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Source code for galaxy_test.api.test_workflows
import base64
import json
import os
import shutil
import time
from json import dumps
from tempfile import mkdtemp
from typing import (
Any,
cast,
Dict,
Optional,
Tuple,
Union,
)
from uuid import uuid4
import pytest
import yaml
from requests import (
delete,
get,
put,
)
from galaxy.exceptions import error_codes
from galaxy_test.base import rules_test_data
from galaxy_test.base.populators import (
DatasetCollectionPopulator,
DatasetPopulator,
RunJobsSummary,
skip_without_tool,
wait_on,
workflow_str,
WorkflowPopulator,
)
from galaxy_test.base.workflow_fixtures import (
WORKFLOW_INPUTS_AS_OUTPUTS,
WORKFLOW_NESTED_REPLACEMENT_PARAMETER,
WORKFLOW_NESTED_RUNTIME_PARAMETER,
WORKFLOW_NESTED_SIMPLE,
WORKFLOW_ONE_STEP_DEFAULT,
WORKFLOW_OPTIONAL_FALSE_INPUT_COLLECTION,
WORKFLOW_OPTIONAL_FALSE_INPUT_DATA,
WORKFLOW_OPTIONAL_INPUT_DELAYED_SCHEDULING,
WORKFLOW_OPTIONAL_TRUE_INPUT_COLLECTION,
WORKFLOW_OPTIONAL_TRUE_INPUT_DATA,
WORKFLOW_PARAMETER_INPUT_INTEGER_DEFAULT,
WORKFLOW_PARAMETER_INPUT_INTEGER_OPTIONAL,
WORKFLOW_PARAMETER_INPUT_INTEGER_REQUIRED,
WORKFLOW_RENAME_ON_INPUT,
WORKFLOW_RUNTIME_PARAMETER_AFTER_PAUSE,
WORKFLOW_WITH_BAD_COLUMN_PARAMETER,
WORKFLOW_WITH_BAD_COLUMN_PARAMETER_GOOD_TEST_DATA,
WORKFLOW_WITH_CUSTOM_REPORT_1,
WORKFLOW_WITH_CUSTOM_REPORT_1_TEST_DATA,
WORKFLOW_WITH_DYNAMIC_OUTPUT_COLLECTION,
WORKFLOW_WITH_MAPPED_OUTPUT_COLLECTION,
WORKFLOW_WITH_OUTPUT_COLLECTION,
WORKFLOW_WITH_OUTPUT_COLLECTION_MAPPING,
WORKFLOW_WITH_RULES_1,
)
from ._framework import ApiTestCase
from .sharable import SharingApiTests
WORKFLOW_SIMPLE = """
class: GalaxyWorkflow
name: Simple Workflow
inputs:
input1: data
outputs:
wf_output_1:
outputSource: first_cat/out_file1
steps:
first_cat:
tool_id: cat1
in:
input1: input1
"""
NESTED_WORKFLOW_AUTO_LABELS_MODERN_SYNTAX = """
class: GalaxyWorkflow
inputs:
outer_input: data
outputs:
outer_output:
outputSource: second_cat/out_file1
steps:
first_cat:
tool_id: cat1
in:
input1: outer_input
nested_workflow:
run:
class: GalaxyWorkflow
inputs:
- id: inner_input
outputs:
- outputSource: 1/out_file1
steps:
random:
tool_id: random_lines1
state:
num_lines: 1
input:
$link: inner_input
seed_source:
seed_source_selector: set_seed
seed: asdf
in:
inner_input: first_cat/out_file1
second_cat:
tool_id: cat1
in:
input1: nested_workflow/1:out_file1
queries_0|input2: nested_workflow/1:out_file1
"""
[docs]class RunsWorkflowFixtures:
workflow_populator: WorkflowPopulator
def _run_workflow_with_inputs_as_outputs(self, history_id: str) -> RunJobsSummary:
summary = self.workflow_populator.run_workflow(
WORKFLOW_INPUTS_AS_OUTPUTS,
test_data={"input1": "hello world", "text_input": {"value": "A text variable", "type": "raw"}},
history_id=history_id,
)
return summary
def _run_workflow_with_output_collections(self, history_id: str) -> RunJobsSummary:
summary = self.workflow_populator.run_workflow(
WORKFLOW_WITH_MAPPED_OUTPUT_COLLECTION,
test_data="""
input1:
collection_type: list
name: the_dataset_list
elements:
- identifier: el1
value: 1.fastq
type: File
""",
history_id=history_id,
round_trip_format_conversion=True,
)
return summary
def _run_workflow_with_runtime_data_column_parameter(self, history_id: str) -> RunJobsSummary:
return self.workflow_populator.run_workflow(
WORKFLOW_WITH_BAD_COLUMN_PARAMETER,
test_data=WORKFLOW_WITH_BAD_COLUMN_PARAMETER_GOOD_TEST_DATA,
history_id=history_id,
)
def _run_workflow_once_get_invocation(self, name: str):
workflow = self.workflow_populator.load_workflow(name=name)
workflow_request, history_id, workflow_id = self.workflow_populator.setup_workflow_run(workflow)
usages = self.workflow_populator.workflow_invocations(workflow_id)
assert len(usages) == 0
self.workflow_populator.invoke_workflow_raw(workflow_id, workflow_request, assert_ok=True)
usages = self.workflow_populator.workflow_invocations(workflow_id)
assert len(usages) == 1
return workflow_id, usages[0]
[docs]class BaseWorkflowsApiTestCase(ApiTestCase, RunsWorkflowFixtures):
