mirror of
https://github.com/galaxyproject/galaxy.git
synced 2026-09-24 16:30:27 +08:00
John Chilton
8af243c176
Allow the rules DSL & GUI component to operate on existing collections to allow filtering, sorting, modifying identifiers and general re-organization of existing collections (e.g. the outputs of tools). Implementing this as a collection operation tool so that it should be executable interactively in the tool form and in a batch fashion as part of workflow executions. For this to be tracked properly as a tool execution and to work properly in the tool form, I've implemented a new tool framework and tool form parameter type called "rules". This can thought of as a more GUI friendly alternative to my proposed collection operations that consumed JavaScript expressions. This includes API tests for both tool and workflow execution of the new tool as well as Selenium tests for tool form execution, workflow editor interactions, and workflow running.
2894 lines
116 KiB
Python
2894 lines
116 KiB
Python
from __future__ import print_function
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import json
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import time
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from collections import namedtuple
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from json import dumps
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from uuid import uuid4
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import yaml
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from requests import delete, put
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from base import api # noqa: I100,I202
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from base import rules_test_data # noqa: I100
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from base.populators import ( # noqa: I100
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DatasetCollectionPopulator,
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DatasetPopulator,
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flakey,
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load_data_dict,
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skip_without_tool,
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wait_on,
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WorkflowPopulator
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)
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from base.workflow_fixtures import ( # noqa: I100
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WORKFLOW_NESTED_SIMPLE,
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WORKFLOW_WITH_DYNAMIC_OUTPUT_COLLECTION,
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WORKFLOW_WITH_OUTPUT_COLLECTION,
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WORKFLOW_WITH_OUTPUT_COLLECTION_MAPPING,
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WORKFLOW_WITH_RULES_1,
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)
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from galaxy.exceptions import error_codes # noqa: I201
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from galaxy.tools.verify.test_data import TestDataResolver
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class BaseWorkflowsApiTestCase(api.ApiTestCase):
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# TODO: Find a new file for this class.
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def setUp(self):
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super(BaseWorkflowsApiTestCase, self).setUp()
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self.workflow_populator = WorkflowPopulator(self.galaxy_interactor)
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self.dataset_populator = DatasetPopulator(self.galaxy_interactor)
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self.dataset_collection_populator = DatasetCollectionPopulator(self.galaxy_interactor)
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def _assert_user_has_workflow_with_name(self, name):
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names = self._workflow_names()
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assert name in names, "No workflows with name %s in users workflows <%s>" % (name, names)
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def _workflow_names(self):
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index_response = self._get("workflows")
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self._assert_status_code_is(index_response, 200)
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names = [w["name"] for w in index_response.json()]
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return names
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def import_workflow(self, workflow, **kwds):
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upload_response = self.workflow_populator.import_workflow(workflow, **kwds)
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return upload_response
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def _upload_yaml_workflow(self, has_yaml, **kwds):
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return self.workflow_populator.upload_yaml_workflow(has_yaml, **kwds)
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def _setup_workflow_run(self, workflow=None, inputs_by='step_id', history_id=None, workflow_id=None):
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if not workflow_id:
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workflow_id = self.workflow_populator.create_workflow(workflow)
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if not history_id:
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history_id = self.dataset_populator.new_history()
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hda1 = self.dataset_populator.new_dataset(history_id, content="1 2 3")
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hda2 = self.dataset_populator.new_dataset(history_id, content="4 5 6")
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workflow_request = dict(
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history="hist_id=%s" % history_id,
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workflow_id=workflow_id,
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)
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label_map = {
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'WorkflowInput1': self._ds_entry(hda1),
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'WorkflowInput2': self._ds_entry(hda2)
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}
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if inputs_by == 'step_id':
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ds_map = self._build_ds_map(workflow_id, label_map)
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workflow_request["ds_map"] = ds_map
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elif inputs_by == "step_index":
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index_map = {
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'0': self._ds_entry(hda1),
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'1': self._ds_entry(hda2)
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}
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workflow_request["inputs"] = dumps(index_map)
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workflow_request["inputs_by"] = 'step_index'
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elif inputs_by == "name":
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workflow_request["inputs"] = dumps(label_map)
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workflow_request["inputs_by"] = 'name'
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elif inputs_by in ["step_uuid", "uuid_implicitly"]:
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uuid_map = {
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workflow["steps"]["0"]["uuid"]: self._ds_entry(hda1),
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workflow["steps"]["1"]["uuid"]: self._ds_entry(hda2),
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}
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workflow_request["inputs"] = dumps(uuid_map)
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if inputs_by == "step_uuid":
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workflow_request["inputs_by"] = "step_uuid"
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return workflow_request, history_id
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def _build_ds_map(self, workflow_id, label_map):
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workflow_inputs = self._workflow_inputs(workflow_id)
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ds_map = {}
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for key, value in workflow_inputs.items():
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label = value["label"]
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if label in label_map:
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ds_map[key] = label_map[label]
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return dumps(ds_map)
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def _ds_entry(self, history_content):
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return self.dataset_populator.ds_entry(history_content)
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def _workflow_inputs(self, uploaded_workflow_id):
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workflow_show_resposne = self._get("workflows/%s" % uploaded_workflow_id)
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self._assert_status_code_is(workflow_show_resposne, 200)
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workflow_inputs = workflow_show_resposne.json()["inputs"]
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return workflow_inputs
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def _invocation_details(self, workflow_id, invocation_id):
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invocation_details_response = self._get("workflows/%s/usage/%s" % (workflow_id, invocation_id))
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self._assert_status_code_is(invocation_details_response, 200)
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invocation_details = invocation_details_response.json()
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return invocation_details
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def _run_jobs(self, has_workflow, history_id=None, wait=True, source_type=None, jobs_descriptions=None, expected_response=200, assert_ok=True):
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def read_test_data(test_dict):
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test_data_resolver = TestDataResolver()
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filename = test_data_resolver.get_filename(test_dict["value"])
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content = open(filename, "r").read()
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return content
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if history_id is None:
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history_id = self.history_id
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workflow_id = self._upload_yaml_workflow(
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has_workflow, source_type=source_type
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)
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if jobs_descriptions is None:
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assert source_type != "path"
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jobs_descriptions = yaml.safe_load(has_workflow)
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test_data = jobs_descriptions.get("test_data", {})
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inputs, label_map, has_uploads = load_data_dict(history_id, test_data, self.dataset_populator, self.dataset_collection_populator)
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workflow_request = dict(
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history="hist_id=%s" % history_id,
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workflow_id=workflow_id,
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)
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workflow_request["inputs"] = dumps(label_map)
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workflow_request["inputs_by"] = 'name'
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if has_uploads:
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self.dataset_populator.wait_for_history(history_id, assert_ok=True)
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url = "workflows/%s/usage" % (workflow_id)
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invocation_response = self._post(url, data=workflow_request)
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self._assert_status_code_is(invocation_response, expected_response)
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invocation = invocation_response.json()
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invocation_id = invocation.get('id')
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if invocation_id:
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# Wait for workflow to become fully scheduled and then for all jobs
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# complete.
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if wait:
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self.workflow_populator.wait_for_workflow(workflow_id, invocation_id, history_id, assert_ok=assert_ok)
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jobs = self._history_jobs(history_id)
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return RunJobsSummary(
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history_id=history_id,
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workflow_id=workflow_id,
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invocation_id=invocation_id,
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inputs=inputs,
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jobs=jobs,
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invocation=invocation,
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workflow_request=workflow_request
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)
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def _history_jobs(self, history_id):
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return self._get("jobs", {"history_id": history_id, "order_by": "create_time"}).json()
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def _assert_history_job_count(self, history_id, n):
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jobs = self._history_jobs(history_id)
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self.assertEqual(len(jobs), n)
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# Workflow API TODO:
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# - Allow history_id as param to workflow run action. (hist_id)
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# - Allow post to workflows/<workflow_id>/run in addition to posting to
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# /workflows with id in payload.
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# - Much more testing obviously, always more testing.
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class WorkflowsApiTestCase(BaseWorkflowsApiTestCase):
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def setUp(self):
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super(WorkflowsApiTestCase, self).setUp()
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def test_show_valid(self):
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workflow_id = self.workflow_populator.simple_workflow("dummy")
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workflow_id = self.workflow_populator.simple_workflow("test_regular")
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show_response = self._get("workflows/%s" % workflow_id, {"style": "instance"})
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workflow = show_response.json()
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self._assert_looks_like_instance_workflow_representation(workflow)
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assert len(workflow["steps"]) == 3
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self.assertEqual(sorted(step["id"] for step in workflow["steps"].values()), [0, 1, 2])
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show_response = self._get("workflows/%s" % workflow_id, {"legacy": True})
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workflow = show_response.json()
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self._assert_looks_like_instance_workflow_representation(workflow)
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assert len(workflow["steps"]) == 3
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# Can't reay say what the legacy IDs are but must be greater than 3 because dummy
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# workflow was created first in this instance.
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self.assertNotEqual(sorted(step["id"] for step in workflow["steps"].values()), [0, 1, 2])
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def test_show_invalid_key_is_400(self):
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show_response = self._get("workflows/%s" % self._random_key())
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self._assert_status_code_is(show_response, 400)
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def test_cannot_show_private_workflow(self):
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workflow_id = self.workflow_populator.simple_workflow("test_not_importportable")
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with self._different_user():
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show_response = self._get("workflows/%s" % workflow_id)
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self._assert_status_code_is(show_response, 403)
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def test_delete(self):
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workflow_id = self.workflow_populator.simple_workflow("test_delete")
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workflow_name = "test_delete"
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self._assert_user_has_workflow_with_name(workflow_name)
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workflow_url = self._api_url("workflows/%s" % workflow_id, use_key=True)
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delete_response = delete(workflow_url)
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self._assert_status_code_is(delete_response, 200)
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# Make sure workflow is no longer in index by default.
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assert workflow_name not in self._workflow_names()
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def test_other_cannot_delete(self):
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workflow_id = self.workflow_populator.simple_workflow("test_other_delete")
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with self._different_user():
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workflow_url = self._api_url("workflows/%s" % workflow_id, use_key=True)
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delete_response = delete(workflow_url)
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self._assert_status_code_is(delete_response, 403)
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def test_index(self):
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index_response = self._get("workflows")
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self._assert_status_code_is(index_response, 200)
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assert isinstance(index_response.json(), list)
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def test_upload(self):
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self.__test_upload(use_deprecated_route=False)
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def test_upload_deprecated(self):
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self.__test_upload(use_deprecated_route=True)
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def test_import_tools_requires_admin(self):
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response = self.__test_upload(import_tools=True, assert_ok=False)
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assert response.status_code == 403
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def __test_upload(self, use_deprecated_route=False, name="test_import", workflow=None, assert_ok=True, import_tools=False):
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if workflow is None:
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workflow = self.workflow_populator.load_workflow(name=name)
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data = dict(
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workflow=dumps(workflow),
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)
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if import_tools:
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data["import_tools"] = import_tools
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if use_deprecated_route:
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route = "workflows/upload"
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else:
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route = "workflows"
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upload_response = self._post(route, data=data)
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if assert_ok:
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self._assert_status_code_is(upload_response, 200)
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self._assert_user_has_workflow_with_name(name)
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return upload_response
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def test_update(self):
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original_workflow = self.workflow_populator.load_workflow(name="test_import")
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uuids = {}
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labels = {}
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for order_index, step_dict in original_workflow["steps"].items():
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uuid = str(uuid4())
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step_dict["uuid"] = uuid
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uuids[order_index] = uuid
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label = "label_%s" % order_index
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step_dict["label"] = label
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labels[order_index] = label
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def check_label_and_uuid(order_index, step_dict):
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assert order_index in uuids
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assert order_index in labels
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self.assertEqual(uuids[order_index], step_dict["uuid"])
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self.assertEqual(labels[order_index], step_dict["label"])
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upload_response = self.__test_upload(workflow=original_workflow)
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workflow_id = upload_response.json()["id"]
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def update(workflow_object):
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put_response = self._update_workflow(workflow_id, workflow_object)
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self._assert_status_code_is(put_response, 200)
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return put_response
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workflow_content = self._download_workflow(workflow_id)
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steps = workflow_content["steps"]
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def tweak_step(step):
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order_index, step_dict = step
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check_label_and_uuid(order_index, step_dict)
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assert step_dict['position']['top'] != 1
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assert step_dict['position']['left'] != 1
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step_dict['position'] = {'top': 1, 'left': 1}
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map(tweak_step, steps.items())
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update(workflow_content)
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def check_step(step):
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order_index, step_dict = step
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check_label_and_uuid(order_index, step_dict)
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assert step_dict['position']['top'] == 1
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assert step_dict['position']['left'] == 1
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updated_workflow_content = self._download_workflow(workflow_id)
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map(check_step, updated_workflow_content['steps'].items())
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# Re-update against original worklfow...
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update(original_workflow)
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updated_workflow_content = self._download_workflow(workflow_id)
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# Make sure the positions have been updated.
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map(tweak_step, updated_workflow_content['steps'].items())
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def test_update_no_tool_id(self):
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workflow_object = self.workflow_populator.load_workflow(name="test_import")
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upload_response = self.__test_upload(workflow=workflow_object)
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workflow_id = upload_response.json()["id"]
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del workflow_object["steps"]["2"]["tool_id"]
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put_response = self._update_workflow(workflow_id, workflow_object)
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self._assert_status_code_is(put_response, 400)
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def test_update_missing_tool(self):
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# Create allows missing tools, update doesn't currently...
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workflow_object = self.workflow_populator.load_workflow(name="test_import")
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upload_response = self.__test_upload(workflow=workflow_object)
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workflow_id = upload_response.json()["id"]
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workflow_object["steps"]["2"]["tool_id"] = "cat-not-found"
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put_response = self._update_workflow(workflow_id, workflow_object)
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self._assert_status_code_is(put_response, 400)
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def test_require_unique_step_uuids(self):
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workflow_dup_uuids = self.workflow_populator.load_workflow(name="test_import")
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uuid0 = str(uuid4())
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for step_dict in workflow_dup_uuids["steps"].values():
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step_dict["uuid"] = uuid0
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response = self.workflow_populator.create_workflow_response(workflow_dup_uuids)
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self._assert_status_code_is(response, 400)
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def test_require_unique_step_labels(self):
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workflow_dup_label = self.workflow_populator.load_workflow(name="test_import")
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for step_dict in workflow_dup_label["steps"].values():
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step_dict["label"] = "my duplicated label"
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response = self.workflow_populator.create_workflow_response(workflow_dup_label)
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self._assert_status_code_is(response, 400)
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def test_import_deprecated(self):
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workflow_id = self.workflow_populator.simple_workflow("test_import_published_deprecated", publish=True)
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with self._different_user():
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other_import_response = self.__import_workflow(workflow_id)
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self._assert_status_code_is(other_import_response, 200)
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self._assert_user_has_workflow_with_name("imported: test_import_published_deprecated")
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def test_import_annotations(self):
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workflow_id = self.workflow_populator.simple_workflow("test_import_annotations", publish=True)
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with self._different_user():
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other_import_response = self.__import_workflow(workflow_id)
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self._assert_status_code_is(other_import_response, 200)
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# Test annotations preserved during upload and copied over during
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# import.
