ -180,8 +181,8 @@ def _from_input_source_galaxy(input_source: InputSource) -> ToolParameterT:
             multiple = input_source.get_bool("multiple", False)
             optional = input_source.parse_optional()
             value = input_source.parse_data_column_value()
-            accept_default = (
-                input_source.get("accept_default", False) or not multiple
+            accept_default = input_source.get("accept_default", False) or (
+                not multiple and profile < 20.01
             )  # wild but that is what the tests say I think
             if value is None and accept_default:
                 if multiple:
@@ -224,7 +225,8 @@ def _from_input_source_galaxy(input_source: InputSource) -> ToolParameterT:
     elif input_type == "conditional":
         test_param_input_source = input_source.parse_test_input_source()
         test_parameter = cast(
-            Union[BooleanParameterModel, SelectParameterModel], _from_input_source_galaxy(test_param_input_source)
+            Union[BooleanParameterModel, SelectParameterModel],
+            _from_input_source_galaxy(test_param_input_source, profile),
         )
         whens = []
         default_test_value = cond_test_parameter_default_value(test_parameter)
@@ -235,7 +237,7 @@ def _from_input_source_galaxy(input_source: InputSource) -> ToolParameterT:
             else:
                 typed_value = value
 
-            tool_parameter_models = input_models_for_page(case_inputs_sources)
+            tool_parameter_models = input_models_for_page(case_inputs_sources, profile)
             is_default_when = False
             if typed_value == default_test_value:
                 is_default_when = True
@@ -254,7 +256,7 @@ def _from_input_source_galaxy(input_source: InputSource) -> ToolParameterT:
         # title = input_source.get("title")
         # help = input_source.get("help", None)
         instance_sources = input_source.parse_nested_inputs_source()
-        instance_tool_parameter_models = input_models_for_page(instance_sources)
+        instance_tool_parameter_models = input_models_for_page(instance_sources, profile)
         min_raw = input_source.get("min", None)
         max_raw = input_source.get("max", None)
         min = int(min_raw) if min_raw is not None else None
@@ -268,7 +270,7 @@ def _from_input_source_galaxy(input_source: InputSource) -> ToolParameterT:
     elif input_type == "section":
         name = input_source.get("name")
         instance_sources = input_source.parse_nested_inputs_source()
-        instance_tool_parameter_models = input_models_for_page(instance_sources)
+        instance_tool_parameter_models = input_models_for_page(instance_sources, profile)
         return SectionParameterModel(
             name=name,
             parameters=instance_tool_parameter_models,
@@ -341,34 +343,35 @@ def tool_parameter_bundle_from_json(json: Dict[str, Any]) -> ToolParameterBundle
 
 def input_models_for_tool_source(tool_source: ToolSource) -> ToolParameterBundleModel:
     pages = tool_source.parse_input_pages()
-    return ToolParameterBundleModel(parameters=input_models_for_pages(pages))
+    profile = parse_profile_version(tool_source)
+    return ToolParameterBundleModel(parameters=input_models_for_pages(pages, profile))
 
 
-def input_models_for_pages(pages: PagesSource) -> List[ToolParameterT]:
+def input_models_for_pages(pages: PagesSource, profile: float) -> List[ToolParameterT]:
     input_models = []
     if pages.inputs_defined:
         for page_source in pages.page_sources:
-            input_models.extend(input_models_for_page(page_source))
+            input_models.extend(input_models_for_page(page_source, profile))
 
     return input_models
 
 
-def input_models_for_page(page_source: PageSource) -> List[ToolParameterT]:
+def input_models_for_page(page_source: PageSource, profile: float) -> List[ToolParameterT]:
     input_models = []
     for input_source in page_source.parse_input_sources():
         input_type = input_source.parse_input_type()
         if input_type == "display":
             # not a real input... just skip this. Should this be handled in the parser layer better?
             continue
-        tool_parameter_model = from_input_source(input_source)
+        tool_parameter_model = from_input_source(input_source, profile)
         input_models.append(tool_parameter_model)
     return input_models
 