# TODO: Find a new file for this class.
[docs] def setUp(self):
super().setUp()
self.workflow_populator = WorkflowPopulator(self.galaxy_interactor)
self.dataset_populator = DatasetPopulator(self.galaxy_interactor)
self.dataset_collection_populator = DatasetCollectionPopulator(self.galaxy_interactor)
def _assert_user_has_workflow_with_name(self, name):
names = self._workflow_names()
assert name in names, f"No workflows with name {name} in users workflows <{names}>"
def _workflow_names(self):
index_response = self._get("workflows")
self._assert_status_code_is(index_response, 200)
names = [w["name"] for w in index_response.json()]
return names
[docs] def import_workflow(self, workflow, **kwds):
upload_response = self.workflow_populator.import_workflow(workflow, **kwds)
return upload_response
def _upload_yaml_workflow(self, has_yaml, **kwds) -> str:
return self.workflow_populator.upload_yaml_workflow(has_yaml, **kwds)
def _setup_workflow_run(
self,
workflow: Optional[Dict[str, Any]] = None,
inputs_by: str = "step_id",
history_id: Optional[str] = None,
workflow_id: Optional[str] = None,
) -> Tuple[Dict[str, Any], str, str]:
return self.workflow_populator.setup_workflow_run(workflow, inputs_by, history_id, workflow_id)
def _ds_entry(self, history_content):
return self.dataset_populator.ds_entry(history_content)
def _invocation_details(self, workflow_id, invocation_id, **kwds):
invocation_details_response = self._get(f"workflows/{workflow_id}/usage/{invocation_id}", data=kwds)
self._assert_status_code_is(invocation_details_response, 200)
invocation_details = invocation_details_response.json()
return invocation_details
def _run_jobs(self, has_workflow, history_id=None, **kwds) -> Union[Dict[str, Any], RunJobsSummary]:
if history_id is None:
history_id = self.history_id
return self.workflow_populator.run_workflow(has_workflow, history_id=history_id, **kwds)
def _run_workflow(self, has_workflow, history_id=None, **kwds) -> RunJobsSummary:
if history_id is None:
history_id = self.history_id
assert "expected_response" not in kwds
run_summary = self.workflow_populator.run_workflow(has_workflow, history_id=history_id, **kwds)
return cast(RunJobsSummary, run_summary)
def _history_jobs(self, history_id):
return self._get("jobs", {"history_id": history_id, "order_by": "create_time"}).json()
def _assert_history_job_count(self, history_id, n):
jobs = self._history_jobs(history_id)
self.assertEqual(len(jobs), n)
def _download_workflow(self, workflow_id, style=None, history_id=None):
return self.workflow_populator.download_workflow(workflow_id, style=style, history_id=history_id)
def _assert_is_runtime_input(self, tool_state_value):
if not isinstance(tool_state_value, dict):
tool_state_value = json.loads(tool_state_value)
assert isinstance(tool_state_value, dict)
assert "__class__" in tool_state_value
assert tool_state_value["__class__"] == "RuntimeValue"
[docs]class ChangeDatatypeTestCase:
dataset_populator: DatasetPopulator
workflow_populator: WorkflowPopulator
[docs] def test_assign_column_pja(self):
with self.dataset_populator.test_history() as history_id:
self.workflow_populator.run_workflow(
"""
class: GalaxyWorkflow
inputs:
input1: data
steps:
first_cat:
tool_id: cat
in:
input1: input1
outputs:
out_file1:
change_datatype: bed
set_columns:
chromCol: 1
endCol: 2
startCol: 3
""",
test_data="""
input1:
value: 1.bed
type: File
""",
history_id=history_id,
)
details_dataset_new_col = self.dataset_populator.get_history_dataset_details(
history_id, hid=2, wait=True, assert_ok=True
)
assert details_dataset_new_col["history_content_type"] == "dataset", details_dataset_new_col
assert details_dataset_new_col["metadata_endCol"] == 2
assert details_dataset_new_col["metadata_startCol"] == 3
[docs]class WorkflowsSharingApiTestCase(ApiTestCase, SharingApiTests):
api_name = "workflows"
[docs] def create(self, name: str) -> str:
"""Creates a shareable resource with the given name and returns it's ID.
:param name: The name of the shareable resource to create.
:return: The ID of the resource.
"""
workflow = self.workflow_populator.load_workflow(name=name)
data = dict(
workflow=dumps(workflow),
)
route = "workflows"
upload_response = self._post(route, data=data)
self._assert_status_code_is(upload_response, 200)
return upload_response.json()["id"]
[docs] def setUp(self):
super().setUp()
self.workflow_populator = WorkflowPopulator(self.galaxy_interactor)