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other_id = other_import_response.json()["id"]
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imported_workflow = self._show_workflow(other_id)
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assert imported_workflow["annotation"] == "simple workflow"
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step_annotations = set(step["annotation"] for step in imported_workflow["steps"].values())
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assert "input1 description" in step_annotations
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def test_import_subworkflows(self):
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def get_subworkflow_content_id(workflow_id):
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workflow_contents = self._download_workflow(workflow_id, style="editor")
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steps = workflow_contents['steps']
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subworkflow_step = next(s for s in steps.values() if s["type"] == "subworkflow")
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return subworkflow_step['content_id']
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workflow_id = self._upload_yaml_workflow(WORKFLOW_NESTED_SIMPLE, publish=True)
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subworkflow_content_id = get_subworkflow_content_id(workflow_id)
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with self._different_user():
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other_import_response = self.__import_workflow(workflow_id)
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self._assert_status_code_is(other_import_response, 200)
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imported_workflow_id = other_import_response.json()["id"]
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imported_subworkflow_content_id = get_subworkflow_content_id(imported_workflow_id)
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assert subworkflow_content_id != imported_subworkflow_content_id
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def test_not_importable_prevents_import(self):
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workflow_id = self.workflow_populator.simple_workflow("test_not_importportable")
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with self._different_user():
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other_import_response = self.__import_workflow(workflow_id)
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self._assert_status_code_is(other_import_response, 403)
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def test_import_published(self):
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workflow_id = self.workflow_populator.simple_workflow("test_import_published", publish=True)
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with self._different_user():
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other_import_response = self.__import_workflow(workflow_id, deprecated_route=True)
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self._assert_status_code_is(other_import_response, 200)
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self._assert_user_has_workflow_with_name("imported: test_import_published")
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def test_export(self):
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uploaded_workflow_id = self.workflow_populator.simple_workflow("test_for_export")
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downloaded_workflow = self._download_workflow(uploaded_workflow_id)
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assert downloaded_workflow["name"] == "test_for_export"
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assert len(downloaded_workflow["steps"]) == 3
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first_input = downloaded_workflow["steps"]["0"]["inputs"][0]
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assert first_input["name"] == "WorkflowInput1"
|
|
assert first_input["description"] == "input1 description"
|
|
self._assert_has_keys(downloaded_workflow, "a_galaxy_workflow", "format-version", "annotation", "uuid", "steps")
|
|
for step in downloaded_workflow["steps"].values():
|
|
self._assert_has_keys(
|
|
step,
|
|
'id',
|
|
'type',
|
|
'tool_id',
|
|
'tool_version',
|
|
'name',
|
|
'tool_state',
|
|
'annotation',
|
|
'inputs',
|
|
'workflow_outputs',
|
|
'outputs'
|
|
)
|
|
if step['type'] == "tool":
|
|
self._assert_has_keys(step, "post_job_actions")
|
|
|
|
def test_export_editor(self):
|
|
uploaded_workflow_id = self.workflow_populator.simple_workflow("test_for_export")
|
|
downloaded_workflow = self._download_workflow(uploaded_workflow_id, style="editor")
|
|
self._assert_has_keys(downloaded_workflow, "name", "steps", "upgrade_messages")
|
|
for step in downloaded_workflow["steps"].values():
|
|
self._assert_has_keys(
|
|
step,
|
|
'id',
|
|
'type',
|
|
'content_id',
|
|
'name',
|
|
'tool_state',
|
|
'tooltip',
|
|
'data_inputs',
|
|
'data_outputs',
|
|
'config_form',
|
|
'annotation',
|
|
'post_job_actions',
|
|
'workflow_outputs',
|
|
'uuid',
|
|
'label',
|
|
)
|
|
|
|
def test_import_missing_tool(self):
|
|
workflow = self.workflow_populator.load_workflow_from_resource(name="test_workflow_missing_tool")
|
|
workflow_id = self.workflow_populator.create_workflow(workflow)
|
|
workflow_description = self._show_workflow(workflow_id)
|
|
steps = workflow_description["steps"]
|
|
missing_tool_steps = [v for v in steps.values() if v['tool_id'] == 'cat_missing_tool']
|
|
assert len(missing_tool_steps) == 1
|
|
|
|
def test_import_no_tool_id(self):
|
|
# Import works with missing tools, but not with absent content/tool id.
|
|
workflow = self.workflow_populator.load_workflow_from_resource(name="test_workflow_missing_tool")
|
|
del workflow["steps"]["2"]["tool_id"]
|
|
create_response = self.__test_upload(workflow=workflow, assert_ok=False)
|
|
self._assert_status_code_is(create_response, 400)
|
|
|
|
def test_import_export_with_runtime_inputs(self):
|
|
workflow = self.workflow_populator.load_workflow_from_resource(name="test_workflow_with_runtime_input")
|
|
workflow_id = self.workflow_populator.create_workflow(workflow)
|
|
downloaded_workflow = self._download_workflow(workflow_id)
|
|
assert len(downloaded_workflow["steps"]) == 2
|
|
runtime_input = downloaded_workflow["steps"]["1"]["inputs"][0]
|
|
assert runtime_input["description"].startswith("runtime parameter for tool")
|
|
assert runtime_input["name"] == "num_lines"
|
|
|
|
@skip_without_tool("cat1")
|
|
def test_run_workflow_by_index(self):
|
|
self.__run_cat_workflow(inputs_by='step_index')
|
|
|
|
@skip_without_tool("cat1")
|
|
def test_run_workflow_by_uuid(self):
|
|
self.__run_cat_workflow(inputs_by='step_uuid')
|
|
|
|
@skip_without_tool("cat1")
|
|
def test_run_workflow_by_uuid_implicitly(self):
|
|
self.__run_cat_workflow(inputs_by='uuid_implicitly')
|
|
|
|
@skip_without_tool("cat1")
|
|
def test_run_workflow_by_name(self):
|
|
self.__run_cat_workflow(inputs_by='name')
|
|
|
|
@skip_without_tool("cat1")
|
|
def test_run_workflow(self):
|
|
self.__run_cat_workflow(inputs_by='step_id')
|
|
|
|
@skip_without_tool("multiple_versions")
|
|
def test_run_versioned_tools(self):
|
|
with self.dataset_populator.test_history() as history_01_id:
|
|
workflow_version_01 = self._upload_yaml_workflow("""
|
|
class: GalaxyWorkflow
|
|
steps:
|
|
- tool_id: multiple_versions
|
|
tool_version: "0.1"
|
|
state:
|
|
inttest: 0
|
|
""")
|
|
self.__invoke_workflow(history_01_id, workflow_version_01)
|
|
self.dataset_populator.wait_for_history(history_01_id, assert_ok=True)
|
|
|
|
with self.dataset_populator.test_history() as history_02_id:
|
|
workflow_version_02 = self._upload_yaml_workflow("""
|
|
class: GalaxyWorkflow
|
|
steps:
|
|
- tool_id: multiple_versions
|
|
tool_version: "0.2"
|
|
state:
|
|
inttest: 1
|
|
""")
|
|
self.__invoke_workflow(history_02_id, workflow_version_02)
|
|
self.dataset_populator.wait_for_history(history_02_id, assert_ok=True)
|
|
|
|
def __run_cat_workflow(self, inputs_by):
|
|
workflow = self.workflow_populator.load_workflow(name="test_for_run")
|
|
workflow["steps"]["0"]["uuid"] = str(uuid4())
|
|
workflow["steps"]["1"]["uuid"] = str(uuid4())
|
|
workflow_request, history_id = self._setup_workflow_run(workflow, inputs_by=inputs_by)
|
|
# TODO: This should really be a post to workflows/<workflow_id>/run or
|
|
# something like that.
|
|
run_workflow_response = self._post("workflows", data=workflow_request)
|
|
self._assert_status_code_is(run_workflow_response, 200)
|
|
invocation_id = run_workflow_response.json()["id"]
|
|
invocation = self._invocation_details(workflow_request["workflow_id"], invocation_id)
|
|
assert invocation["state"] == "scheduled", invocation
|
|
|
|
self._assert_status_code_is(run_workflow_response, 200)
|
|
self.dataset_populator.wait_for_history(history_id, assert_ok=True)
|
|
|
|
@skip_without_tool("collection_creates_pair")
|
|
def test_workflow_run_output_collections(self):
|
|
with self.dataset_populator.test_history() as history_id:
|
|
self._run_jobs(WORKFLOW_WITH_OUTPUT_COLLECTION, history_id=history_id, assert_ok=True, wait=True)
|
|
self.assertEqual("a\nc\nb\nd\n", self.dataset_populator.get_history_dataset_content(history_id, hid=0))
|
|
|
|
@skip_without_tool("job_properties")
|
|
@skip_without_tool("identifier_multiple_in_conditional")
|
|
def test_workflow_resume_from_failed_step(self):
|
|
workflow_id = self._upload_yaml_workflow("""
|
|
class: GalaxyWorkflow
|
|
steps:
|
|
- tool_id: job_properties
|
|
state:
|
|
thebool: true
|
|
failbool: true
|
|
- tool_id: identifier_multiple_in_conditional
|
|
state:
|
|
outer_cond:
|
|
cond_param_outer: true
|
|
inner_cond:
|
|
cond_param_inner: true
|
|
input1:
|
|
$link: 0#out_file1
|
|
""")
|
|
with self.dataset_populator.test_history() as history_id:
|
|
invocation_id = self.__invoke_workflow(history_id, workflow_id)
|
|
self.wait_for_invocation_and_jobs(history_id, workflow_id, invocation_id, assert_ok=False)
|
|
failed_dataset_one = self.dataset_populator.get_history_dataset_details(history_id, hid=1, wait=True, assert_ok=False)
|
|
assert failed_dataset_one['state'] == 'error', failed_dataset_one
|
|
paused_dataset = self.dataset_populator.get_history_dataset_details(history_id, hid=5, wait=True, assert_ok=False)
|
|
assert paused_dataset['state'] == 'paused', paused_dataset
|
|
inputs = {"thebool": "false",
|
|
"failbool": "false",
|
|
"rerun_remap_job_id": failed_dataset_one['creating_job']}
|
|
self.dataset_populator.run_tool(tool_id='job_properties',
|
|
inputs=inputs,
|
|
history_id=history_id,
|
|
assert_ok=True)
|
|
unpaused_dataset = self.dataset_populator.get_history_dataset_details(history_id, hid=5, wait=True, assert_ok=False)
|
|
assert unpaused_dataset['state'] == 'ok'
|
|
|
|
@skip_without_tool("job_properties")
|
|
@skip_without_tool("identifier_multiple_in_conditional")
|
|
def test_workflow_resume_from_failed_step_with_hdca_input(self):
|
|
workflow_id = self._upload_yaml_workflow("""
|
|
class: GalaxyWorkflow
|
|
steps:
|
|
- tool_id: job_properties
|
|
state:
|
|
thebool: true
|
|
failbool: true
|
|
- tool_id: identifier_collection
|
|
state:
|
|
input1:
|
|
$link: 0#list_output
|
|
""")
|
|
with self.dataset_populator.test_history() as history_id:
|
|
invocation_id = self.__invoke_workflow(history_id, workflow_id)
|
|
self.wait_for_invocation_and_jobs(history_id, workflow_id, invocation_id, assert_ok=False)
|
|
failed_dataset_one = self.dataset_populator.get_history_dataset_details(history_id, hid=1, wait=True, assert_ok=False)
|
|
assert failed_dataset_one['state'] == 'error', failed_dataset_one
|
|
paused_dataset = self.dataset_populator.get_history_dataset_details(history_id, hid=5, wait=True, assert_ok=False)
|
|
assert paused_dataset['state'] == 'paused', paused_dataset
|
|
inputs = {"thebool": "false",
|
|
"failbool": "false",
|
|
"rerun_remap_job_id": failed_dataset_one['creating_job']}
|
|
self.dataset_populator.run_tool(tool_id='job_properties',
|
|
inputs=inputs,
|
|
history_id=history_id,
|
|
assert_ok=True)
|
|
unpaused_dataset = self.dataset_populator.get_history_dataset_details(history_id, hid=5, wait=True,
|
|
assert_ok=False)
|
|
assert unpaused_dataset['state'] == 'ok'
|
|
|
|
@skip_without_tool("fail_identifier")
|
|
@skip_without_tool("identifier_multiple_in_conditional")
|
|
def test_workflow_resume_with_mapped_over_input(self):
|
|
with self.dataset_populator.test_history() as history_id:
|
|
job_summary = self._run_jobs("""
|
|
class: GalaxyWorkflow
|
|
steps:
|
|
- label: input_datasets
|
|
type: input_collection
|
|
- label: fail_identifier_1
|
|
tool_id: fail_identifier
|
|
state:
|
|
input1:
|
|
$link: input_datasets
|
|
failbool: true
|
|
- tool_id: identifier_collection
|
|
state:
|
|
input1:
|
|
$link: fail_identifier_1#out_file1
|
|
test_data:
|
|
input_datasets:
|
|
type: list
|
|
elements:
|
|
- identifier: fail
|
|
value: 1.fastq
|
|
type: File
|
|
- identifier: success
|
|
value: 1.fastq
|
|
type: File
|
|
""", history_id=history_id, assert_ok=False, wait=False)
|
|
self.wait_for_invocation_and_jobs(history_id, job_summary.workflow_id, job_summary.invocation_id, assert_ok=False)
|
|
history_contents = self.dataset_populator._get_contents_request(history_id=history_id).json()
|
|
paused_dataset = history_contents[-1]
|
|
failed_dataset = self.dataset_populator.get_history_dataset_details(history_id, hid=5, assert_ok=False)
|
|
assert paused_dataset['state'] == 'paused', paused_dataset
|
|
assert failed_dataset['state'] == 'error', failed_dataset
|
|
inputs = {"input1": {'values': [{'src': 'hda',
|
|
'id': history_contents[0]['id']}]
|
|
},
|
|
"failbool": "false",
|
|
"rerun_remap_job_id": failed_dataset['creating_job']}
|
|
self.dataset_populator.run_tool(tool_id='fail_identifier',
|
|
inputs=inputs,
|
|
history_id=history_id,
|
|
assert_ok=True)
|
|
unpaused_dataset = self.dataset_populator.get_history_dataset_details(history_id, wait=True, assert_ok=False)
|
|
assert unpaused_dataset['state'] == 'ok'
|
|
contents = self.dataset_populator.get_history_dataset_content(history_id, hid=7, assert_ok=False)
|
|
assert contents == 'fail\nsuccess\n', contents
|
|
|
|
@skip_without_tool("collection_creates_pair")
|
|
def test_workflow_run_output_collection_mapping(self):
|
|
workflow_id = self._upload_yaml_workflow(WORKFLOW_WITH_OUTPUT_COLLECTION_MAPPING)
|
|
with self.dataset_populator.test_history() as history_id:
|
|
hdca1 = self.dataset_collection_populator.create_list_in_history(history_id, contents=["a\nb\nc\nd\n", "e\nf\ng\nh\n"]).json()
|
|
self.dataset_populator.wait_for_history(history_id, assert_ok=True)
|
|
inputs = {
|
|
'0': self._ds_entry(hdca1),
|
|
}
|
|
invocation_id = self.__invoke_workflow(history_id, workflow_id, inputs)
|
|
self.wait_for_invocation_and_jobs(history_id, workflow_id, invocation_id)
|
|
self.dataset_populator.wait_for_history(history_id, assert_ok=True)
|
|
self.assertEqual("a\nc\nb\nd\ne\ng\nf\nh\n", self.dataset_populator.get_history_dataset_content(history_id, hid=0))
|
|
|
|
@skip_without_tool("collection_split_on_column")
|
|
def test_workflow_run_dynamic_output_collections(self):
|
|
with self.dataset_populator.test_history() as history_id:
|
|
self._run_jobs(WORKFLOW_WITH_DYNAMIC_OUTPUT_COLLECTION, history_id=history_id, assert_ok=True, wait=True)
|
|
details = self.dataset_populator.get_history_dataset_details(history_id, hid=0)
|
|
last_item_hid = details["hid"]
|
|
assert last_item_hid == 7, "Expected 7 history items, got %s" % last_item_hid
|
|
content = self.dataset_populator.get_history_dataset_content(history_id, hid=0)
|
|
self.assertEqual("10.0\n30.0\n20.0\n40.0\n", content)
|
|
|
|
@skip_without_tool("collection_split_on_column")
|
|
@skip_without_tool("min_repeat")
|
|
def test_workflow_run_dynamic_output_collections_2(self):
|
|
# A more advanced output collection workflow, testing regression of
|
|
# https://github.com/galaxyproject/galaxy/issues/776
|
|
with self.dataset_populator.test_history() as history_id:
|
|
workflow_id = self._upload_yaml_workflow("""
|
|
class: GalaxyWorkflow
|
|
steps:
|
|
- label: test_input_1
|
|
type: input
|
|
- label: test_input_2
|
|
type: input
|
|
- label: test_input_3
|
|
type: input
|
|
- label: split_up
|
|
tool_id: collection_split_on_column
|
|
state:
|
|
input1:
|
|
$link: test_input_2
|
|
- label: min_repeat
|
|
tool_id: min_repeat
|
|
state:
|
|
queries:
|
|
- input:
|
|
$link: test_input_1
|
|
queries2:
|
|
- input2:
|
|
$link: split_up#split_output
|
|
""")
|
|
hda1 = self.dataset_populator.new_dataset(history_id, content="samp1\t10.0\nsamp2\t20.0\n")
|
|
hda2 = self.dataset_populator.new_dataset(history_id, content="samp1\t20.0\nsamp2\t40.0\n")
|
|
hda3 = self.dataset_populator.new_dataset(history_id, content="samp1\t30.0\nsamp2\t60.0\n")
|
|
self.dataset_populator.wait_for_history(history_id, assert_ok=True)
|
|
inputs = {
|
|
'0': self._ds_entry(hda1),
|
|
'1': self._ds_entry(hda2),
|
|
'2': self._ds_entry(hda3),
|
|
}
|
|
invocation_id = self.__invoke_workflow(history_id, workflow_id, inputs)
|
|
self.wait_for_invocation_and_jobs(history_id, workflow_id, invocation_id)
|
|
collection_details = self.dataset_populator.get_history_collection_details(history_id, hid=7)
|
|
assert collection_details["populated_state"] == "ok"
|
|
content = self.dataset_populator.get_history_dataset_content(history_id, hid=11)
|
|
self.assertEqual(content.strip(), "samp1\t10.0\nsamp2\t20.0")
|
|
|
|
@skip_without_tool("collection_split_on_column")
|
|
def test_workflow_run_dynamic_output_collections_3(self):
