Unverified Commit 76cb40de authored by John Chilton's avatar John Chilton Committed by GitHub
Browse files

Merge pull request #10560 from... 

Merge pull request #10560 from mvdbeek/fix_extracting_workflow_from_history_with_netsed_collection_input

[20.05] Fix workflow extraction if nested collection in input step
parents cffa939e bca4203a

lib/galaxy/workflow/extract.py

+10 −20
Original line number Diff line number Diff line
@@ -15,6 +15,7 @@ from galaxy.tools.parameters.grouping import ( 
    Repeat,

    Section

)

from galaxy.util import listify

from .steps import (

    attach_ordered_steps,

    order_workflow_steps_with_levels
@@ -54,18 +55,9 @@ def extract_workflow(trans, user, history=None, job_ids=None, dataset_ids=None, 


def extract_steps(trans, history=None, job_ids=None, dataset_ids=None, dataset_collection_ids=None, dataset_names=None, dataset_collection_names=None):

    # Ensure job_ids and dataset_ids are lists (possibly empty)

    if job_ids is None:

        job_ids = []

    elif type(job_ids) is not list:

        job_ids = [job_ids]

    if dataset_ids is None:

        dataset_ids = []

    elif type(dataset_ids) is not list:

        dataset_ids = [dataset_ids]

    if dataset_collection_ids is None:

        dataset_collection_ids = []

    elif type(dataset_collection_ids) is not list:

        dataset_collection_ids = [dataset_collection_ids]

    job_ids = listify(job_ids)

    dataset_ids = listify(dataset_ids)

    dataset_collection_ids = listify(dataset_collection_ids)

    # Convert both sets of ids to integers

    job_ids = [int(_) for _ in job_ids]

    dataset_ids = [int(_) for _ in dataset_ids]
@@ -328,18 +320,16 @@ def __cleanup_param_values(inputs, values): 
    def cleanup(prefix, inputs, values):

        for key, input in inputs.items():

            if isinstance(input, DataToolParameter) or isinstance(input, DataCollectionToolParameter):

                tmp = values[key]

                items = values[key]

                values[key] = None

                # HACK: Nested associations are not yet working, but we

                #       still need to clean them up so we can serialize

                # if not( prefix ):

                if isinstance(tmp, model.DatasetCollectionElement):

                    tmp = tmp.first_dataset_instance()

                if tmp:  # this is false for a non-set optional dataset

                    if not isinstance(tmp, list):

                        associations.append((tmp.hid, prefix + key))

                    else:

                        associations.extend([(t.hid, prefix + key) for t in tmp])

                for item in listify(items):

                    if isinstance(item, model.DatasetCollectionElement):

                        item = item.first_dataset_instance()

                    if item:  # this is false for a non-set optional dataset

                        associations.append((item.hid, prefix + key))



                # Cleanup the other deprecated crap associated with datasets

                # as well. Worse, for nested datasets all the metadata is

lib/galaxy_test/api/test_workflow_extraction.py

+23 −0
Original line number Diff line number Diff line
@@ -253,6 +253,29 @@ test_data: 
        collection_step_state = loads(collection_step["tool_state"])

        self.assertEqual(collection_step_state["collection_type"], "list:paired")



    @skip_without_tool("cat_list")

    @skip_without_tool("collection_creates_dynamic_nested")

    def test_subcollection_reduction(self):

        jobs_summary = self._run_jobs("""

class: GalaxyWorkflow

steps:

  creates_nested_list:

    tool_id: collection_creates_dynamic_nested

  reduce_nested_list:

    tool_id: cat_list

    in:

      input1: creates_nested_list/list_output

""")

        job1_id = self._job_id_for_tool(jobs_summary.jobs, "cat_list")

        job2_id = self._job_id_for_tool(jobs_summary.jobs, "collection_creates_dynamic_nested")

        self._extract_and_download_workflow(

            reimport_as="test_extract_workflows_with_subcollection_reduction",

            dataset_collection_ids=["1"],

            job_ids=[job1_id, job2_id],

        )

        # TODO: refactor workflow extraction to not rely on HID, so we can actually properly connect

        # this workflow



    @skip_without_tool("collection_split_on_column")

    def test_extract_workflow_with_output_collections(self):

        jobs_summary = self._run_jobs("""