# Workflow API TODO:
# - Allow history_id as param to workflow run action. (hist_id)
# - Allow post to workflows/<workflow_id>/run in addition to posting to
# /workflows with id in payload.
# - Much more testing obviously, always more testing.
[docs]class WorkflowsApiTestCase(BaseWorkflowsApiTestCase, ChangeDatatypeTestCase):
[docs] def test_show_valid(self):
workflow_id = self.workflow_populator.simple_workflow("dummy")
workflow_id = self.workflow_populator.simple_workflow("test_regular")
show_response = self._get(f"workflows/{workflow_id}", {"style": "instance"})
workflow = show_response.json()
self._assert_looks_like_instance_workflow_representation(workflow)
assert len(workflow["steps"]) == 3
self.assertEqual(sorted(step["id"] for step in workflow["steps"].values()), [0, 1, 2])
show_response = self._get(f"workflows/{workflow_id}", {"legacy": True})
workflow = show_response.json()
self._assert_looks_like_instance_workflow_representation(workflow)
assert len(workflow["steps"]) == 3
# Can't reay say what the legacy IDs are but must be greater than 3 because dummy
# workflow was created first in this instance.
self.assertNotEqual(sorted(step["id"] for step in workflow["steps"].values()), [0, 1, 2])
[docs] def test_show_invalid_key_is_400(self):
show_response = self._get(f"workflows/{self._random_key()}")
self._assert_status_code_is(show_response, 400)
[docs] def test_cannot_show_private_workflow(self):
workflow_id = self.workflow_populator.simple_workflow("test_not_importable")
with self._different_user():
show_response = self._get(f"workflows/{workflow_id}")
self._assert_status_code_is(show_response, 403)
# Try as anonymous user
workflows_url = self._api_url(f"workflows/{workflow_id}")
assert get(workflows_url).status_code == 403
[docs] def test_cannot_download_private_workflow(self):
workflow_id = self.workflow_populator.simple_workflow("test_not_downloadable")
with self._different_user():
with pytest.raises(AssertionError) as excinfo:
self._download_workflow(workflow_id)
assert "403" in str(excinfo.value)
workflows_url = self._api_url(f"workflows/{workflow_id}/download")
assert get(workflows_url).status_code == 403
[docs] def test_anon_can_download_importable_workflow(self):
workflow_id = self.workflow_populator.simple_workflow("test_downloadable", importable=True)
workflows_url = self._api_url(f"workflows/{workflow_id}/download")
response = get(workflows_url)
response.raise_for_status()
assert response.json()["a_galaxy_workflow"] == "true"
[docs] def test_anon_can_download_public_workflow(self):
workflow_id = self.workflow_populator.simple_workflow("test_downloadable", publish=True)
workflows_url = self._api_url(f"workflows/{workflow_id}/download")
response = get(workflows_url)
response.raise_for_status()
assert response.json()["a_galaxy_workflow"] == "true"
[docs] def test_delete(self):
workflow_id = self.workflow_populator.simple_workflow("test_delete")
workflow_name = "test_delete"
self._assert_user_has_workflow_with_name(workflow_name)
workflow_url = self._api_url(f"workflows/{workflow_id}", use_key=True)
delete_response = delete(workflow_url)
self._assert_status_code_is(delete_response, 200)
# Make sure workflow is no longer in index by default.
assert workflow_name not in self._workflow_names()
[docs] def test_other_cannot_delete(self):
workflow_id = self.workflow_populator.simple_workflow("test_other_delete")
with self._different_user():
workflow_url = self._api_url(f"workflows/{workflow_id}", use_key=True)
delete_response = delete(workflow_url)
self._assert_status_code_is(delete_response, 403)
[docs] def test_index(self):
index_response = self._get("workflows")
self._assert_status_code_is(index_response, 200)
assert isinstance(index_response.json(), list)
[docs] def test_index_deleted(self):
workflow_id = self.workflow_populator.simple_workflow("test_delete")
workflow_index = self._get("workflows").json()
assert [w for w in workflow_index if w["id"] == workflow_id]
workflow_url = self._api_url(f"workflows/{workflow_id}", use_key=True)
delete_response = delete(workflow_url)
self._assert_status_code_is(delete_response, 200)
workflow_index = self._get("workflows").json()
assert not [w for w in workflow_index if w["id"] == workflow_id]
workflow_index = self._get("workflows?show_deleted=true").json()
assert [w for w in workflow_index if w["id"] == workflow_id]
workflow_index = self._get("workflows?show_deleted=false").json()
assert not [w for w in workflow_index if w["id"] == workflow_id]
[docs] def test_index_ordering(self):
# ordered by update_time on the stored workflows with all user's workflows
# before workflows shared with user.
my_workflow_id_1 = self.workflow_populator.simple_workflow("mine_1")
my_workflow_id_2 = self.workflow_populator.simple_workflow("mine_2")
my_email = self.dataset_populator.user_email()
with self._different_user():
their_workflow_id_1 = self.workflow_populator.simple_workflow("theirs_1")
their_workflow_id_2 = self.workflow_populator.simple_workflow("theirs_2")
self.workflow_populator.share_with_user(their_workflow_id_1, my_email)
self.workflow_populator.share_with_user(their_workflow_id_2, my_email)
index_ids = self.workflow_populator.index_ids()
assert index_ids.index(my_workflow_id_1) >= 0
assert index_ids.index(my_workflow_id_2) >= 0
assert index_ids.index(their_workflow_id_1) >= 0
assert index_ids.index(their_workflow_id_2) >= 0
# ordered by update time...
assert index_ids.index(my_workflow_id_2) < index_ids.index(my_workflow_id_1)
assert index_ids.index(their_workflow_id_2) < index_ids.index(their_workflow_id_1)