|
|
# Test a workflow that create a list:list:list followed by a mapping step.
|
|
with self.dataset_populator.test_history() as history_id:
|
|
workflow_id = self._upload_yaml_workflow("""
|
|
class: GalaxyWorkflow
|
|
steps:
|
|
- label: text_input1
|
|
type: input
|
|
- label: text_input2
|
|
type: input
|
|
- label: cat_inputs
|
|
tool_id: cat1
|
|
state:
|
|
input1:
|
|
$link: text_input1
|
|
queries:
|
|
- input2:
|
|
$link: text_input2
|
|
- label: split_up_1
|
|
tool_id: collection_split_on_column
|
|
state:
|
|
input1:
|
|
$link: cat_inputs#out_file1
|
|
- label: split_up_2
|
|
tool_id: collection_split_on_column
|
|
state:
|
|
input1:
|
|
$link: split_up_1#split_output
|
|
- tool_id: cat
|
|
state:
|
|
input1:
|
|
$link: split_up_2#split_output
|
|
""")
|
|
hda1 = self.dataset_populator.new_dataset(history_id, content="samp1\t10.0\nsamp2\t20.0\n")
|
|
hda2 = self.dataset_populator.new_dataset(history_id, content="samp1\t30.0\nsamp2\t40.0\n")
|
|
self.dataset_populator.wait_for_history(history_id, assert_ok=True)
|
|
inputs = {
|
|
'0': self._ds_entry(hda1),
|
|
'1': self._ds_entry(hda2),
|
|
}
|
|
invocation_id = self.__invoke_workflow(history_id, workflow_id, inputs)
|
|
self.wait_for_invocation_and_jobs(history_id, workflow_id, invocation_id)
|
|
|
|
@skip_without_tool("mapper")
|
|
@skip_without_tool("pileup")
|
|
def test_workflow_metadata_validation_0(self):
|
|
# Testing regression of
|
|
# https://github.com/galaxyproject/galaxy/issues/1514
|
|
with self.dataset_populator.test_history() as history_id:
|
|
self._run_jobs("""
|
|
class: GalaxyWorkflow
|
|
steps:
|
|
- label: input_fastqs
|
|
type: input_collection
|
|
- label: reference
|
|
type: input
|
|
- label: map_over_mapper
|
|
tool_id: mapper
|
|
state:
|
|
input1:
|
|
$link: input_fastqs
|
|
reference:
|
|
$link: reference
|
|
- label: pileup
|
|
tool_id: pileup
|
|
state:
|
|
input1:
|
|
$link: map_over_mapper#out_file1
|
|
reference:
|
|
$link: reference
|
|
test_data:
|
|
input_fastqs:
|
|
type: list
|
|
elements:
|
|
- identifier: samp1
|
|
value: 1.fastq
|
|
type: File
|
|
- identifier: samp2
|
|
value: 1.fastq
|
|
type: File
|
|
reference:
|
|
value: 1.fasta
|
|
type: File
|
|
""", history_id=history_id)
|
|
|
|
def test_run_subworkflow_simple(self):
|
|
with self.dataset_populator.test_history() as history_id:
|
|
workflow_run_description = """%s
|
|
|
|
test_data:
|
|
outer_input:
|
|
value: 1.bed
|
|
type: File
|
|
""" % WORKFLOW_NESTED_SIMPLE
|
|
self._run_jobs(workflow_run_description, history_id=history_id)
|
|
|
|
content = self.dataset_populator.get_history_dataset_content(history_id)
|
|
self.assertEqual("chr5\t131424298\t131424460\tCCDS4149.1_cds_0_0_chr5_131424299_f\t0\t+\nchr5\t131424298\t131424460\tCCDS4149.1_cds_0_0_chr5_131424299_f\t0\t+\n", content)
|
|
|
|
@skip_without_tool("cat1")
|
|
@skip_without_tool("collection_paired_test")
|
|
def test_workflow_run_zip_collections(self):
|
|
with self.dataset_populator.test_history() as history_id:
|
|
workflow_id = self._upload_yaml_workflow("""
|
|
class: GalaxyWorkflow
|
|
steps:
|
|
- label: test_input_1
|
|
type: input
|
|
- label: test_input_2
|
|
type: input
|
|
- label: first_cat
|
|
tool_id: cat1
|
|
state:
|
|
input1:
|
|
$link: test_input_1
|
|
- label: zip_it
|
|
tool_id: "__ZIP_COLLECTION__"
|
|
state:
|
|
input_forward:
|
|
$link: first_cat#out_file1
|
|
input_reverse:
|
|
$link: test_input_2
|
|
- label: concat_pair
|
|
tool_id: collection_paired_test
|
|
state:
|
|
f1:
|
|
$link: zip_it#output
|
|
""")
|
|
hda1 = self.dataset_populator.new_dataset(history_id, content="samp1\t10.0\nsamp2\t20.0\n")
|
|
hda2 = self.dataset_populator.new_dataset(history_id, content="samp1\t20.0\nsamp2\t40.0\n")
|
|
self.dataset_populator.wait_for_history(history_id, assert_ok=True)
|
|
inputs = {
|
|
'0': self._ds_entry(hda1),
|
|
'1': self._ds_entry(hda2),
|
|
}
|
|
invocation_id = self.__invoke_workflow(history_id, workflow_id, inputs)
|
|
self.wait_for_invocation_and_jobs(history_id, workflow_id, invocation_id)
|
|
content = self.dataset_populator.get_history_dataset_content(history_id)
|
|
self.assertEqual(content.strip(), "samp1\t10.0\nsamp2\t20.0\nsamp1\t20.0\nsamp2\t40.0")
|
|
|
|
@skip_without_tool("__APPLY_RULES__")
|
|
def test_workflow_run_apply_rules(self):
|
|
with self.dataset_populator.test_history() as history_id:
|
|
self._run_jobs(WORKFLOW_WITH_RULES_1, history_id=history_id, wait=True, assert_ok=True)
|
|
output_content = self.dataset_populator.get_history_collection_details(history_id, hid=6)
|
|
rules_test_data.check_example_2(output_content, self.dataset_populator)
|
|
|
|
def test_filter_failed_mapping(self):
|
|
with self.dataset_populator.test_history() as history_id:
|
|
summary = self._run_jobs("""
|
|
class: GalaxyWorkflow
|
|
inputs:
|
|
- type: collection
|
|
label: input_c
|
|
steps:
|
|
- label: mixed_collection
|
|
tool_id: exit_code_from_file
|
|
state:
|
|
input:
|
|
$link: input_c
|
|
|
|
- label: filtered_collection
|
|
tool_id: "__FILTER_FAILED_DATASETS__"
|
|
state:
|
|
input:
|
|
$link: mixed_collection#out_file1
|
|
|
|
- tool_id: cat1
|
|
state:
|
|
input1:
|
|
$link: filtered_collection
|
|
test_data:
|
|
input_c:
|
|
type: list
|
|
elements:
|
|
- identifier: i1
|
|
content: "0"
|
|
- identifier: i2
|
|
content: "1"
|
|
""", history_id=history_id, wait=True, assert_ok=False)
|
|
jobs = summary.jobs
|
|
|
|
def filter_jobs_by_tool(tool_id):
|
|
return [j for j in summary.jobs if j["tool_id"] == tool_id]
|
|
|
|
assert len(filter_jobs_by_tool("upload1")) == 2, jobs
|
|
assert len(filter_jobs_by_tool("exit_code_from_file")) == 2, jobs
|
|
assert len(filter_jobs_by_tool("__FILTER_FAILED_DATASETS__")) == 1, jobs
|
|
# Follow proves one job was filtered out of the result of cat1
|
|
assert len(filter_jobs_by_tool("cat1")) == 1, jobs
|
|
|
|
def test_workflow_request(self):
|
|
workflow = self.workflow_populator.load_workflow(name="test_for_queue")
|
|
workflow_request, history_id = self._setup_workflow_run(workflow)
|
|
url = "workflows/%s/usage" % (workflow_request["workflow_id"])
|
|
del workflow_request["workflow_id"]
|
|
run_workflow_response = self._post(url, data=workflow_request)
|
|
|
|
self._assert_status_code_is(run_workflow_response, 200)
|
|
# Give some time for workflow to get scheduled before scanning the history.
|
|
time.sleep(5)
|
|
self.dataset_populator.wait_for_history(history_id, assert_ok=True)
|
|
|
|
def test_workflow_output_dataset(self):
|
|
with self.dataset_populator.test_history() as history_id:
|
|
summary = self._run_jobs("""
|
|
class: GalaxyWorkflow
|
|
inputs:
|
|
- id: input1
|
|
outputs:
|
|
- id: wf_output_1
|
|
source: first_cat#out_file1
|
|
steps:
|
|
- tool_id: cat1
|
|
label: first_cat
|
|
state:
|
|
input1:
|
|
$link: input1
|
|
|
|
test_data:
|
|
input1: "hello world"
|
|
""", history_id=history_id)
|
|
workflow_id = summary.workflow_id
|
|
invocation_id = summary.invocation_id
|
|
invocation_response = self._get("workflows/%s/invocations/%s" % (workflow_id, invocation_id))
|
|
self._assert_status_code_is(invocation_response, 200)
|
|
invocation = invocation_response.json()
|
|
self._assert_has_keys(invocation , "id", "outputs", "output_collections")
|
|
assert len(invocation["output_collections"]) == 0
|
|
assert len(invocation["outputs"]) == 1
|
|
output_content = self.dataset_populator.get_history_dataset_content(history_id, dataset_id=invocation["outputs"]["wf_output_1"]["id"])
|
|
assert "hello world" == output_content.strip()
|
|
|
|
def test_workflow_output_dataset_collection(self):
|
|
with self.dataset_populator.test_history() as history_id:
|
|
summary = self._run_jobs("""
|
|
class: GalaxyWorkflow
|
|
inputs:
|
|
- id: input1
|
|
type: data_collection_input
|
|
collection_type: list
|
|
outputs:
|
|
- id: wf_output_1
|
|
source: first_cat#out_file1
|
|
steps:
|
|
- tool_id: cat
|
|
label: first_cat
|
|
state:
|
|
input1:
|
|
$link: input1
|
|
test_data:
|
|
input1:
|
|
type: list
|
|
name: the_dataset_list
|
|
elements:
|
|
- identifier: el1
|
|
value: 1.fastq
|
|
type: File
|
|
""", history_id=history_id)
|
|
workflow_id = summary.workflow_id
|
|
invocation_id = summary.invocation_id
|
|
invocation_response = self._get("workflows/%s/invocations/%s" % (workflow_id, invocation_id))
|
|
self._assert_status_code_is(invocation_response, 200)
|
|
invocation = invocation_response.json()
|
|
self._assert_has_keys(invocation , "id", "outputs", "output_collections")
|
|
assert len(invocation["output_collections"]) == 1
|
|
assert len(invocation["outputs"]) == 0
|
|
output_content = self.dataset_populator.get_history_collection_details(history_id, content_id=invocation["output_collections"]["wf_output_1"]["id"])
|
|
self._assert_has_keys(output_content , "id", "elements")
|
|
assert output_content["collection_type"] == "list"
|
|
elements = output_content["elements"]
|
|
assert len(elements) == 1
|
|
elements0 = elements[0]
|
|
assert elements0["element_identifier"] == "el1"
|
|
|
|
def test_worklfow_input_mapping(self):
|
|
with self.dataset_populator.test_history() as history_id:
|
|
summary = self._run_jobs("""
|
|
class: GalaxyWorkflow
|
|
inputs:
|
|
- id: input1
|
|
outputs:
|
|
- id: wf_output_1
|
|
source: first_cat#out_file1
|
|
steps:
|
|
- tool_id: cat
|
|
label: first_cat
|
|
state:
|
|
input1:
|
|
$link: input1
|
|
test_data:
|
|
input1:
|
|
type: list
|
|
name: the_dataset_list
|
|
elements:
|
|
- identifier: el1
|
|
value: 1.fastq
|
|
type: File
|
|
- identifier: el2
|
|
value: 1.fastq
|
|
type: File
|
|
""", history_id=history_id)
|
|
workflow_id = summary.workflow_id
|
|
invocation_id = summary.invocation_id
|
|
invocation_response = self._get("workflows/%s/invocations/%s" % (workflow_id, invocation_id))
|
|
self._assert_status_code_is(invocation_response, 200)
|
|
invocation = invocation_response.json()
|
|
self._assert_has_keys(invocation , "id", "outputs", "output_collections")
|
|
assert len(invocation["output_collections"]) == 1
|
|
assert len(invocation["outputs"]) == 0
|
|
output_content = self.dataset_populator.get_history_collection_details(history_id, content_id=invocation["output_collections"]["wf_output_1"]["id"])
|
|
self._assert_has_keys(output_content , "id", "elements")
|
|
elements = output_content["elements"]
|
|
assert len(elements) == 2
|
|
elements0 = elements[0]
|
|
assert elements0["element_identifier"] == "el1"
|
|
|
|
@skip_without_tool("collection_creates_pair")
|
|
def test_workflow_run_input_mapping_with_output_collections(self):
|
|
with self.dataset_populator.test_history() as history_id:
|
|
summary = self._run_jobs("""
|
|
class: GalaxyWorkflow
|
|
outputs:
|
|
- id: wf_output_1
|
|
source: split_up#paired_output
|
|
steps:
|
|
- label: text_input
|
|
type: input
|
|
- label: split_up
|
|
tool_id: collection_creates_pair
|
|
state:
|
|
input1:
|
|
$link: text_input
|
|
test_data:
|
|
text_input:
|
|
type: list
|
|
name: the_dataset_list
|
|
elements:
|
|
- identifier: el1
|
|
value: 1.fastq
|
|
type: File
|
|
- identifier: el2
|
|
value: 1.fastq
|
|
type: File
|
|
""", history_id=history_id)
|
|
workflow_id = summary.workflow_id
|
|
invocation_id = summary.invocation_id
|
|
invocation_response = self._get("workflows/%s/invocations/%s" % (workflow_id, invocation_id))
|
|
self._assert_status_code_is(invocation_response, 200)
|
|
invocation = invocation_response.json()
|
|
self._assert_has_keys(invocation , "id", "outputs", "output_collections")
|
|
assert len(invocation["output_collections"]) == 1
|
|
assert len(invocation["outputs"]) == 0
|
|
output_content = self.dataset_populator.get_history_collection_details(history_id, content_id=invocation["output_collections"]["wf_output_1"]["id"])
|
|
self._assert_has_keys(output_content , "id", "elements")
|
|
assert output_content["collection_type"] == "list:paired", output_content
|
|
elements = output_content["elements"]
|
|
assert len(elements) == 2
|
|
elements0 = elements[0]
|
|
assert elements0["element_identifier"] == "el1"
|
|
|
|
def test_workflow_run_input_mapping_with_subworkflows(self):
|
|
with self.dataset_populator.test_history() as history_id:
|
|
summary = self._run_jobs("""%s
|
|
|
|
test_data:
|
|
outer_input:
|
|
type: list
|
|
name: the_dataset_list
|
|
elements:
|
|
- identifier: el1
|
|
value: 1.fastq
|
|
type: File
|
|
- identifier: el2
|
|
value: 1.fastq
|
|
type: File
|
|
""" % WORKFLOW_NESTED_SIMPLE, history_id=history_id)
|
|
workflow_id = summary.workflow_id
|
|
invocation_id = summary.invocation_id
|
|
invocation_response = self._get("workflows/%s/invocations/%s" % (workflow_id, invocation_id))
|
|
self._assert_status_code_is(invocation_response, 200)
|
|
invocation_response = self._get("workflows/%s/invocations/%s" % (workflow_id, invocation_id))
|
|
self._assert_status_code_is(invocation_response, 200)
|
|
invocation = invocation_response.json()
|
|
self._assert_has_keys(invocation , "id", "outputs", "output_collections")
|
|
assert len(invocation["output_collections"]) == 1, invocation
|
|
assert len(invocation["outputs"]) == 0
|
|
output_content = self.dataset_populator.get_history_collection_details(history_id, content_id=invocation["output_collections"]["outer_output"]["id"])
|
|
self._assert_has_keys(output_content , "id", "elements")
|
|
assert output_content["collection_type"] == "list", output_content
|
|
elements = output_content["elements"]
|
|
assert len(elements) == 2
|
|
elements0 = elements[0]
|
|
assert elements0["element_identifier"] == "el1"
|
|
|
|
@skip_without_tool("cat_list")
|
|
@skip_without_tool("random_lines1")
|
|
@skip_without_tool("split")
|
|
def test_subworkflow_recover_mapping_1(self):
