[23.2] Fix missing implicit conversion for mapped over jobs

lib/galaxy/tools/evaluation.py

@@ -355,6 +355,7 @@ def wrap_input(input_values, input):
                 element_identifier = element_identifier_mapper.identifier(dataset, param_dict)
                 if element_identifier:
                     wrapper_kwds["identifier"] = element_identifier
+                wrapper_kwds["formats"] = input.formats
                 input_values[input.name] = DatasetFilenameWrapper(dataset, **wrapper_kwds)
             elif isinstance(input, DataCollectionToolParameter):
                 dataset_collection = value

lib/galaxy_test/api/test_workflows.py

@@ -3828,6 +3828,31 @@ def test_subworkflow_map_over_data_column(self):
                 assert_ok=True,
             )
 
+    @skip_without_tool("implicit_conversion_format_input")
+    def test_run_with_implicit_collection_map_over(self):
+        with self.dataset_populator.test_history() as history_id:
+            self._run_workflow(
+                """
+class: GalaxyWorkflow
+inputs:
+  collection: collection
+steps:
+  map_over:
+    tool_id: implicit_conversion_format_input
+    in:
+      input1: collection
+test_data:
+  collection:
+    collection_type: list
+    elements:
+      - identifier: 1
+        value: 1.fasta.gz
+        type: File
+""",
+                history_id=history_id,
+                assert_ok=True,
+            )
+
     @skip_without_tool("random_lines1")
     def test_change_datatype_collection_map_over(self):
         with self.dataset_populator.test_history() as history_id:

lib/galaxy_test/base/populators.py

@@ -2857,6 +2857,8 @@ def __create_payload_fetch(self, history_id: str, collection_type, **kwds):
             history_id=history_id,
             targets=targets,
         )
+        if "__files" in kwds:
+            payload["__files"] = kwds.pop("__files")
         return payload
 
     def wait_for_fetched_collection(self, fetch_response: Union[Dict[str, Any], Response]):
@@ -2992,22 +2994,26 @@ def read_test_data(test_dict):
         if is_dict and ("elements" in value or value.get("collection_type")):
             elements_data = value.get("elements", [])
             elements = []
-            for element_data in elements_data:
+            new_collection_kwds: Dict[str, Any] = {}
+            for i, element_data in enumerate(elements_data):
                 # Adapt differences between test_data dict and fetch API description.
                 if "name" not in element_data:
                     identifier = element_data.pop("identifier")
                     element_data["name"] = identifier
                 input_type = element_data.pop("type", "raw")
                 content = None
                 if input_type == "File":
-                    content = read_test_data(element_data)
+                    content = open_test_data(element_data)
+                    element_data["src"] = "files"
+                    if "__files" not in new_collection_kwds:
+                        new_collection_kwds["__files"] = {}
+                    new_collection_kwds["__files"][f"file_{i}|file_data"] = content
                 else:
                     content = element_data.pop("content")
-                if content is not None:
-                    element_data["src"] = "pasted"
-                    element_data["paste_content"] = content
+                    if content is not None:
+                        element_data["src"] = "pasted"
+                        element_data["paste_content"] = content
                 elements.append(element_data)
-            new_collection_kwds = {}
             if "name" in value:
                 new_collection_kwds["name"] = value["name"]
             collection_type = value.get("collection_type", "")