# my workflows before theirs...
assert index_ids.index(my_workflow_id_1) < index_ids.index(their_workflow_id_1)
assert index_ids.index(my_workflow_id_2) < index_ids.index(their_workflow_id_1)
assert index_ids.index(my_workflow_id_1) < index_ids.index(their_workflow_id_2)
assert index_ids.index(my_workflow_id_2) < index_ids.index(their_workflow_id_2)
actions = [
{"action_type": "update_name", "name": "mine_1(updated)"},
]
refactor_response = self.workflow_populator.refactor_workflow(my_workflow_id_1, actions)
refactor_response.raise_for_status()
index_ids = self.workflow_populator.index_ids()
# after an update to workflow 1, it now comes before workflow 2
assert index_ids.index(my_workflow_id_1) < index_ids.index(my_workflow_id_2)
[docs] def test_index_sort_by(self):
my_workflow_id_y = self.workflow_populator.simple_workflow("y_1")
my_workflow_id_z = self.workflow_populator.simple_workflow("z_2")
index_ids = self.workflow_populator.index_ids()
assert index_ids.index(my_workflow_id_z) < index_ids.index(my_workflow_id_y)
index_ids = self.workflow_populator.index_ids(sort_by="create_time", sort_desc=True)
assert index_ids.index(my_workflow_id_z) < index_ids.index(my_workflow_id_y)
index_ids = self.workflow_populator.index_ids(sort_by="create_time", sort_desc=False)
assert index_ids.index(my_workflow_id_y) < index_ids.index(my_workflow_id_z)
index_ids = self.workflow_populator.index_ids(sort_by="name")
assert index_ids.index(my_workflow_id_y) < index_ids.index(my_workflow_id_z)
index_ids = self.workflow_populator.index_ids(sort_by="name", sort_desc=False)
assert index_ids.index(my_workflow_id_y) < index_ids.index(my_workflow_id_z)
index_ids = self.workflow_populator.index_ids(sort_by="name", sort_desc=True)
assert index_ids.index(my_workflow_id_z) < index_ids.index(my_workflow_id_y)
[docs] def test_index_limit_and_offset(self):
self.workflow_populator.simple_workflow("y_1")
self.workflow_populator.simple_workflow("z_2")
index_ids = self.workflow_populator.index_ids(limit=1)
assert len(index_ids) == 1
index_ids_offset = self.workflow_populator.index_ids(limit=1, offset=1)
assert len(index_ids_offset) == 1
assert index_ids[0] != index_ids_offset[0]
[docs] def test_index_skip_step_counts(self):
self.workflow_populator.simple_workflow("mine_1")
index = self.workflow_populator.index()
index_0 = index[0]
assert "number_of_steps" in index_0
assert index_0["number_of_steps"]
index = self.workflow_populator.index(skip_step_counts=True)
index_0 = index[0]
assert "number_of_steps" not in index_0
[docs] def test_index_search(self):
name1, name2 = self.dataset_populator.get_random_name(), self.dataset_populator.get_random_name()
workflow_id_1 = self.workflow_populator.simple_workflow(name1)
self.workflow_populator.simple_workflow(name2)
index_ids = self.workflow_populator.index_ids(search=name1)
assert len(index_ids) == 1
assert workflow_id_1 in index_ids
[docs] def test_index_search_name(self):
name1, name2 = self.dataset_populator.get_random_name(), self.dataset_populator.get_random_name()
workflow_id_1 = self.workflow_populator.simple_workflow(name1)
self.workflow_populator.simple_workflow(name2)
self.workflow_populator.set_tags(workflow_id_1, [name2])
index_ids = self.workflow_populator.index_ids(search=name2)
# one found by tag and one found by name...
assert len(index_ids) == 2
assert workflow_id_1 in index_ids
index_ids = self.workflow_populator.index_ids(search=f"name:{name2}")
assert len(index_ids) == 1
assert workflow_id_1 not in index_ids
[docs] def test_index_search_name_exact_vs_inexact(self):
name_prefix = self.dataset_populator.get_random_name()
workflow_id_1 = self.workflow_populator.simple_workflow(name_prefix)
longer_name = f"{name_prefix}_some_stuff_on_it"
workflow_id_2 = self.workflow_populator.simple_workflow(longer_name)
index_ids = self.workflow_populator.index_ids(search=f"name:{name_prefix}")