|
|
# This test case tests an outer workflow continues to scheduling and handle
|
|
# collection mapping properly after the last step of a subworkflow requires delayed
|
|
# evaluation. Testing rescheduling and propagating connections within a subworkflow
|
|
# is handled by the next test case.
|
|
with self.dataset_populator.test_history() as history_id:
|
|
self._run_jobs("""
|
|
class: GalaxyWorkflow
|
|
inputs:
|
|
- id: outer_input
|
|
outputs:
|
|
- id: outer_output
|
|
source: second_cat#out_file1
|
|
steps:
|
|
- tool_id: cat1
|
|
label: first_cat
|
|
state:
|
|
input1:
|
|
$link: outer_input
|
|
- run:
|
|
class: GalaxyWorkflow
|
|
inputs:
|
|
- id: inner_input
|
|
outputs:
|
|
- id: workflow_output
|
|
source: random_lines#out_file1
|
|
steps:
|
|
- tool_id: random_lines1
|
|
label: random_lines
|
|
state:
|
|
num_lines: 2
|
|
input:
|
|
$link: inner_input
|
|
seed_source:
|
|
seed_source_selector: set_seed
|
|
seed: asdf
|
|
label: nested_workflow
|
|
connect:
|
|
inner_input: first_cat#out_file1
|
|
- tool_id: split
|
|
label: split
|
|
state:
|
|
input1:
|
|
$link: nested_workflow#workflow_output
|
|
- tool_id: cat_list
|
|
label: second_cat
|
|
state:
|
|
input1:
|
|
$link: split#output
|
|
|
|
test_data:
|
|
outer_input:
|
|
value: 1.bed
|
|
type: File
|
|
""", history_id=history_id, wait=True)
|
|
self.assertEqual("chr16\t142908\t143003\tCCDS10397.1_cds_0_0_chr16_142909_f\t0\t+\nchr5\t131424298\t131424460\tCCDS4149.1_cds_0_0_chr5_131424299_f\t0\t+\n", self.dataset_populator.get_history_dataset_content(history_id))
|
|
|
|
@skip_without_tool("cat_list")
|
|
@skip_without_tool("random_lines1")
|
|
@skip_without_tool("split")
|
|
def test_subworkflow_recover_mapping_2(self):
|
|
# Like the above test case, this test case tests an outer workflow continues to
|
|
# schedule and handle collection mapping properly after a subworkflow needs to be
|
|
# delayed, but this also tests recovering and handling scheduling within the subworkflow
|
|
# since the delayed step (split) isn't the last step of the subworkflow.
|
|
with self.dataset_populator.test_history() as history_id:
|
|
self._run_jobs("""
|
|
class: GalaxyWorkflow
|
|
inputs:
|
|
- id: outer_input
|
|
outputs:
|
|
- id: outer_output
|
|
source: second_cat#out_file1
|
|
steps:
|
|
- tool_id: cat1
|
|
label: first_cat
|
|
state:
|
|
input1:
|
|
$link: outer_input
|
|
- run:
|
|
class: GalaxyWorkflow
|
|
inputs:
|
|
- id: inner_input
|
|
outputs:
|
|
- id: workflow_output
|
|
source: inner_cat#out_file1
|
|
steps:
|
|
- tool_id: random_lines1
|
|
label: random_lines
|
|
state:
|
|
num_lines: 2
|
|
input:
|
|
$link: inner_input
|
|
seed_source:
|
|
seed_source_selector: set_seed
|
|
seed: asdf
|
|
- tool_id: split
|
|
label: split
|
|
state:
|
|
input1:
|
|
$link: random_lines#out_file1
|
|
- tool_id: cat1
|
|
label: inner_cat
|
|
state:
|
|
input1:
|
|
$link: split#output
|
|
|
|
label: nested_workflow
|
|
connect:
|
|
inner_input: first_cat#out_file1
|
|
- tool_id: cat_list
|
|
label: second_cat
|
|
state:
|
|
input1:
|
|
$link: nested_workflow#workflow_output
|
|
|
|
test_data:
|
|
outer_input:
|
|
value: 1.bed
|
|
type: File
|
|
""", history_id=history_id, wait=True)
|
|
self.assertEqual("chr16\t142908\t143003\tCCDS10397.1_cds_0_0_chr16_142909_f\t0\t+\nchr5\t131424298\t131424460\tCCDS4149.1_cds_0_0_chr5_131424299_f\t0\t+\n", self.dataset_populator.get_history_dataset_content(history_id))
|
|
|
|
@skip_without_tool("cat_list")
|
|
@skip_without_tool("random_lines1")
|
|
@skip_without_tool("split")
|
|
def test_recover_mapping_in_subworkflow(self):
|
|
with self.dataset_populator.test_history() as history_id:
|
|
self._run_jobs("""
|
|
class: GalaxyWorkflow
|
|
inputs:
|
|
- id: outer_input
|
|
outputs:
|
|
- id: outer_output
|
|
source: second_cat#out_file1
|
|
steps:
|
|
- tool_id: cat1
|
|
label: first_cat
|
|
state:
|
|
input1:
|
|
$link: outer_input
|
|
- run:
|
|
class: GalaxyWorkflow
|
|
inputs:
|
|
- id: inner_input
|
|
outputs:
|
|
- id: workflow_output
|
|
source: split#output
|
|
steps:
|
|
- tool_id: random_lines1
|
|
label: random_lines
|
|
state:
|
|
num_lines: 2
|
|
input:
|
|
$link: inner_input
|
|
seed_source:
|
|
seed_source_selector: set_seed
|
|
seed: asdf
|
|
- tool_id: split
|
|
label: split
|
|
state:
|
|
input1:
|
|
$link: random_lines#out_file1
|
|
label: nested_workflow
|
|
connect:
|
|
inner_input: first_cat#out_file1
|
|
- tool_id: cat_list
|
|
label: second_cat
|
|
state:
|
|
input1:
|
|
$link: nested_workflow#workflow_output
|
|
|
|
test_data:
|
|
outer_input:
|
|
value: 1.bed
|
|
type: File
|
|
""", history_id=history_id, wait=True)
|
|
self.assertEqual("chr16\t142908\t143003\tCCDS10397.1_cds_0_0_chr16_142909_f\t0\t+\nchr5\t131424298\t131424460\tCCDS4149.1_cds_0_0_chr5_131424299_f\t0\t+\n", self.dataset_populator.get_history_dataset_content(history_id))
|
|
|
|
@skip_without_tool("empty_list")
|
|
@skip_without_tool("count_list")
|
|
@skip_without_tool("random_lines1")
|
|
def test_empty_list_mapping(self):
|
|
with self.dataset_populator.test_history() as history_id:
|
|
self._run_jobs("""
|
|
class: GalaxyWorkflow
|
|
inputs:
|
|
- id: input1
|
|
outputs:
|
|
- id: count_list
|
|
source: count_list#out_file1
|
|
steps:
|
|
- tool_id: empty_list
|
|
label: empty_list
|
|
state:
|
|
input1:
|
|
$link: input1
|
|
- tool_id: random_lines1
|
|
label: random_lines
|
|
state:
|
|
num_lines: 2
|
|
input:
|
|
$link: empty_list#output
|
|
seed_source:
|
|
seed_source_selector: set_seed
|
|
seed: asdf
|
|
- tool_id: count_list
|
|
label: count_list
|
|
state:
|
|
input1:
|
|
$link: random_lines#out_file1
|
|
|
|
test_data:
|
|
input1:
|
|
value: 1.bed
|
|
type: File
|
|
""", history_id=history_id, wait=True)
|
|
self.assertEqual("0\n", self.dataset_populator.get_history_dataset_content(history_id))
|
|
|
|
@skip_without_tool("empty_list")
|
|
@skip_without_tool("count_multi_file")
|
|
@skip_without_tool("random_lines1")
|
|
def test_empty_list_reduction(self):
|
|
with self.dataset_populator.test_history() as history_id:
|
|
self._run_jobs("""
|
|
class: GalaxyWorkflow
|
|
inputs:
|
|
- id: input1
|
|
outputs:
|
|
- id: count_multi_file
|
|
source: count_multi_file#out_file1
|
|
steps:
|
|
- tool_id: empty_list
|
|
label: empty_list
|
|
state:
|
|
input1:
|
|
$link: input1
|
|
- tool_id: random_lines1
|
|
label: random_lines
|
|
state:
|
|
num_lines: 2
|
|
input:
|
|
$link: empty_list#output
|
|
seed_source:
|
|
seed_source_selector: set_seed
|
|
seed: asdf
|
|
- tool_id: count_multi_file
|
|
label: count_multi_file
|
|
state:
|
|
input1:
|
|
$link: random_lines#out_file1
|
|
|
|
test_data:
|
|
input1:
|
|
value: 1.bed
|
|
type: File
|
|
""", history_id=history_id, wait=True)
|
|
self.assertEqual("0\n", self.dataset_populator.get_history_dataset_content(history_id))
|
|
|
|
@skip_without_tool("cat")
|
|
def test_cancel_new_workflow_when_history_deleted(self):
|
|
with self.dataset_populator.test_history() as history_id:
|
|
# Invoke a workflow with a pause step.
|
|
uploaded_workflow_id, invocation_id = self._invoke_paused_workflow(history_id)
|
|
|
|
# There is no pause of anything in here, so likely the invocation is
|
|
# is still in a new state. If it isn't that is fine, continue with the
|
|
# test it will just happen to test the same thing as below.
|
|
|
|
# Wait for all the datasets to complete, make sure the workflow invocation
|
|
# is not complete.
|
|
self._assert_invocation_non_terminal(uploaded_workflow_id, invocation_id)
|
|
|
|
self._delete("histories/%s" % history_id)
|
|
|
|
invocation_cancelled = self._wait_for_invocation_state(uploaded_workflow_id, invocation_id, 'cancelled')
|
|
assert invocation_cancelled, "Workflow state is not cancelled..."
|
|
|
|
@skip_without_tool("cat")
|
|
def test_cancel_ready_workflow_when_history_deleted(self):
|
|
# Same as previous test but make sure invocation isn't a new state before
|
|
# cancelling.
|
|
with self.dataset_populator.test_history() as history_id:
|
|
# Invoke a workflow with a pause step.
|
|
uploaded_workflow_id, invocation_id = self._invoke_paused_workflow(history_id)
|
|
|
|
# Wait for at least one scheduling step.
|
|
self._wait_for_invocation_non_new(uploaded_workflow_id, invocation_id)
|
|
|
|
# Wait for all the datasets to complete, make sure the workflow invocation
|
|
# is not complete.
|
|
self._assert_invocation_non_terminal(uploaded_workflow_id, invocation_id)
|
|
|
|
self._delete("histories/%s" % history_id)
|
|
|
|
invocation_cancelled = self._wait_for_invocation_state(uploaded_workflow_id, invocation_id, 'cancelled')
|
|
assert invocation_cancelled, "Workflow state is not cancelled..."
|
|
|
|
@skip_without_tool("cat")
|
|
def test_workflow_pause(self):
|
|
with self.dataset_populator.test_history() as history_id:
|
|
# Invoke a workflow with a pause step.
|
|
uploaded_workflow_id, invocation_id = self._invoke_paused_workflow(history_id)
|
|
|
|
# Wait for at least one scheduling step.
|
|
self._wait_for_invocation_non_new(uploaded_workflow_id, invocation_id)
|
|
|
|
# Make sure the history didn't enter a failed state in there.
|
|
self.dataset_populator.wait_for_history(history_id, assert_ok=True)
|
|
|
|
# Assert the workflow hasn't finished scheduling, we can be pretty sure we
|
|
# are at the pause step in this case then.
|
|
self._assert_invocation_non_terminal(uploaded_workflow_id, invocation_id)
|
|
|
|
# Review the paused steps to allow the workflow to continue.
|
|
self.__review_paused_steps(uploaded_workflow_id, invocation_id, order_index=2, action=True)
|
|
|
|
# Wait for the workflow to finish scheduling and ensure both the invocation
|
|
# and the history are in valid states.
|
|
invocation_scheduled = self._wait_for_invocation_state(uploaded_workflow_id, invocation_id, 'scheduled')
|
|
assert invocation_scheduled, "Workflow state is not scheduled..."
|
|
self.dataset_populator.wait_for_history(history_id, assert_ok=True)
|
|
|
|
@skip_without_tool("cat")
|
|
def test_workflow_pause_cancel(self):
|
|
with self.dataset_populator.test_history() as history_id:
|
|
# Invoke a workflow with a pause step.
|
|
uploaded_workflow_id, invocation_id = self._invoke_paused_workflow(history_id)
|
|
|
|
# Wait for at least one scheduling step.
|
|
self._wait_for_invocation_non_new(uploaded_workflow_id, invocation_id)
|
|
|
|
# Make sure the history didn't enter a failed state in there.
|
|
self.dataset_populator.wait_for_history(history_id, assert_ok=True)
|
|
|
|
# Assert the workflow hasn't finished scheduling, we can be pretty sure we
|
|
# are at the pause step in this case then.
|
|
self._assert_invocation_non_terminal(uploaded_workflow_id, invocation_id)
|
|
|
|
# Review the paused workflow and cancel it at the paused step.
|
|
self.__review_paused_steps(uploaded_workflow_id, invocation_id, order_index=2, action=False)
|
|
|
|
# Ensure the workflow eventually becomes cancelled.
|
|
invocation_cancelled = self._wait_for_invocation_state(uploaded_workflow_id, invocation_id, 'cancelled')
|
|
assert invocation_cancelled, "Workflow state is not cancelled..."