 
-def from_input_source(input_source: InputSource) -> ToolParameterT:
+def from_input_source(input_source: InputSource, profile: float) -> ToolParameterT:
     tool_parameter: ToolParameterT
     if isinstance(input_source, CwlInputSource):
         tool_parameter = _from_input_source_cwl(input_source)
     else:
-        tool_parameter = _from_input_source_galaxy(input_source)
+        tool_parameter = _from_input_source_galaxy(input_source, profile)
     return tool_parameter

lib/galaxy/tool_util/parameters/models.py

@@ -1033,15 +1033,25 @@ def model_x_discriminator(v: Any) -> Optional[str]:
                 else:
                     return str(test_param_val)
 
-        cond_type = union_type(when_types)
+        if len(when_types) > 1:
+            cond_type = union_type(when_types)
 
-        class ConditionalType(RootModel):
-            root: cond_type = Field(..., discriminator=Discriminator(model_x_discriminator))  # type: ignore[valid-type]
+            class ConditionalType(RootModel):
+                root: cond_type = Field(..., discriminator=Discriminator(model_x_discriminator))  # type: ignore[valid-type]
+
+            if default_type is not None:
+                initialize_cond = None
+            else:
+                initialize_cond = ...
 
-        if default_type is not None:
-            initialize_cond = None
         else:
-            initialize_cond = ...
+            ConditionalType = when_types[0]
+            # a better check here would be if any of the parameters below this have a required value,
+            # in the case of job_internal though this is correct
+            if state_representation == "job_internal":
+                initialize_cond = ...
+            else:
+                initialize_cond = None
 
         py_type = ConditionalType
 

lib/galaxy/tool_util/parser/interface.py

@@ -706,7 +706,9 @@ def to_element(xml_element_dict: "TestCollectionDefElementInternal") -> "JsonTes
                     identifier=identifier, **element_object._test_format_to_dict()
                 )
             else:
-                input_as_dict: Optional[JsonTestDatasetDefDict] = xml_data_input_to_json(cast(ToolSourceTestInput, element_object))
+                input_as_dict: Optional[JsonTestDatasetDefDict] = xml_data_input_to_json(
+                    cast(ToolSourceTestInput, element_object)
+                )
                 if input_as_dict is not None:
                     as_dict = JsonTestCollectionDefDatasetElementDict(
                         identifier=identifier,

lib/galaxy/tool_util/verify/interactor.py

@@ -670,7 +670,10 @@ def run_tool(
             parameters = request_schema["parameters"]
 
             def adapt_datasets(test_input: JsonTestDatasetDefDict) -> DataRequestHda:
-                return DataRequestHda(**self.uploads[test_input["path"]])
+                # if path is not set it might be a composite file with a path,
+                # e.g. composite_shapefile
+                test_input_path = test_input.get("path", "")
+                return DataRequestHda(**self.uploads[test_input_path])
 
             def adapt_collections(test_input: JsonTestCollectionDefDict) -> DataCollectionRequest:
                 test_collection_def = TestCollectionDef.from_dict(test_input)
@@ -709,7 +712,8 @@ def adapt_collections(test_input: JsonTestCollectionDefDict) -> DataCollectionRe
             if not successful:
                 request = self.get_tool_request(tool_request_id) or {}
                 raise RunToolException(
-                    f"Tool request failure - state {request.get('state')}, message: {request.get('state_message')}", inputs_tree
+                    f"Tool request failure - state {request.get('state')}, message: {request.get('state_message')}",
+                    inputs_tree,
                 )
             jobs = self.jobs_for_tool_request(tool_request_id)
             outputs = OutputsDict()

lib/galaxy/tools/__init__.py

@@ -73,7 +73,7 @@
 )
 from galaxy.tool_util.output_checker import DETECTED_JOB_STATE
 from galaxy.tool_util.parameters import (
-    fill_defaults,
+    fill_static_defaults,
     input_models_for_pages,
     JobInternalToolState,
     RequestInternalDereferencedToolState,
@@ -127,6 +127,7 @@
 from galaxy.tools.imp_exp import JobImportHistoryArchiveWrapper
 from galaxy.tools.parameters import (
     check_param,
+    fill_dynamic_defaults,
     params_from_strings,
     params_to_incoming,
     params_to_json,
@@ -1439,7 +1440,7 @@ def parse_inputs(self, tool_source: ToolSource):
         pages = tool_source.parse_input_pages()
         enctypes: Set[str] = set()
         try:
-            parameters = input_models_for_pages(pages)
+            parameters = input_models_for_pages(pages, tool_source.parse_profile())
             self.parameters = parameters
         except Exception:
             pass
@@ -1874,10 +1875,10 @@ def expand_incoming_async(
         all_params: List[ToolStateJobInstancePopulatedT] = []
         internal_states: List[JobInternalToolState] = []
         for expanded_incoming in job_tool_states:
-            expanded_incoming = fill_defaults(expanded_incoming, self)
+            expanded_incoming = fill_static_defaults(expanded_incoming, self, self.profile)
+            fill_dynamic_defaults(request_context, self.inputs, expanded_incoming)
             internal_tool_state = JobInternalToolState(expanded_incoming)
-            # internal_tool_state.validate(self)
-            # some defaults might not be available until populate runs...
+            internal_tool_state.validate(self)
             internal_states.append(internal_tool_state)
             params, errors = self._populate(request_context, expanded_incoming, "21.01")
 