assert len(index_ids) == 2
assert workflow_id_1 in index_ids
assert workflow_id_2 in index_ids
# quoting it will ensure the name matches exactly.
index_ids = self.workflow_populator.index_ids(search=f"name:'{name_prefix}'")
assert len(index_ids) == 1
assert workflow_id_1 in index_ids
assert workflow_id_2 not in index_ids
[docs] def test_index_search_tags(self):
name1, name2 = self.dataset_populator.get_random_name(), self.dataset_populator.get_random_name()
workflow_id_1 = self.workflow_populator.simple_workflow(name1)
self.workflow_populator.simple_workflow(name2)
index_ids = self.workflow_populator.index_ids(search="moocowatag")
assert len(index_ids) == 0
self.workflow_populator.set_tags(workflow_id_1, ["moocowatag", "moocowanothertag"])
index_ids = self.workflow_populator.index_ids(search="moocowatag")
assert workflow_id_1 in index_ids
index_ids = self.workflow_populator.index_ids(search="tag:moocowatag")
assert workflow_id_1 in index_ids
[docs] def test_index_search_tags_multiple(self):
name1 = self.dataset_populator.get_random_name()
name2 = self.dataset_populator.get_random_name()
name3 = self.dataset_populator.get_random_name()
workflow_id_1 = self.workflow_populator.simple_workflow(name1)
workflow_id_2 = self.workflow_populator.simple_workflow(name2)
workflow_id_3 = self.workflow_populator.simple_workflow(name3)
self.workflow_populator.set_tags(workflow_id_1, ["multipletagfilter1", "multipletagfilter2", "decoy1"])
self.workflow_populator.set_tags(workflow_id_2, ["multipletagfilter1", "decoy2"])
self.workflow_populator.set_tags(workflow_id_3, ["multipletagfilter2", "decoy3"])
for search in ["multipletagfilter1", "tag:ipletagfilter1", "tag:'multipletagfilter1'"]:
index_ids = self.workflow_populator.index_ids(search=search)
assert workflow_id_1 in index_ids
assert workflow_id_2 in index_ids
assert workflow_id_3 not in index_ids
for search in ["multipletagfilter2", "tag:ipletagfilter2", "tag:'multipletagfilter2'"]:
index_ids = self.workflow_populator.index_ids(search=search)
assert workflow_id_1 in index_ids
assert workflow_id_2 not in index_ids
assert workflow_id_3 in index_ids
for search in [
"multipletagfilter2 multipletagfilter1",
"tag:filter2 tag:tagfilter1",
"tag:'multipletagfilter2' tag:'multipletagfilter1'",
]:
index_ids = self.workflow_populator.index_ids(search=search)
assert workflow_id_1 in index_ids
assert workflow_id_2 not in index_ids
assert workflow_id_3 not in index_ids
[docs] def test_search_casing(self):
name1, name2 = (
self.dataset_populator.get_random_name().upper(),
self.dataset_populator.get_random_name().upper(),
)
workflow_id_1 = self.workflow_populator.simple_workflow(name1)
self.workflow_populator.simple_workflow(name2)
self.workflow_populator.set_tags(workflow_id_1, ["searchcasingtag", "searchcasinganothertag"])
index_ids = self.workflow_populator.index_ids(search=name1.lower())
assert len(index_ids) == 1
assert workflow_id_1 in index_ids
index_ids = self.workflow_populator.index_ids(search="SEARCHCASINGTAG")
assert len(index_ids) == 1
assert workflow_id_1 in index_ids
[docs] def test_index_search_tags_exact(self):
name1, name2 = self.dataset_populator.get_random_name(), self.dataset_populator.get_random_name()
workflow_id_1 = self.workflow_populator.simple_workflow(name1)
workflow_id_2 = self.workflow_populator.simple_workflow(name2)
index_ids = self.workflow_populator.index_ids(search="exacttagtosearch")
assert len(index_ids) == 0
self.workflow_populator.set_tags(workflow_id_1, ["exacttagtosearch"])
self.workflow_populator.set_tags(workflow_id_2, ["exacttagtosearchlonger"])
index_ids = self.workflow_populator.index_ids(search="exacttagtosearch")
assert workflow_id_1 in index_ids
assert workflow_id_2 in index_ids
index_ids = self.workflow_populator.index_ids(search="tag:exacttagtosearch")
assert workflow_id_1 in index_ids
assert workflow_id_2 in index_ids
index_ids = self.workflow_populator.index_ids(search="tag:'exacttagtosearch'")
assert workflow_id_1 in index_ids
assert workflow_id_2 not in index_ids
[docs] def test_index_published(self):
# published workflows are also the default of what is displayed for anonymous API requests
# this is tested in test_anonymous_published.
uuid = str(uuid4())
workflow_name = f"test_pubished_anon_{uuid}"
with self._different_user():
workflow_id = self.workflow_populator.simple_workflow(workflow_name, publish=True)
assert workflow_id not in self.workflow_populator.index_ids()
assert workflow_id in self.workflow_populator.index_ids(show_published=True)
assert workflow_id not in self.workflow_populator.index_ids(show_published=False)
[docs] def test_index_search_is_tags(self):
my_workflow_id_1 = self.workflow_populator.simple_workflow("sitags_m_1")
my_email = self.dataset_populator.user_email()
with self._different_user():
their_workflow_id_1 = self.workflow_populator.simple_workflow("sitags_shwm_1")
self.workflow_populator.share_with_user(their_workflow_id_1, my_email)
published_workflow_id_1 = self.workflow_populator.simple_workflow("sitags_p_1", publish=True)
index_ids = self.workflow_populator.index_ids(search="is:published", show_published=True)
assert published_workflow_id_1 in index_ids
assert their_workflow_id_1 not in index_ids
assert my_workflow_id_1 not in index_ids
index_ids = self.workflow_populator.index_ids(search="is:shared_with_me")
assert published_workflow_id_1 not in index_ids
assert their_workflow_id_1 in index_ids
assert my_workflow_id_1 not in index_ids
[docs] def test_index_owner(self):
my_workflow_id_1 = self.workflow_populator.simple_workflow("ownertags_m_1")
email_1 = f"{uuid4()}@test.com"
with self._different_user(email=email_1):
published_workflow_id_1 = self.workflow_populator.simple_workflow("ownertags_p_1", publish=True)
owner_1 = self._show_workflow(published_workflow_id_1)["owner"]
email_2 = f"{uuid4()}@test.com"
with self._different_user(email=email_2):
published_workflow_id_2 = self.workflow_populator.simple_workflow("ownertags_p_2", publish=True)
index_ids = self.workflow_populator.index_ids(search="is:published", show_published=True)
assert published_workflow_id_1 in index_ids
assert published_workflow_id_2 in index_ids
assert my_workflow_id_1 not in index_ids
index_ids = self.workflow_populator.index_ids(search=f"is:published u:{owner_1}", show_published=True)
assert published_workflow_id_1 in index_ids
assert published_workflow_id_2 not in index_ids
assert my_workflow_id_1 not in index_ids
index_ids = self.workflow_populator.index_ids(search=f"is:published u:'{owner_1}'", show_published=True)
assert published_workflow_id_1 in index_ids
assert published_workflow_id_2 not in index_ids
assert my_workflow_id_1 not in index_ids
index_ids = self.workflow_populator.index_ids(search=f"is:published {owner_1}", show_published=True)
assert published_workflow_id_1 in index_ids
assert published_workflow_id_2 not in index_ids
assert my_workflow_id_1 not in index_ids
[docs] def test_index_parameter_invalid_combinations(self):