|
|
|
|
@skip_without_tool("head")
|
|
def test_workflow_map_reduce_pause(self):
|
|
with self.dataset_populator.test_history() as history_id:
|
|
workflow = self.workflow_populator.load_workflow_from_resource("test_workflow_map_reduce_pause")
|
|
uploaded_workflow_id = self.workflow_populator.create_workflow(workflow)
|
|
hda1 = self.dataset_populator.new_dataset(history_id, content="reviewed\nunreviewed")
|
|
hdca1 = self.dataset_collection_populator.create_list_in_history(history_id, contents=["1\n2\n3", "4\n5\n6"]).json()
|
|
index_map = {
|
|
'0': self._ds_entry(hda1),
|
|
'1': self._ds_entry(hdca1),
|
|
}
|
|
invocation_id = self.__invoke_workflow(history_id, uploaded_workflow_id, index_map)
|
|
|
|
# Wait for at least one scheduling step.
|
|
self._wait_for_invocation_non_new(uploaded_workflow_id, invocation_id)
|
|
|
|
# Make sure the history didn't enter a failed state in there.
|
|
self.dataset_populator.wait_for_history(history_id, assert_ok=True)
|
|
|
|
# Assert the workflow hasn't finished scheduling, we can be pretty sure we
|
|
# are at the pause step in this case then.
|
|
self._assert_invocation_non_terminal(uploaded_workflow_id, invocation_id)
|
|
|
|
self.__review_paused_steps(uploaded_workflow_id, invocation_id, order_index=4, action=True)
|
|
self.wait_for_invocation_and_jobs(history_id, uploaded_workflow_id, invocation_id)
|
|
invocation = self._invocation_details(uploaded_workflow_id, invocation_id)
|
|
assert invocation['state'] == 'scheduled'
|
|
self.assertEqual("reviewed\n1\nreviewed\n4\n", self.dataset_populator.get_history_dataset_content(history_id))
|
|
|
|
@skip_without_tool("cat")
|
|
def test_cancel_workflow_invocation(self):
|
|
with self.dataset_populator.test_history() as history_id:
|
|
# Invoke a workflow with a pause step.
|
|
uploaded_workflow_id, invocation_id = self._invoke_paused_workflow(history_id)
|
|
|
|
# Wait for at least one scheduling step.
|
|
self._wait_for_invocation_non_new(uploaded_workflow_id, invocation_id)
|
|
|
|
# Make sure the history didn't enter a failed state in there.
|
|
self.dataset_populator.wait_for_history(history_id, assert_ok=True)
|
|
|
|
# Assert the workflow hasn't finished scheduling, we can be pretty sure we
|
|
# are at the pause step in this case then.
|
|
self._assert_invocation_non_terminal(uploaded_workflow_id, invocation_id)
|
|
|
|
invocation_url = self._api_url("workflows/%s/usage/%s" % (uploaded_workflow_id, invocation_id), use_key=True)
|
|
delete_response = delete(invocation_url)
|
|
self._assert_status_code_is(delete_response, 200)
|
|
|
|
invocation = self._invocation_details(uploaded_workflow_id, invocation_id)
|
|
assert invocation['state'] == 'cancelled'
|
|
|
|
def test_run_with_implicit_connection(self):
|
|
with self.dataset_populator.test_history() as history_id:
|
|
run_summary = self._run_jobs("""
|
|
class: GalaxyWorkflow
|
|
steps:
|
|
- label: test_input
|
|
type: input
|
|
- label: first_cat
|
|
tool_id: cat1
|
|
state:
|
|
input1:
|
|
$link: test_input
|
|
- label: the_pause
|
|
type: pause
|
|
connect:
|
|
input:
|
|
- first_cat#out_file1
|
|
- label: second_cat
|
|
tool_id: cat1
|
|
state:
|
|
input1:
|
|
$link: the_pause
|
|
- label: third_cat
|
|
tool_id: random_lines1
|
|
connect:
|
|
$step: second_cat
|
|
state:
|
|
num_lines: 1
|
|
input:
|
|
$link: test_input
|
|
seed_source:
|
|
seed_source_selector: set_seed
|
|
seed: asdf
|
|
test_data:
|
|
test_input: "hello world"
|
|
""", history_id=history_id, wait=False)
|
|
history_id = run_summary.history_id
|
|
workflow_id = run_summary.workflow_id
|
|
invocation_id = run_summary.invocation_id
|
|
# Wait for first two jobs to be scheduled - upload and first cat.
|
|
wait_on(lambda: len(self._history_jobs(history_id)) >= 2 or None, "history jobs")
|
|
self.dataset_populator.wait_for_history(history_id, assert_ok=True)
|
|
invocation = self._invocation_details(workflow_id, invocation_id)
|
|
assert invocation['state'] != 'scheduled', invocation
|
|
# Expect two jobs - the upload and first cat. randomlines shouldn't run
|
|
# it is implicitly dependent on second cat.
|
|
self._assert_history_job_count(history_id, 2)
|
|
|
|
self.__review_paused_steps(workflow_id, invocation_id, order_index=2, action=True)
|
|
self.wait_for_invocation_and_jobs(history_id, workflow_id, invocation_id)
|
|
self._assert_history_job_count(history_id, 4)
|
|
|
|
def test_run_with_validated_parameter_connection_valid(self):
|
|
with self.dataset_populator.test_history() as history_id:
|
|
run_summary = self._run_jobs("""
|
|
class: GalaxyWorkflow
|
|
inputs:
|
|
- label: text_input
|
|
type: text
|
|
steps:
|
|
- tool_id: validation_repeat
|
|
state:
|
|
r2:
|
|
- text:
|
|
$link: text_input
|
|
test_data:
|
|
text_input:
|
|
value: "abd"
|
|
type: raw
|
|
""", history_id=history_id, wait=True)
|
|
time.sleep(10)
|
|
self.workflow_populator.wait_for_invocation(run_summary.workflow_id, run_summary.invocation_id)
|
|
jobs = self._history_jobs(history_id)
|
|
assert len(jobs) == 1
|
|
|
|
def test_run_with_validated_parameter_connection_invalid(self):
|
|
with self.dataset_populator.test_history() as history_id:
|
|
self._run_jobs("""
|
|
class: GalaxyWorkflow
|
|
inputs:
|
|
- label: text_input
|
|
type: text
|
|
steps:
|
|
- tool_id: validation_repeat
|
|
state:
|
|
r2:
|
|
- text:
|
|
$link: text_input
|
|
test_data:
|
|
text_input:
|
|
value: ""
|
|
type: raw
|
|
""", history_id=history_id, wait=True, assert_ok=False)
|
|
|
|
def test_run_with_text_connection(self):
|
|
with self.dataset_populator.test_history() as history_id:
|
|
self._run_jobs("""
|
|
class: GalaxyWorkflow
|
|
inputs:
|
|
- label: data_input
|
|
type: data
|
|
- label: text_input
|
|
type: text
|
|
steps:
|
|
- label: randomlines
|
|
tool_id: random_lines1
|
|
state:
|
|
num_lines: 1
|
|
input:
|
|
$link: data_input
|
|
seed_source:
|
|
seed_source_selector: set_seed
|
|
seed:
|
|
$link: text_input
|
|
test_data:
|
|
data_input:
|
|
value: 1.bed
|
|
type: File
|
|
text_input:
|
|
value: asdf
|
|
type: raw
|
|
""", history_id=history_id)
|
|
|
|
self.dataset_populator.wait_for_history(history_id, assert_ok=True)
|
|
content = self.dataset_populator.get_history_dataset_content(history_id)
|
|
self.assertEqual("chr5\t131424298\t131424460\tCCDS4149.1_cds_0_0_chr5_131424299_f\t0\t+\n", content)
|
|
|
|
def wait_for_invocation_and_jobs(self, history_id, workflow_id, invocation_id, assert_ok=True):
|
|
state = self.workflow_populator.wait_for_invocation(workflow_id, invocation_id)
|
|
if assert_ok:
|
|
assert state == "scheduled", state
|
|
time.sleep(.5)
|
|
self.dataset_populator.wait_for_history_jobs(history_id, assert_ok=assert_ok)
|
|
time.sleep(.5)
|
|
|
|
@flakey
|
|
@skip_without_tool('cat1')
|
|
def test_workflow_rerun_with_use_cached_job(self):
|
|
workflow = self.workflow_populator.load_workflow(name="test_for_run")
|
|
# We launch a workflow
|
|
with self.dataset_populator.test_history() as history_id:
|
|
workflow_request, _ = self._setup_workflow_run(workflow, history_id=history_id)
|
|
run_workflow_response = self._post("workflows", data=workflow_request).json()
|
|
# We copy the workflow inputs to a new history
|
|
new_workflow_request = workflow_request.copy()
|
|
new_ds_map = json.loads(new_workflow_request['ds_map'])
|
|
with self.dataset_populator.test_history() as new_history_id:
|
|
for key, input_values in run_workflow_response['inputs'].items():
|
|
copy_payload = {"content": input_values['id'], "source": "hda", "type": "dataset"}
|
|
copy_response = self._post("histories/%s/contents" % new_history_id, data=copy_payload).json()
|
|
new_ds_map[key]['id'] = copy_response['id']
|
|
new_workflow_request['ds_map'] = json.dumps(new_ds_map)
|
|
new_workflow_request['history'] = "hist_id=%s" % new_history_id
|
|
new_workflow_request['use_cached_job'] = True
|
|
# We run the workflow again, it should not produce any new outputs
|
|
new_workflow_response = self._post("workflows", data=new_workflow_request).json()
|
|
first_wf_output = self._get("datasets/%s" % run_workflow_response['outputs'][0]).json()
|
|
second_wf_output = self._get("datasets/%s" % new_workflow_response['outputs'][0]).json()
|
|
assert first_wf_output['file_name'] == second_wf_output['file_name'], \
|
|
"first output:\n%s\nsecond output:\n%s" % (first_wf_output, second_wf_output)
|
|
|
|
@skip_without_tool('cat1')
|
|
def test_nested_workflow_rerun_with_use_cached_job(self):
|
|
with self.dataset_populator.test_history() as history_id_one, self.dataset_populator.test_history() as history_id_two:
|
|
workflow_run_description = """%s
|
|
|
|
test_data:
|
|
outer_input:
|
|
value: 1.bed
|
|
type: File
|
|
""" % WORKFLOW_NESTED_SIMPLE
|
|
run_jobs_summary = self._run_jobs(workflow_run_description, history_id=history_id_one)
|
|
self.dataset_populator.wait_for_history(history_id_one, assert_ok=True)
|
|
workflow_request = run_jobs_summary.workflow_request
|
|
# We copy the inputs to a new history and re-run the workflow
|
|
inputs = json.loads(workflow_request['inputs'])
|
|
dataset_type = inputs['outer_input']['src']
|
|
dataset_id = inputs['outer_input']['id']
|
|
copy_payload = {"content": dataset_id, "source": dataset_type, "type": "dataset"}
|
|
copy_response = self._post("histories/%s/contents" % history_id_two, data=copy_payload)
|
|
self._assert_status_code_is(copy_response, 200)
|
|
new_dataset_id = copy_response.json()['id']
|
|
inputs['outer_input']['id'] = new_dataset_id
|
|
workflow_request['use_cached_job'] = True
|
|
workflow_request['history'] = "hist_id={history_id_two}".format(history_id_two=history_id_two)
|
|
workflow_request['inputs'] = json.dumps(inputs)
|
|
run_workflow_response = self._post("workflows", data=run_jobs_summary.workflow_request).json()
|
|
self.workflow_populator.wait_for_workflow(workflow_request['workflow_id'],
|
|
run_workflow_response['id'],
|
|
history_id_two,
|
|
assert_ok=True)
|
|
# Now make sure that the HDAs in each history point to the same dataset instances
|
|
history_one_contents = self.__history_contents(history_id_one)
|
|
history_two_contents = self.__history_contents(history_id_two)
|
|
assert len(history_one_contents) == len(history_two_contents)
|
|
for i, (item_one, item_two) in enumerate(zip(history_one_contents, history_two_contents)):
|
|
assert item_one['dataset_id'] == item_two['dataset_id'], \
|
|
'Dataset ids should match, but "%s" and "%s" are not the same for History item %i.' % (item_one['dataset_id'],
|
|
item_two['dataset_id'],
|
|
i + 1)
|
|
|
|
def test_cannot_run_inaccessible_workflow(self):
|
|
workflow = self.workflow_populator.load_workflow(name="test_for_run_cannot_access")
|
|
workflow_request, history_id = self._setup_workflow_run(workflow)
|
|
with self._different_user():
|
|
run_workflow_response = self._post("workflows", data=workflow_request)
|
|
self._assert_status_code_is(run_workflow_response, 403)
|
|
|
|
def test_400_on_invalid_workflow_id(self):
|
|
workflow = self.workflow_populator.load_workflow(name="test_for_run_does_not_exist")
|
|
workflow_request, history_id = self._setup_workflow_run(workflow)
|
|
workflow_request["workflow_id"] = self._random_key()
|
|
run_workflow_response = self._post("workflows", data=workflow_request)
|
|
self._assert_status_code_is(run_workflow_response, 400)
|
|
|
|
def test_cannot_run_against_other_users_history(self):
|
|
workflow = self.workflow_populator.load_workflow(name="test_for_run_does_not_exist")
|
|
workflow_request, history_id = self._setup_workflow_run(workflow)
|
|
with self._different_user():
|
|
other_history_id = self.dataset_populator.new_history()
|
|
workflow_request["history"] = "hist_id=%s" % other_history_id
|
|
run_workflow_response = self._post("workflows", data=workflow_request)
|
|
self._assert_status_code_is(run_workflow_response, 403)
|
|
|
|
@skip_without_tool("cat")
|
|
@skip_without_tool("cat_list")
|
|
def test_workflow_run_with_matching_lists(self):
|
|
workflow = self.workflow_populator.load_workflow_from_resource("test_workflow_matching_lists")
|
|
workflow_id = self.workflow_populator.create_workflow(workflow)
|
|
with self.dataset_populator.test_history() as history_id:
|
|
hdca1 = self.dataset_collection_populator.create_list_in_history(history_id, contents=[("sample1-1", "1 2 3"), ("sample2-1", "7 8 9")]).json()
|
|
hdca2 = self.dataset_collection_populator.create_list_in_history(history_id, contents=[("sample1-2", "4 5 6"), ("sample2-2", "0 a b")]).json()
|
|
self.dataset_populator.wait_for_history(history_id, assert_ok=True)
|
|
label_map = {"list1": self._ds_entry(hdca1), "list2": self._ds_entry(hdca2)}
|
|
workflow_request = dict(
|
|
history="hist_id=%s" % history_id,
|
|
workflow_id=workflow_id,
|
|
ds_map=self._build_ds_map(workflow_id, label_map),
|
|
)
|
|
run_workflow_response = self._post("workflows", data=workflow_request)
|
|
self._assert_status_code_is(run_workflow_response, 200)
|
|
self.dataset_populator.wait_for_history(history_id, assert_ok=True)
|
|
self.assertEqual("1 2 3\n4 5 6\n7 8 9\n0 a b\n", self.dataset_populator.get_history_dataset_content(history_id))
|
|
|
|
def test_workflow_stability(self):
|
|
# Run this index stability test with following command:
|
|
# ./run_tests.sh test/api/test_workflows.py:WorkflowsApiTestCase.test_workflow_stability
|
|
num_tests = 1
|
|
for workflow_file in ["test_workflow_topoambigouity", "test_workflow_topoambigouity_auto_laidout"]:
|
|
workflow = self.workflow_populator.load_workflow_from_resource(workflow_file)
|
|
last_step_map = self._step_map(workflow)
|
|
for i in range(num_tests):
|
|
uploaded_workflow_id = self.workflow_populator.create_workflow(workflow)
|
|
downloaded_workflow = self._download_workflow(uploaded_workflow_id)
|
|
step_map = self._step_map(downloaded_workflow)
|
|
assert step_map == last_step_map
|
|
last_step_map = step_map
|
|
|
|
def _step_map(self, workflow):