lib/galaxy/tools/parameters/__init__.py

@@ -688,6 +688,61 @@ def _populate_state_legacy(
             state[input.name] = value
 
 
+def fill_dynamic_defaults(
+    request_context,
+    inputs: ToolInputsT,
+    incoming: ToolStateJobInstanceT,
+    context=None,
+):
+    """
+    Expands incoming parameters with default values.
+    """
+    if context is None:
+        context = flat_to_nested_state(incoming)
+    for input in inputs.values():
+        if input.type == "repeat":
+            repeat_input = cast(Repeat, input)
+            for rep in incoming[repeat_input.name]:
+                fill_dynamic_defaults(
+                    request_context,
+                    repeat_input.inputs,
+                    rep,
+                    context=context,
+                )
+
+        elif input.type == "conditional":
+            conditional_input = cast(Conditional, input)
+            test_param = cast(ToolParameter, conditional_input.test_param)
+            test_param_value = incoming.get(conditional_input.name, {}).get(test_param.name)
+            try:
+                current_case = conditional_input.get_current_case(test_param_value)
+                fill_dynamic_defaults(
+                    request_context,
+                    conditional_input.cases[current_case].inputs,
+                    cast(ToolStateJobInstanceT, incoming.get(conditional_input.name)),
+                    context=context,
+                )
+            except Exception:
+                raise Exception("The selected case is unavailable/invalid.")
+
+        elif input.type == "section":
+            section_input = cast(Section, input)
+            fill_dynamic_defaults(
+                request_context,
+                section_input.inputs,
+                cast(ToolStateJobInstanceT, incoming.get(section_input.name)),
+                context=context,
+            )
+
+        elif input.type == "upload_dataset":
+            raise NotImplementedError
+
+        else:
+            if input.name not in incoming:
+                param_value = input.get_initial_value(request_context, context)
+                incoming[input.name] = param_value
+
+
 def _get_incoming_value(incoming, key, default):
     """
     Fetch value from incoming dict directly or check special nginx upload

test/functional/tools/select_optional.xml

@@ -1,4 +1,5 @@
 <tool id="select_optional" name="Optional select" version="1.0.0" profile="20.01">
+    <!-- this tool has a profile of 20.01, but has an identical behavior without it -->
     <command><![CDATA[
         echo select_opt $select_opt >> '$output1' &&
         echo select_mult_opt $select_mult_opt >> '$output1' &&

test/unit/tool_util/framework_tool_checks.yml

@@ -6,3 +6,37 @@ empty_select:
   - {}
   request_invalid:
   - select_optional: anyoption
+
+select_from_dataset_in_conditional:
+  request_valid:
+  - single: {src: hda, id: abcde133543d}
+  request_invalid:
+  - single: 7
+  request_internal_valid:
+  - single: {src: hda, id: 7}
+  request_internal_invalid:
+  - single: 7
+  job_internal_valid:
+  - single: {src: hda, id: 7}
+  job_internal_valid:
+  - single: {src: hda, id: 7}
+    cond:
+      cond: single
+      select_single: chr10
+      inner_cond:
+        inner_cond: single
+        select_single: chr10
+  job_internal_invalid:
+  - single: {src: hda, id: 7}
+    cond:
+      cond: single
+      select_single: chr10
+      inner_cond:
+        inner_cond: single
+        select_single: chr10
+        badoption: true
+  - single: {src: hda, id: 7}
+    cond:
+      cond: single
+      select_single: chr10
+