# these can all be called by themselves and return 200...
response = self._get("workflows?show_hidden=true")
self._assert_status_code_is(response, 200)
response = self._get("workflows?show_deleted=true")
self._assert_status_code_is(response, 200)
response = self._get("workflows?show_shared=true")
self._assert_status_code_is(response, 200)
# but showing shared workflows along with deleted or hidden results in an error
response = self._get("workflows?show_hidden=true&show_shared=true")
self._assert_status_code_is(response, 400)
self._assert_error_code_is(response, error_codes.error_codes_by_name["USER_REQUEST_INVALID_PARAMETER"])
response = self._get("workflows?show_deleted=true&show_shared=true")
self._assert_status_code_is(response, 400)
self._assert_error_code_is(response, error_codes.error_codes_by_name["USER_REQUEST_INVALID_PARAMETER"])
[docs] def test_import_tools_requires_admin(self):
response = self.__test_upload(import_tools=True, assert_ok=False)
assert response.status_code == 403
def __test_upload(
self, use_deprecated_route=False, name="test_import", workflow=None, assert_ok=True, import_tools=False
):
if workflow is None:
workflow = self.workflow_populator.load_workflow(name=name)
data = dict(
workflow=dumps(workflow),
)
if import_tools:
data["import_tools"] = import_tools
if use_deprecated_route:
route = "workflows/upload"
else:
route = "workflows"
upload_response = self._post(route, data=data)
if assert_ok:
self._assert_status_code_is(upload_response, 200)
self._assert_user_has_workflow_with_name(name)
return upload_response
[docs] def test_get_tool_predictions(self):
request = {
"tool_sequence": "Cut1",
"remote_model_url": "https://github.com/galaxyproject/galaxy-test-data/raw/master/tool_recommendation_model.hdf5",
}
actual_recommendations = ["Filter1", "cat1", "addValue", "comp1", "Grep1"]
route = "workflows/get_tool_predictions"
response = self._post(route, data=request)
recommendation_response = response.json()
is_empty = bool(recommendation_response["current_tool"])
if is_empty is False:
self._assert_status_code_is(response, 400)
else:
# check Ok response from the API
self._assert_status_code_is(response, 200)
recommendation_response = response.json()
# check the input tool sequence
assert recommendation_response["current_tool"] == request["tool_sequence"]
# check non-empty predictions list
predicted_tools = recommendation_response["predicted_data"]["children"]
assert len(predicted_tools) > 0
# check for the correct predictions
for tool in predicted_tools:
assert tool["tool_id"] in actual_recommendations
break
[docs] def test_update(self):
original_workflow = self.workflow_populator.load_workflow(name="test_import")
uuids = {}
labels = {}
for order_index, step_dict in original_workflow["steps"].items():
uuid = str(uuid4())
step_dict["uuid"] = uuid
uuids[order_index] = uuid
label = f"label_{order_index}"
step_dict["label"] = label
labels[order_index] = label
def check_label_and_uuid(order_index, step_dict):
assert order_index in uuids
assert order_index in labels
self.assertEqual(uuids[order_index], step_dict["uuid"])
self.assertEqual(labels[order_index], step_dict["label"])
upload_response = self.__test_upload(workflow=original_workflow)
workflow_id = upload_response.json()["id"]
def update(workflow_object):
put_response = self._update_workflow(workflow_id, workflow_object)
self._assert_status_code_is(put_response, 200)
return put_response
workflow_content = self._download_workflow(workflow_id)
steps = workflow_content["steps"]
def tweak_step(step):
order_index, step_dict = step
check_label_and_uuid(order_index, step_dict)
assert step_dict["position"]["top"] != 1
assert step_dict["position"]["left"] != 1
step_dict["position"] = {"top": 1, "left": 1}
map(tweak_step, steps.items())
update(workflow_content)
def check_step(step):
order_index, step_dict = step
check_label_and_uuid(order_index, step_dict)
assert step_dict["position"]["top"] == 1
assert step_dict["position"]["left"] == 1
updated_workflow_content = self._download_workflow(workflow_id)
map(check_step, updated_workflow_content["steps"].items())
# Re-update against original workflow...
update(original_workflow)
updated_workflow_content = self._download_workflow(workflow_id)