|
|
# Build dict mapping 'tep index to input name.
|
|
step_map = {}
|
|
for step_index, step in workflow["steps"].items():
|
|
if step["type"] == "data_input":
|
|
step_map[step_index] = step["inputs"][0]["name"]
|
|
return step_map
|
|
|
|
def test_empty_create(self):
|
|
response = self._post("workflows")
|
|
self._assert_status_code_is(response, 400)
|
|
self._assert_error_code_is(response, error_codes.USER_REQUEST_MISSING_PARAMETER)
|
|
|
|
def test_invalid_create_multiple_types(self):
|
|
data = {
|
|
'shared_workflow_id': '1234567890abcdef',
|
|
'from_history_id': '1234567890abcdef'
|
|
}
|
|
response = self._post("workflows", data)
|
|
self._assert_status_code_is(response, 400)
|
|
self._assert_error_code_is(response, error_codes.USER_REQUEST_INVALID_PARAMETER)
|
|
|
|
@skip_without_tool("cat1")
|
|
def test_run_with_pja(self):
|
|
workflow = self.workflow_populator.load_workflow(name="test_for_pja_run", add_pja=True)
|
|
workflow_request, history_id = self._setup_workflow_run(workflow, inputs_by='step_index')
|
|
workflow_request["replacement_params"] = dumps(dict(replaceme="was replaced"))
|
|
run_workflow_response = self._post("workflows", data=workflow_request)
|
|
self._assert_status_code_is(run_workflow_response, 200)
|
|
content = self.dataset_populator.get_history_dataset_details(history_id, wait=True, assert_ok=True)
|
|
assert content["name"] == "foo was replaced"
|
|
|
|
@skip_without_tool("output_filter")
|
|
def test_optional_workflow_output(self):
|
|
with self.dataset_populator.test_history() as history_id:
|
|
run_object = self._run_jobs("""
|
|
class: GalaxyWorkflow
|
|
inputs: []
|
|
outputs:
|
|
- id: wf_output_1
|
|
source: output_filter#out_1
|
|
steps:
|
|
- tool_id: output_filter
|
|
label: output_filter
|
|
state:
|
|
produce_out_1: False
|
|
filter_text_1: '1'
|
|
test_data: {}
|
|
""", history_id=history_id, wait=False)
|
|
self.wait_for_invocation_and_jobs(history_id, run_object.workflow_id, run_object.invocation_id)
|
|
contents = self.__history_contents(history_id)
|
|
assert len(contents) == 1
|
|
okay_dataset = contents[0]
|
|
assert okay_dataset["state"] == "ok"
|
|
|
|
@skip_without_tool("cat")
|
|
def test_run_rename_on_mapped_over_collection(self):
|
|
with self.dataset_populator.test_history() as history_id:
|
|
self._run_jobs("""
|
|
class: GalaxyWorkflow
|
|
inputs:
|
|
- id: input1
|
|
type: data_collection_input
|
|
collection_type: list
|
|
steps:
|
|
- tool_id: cat
|
|
label: first_cat
|
|
state:
|
|
input1:
|
|
$link: input1
|
|
outputs:
|
|
out_file1:
|
|
rename: "my new name"
|
|
test_data:
|
|
input1:
|
|
type: list
|
|
name: the_dataset_list
|
|
elements:
|
|
- identifier: el1
|
|
value: 1.fastq
|
|
type: File
|
|
""", history_id=history_id)
|
|
content = self.dataset_populator.get_history_dataset_details(history_id, hid=4, wait=True, assert_ok=True)
|
|
name = content["name"]
|
|
assert name == "my new name", name
|
|
assert content["history_content_type"] == "dataset"
|
|
content = self.dataset_populator.get_history_collection_details(history_id, hid=3, wait=True, assert_ok=True)
|
|
name = content["name"]
|
|
assert content["history_content_type"] == "dataset_collection", content
|
|
assert name == "my new name", name
|
|
|
|
@skip_without_tool("cat")
|
|
def test_run_rename_based_on_inputs_on_mapped_over_collection(self):
|
|
with self.dataset_populator.test_history() as history_id:
|
|
self._run_jobs("""
|
|
class: GalaxyWorkflow
|
|
inputs:
|
|
- id: input1
|
|
type: data_collection_input
|
|
collection_type: list
|
|
steps:
|
|
- tool_id: cat
|
|
label: first_cat
|
|
state:
|
|
input1:
|
|
$link: input1
|
|
outputs:
|
|
out_file1:
|
|
rename: "#{input1} suffix"
|
|
test_data:
|
|
input1:
|
|
type: list
|
|
name: the_dataset_list
|
|
elements:
|
|
- identifier: el1
|
|
value: 1.fastq
|
|
type: File
|
|
""", history_id=history_id)
|
|
content = self.dataset_populator.get_history_collection_details(history_id, hid=3, wait=True, assert_ok=True)
|
|
name = content["name"]
|
|
assert content["history_content_type"] == "dataset_collection", content
|
|
assert name == "the_dataset_list suffix", name
|
|
|
|
@skip_without_tool("collection_creates_pair")
|
|
def test_run_rename_collection_output(self):
|
|
with self.dataset_populator.test_history() as history_id:
|
|
self._run_jobs("""
|
|
class: GalaxyWorkflow
|
|
inputs:
|
|
- id: input1
|
|
steps:
|
|
- tool_id: collection_creates_pair
|
|
state:
|
|
input1:
|
|
$link: input1
|
|
outputs:
|
|
paired_output:
|
|
rename: "my new name"
|
|
test_data:
|
|
input1:
|
|
value: 1.fasta
|
|
type: File
|
|
name: fasta1
|
|
""", history_id=history_id)
|
|
details1 = self.dataset_populator.get_history_collection_details(history_id, hid=4, wait=True, assert_ok=True)
|
|
|
|
assert details1["name"] == "my new name", details1
|
|
assert details1["history_content_type"] == "dataset_collection"
|
|
|
|
@skip_without_tool("create_2")
|
|
def test_run_rename_multiple_outputs(self):
|
|
with self.dataset_populator.test_history() as history_id:
|
|
self._run_jobs("""
|
|
class: GalaxyWorkflow
|
|
inputs: []
|
|
steps:
|
|
- tool_id: create_2
|
|
state:
|
|
sleep_time: 0
|
|
outputs:
|
|
out_file1:
|
|
rename: "my new name"
|
|
out_file2:
|
|
rename: "my other new name"
|
|
test_data: {}
|
|
""", history_id=history_id)
|
|
details1 = self.dataset_populator.get_history_dataset_details(history_id, hid=1, wait=True, assert_ok=True)
|
|
details2 = self.dataset_populator.get_history_dataset_details(history_id, hid=2)
|
|
|
|
assert details1["name"] == "my new name"
|
|
assert details2["name"] == "my other new name"
|
|
|
|
@skip_without_tool("cat")
|
|
def test_run_rename_based_on_input(self):
|
|
with self.dataset_populator.test_history() as history_id:
|
|
self._run_jobs("""
|
|
class: GalaxyWorkflow
|
|
inputs:
|
|
- id: input1
|
|
steps:
|
|
- tool_id: cat
|
|
label: first_cat
|
|
state:
|
|
input1:
|
|
$link: input1
|
|
outputs:
|
|
out_file1:
|
|
rename: "#{input1 | basename} suffix"
|
|
test_data:
|
|
input1:
|
|
value: 1.fasta
|
|
type: File
|
|
name: fasta1
|
|
""", history_id=history_id)
|
|
content = self.dataset_populator.get_history_dataset_details(history_id, wait=True, assert_ok=True)
|
|
name = content["name"]
|
|
assert name == "fasta1 suffix", name
|
|
|
|
@skip_without_tool("fail_identifier")
|
|
@skip_without_tool("cat")
|
|
def test_run_rename_when_resuming_jobs(self):
|
|
with self.dataset_populator.test_history() as history_id:
|
|
self._run_jobs("""
|
|
class: GalaxyWorkflow
|
|
inputs:
|
|
- id: input1
|
|
steps:
|
|
- tool_id: fail_identifier
|
|
label: first_fail
|
|
state:
|
|
failbool: true
|
|
input1:
|
|
$link: input1
|
|
outputs:
|
|
out_file1:
|
|
rename: "cat1 out"
|
|
- tool_id: cat
|
|
state:
|
|
input1:
|
|
$link: first_fail#out_file1
|
|
outputs:
|
|
out_file1:
|
|
rename: "#{input1} suffix"
|
|
test_data:
|
|
input1:
|
|
value: 1.fasta
|
|
type: File
|
|
name: fail
|
|
""", history_id=history_id, wait=True, assert_ok=False)
|
|
content = self.dataset_populator.get_history_dataset_details(history_id, hid=2, wait=True, assert_ok=False)
|
|
name = content["name"]
|
|
assert content['state'] == 'error', content
|
|
input1 = self.dataset_populator.get_history_dataset_details(history_id, hid=1, wait=True, assert_ok=False)
|
|
job_id = content['creating_job']
|
|
inputs = {"input1": {'values': [{'src': 'hda',
|
|
'id': input1['id']}]
|
|
},
|
|
"failbool": "false",
|
|
"rerun_remap_job_id": job_id}
|
|
self.dataset_populator.run_tool(tool_id='fail_identifier',
|
|
inputs=inputs,
|
|
history_id=history_id,
|
|
assert_ok=True)
|
|
unpaused_dataset = self.dataset_populator.get_history_dataset_details(history_id, wait=True, assert_ok=False)
|
|
assert unpaused_dataset['state'] == 'ok'
|
|
assert unpaused_dataset['name'] == "%s suffix" % name
|
|
|
|
@skip_without_tool("cat")
|
|
def test_run_rename_based_on_input_recursive(self):
|
|
with self.dataset_populator.test_history() as history_id:
|
|
self._run_jobs("""
|
|
class: GalaxyWorkflow
|
|
inputs:
|
|
- id: input1
|
|
steps:
|
|
- tool_id: cat
|
|
label: first_cat
|
|
state:
|
|
input1:
|
|
$link: input1
|
|
outputs:
|
|
out_file1:
|
|
rename: "#{input1} #{input1 | upper} suffix"
|
|
test_data:
|
|
input1:
|
|
value: 1.fasta
|
|
type: File
|
|
name: '#{input1}'
|
|
""", history_id=history_id)
|
|
content = self.dataset_populator.get_history_dataset_details(history_id, wait=True, assert_ok=True)
|
|
name = content["name"]
|
|
assert name == "#{input1} #{INPUT1} suffix", name
|
|
|
|
@skip_without_tool("cat")
|
|
def test_run_rename_based_on_input_repeat(self):
|
|
with self.dataset_populator.test_history() as history_id:
|
|
self._run_jobs("""
|
|
class: GalaxyWorkflow
|
|
inputs:
|
|
- id: input1
|
|
- id: input2
|
|
steps:
|
|
- tool_id: cat
|
|
label: first_cat
|
|
state:
|
|
input1:
|
|
$link: input1
|
|
queries:
|
|
- input2:
|
|
$link: input2
|
|
outputs:
|
|
out_file1:
|
|
rename: "#{queries_0.input2| basename} suffix"
|
|
test_data:
|
|
input1:
|
|
value: 1.fasta
|
|
type: File
|
|
name: fasta1
|
|
input2:
|
|
value: 1.fasta
|
|
type: File
|
|
name: fasta2
|
|
""", history_id=history_id)
|
|
content = self.dataset_populator.get_history_dataset_details(history_id, wait=True, assert_ok=True)
|
|
name = content["name"]
|
|
assert name == "fasta2 suffix", name
|
|
|
|
@skip_without_tool("mapper2")
|
|
def test_run_rename_based_on_input_conditional(self):
|
|
with self.dataset_populator.test_history() as history_id:
|
|
self._run_jobs("""
|
|
class: GalaxyWorkflow
|
|
inputs:
|
|
- id: fasta_input
|
|
- id: fastq_input
|
|
steps:
|
|
- tool_id: mapper2
|
|
state:
|
|
fastq_input:
|
|
fastq_input_selector: single
|
|
fastq_input1:
|
|
$link: fastq_input
|
|
reference:
|
|
$link: fasta_input
|
|
outputs:
|
|
out_file1:
|
|
# Wish it was qualified for conditionals but it doesn't seem to be. -John
|
|
# rename: "#{fastq_input.fastq_input1 | basename} suffix"
|
|
rename: "#{fastq_input1 | basename} suffix"
|
|
test_data:
|
|
fasta_input:
|
|
value: 1.fasta
|
|
type: File
|
|
name: fasta1
|
|
file_type: fasta
|
|
fastq_input:
|
|
value: 1.fastqsanger
|
|
type: File
|
|
name: fastq1
|
|
file_type: fastqsanger
|
|
""", history_id=history_id)
|
|
content = self.dataset_populator.get_history_dataset_details(history_id, wait=True, assert_ok=True)
|
|
name = content["name"]
|
|
assert name == "fastq1 suffix", name
|
|
|
|
@skip_without_tool("mapper2")
|
|
def test_run_rename_based_on_input_collection(self):
|
|
with self.dataset_populator.test_history() as history_id:
|
|
self._run_jobs("""
|
|
class: GalaxyWorkflow
|
|
inputs:
|
|
- id: fasta_input
|
|
- id: fastq_inputs
|
|
steps:
|
|
- tool_id: mapper2
|
|
state:
|
|
fastq_input:
|
|
fastq_input_selector: paired_collection
|
|
fastq_input1:
|
|
$link: fastq_inputs
|
|
reference:
|
|
$link: fasta_input
|
|
outputs:
|
|
out_file1:
|
|
# Wish it was qualified for conditionals but it doesn't seem to be. -John
|
|
# rename: "#{fastq_input.fastq_input1 | basename} suffix"
|
|
rename: "#{fastq_input1} suffix"
|
|
test_data:
|
|
fasta_input:
|
|
value: 1.fasta
|
|
type: File
|
|
name: fasta1
|
|
file_type: fasta
|
|
fastq_inputs:
|
|
type: list
|
|
name: the_dataset_pair
|
|
elements:
|
|
- identifier: forward
|
|
value: 1.fastq
|
|
type: File
|
|
- identifier: reverse
|
|
value: 1.fastq
|
|
type: File
|
|
""", history_id=history_id)
|
|
content = self.dataset_populator.get_history_dataset_details(history_id, wait=True, assert_ok=True)
|
|
name = content["name"]
|
|
assert name == "the_dataset_pair suffix", name
|
|
|
|
@skip_without_tool("collection_creates_pair")
|
|
def test_run_hide_on_collection_output(self):
|
|
with self.dataset_populator.test_history() as history_id:
|
|
self._run_jobs("""
|
|
class: GalaxyWorkflow
|
|
inputs:
|
|
- id: input1
|
|
steps:
|
|
- tool_id: collection_creates_pair
|
|
state:
|
|
input1:
|
|
$link: input1
|
|
outputs:
|
|
paired_output:
|
|
hide: true
|
|
test_data:
|
|
input1:
|
|
value: 1.fasta
|
|
type: File
|
|
name: fasta1
|
|
""", history_id=history_id)
|
|
details1 = self.dataset_populator.get_history_collection_details(history_id, hid=4, wait=True, assert_ok=True)
|
|
|
|
assert details1["history_content_type"] == "dataset_collection"
|
|
assert not details1["visible"], details1
|
|
|
|
@skip_without_tool("cat")
|
|
def test_run_hide_on_mapped_over_collection(self):
|
|
with self.dataset_populator.test_history() as history_id:
|
|
self._run_jobs("""
|
|
class: GalaxyWorkflow
|
|
inputs:
|
|
- id: input1
|
|
type: data_collection_input
|
|
collection_type: list
|
|
steps:
|
|
- tool_id: cat
|
|
label: first_cat
|
|
state:
|
|
input1:
|
|
$link: input1
|
|
outputs:
|
|
out_file1:
|
|
hide: true
|
|
test_data:
|
|
input1:
|
|
type: list