# Make sure the positions have been updated.
map(tweak_step, updated_workflow_content["steps"].items())
[docs] def test_update_tags(self):
workflow_object = self.workflow_populator.load_workflow(name="test_import")
workflow_id = self.__test_upload(workflow=workflow_object).json()["id"]
update_payload = {}
update_payload["tags"] = ["a_tag", "b_tag"]
update_response = self._update_workflow(workflow_id, update_payload).json()
assert update_response["tags"] == ["a_tag", "b_tag"]
del update_payload["tags"]
update_response = self._update_workflow(workflow_id, update_payload).json()
assert update_response["tags"] == ["a_tag", "b_tag"]
update_payload["tags"] = []
update_response = self._update_workflow(workflow_id, update_payload).json()
assert update_response["tags"] == []
[docs] def test_update_name(self):
original_name = "test update name"
workflow_object = self.workflow_populator.load_workflow(name=original_name)
workflow_object["license"] = "AAL"
upload_response = self.__test_upload(workflow=workflow_object, name=original_name)
workflow = upload_response.json()
workflow_id = workflow["id"]
assert workflow["name"] == original_name
workflow_dict = self.workflow_populator.download_workflow(workflow_id)
assert workflow_dict["license"] == "AAL"
data = {"name": "my cool new name"}
update_response = self._update_workflow(workflow["id"], data).json()
assert update_response["name"] == "my cool new name"
workflow_dict = self.workflow_populator.download_workflow(workflow_id)
assert workflow_dict["license"] == "AAL"
[docs] def test_refactor(self):
workflow_id = self.workflow_populator.upload_yaml_workflow(
"""
class: GalaxyWorkflow
inputs:
test_input: data
steps:
first_cat:
tool_id: cat
in:
input1: test_input
"""
)
actions = [
{"action_type": "update_step_label", "step": {"order_index": 0}, "label": "new_label"},
]
# perform refactoring as dry run
refactor_response = self.workflow_populator.refactor_workflow(workflow_id, actions, dry_run=True)
refactor_response.raise_for_status()
assert refactor_response.json()["workflow"]["steps"]["0"]["label"] == "new_label"
# perform refactoring as dry run but specify editor style response
refactor_response = self.workflow_populator.refactor_workflow(
workflow_id, actions, dry_run=True, style="editor"
)
refactor_response.raise_for_status()
assert refactor_response.json()["workflow"]["steps"]["0"]["label"] == "new_label"
# download the original workflow and make sure the dry run didn't modify that label
workflow_dict = self.workflow_populator.download_workflow(workflow_id)
assert workflow_dict["steps"]["0"]["label"] == "test_input"
refactor_response = self.workflow_populator.refactor_workflow(workflow_id, actions)
refactor_response.raise_for_status()
assert refactor_response.json()["workflow"]["steps"]["0"]["label"] == "new_label"
# this time dry_run was default of False, so the label is indeed changed
workflow_dict = self.workflow_populator.download_workflow(workflow_id)
assert workflow_dict["steps"]["0"]["label"] == "new_label"
[docs] def test_update_no_tool_id(self):
workflow_object = self.workflow_populator.load_workflow(name="test_import")
upload_response = self.__test_upload(workflow=workflow_object)
workflow_id = upload_response.json()["id"]
del workflow_object["steps"]["2"]["tool_id"]
put_response = self._update_workflow(workflow_id, workflow_object)
self._assert_status_code_is(put_response, 400)
[docs] def test_update_missing_tool(self):
# Create allows missing tools, update doesn't currently...
workflow_object = self.workflow_populator.load_workflow(name="test_import")
upload_response = self.__test_upload(workflow=workflow_object)
workflow_id = upload_response.json()["id"]
workflow_object["steps"]["2"]["tool_id"] = "cat-not-found"
put_response = self._update_workflow(workflow_id, workflow_object)
self._assert_status_code_is(put_response, 400)
[docs] def test_require_unique_step_uuids(self):
workflow_dup_uuids = self.workflow_populator.load_workflow(name="test_import")
uuid0 = str(uuid4())
for step_dict in workflow_dup_uuids["steps"].values():
step_dict["uuid"] = uuid0
response = self.workflow_populator.create_workflow_response(workflow_dup_uuids)
self._assert_status_code_is(response, 400)
[docs] def test_require_unique_step_labels(self):
workflow_dup_label = self.workflow_populator.load_workflow(name="test_import")
for step_dict in workflow_dup_label["steps"].values():
step_dict["label"] = "my duplicated label"
response = self.workflow_populator.create_workflow_response(workflow_dup_label)
self._assert_status_code_is(response, 400)
[docs] def test_import_deprecated(self):
workflow_id = self.workflow_populator.simple_workflow("test_import_published_deprecated", publish=True)
with self._different_user():
other_import_response = self.__import_workflow(workflow_id)
self._assert_status_code_is(other_import_response, 200)
self._assert_user_has_workflow_with_name("imported: test_import_published_deprecated")
[docs] def test_import_export_dynamic(self):
workflow_id = self._upload_yaml_workflow(
"""
class: GalaxyWorkflow
steps:
- type: input
label: input1
- tool_id: cat1
label: first_cat
state:
input1:
$link: 0
- label: embed1
run:
class: GalaxyTool
command: echo 'hello world 2' > $output1
outputs:
output1:
format: txt
- tool_id: cat1
state:
input1:
$link: first_cat/out_file1
queries:
input2:
$link: embed1/output1
test_data:
input1: "hello world"
"""
)
downloaded_workflow = self._download_workflow(workflow_id)
# The _upload_yaml_workflow entry point uses an admin key, but if we try to
# do the raw re-import as a regular user we expect a 403 error.
response = self.workflow_populator.create_workflow_response(downloaded_workflow)
self._assert_status_code_is(response, 403)
[docs] def test_import_annotations(self):
workflow_id = self.workflow_populator.simple_workflow("test_import_annotations", publish=True)
with self._different_user():
other_import_response = self.__import_workflow(workflow_id)
self._assert_status_code_is(other_import_response, 200)