|
|
name: the_dataset_list
|
|
elements:
|
|
- identifier: el1
|
|
value: 1.fastq
|
|
type: File
|
|
""", history_id=history_id)
|
|
|
|
content = self.dataset_populator.get_history_dataset_details(history_id, hid=4, wait=True, assert_ok=True)
|
|
assert content["history_content_type"] == "dataset"
|
|
assert content["visible"] is False
|
|
|
|
content = self.dataset_populator.get_history_collection_details(history_id, hid=3, wait=True, assert_ok=True)
|
|
assert content["history_content_type"] == "dataset_collection", content
|
|
assert content["visible"] is False
|
|
|
|
@skip_without_tool("collection_creates_pair")
|
|
def test_run_add_tag_on_collection_output(self):
|
|
with self.dataset_populator.test_history() as history_id:
|
|
self._run_jobs("""
|
|
class: GalaxyWorkflow
|
|
inputs:
|
|
- id: input1
|
|
steps:
|
|
- tool_id: collection_creates_pair
|
|
state:
|
|
input1:
|
|
$link: input1
|
|
outputs:
|
|
paired_output:
|
|
add_tags:
|
|
- "name:foo"
|
|
test_data:
|
|
input1:
|
|
value: 1.fasta
|
|
type: File
|
|
name: fasta1
|
|
""", history_id=history_id)
|
|
details1 = self.dataset_populator.get_history_collection_details(history_id, hid=4, wait=True, assert_ok=True)
|
|
|
|
assert details1["history_content_type"] == "dataset_collection"
|
|
assert details1["tags"][0] == "name:foo", details1
|
|
|
|
@skip_without_tool("collection_creates_pair")
|
|
def test_run_add_tag_on_mapped_over_collection(self):
|
|
with self.dataset_populator.test_history() as history_id:
|
|
self._run_jobs("""
|
|
class: GalaxyWorkflow
|
|
inputs:
|
|
- id: input1
|
|
type: data_collection_input
|
|
collection_type: list
|
|
steps:
|
|
- tool_id: cat
|
|
label: first_cat
|
|
state:
|
|
input1:
|
|
$link: input1
|
|
outputs:
|
|
out_file1:
|
|
add_tags:
|
|
- "name:foo"
|
|
test_data:
|
|
input1:
|
|
type: list
|
|
name: the_dataset_list
|
|
elements:
|
|
- identifier: el1
|
|
value: 1.fastq
|
|
type: File
|
|
""", history_id=history_id)
|
|
details1 = self.dataset_populator.get_history_collection_details(history_id, hid=3, wait=True, assert_ok=True)
|
|
|
|
assert details1["history_content_type"] == "dataset_collection"
|
|
assert details1["tags"][0] == "name:foo", details1
|
|
|
|
@skip_without_tool("collection_creates_pair")
|
|
@skip_without_tool("cat")
|
|
def test_run_remove_tag_on_collection_output(self):
|
|
with self.dataset_populator.test_history() as history_id:
|
|
self._run_jobs("""
|
|
class: GalaxyWorkflow
|
|
inputs:
|
|
- id: input1
|
|
steps:
|
|
- tool_id: cat
|
|
label: first_cat
|
|
state:
|
|
input1:
|
|
$link: input1
|
|
outputs:
|
|
out_file1:
|
|
add_tags:
|
|
- "name:foo"
|
|
- tool_id: collection_creates_pair
|
|
state:
|
|
input1:
|
|
$link: first_cat#out_file1
|
|
outputs:
|
|
paired_output:
|
|
remove_tags:
|
|
- "name:foo"
|
|
test_data:
|
|
input1:
|
|
value: 1.fasta
|
|
type: File
|
|
name: fasta1
|
|
""", history_id=history_id)
|
|
details_dataset_with_tag = self.dataset_populator.get_history_dataset_details(history_id, hid=2, wait=True, assert_ok=True)
|
|
|
|
assert details_dataset_with_tag["history_content_type"] == "dataset", details_dataset_with_tag
|
|
assert details_dataset_with_tag["tags"][0] == "name:foo", details_dataset_with_tag
|
|
|
|
details_collection_without_tag = self.dataset_populator.get_history_collection_details(history_id, hid=5, wait=True, assert_ok=True)
|
|
assert details_collection_without_tag["history_content_type"] == "dataset_collection", details_collection_without_tag
|
|
assert len(details_collection_without_tag["tags"]) == 0, details_collection_without_tag
|
|
|
|
@skip_without_tool("cat1")
|
|
def test_run_with_runtime_pja(self):
|
|
workflow = self.workflow_populator.load_workflow(name="test_for_pja_runtime")
|
|
uuid0, uuid1, uuid2 = str(uuid4()), str(uuid4()), str(uuid4())
|
|
workflow["steps"]["0"]["uuid"] = uuid0
|
|
workflow["steps"]["1"]["uuid"] = uuid1
|
|
workflow["steps"]["2"]["uuid"] = uuid2
|
|
workflow_request, history_id = self._setup_workflow_run(workflow, inputs_by='step_index')
|
|
workflow_request["replacement_params"] = dumps(dict(replaceme="was replaced"))
|
|
|
|
pja_map = {
|
|
"RenameDatasetActionout_file1": dict(
|
|
action_type="RenameDatasetAction",
|
|
output_name="out_file1",
|
|
action_arguments=dict(newname="foo ${replaceme}"),
|
|
)
|
|
}
|
|
workflow_request["parameters"] = dumps({
|
|
uuid2: {"__POST_JOB_ACTIONS__": pja_map}
|
|
})
|
|
|
|
run_workflow_response = self._post("workflows", data=workflow_request)
|
|
self._assert_status_code_is(run_workflow_response, 200)
|
|
content = self.dataset_populator.get_history_dataset_details(history_id, wait=True, assert_ok=True)
|
|
assert content["name"] == "foo was replaced", content["name"]
|
|
|
|
# Test for regression of previous behavior where runtime post job actions
|
|
# would be added to the original workflow post job actions.
|
|
workflow_id = workflow_request["workflow_id"]
|
|
downloaded_workflow = self._download_workflow(workflow_id)
|
|
pjas = list(downloaded_workflow["steps"]["2"]["post_job_actions"].values())
|
|
assert len(pjas) == 0, len(pjas)
|
|
|
|
@skip_without_tool("cat1")
|
|
def test_run_with_delayed_runtime_pja(self):
|
|
workflow_id = self._upload_yaml_workflow("""
|
|
class: GalaxyWorkflow
|
|
steps:
|
|
- label: test_input
|
|
type: input
|
|
- label: first_cat
|
|
tool_id: cat1
|
|
state:
|
|
input1:
|
|
$link: test_input
|
|
- label: the_pause
|
|
type: pause
|
|
connect:
|
|
input:
|
|
- first_cat#out_file1
|
|
- label: second_cat
|
|
tool_id: cat1
|
|
state:
|
|
input1:
|
|
$link: the_pause
|
|
""")
|
|
downloaded_workflow = self._download_workflow(workflow_id)
|
|
uuid_dict = dict((int(index), step["uuid"]) for index, step in downloaded_workflow["steps"].items())
|
|
with self.dataset_populator.test_history() as history_id:
|
|
hda = self.dataset_populator.new_dataset(history_id, content="1 2 3")
|
|
self.dataset_populator.wait_for_history(history_id)
|
|
inputs = {
|
|
'0': self._ds_entry(hda),
|
|
}
|
|
print(inputs)
|
|
uuid2 = uuid_dict[3]
|
|
workflow_request = {}
|
|
workflow_request["replacement_params"] = dumps(dict(replaceme="was replaced"))
|
|
pja_map = {
|
|
"RenameDatasetActionout_file1": dict(
|
|
action_type="RenameDatasetAction",
|
|
output_name="out_file1",
|
|
action_arguments=dict(newname="foo ${replaceme}"),
|
|
)
|
|
}
|
|
workflow_request["parameters"] = dumps({
|
|
uuid2: {"__POST_JOB_ACTIONS__": pja_map}
|
|
})
|
|
invocation_id = self.__invoke_workflow(history_id, workflow_id, inputs=inputs, request=workflow_request)
|
|
|
|
time.sleep(2)
|
|
self.dataset_populator.wait_for_history(history_id)
|
|
self.__review_paused_steps(workflow_id, invocation_id, order_index=2, action=True)
|
|
|
|
self.workflow_populator.wait_for_workflow(workflow_id, invocation_id, history_id)
|
|
time.sleep(1)
|
|
content = self.dataset_populator.get_history_dataset_details(history_id)
|
|
assert content["name"] == "foo was replaced", content["name"]
|
|
|
|
@skip_without_tool("cat1")
|
|
def test_delete_intermediate_datasets_pja_1(self):
|
|
with self.dataset_populator.test_history() as history_id:
|
|
self._run_jobs("""
|
|
class: GalaxyWorkflow
|
|
inputs:
|
|
- id: input1
|
|
outputs:
|
|
- id: wf_output_1
|
|
source: third_cat#out_file1
|
|
steps:
|
|
- tool_id: cat1
|
|
label: first_cat
|
|
state:
|
|
input1:
|
|
$link: input1
|
|
- tool_id: cat1
|
|
label: second_cat
|
|
state:
|
|
input1:
|
|
$link: first_cat#out_file1
|
|
- tool_id: cat1
|
|
label: third_cat
|
|
state:
|
|
input1:
|
|
$link: second_cat#out_file1
|
|
outputs:
|
|
out_file1:
|
|
delete_intermediate_datasets: true
|
|
test_data:
|
|
input1: "hello world"
|
|
""", history_id=history_id)
|
|
hda1 = self.dataset_populator.get_history_dataset_details(history_id, hid=1)
|
|
hda2 = self.dataset_populator.get_history_dataset_details(history_id, hid=2)
|
|
hda3 = self.dataset_populator.get_history_dataset_details(history_id, hid=3)
|
|
hda4 = self.dataset_populator.get_history_dataset_details(history_id, hid=4)
|
|
assert not hda1["deleted"]
|
|
assert hda2["deleted"]
|
|
# I think hda3 should be deleted, but the inputs to
|
|
# steps with workflow outputs are not deleted.
|
|
# assert hda3["deleted"]
|
|
print(hda3["deleted"])
|
|
assert not hda4["deleted"]
|
|
|
|
@skip_without_tool("random_lines1")
|
|
def test_run_replace_params_by_tool(self):
|
|
workflow_request, history_id = self._setup_random_x2_workflow("test_for_replace_tool_params")
|
|
workflow_request["parameters"] = dumps(dict(random_lines1=dict(num_lines=5)))
|
|
run_workflow_response = self._post("workflows", data=workflow_request)
|
|
self._assert_status_code_is(run_workflow_response, 200)
|
|
self.dataset_populator.wait_for_history(history_id, assert_ok=True)
|
|
# Would be 8 and 6 without modification
|
|
self.__assert_lines_hid_line_count_is(history_id, 2, 5)
|
|
self.__assert_lines_hid_line_count_is(history_id, 3, 5)
|
|
|
|
@skip_without_tool("random_lines1")
|
|
def test_run_replace_params_by_uuid(self):
|
|
workflow_request, history_id = self._setup_random_x2_workflow("test_for_replace_tool_params")
|
|
workflow_request["parameters"] = dumps({
|
|
"58dffcc9-bcb7-4117-a0e1-61513524b3b1": dict(num_lines=4),
|
|
"58dffcc9-bcb7-4117-a0e1-61513524b3b2": dict(num_lines=3),
|
|
})
|
|
run_workflow_response = self._post("workflows", data=workflow_request)
|
|
self._assert_status_code_is(run_workflow_response, 200)
|
|
self.dataset_populator.wait_for_history(history_id, assert_ok=True)
|
|
# Would be 8 and 6 without modification
|
|
self.__assert_lines_hid_line_count_is(history_id, 2, 4)
|
|
self.__assert_lines_hid_line_count_is(history_id, 3, 3)
|
|
|
|
@skip_without_tool("cat1")
|
|
@skip_without_tool("addValue")
|
|
def test_run_batch(self):
|
|
workflow = self.workflow_populator.load_workflow_from_resource("test_workflow_batch")
|
|
workflow_id = self.workflow_populator.create_workflow(workflow)
|
|
with self.dataset_populator.test_history() as history_id:
|
|
hda1 = self.dataset_populator.new_dataset(history_id, content="1 2 3")
|
|
hda2 = self.dataset_populator.new_dataset(history_id, content="4 5 6")
|
|
hda3 = self.dataset_populator.new_dataset(history_id, content="7 8 9")
|
|
hda4 = self.dataset_populator.new_dataset(history_id, content="10 11 12")
|
|
parameters = {
|
|
"0": {"input": {"batch": True, "values": [{"id" : hda1.get("id"), "hid": hda1.get("hid"), "src": "hda"},
|
|
{"id" : hda2.get("id"), "hid": hda2.get("hid"), "src": "hda"},
|
|
{"id" : hda3.get("id"), "hid": hda2.get("hid"), "src": "hda"},
|
|
{"id" : hda4.get("id"), "hid": hda2.get("hid"), "src": "hda"}]}},
|
|
"1": {"input": {"batch": False, "values": [{"id" : hda1.get("id"), "hid": hda1.get("hid"), "src": "hda"}]}, "exp": "2"}}
|
|
workflow_request = {
|
|
"history_id" : history_id,
|
|
"batch" : True,
|
|
"parameters_normalized": True,
|
|
"parameters" : dumps(parameters),
|
|
}
|
|
invocation_response = self._post("workflows/%s/usage" % workflow_id, data=workflow_request)
|
|
self._assert_status_code_is(invocation_response, 200)
|
|
time.sleep(5)
|
|
self.dataset_populator.wait_for_history(history_id, assert_ok=True)
|
|
r1 = "1 2 3\t1\n1 2 3\t2\n"
|
|
r2 = "4 5 6\t1\n1 2 3\t2\n"
|
|
r3 = "7 8 9\t1\n1 2 3\t2\n"
|
|
r4 = "10 11 12\t1\n1 2 3\t2\n"
|
|
t1 = self.dataset_populator.get_history_dataset_content(history_id, hid=7)
|
|
t2 = self.dataset_populator.get_history_dataset_content(history_id, hid=10)
|
|
t3 = self.dataset_populator.get_history_dataset_content(history_id, hid=13)
|
|
t4 = self.dataset_populator.get_history_dataset_content(history_id, hid=16)
|
|
self.assertEqual(r1, t1)
|
|
self.assertEqual(r2, t2)
|
|
self.assertEqual(r3, t3)
|
|
self.assertEqual(r4, t4)
|
|
|
|
@skip_without_tool("validation_default")
|
|
def test_parameter_substitution_sanitization(self):
|
|
substitions = dict(input1="\" ; echo \"moo")
|
|
run_workflow_response, history_id = self._run_validation_workflow_with_substitions(substitions)
|
|
|
|
self.dataset_populator.wait_for_history(history_id, assert_ok=True)
|
|
self.assertEqual("__dq__ X echo __dq__moo\n", self.dataset_populator.get_history_dataset_content(history_id, hid=1))
|
|
|
|
@skip_without_tool("validation_repeat")
|
|
def test_parameter_substitution_validation_value_errors_0(self):
|
|
with self.dataset_populator.test_history() as history_id:
|
|
workflow_id = self._upload_yaml_workflow("""
|
|
class: GalaxyWorkflow
|
|
steps:
|
|
- tool_id: validation_repeat
|
|
state:
|
|
r2:
|
|
- text: "abd"
|
|
""")
|
|
workflow_request = dict(
|
|
history="hist_id=%s" % history_id,
|
|
parameters=dumps(dict(validation_repeat={"r2_0|text": ""}))
|
|
)
|
|
url = "workflows/%s/invocations" % workflow_id
|
|
invocation_response = self._post(url, data=workflow_request)
|
|
# Take a valid stat and make it invalid, assert workflow won't run.
|
|
self._assert_status_code_is(invocation_response, 400)
|
|
|
|
@skip_without_tool("validation_default")
|
|
def test_parameter_substitution_validation_value_errors_1(self):
|
|
substitions = dict(select_param="\" ; echo \"moo")
|
|
run_workflow_response, history_id = self._run_validation_workflow_with_substitions(substitions)
|
|
|
|
self._assert_status_code_is(run_workflow_response, 400)
|
|
|
|
@skip_without_tool("validation_repeat")
|
|
def test_workflow_import_state_validation_1(self):
|
|
with self.dataset_populator.test_history() as history_id:
|
|
self._run_jobs("""
|
|
class: GalaxyWorkflow
|
|
steps:
|
|
- tool_id: validation_repeat
|
|
state:
|
|
r2:
|
|
- text: ""
|
|
""", history_id=history_id, wait=False, expected_response=400)
|
|
|
|
def _run_validation_workflow_with_substitions(self, substitions):
|
|
workflow = self.workflow_populator.load_workflow_from_resource("test_workflow_validation_1")
|
|
uploaded_workflow_id = self.workflow_populator.create_workflow(workflow)
|
|
history_id = self.dataset_populator.new_history()
|
|
workflow_request = dict(
|
|
history="hist_id=%s" % history_id,
|
|
workflow_id=uploaded_workflow_id,
|
|
parameters=dumps(dict(validation_default=substitions))
|
|
)
|
|
run_workflow_response = self._post("workflows", data=workflow_request)
|
|
return run_workflow_response, history_id
|
|
|
|
@skip_without_tool("random_lines1")
|
|
def test_run_replace_params_by_steps(self):
|
|
workflow_request, history_id, steps = self._setup_random_x2_workflow_steps("test_for_replace_step_params")
|
|
params = dumps({str(steps[1]["id"]): dict(num_lines=5)})
|
|
workflow_request["parameters"] = params
|
|
run_workflow_response = self._post("workflows", data=workflow_request)
|
|
self._assert_status_code_is(run_workflow_response, 200)
|
|
self.dataset_populator.wait_for_history(history_id, assert_ok=True)
|
|
# Would be 8 and 6 without modification
|
|
self.__assert_lines_hid_line_count_is(history_id, 2, 8)
|
|
self.__assert_lines_hid_line_count_is(history_id, 3, 5)
|
|
|
|
@skip_without_tool("random_lines1")
|
|
def test_run_replace_params_nested(self):
|
|
workflow_request, history_id, steps = self._setup_random_x2_workflow_steps("test_for_replace_step_params_nested")
|
|
seed_source = dict(
|
|
seed_source_selector="set_seed",
|
|
seed="moo",
|
|
)
|
|
params = dumps({str(steps[0]["id"]): dict(num_lines=1, seed_source=seed_source),
|
|
str(steps[1]["id"]): dict(num_lines=1, seed_source=seed_source)})
|
|
workflow_request["parameters"] = params
|
|
run_workflow_response = self._post("workflows", data=workflow_request)
|
|
self._assert_status_code_is(run_workflow_response, 200)
|
|
self.dataset_populator.wait_for_history(history_id, assert_ok=True)
|
|
self.assertEqual("3\n", self.dataset_populator.get_history_dataset_content(history_id))
|
|
|
|
def test_pja_import_export(self):
|
|
workflow = self.workflow_populator.load_workflow(name="test_for_pja_import", add_pja=True)
|
|
uploaded_workflow_id = self.workflow_populator.create_workflow(workflow)
|
|
downloaded_workflow = self._download_workflow(uploaded_workflow_id)
|
|
self._assert_has_keys(downloaded_workflow["steps"], "0", "1", "2")
|
|
pjas = list(downloaded_workflow["steps"]["2"]["post_job_actions"].values())
|
|
assert len(pjas) == 1, len(pjas)
|
|
pja = pjas[0]
|
|
self._assert_has_keys(pja, "action_type", "output_name", "action_arguments")
|
|
|
|
@skip_without_tool("cat1")
|
|
def test_only_own_invocations_accessible(self):
|
|
workflow_id, usage = self._run_workflow_once_get_invocation("test_usage")
|
|
with self._different_user():
|
|
usage_details_response = self._get("workflows/%s/usage/%s" % (workflow_id, usage["id"]))
|
|
self._assert_status_code_is(usage_details_response, 403)
|
|
|
|
@skip_without_tool("cat1")
|
|
def test_invocation_usage(self):
|
|
workflow_id, usage = self._run_workflow_once_get_invocation("test_usage")
|
|
invocation_id = usage["id"]
|
|
usage_details = self._invocation_details(workflow_id, invocation_id)
|
|
# Assert some high-level things about the structure of data returned.
|
|
self._assert_has_keys(usage_details, "inputs", "steps")
|
|
invocation_steps = usage_details["steps"]
|
|
for step in invocation_steps:
|
|
self._assert_has_keys(step, "workflow_step_id", "order_index", "id")
|
|
an_invocation_step = invocation_steps[0]
|
|
step_id = an_invocation_step["id"]
|
|
step_response = self._get("workflows/%s/usage/%s/steps/%s" % (workflow_id, invocation_id, step_id))
|
|
self._assert_status_code_is(step_response, 200)
|
|
self._assert_has_keys(step_response.json(), "id", "order_index")
|
|
|
|
@skip_without_tool("cat1")
|
|
def test_invocations_accessible_imported_workflow(self):
|
|
workflow_id = self.workflow_populator.simple_workflow("test_usage", publish=True)
|
|
with self._different_user():
|
|
other_import_response = self.__import_workflow(workflow_id)
|
|
self._assert_status_code_is(other_import_response, 200)
|
|
other_id = other_import_response.json()["id"]
|
|
workflow_request, history_id = self._setup_workflow_run(workflow_id=other_id)
|
|
response = self._get("workflows/%s/usage" % other_id)
|
|
self._assert_status_code_is(response, 200)
|
|
assert len(response.json()) == 0
|
|
run_workflow_response = self._post("workflows", data=workflow_request)
|
|
self._assert_status_code_is(run_workflow_response, 200)
|
|
run_workflow_response = run_workflow_response.json()
|
|
invocation_id = run_workflow_response['id']
|
|
usage_details_response = self._get("workflows/%s/usage/%s" % (other_id, invocation_id))
|
|
self._assert_status_code_is(usage_details_response, 200)
|
|
|
|
@skip_without_tool("cat1")
|
|
def test_invocations_accessible_published_workflow(self):
|
|
workflow_id = self.workflow_populator.simple_workflow("test_usage", publish=True)
|
|
with self._different_user():
|
|
workflow_request, history_id = self._setup_workflow_run(workflow_id=workflow_id)
|
|
workflow_request['workflow_id'] = workflow_request.pop('workflow_id')
|
|
response = self._get("workflows/%s/usage" % workflow_id)
|
|
self._assert_status_code_is(response, 200)
|
|
assert len(response.json()) == 0
|
|
run_workflow_response = self._post("workflows", data=workflow_request)
|
|
self._assert_status_code_is(run_workflow_response, 200)
|
|
run_workflow_response = run_workflow_response.json()
|
|
invocation_id = run_workflow_response['id']
|
|
usage_details_response = self._get("workflows/%s/usage/%s" % (workflow_id, invocation_id))
|
|
self._assert_status_code_is(usage_details_response, 200)
|
|
|
|
@skip_without_tool("cat1")
|
|
def test_invocations_not_accessible_by_different_user_for_published_workflow(self):
|
|
workflow_id = self.workflow_populator.simple_workflow("test_usage", publish=True)
|
|
workflow_request, history_id = self._setup_workflow_run(workflow_id=workflow_id)
|
|
workflow_request['workflow_id'] = workflow_request.pop('workflow_id')
|
|
response = self._get("workflows/%s/usage" % workflow_id)
|
|
self._assert_status_code_is(response, 200)
|
|
assert len(response.json()) == 0
|
|
run_workflow_response = self._post("workflows", data=workflow_request)
|
|
self._assert_status_code_is(run_workflow_response, 200)
|
|
run_workflow_response = run_workflow_response.json()
|
|
invocation_id = run_workflow_response['id']
|
|
with self._different_user():
|
|
usage_details_response = self._get("workflows/%s/usage/%s" % (workflow_id, invocation_id))
|
|
self._assert_status_code_is(usage_details_response, 403)
|
|
|
|
def _invoke_paused_workflow(self, history_id):
|
|
workflow = self.workflow_populator.load_workflow_from_resource("test_workflow_pause")
|
|
workflow_id = self.workflow_populator.create_workflow(workflow)
|
|
hda1 = self.dataset_populator.new_dataset(history_id, content="1 2 3")
|
|
index_map = {
|
|
'0': self._ds_entry(hda1),
|
|
}
|
|
invocation_id = self.__invoke_workflow(
|
|
history_id,
|
|
workflow_id,
|
|
index_map,
|
|
)
|
|
return workflow_id, invocation_id
|
|
|
|
def _wait_for_invocation_non_new(self, workflow_id, invocation_id):
|
|
target_state_reached = False
|
|
for i in range(50):
|
|
invocation = self._invocation_details(workflow_id, invocation_id)
|
|
if invocation['state'] != 'new':
|
|
target_state_reached = True
|
|
break
|
|
|
|
time.sleep(.25)
|
|
|
|
return target_state_reached
|
|
|
|
def _assert_invocation_non_terminal(self, workflow_id, invocation_id):
|
|
invocation = self._invocation_details(workflow_id, invocation_id)
|
|
assert invocation['state'] in ['ready', 'new'], invocation
|
|
|
|
def _wait_for_invocation_state(self, workflow_id, invocation_id, target_state):
|
|
target_state_reached = False
|
|
for i in range(25):
|
|
invocation = self._invocation_details(workflow_id, invocation_id)
|
|
if invocation['state'] == target_state:
|
|
target_state_reached = True
|
|
break
|
|
|
|
time.sleep(.5)
|
|
|
|
return target_state_reached
|
|
|
|
def _update_workflow(self, workflow_id, workflow_object):
|
|
data = dict(
|
|
workflow=workflow_object
|
|
)
|
|
raw_url = 'workflows/%s' % workflow_id
|
|
url = self._api_url(raw_url, use_key=True)
|
|
put_response = put(url, data=dumps(data))
|
|
return put_response
|
|
|
|
def _invocation_step_details(self, workflow_id, invocation_id, step_id):
|
|
invocation_step_response = self._get("workflows/%s/usage/%s/steps/%s" % (workflow_id, invocation_id, step_id))
|
|
self._assert_status_code_is(invocation_step_response, 200)
|
|
invocation_step_details = invocation_step_response.json()
|
|
return invocation_step_details
|
|
|
|
def _execute_invocation_step_action(self, workflow_id, invocation_id, step_id, action):
|
|
raw_url = "workflows/%s/usage/%s/steps/%s" % (workflow_id, invocation_id, step_id)
|
|
url = self._api_url(raw_url, use_key=True)
|
|
payload = dumps(dict(action=action))
|
|
action_response = put(url, data=payload)
|
|
self._assert_status_code_is(action_response, 200)
|
|
invocation_step_details = action_response.json()
|
|
return invocation_step_details
|
|
|
|
def _run_workflow_once_get_invocation(self, name):
|
|
workflow = self.workflow_populator.load_workflow(name=name)
|
|
workflow_request, history_id = self._setup_workflow_run(workflow)
|
|
workflow_id = workflow_request["workflow_id"]
|
|
response = self._get("workflows/%s/usage" % workflow_id)
|
|
self._assert_status_code_is(response, 200)
|
|
assert len(response.json()) == 0
|
|
run_workflow_response = self._post("workflows", data=workflow_request)
|
|
self._assert_status_code_is(run_workflow_response, 200)
|
|
|
|
response = self._get("workflows/%s/usage" % workflow_id)
|
|
self._assert_status_code_is(response, 200)
|
|
usages = response.json()
|
|
assert len(usages) == 1
|
|
return workflow_id, usages[0]
|
|
|
|
def _setup_random_x2_workflow_steps(self, name):
|
|
workflow_request, history_id = self._setup_random_x2_workflow("test_for_replace_step_params")
|
|
random_line_steps = self._random_lines_steps(workflow_request)
|
|
return workflow_request, history_id, random_line_steps
|
|
|
|
def _random_lines_steps(self, workflow_request):
|
|
workflow_summary_response = self._get("workflows/%s" % workflow_request["workflow_id"])
|
|
self._assert_status_code_is(workflow_summary_response, 200)
|
|
steps = workflow_summary_response.json()["steps"]
|
|
return sorted((step for step in steps.values() if step["tool_id"] == "random_lines1"), key=lambda step: step["id"])
|
|
|
|
def _setup_random_x2_workflow(self, name):
|
|
workflow = self.workflow_populator.load_random_x2_workflow(name)
|
|
uploaded_workflow_id = self.workflow_populator.create_workflow(workflow)
|
|
workflow_inputs = self._workflow_inputs(uploaded_workflow_id)
|
|
key = next(iter(workflow_inputs.keys()))
|
|
history_id = self.dataset_populator.new_history()
|
|
ten_lines = "\n".join(str(_) for _ in range(10))
|
|
hda1 = self.dataset_populator.new_dataset(history_id, content=ten_lines)
|
|
workflow_request = dict(
|
|
history="hist_id=%s" % history_id,
|
|
workflow_id=uploaded_workflow_id,
|
|
ds_map=dumps({
|
|
key: self._ds_entry(hda1),
|
|
}),
|
|
)
|
|
return workflow_request, history_id
|
|
|
|
def __review_paused_steps(self, uploaded_workflow_id, invocation_id, order_index, action=True):
|
|
invocation = self._invocation_details(uploaded_workflow_id, invocation_id)
|
|
invocation_steps = invocation["steps"]
|
|
pause_steps = [s for s in invocation_steps if s['order_index'] == order_index]
|
|
for pause_step in pause_steps:
|
|
pause_step_id = pause_step['id']
|
|
|
|
self._execute_invocation_step_action(uploaded_workflow_id, invocation_id, pause_step_id, action=action)
|
|
|
|
def __assert_lines_hid_line_count_is(self, history, hid, lines):
|
|
contents_url = "histories/%s/contents" % history
|
|
history_contents = self.__history_contents(history)
|
|
hda_summary = next(hc for hc in history_contents if hc["hid"] == hid)
|
|
hda_info_response = self._get("%s/%s" % (contents_url, hda_summary["id"]))
|
|
self._assert_status_code_is(hda_info_response, 200)
|
|
self.assertEqual(hda_info_response.json()["metadata_data_lines"], lines)
|
|
|
|
def __history_contents(self, history_id):
|
|
contents_url = "histories/%s/contents" % history_id
|
|
history_contents_response = self._get(contents_url)
|
|
self._assert_status_code_is(history_contents_response, 200)
|
|
return history_contents_response.json()
|
|
|
|
def __invoke_workflow(self, *args, **kwds):
|
|
return self.workflow_populator.invoke_workflow(*args, **kwds)
|
|
|
|
def __import_workflow(self, workflow_id, deprecated_route=False):
|
|
if deprecated_route:
|
|
route = "workflows/import"
|
|
import_data = dict(
|
|
workflow_id=workflow_id,
|
|
)
|
|
else:
|
|
route = "workflows"
|
|
import_data = dict(
|
|
shared_workflow_id=workflow_id,
|
|
)
|
|
return self._post(route, import_data)
|
|
|
|
def _download_workflow(self, workflow_id, style=None):
|
|
params = {}
|
|
if style:
|
|
params = {"style": style}
|
|
download_response = self._get("workflows/%s/download" % workflow_id, params)
|
|
self._assert_status_code_is(download_response, 200)
|
|
downloaded_workflow = download_response.json()
|
|
return downloaded_workflow
|
|
|
|
def _show_workflow(self, workflow_id):
|
|
show_response = self._get("workflows/%s" % workflow_id)
|
|
self._assert_status_code_is(show_response, 200)
|
|
return show_response.json()
|
|
|
|
def _assert_looks_like_instance_workflow_representation(self, workflow):
|
|
self._assert_has_keys(
|
|
workflow,
|
|
'url',
|
|
'owner',
|
|
'inputs',
|
|
'annotation',
|
|
'steps'
|
|
)
|
|
for step in workflow["steps"].values():
|
|
self._assert_has_keys(
|
|
step,
|
|
'id',
|
|
'type',
|
|
'tool_id',
|
|
'tool_version',
|
|
'annotation',
|
|
'tool_inputs',
|
|
'input_steps',
|
|
)
|
|
|
|
|
|
RunJobsSummary = namedtuple('RunJobsSummary', ['history_id', 'workflow_id', 'invocation_id', 'inputs', 'jobs', 'invocation', 'workflow_request'])
|