# Test annotations preserved during upload and copied over during
# import.
other_id = other_import_response.json()["id"]
imported_workflow = self._show_workflow(other_id)
assert imported_workflow["annotation"] == "simple workflow"
step_annotations = {step["annotation"] for step in imported_workflow["steps"].values()}
assert "input1 description" in step_annotations
[docs] def test_import_subworkflows(self):
def get_subworkflow_content_id(workflow_id):
workflow_contents = self._download_workflow(workflow_id, style="editor")
steps = workflow_contents["steps"]
subworkflow_step = next(s for s in steps.values() if s["type"] == "subworkflow")
return subworkflow_step["content_id"]
workflow_id = self._upload_yaml_workflow(WORKFLOW_NESTED_SIMPLE, publish=True)
subworkflow_content_id = get_subworkflow_content_id(workflow_id)
instance_response = self._get(f"workflows/{subworkflow_content_id}?instance=true")
self._assert_status_code_is(instance_response, 200)
subworkflow = instance_response.json()
assert subworkflow["inputs"]["0"]["label"] == "inner_input"
assert subworkflow["name"] == "Workflow"
assert subworkflow["hidden"]
with self._different_user():
other_import_response = self.__import_workflow(workflow_id)
self._assert_status_code_is(other_import_response, 200)
imported_workflow_id = other_import_response.json()["id"]
imported_subworkflow_content_id = get_subworkflow_content_id(imported_workflow_id)
assert subworkflow_content_id != imported_subworkflow_content_id
[docs] def test_subworkflow_inputs_optional_editor(self):
workflow_id = self._upload_yaml_workflow(
"""
class: GalaxyWorkflow
steps:
nested_workflow:
run:
class: GalaxyWorkflow
inputs:
- id: inner_input
optional: true
outputs:
- outputSource: inner_input/output
steps: []
"""
)
workflow_contents = self._download_workflow(workflow_id, style="editor")
assert workflow_contents["steps"]["0"]["inputs"][0]["optional"]
[docs] def test_not_importable_prevents_import(self):
workflow_id = self.workflow_populator.simple_workflow("test_not_importportable")
with self._different_user():
other_import_response = self.__import_workflow(workflow_id)
self._assert_status_code_is(other_import_response, 403)
[docs] def test_url_import(self):
url = "https://raw.githubusercontent.com/galaxyproject/galaxy/release_19.09/test/base/data/test_workflow_1.ga"
workflow_id = self._post("workflows", data={"archive_source": url}).json()["id"]
workflow = self._download_workflow(workflow_id)
assert "TestWorkflow1" in workflow["name"]
assert (
workflow.get("source_metadata").get("url") == url
) # disappearance of source_metadata on modification is tested in test_trs_import
[docs] def test_base64_import(self):
base64_url = "base64://" + base64.b64encode(workflow_str.encode("utf-8")).decode("utf-8")
response = self._post("workflows", data={"archive_source": base64_url})
print(response.content)
response.raise_for_status()
workflow_id = response.json()["id"]
workflow = self._download_workflow(workflow_id)
assert "TestWorkflow1" in workflow["name"]
[docs] def test_trs_import(self):
trs_payload = {
"archive_source": "trs_tool",
"trs_server": "dockstore",
"trs_tool_id": "#workflow/github.com/jmchilton/galaxy-workflow-dockstore-example-1/mycoolworkflow",
"trs_version_id": "master",
}
workflow_id = self._post("workflows", data=trs_payload).json()["id"]
original_workflow = self._download_workflow(workflow_id)
assert "Test Workflow" in original_workflow["name"]
assert original_workflow.get("source_metadata").get("trs_tool_id") == trs_payload["trs_tool_id"]
assert original_workflow.get("source_metadata").get("trs_version_id") == trs_payload["trs_version_id"]
# refactor workflow and check that the trs id is removed
actions = [
{"action_type": "update_step_label", "step": {"order_index": 0}, "label": "new_label"},
]
self.workflow_populator.refactor_workflow(workflow_id, actions)
refactored_workflow = self._download_workflow(workflow_id)
assert refactored_workflow.get("source_metadata") is None
# reupload original_workflow and check that the trs id is removed
reuploaded_workflow_id = self.workflow_populator.create_workflow(original_workflow)
reuploaded_workflow = self._download_workflow(reuploaded_workflow_id)
assert reuploaded_workflow.get("source_metadata") is None
[docs] def test_anonymous_published(self):
def anonymous_published_workflows(explicit_query_parameter):
if explicit_query_parameter:
index_url = "workflows?show_published=True"
else:
index_url = "workflows"
workflows_url = self._api_url(index_url)
response = get(workflows_url)
response.raise_for_status()
return response.json()
names = [w["name"] for w in anonymous_published_workflows(True)]
assert "test published example" not in names
workflow_id = self.workflow_populator.simple_workflow("test published example", publish=True)
for explicit_query_parameter in [True, False]:
workflow_index = anonymous_published_workflows(explicit_query_parameter)
names = [w["name"] for w in workflow_index]
assert "test published example" in names
ids = [w["id"] for w in workflow_index]
assert workflow_id in ids
[docs] def test_import_published(self):
workflow_id = self.workflow_populator.simple_workflow("test_import_published", publish=True)
with self._different_user():
other_import_response = self.__import_workflow(workflow_id, deprecated_route=True)
self._assert_status_code_is(other_import_response, 200)
self._assert_user_has_workflow_with_name("imported: test_import_published")
[docs] def test_export(self):
uploaded_workflow_id = self.workflow_populator.simple_workflow("test_for_export")
downloaded_workflow = self._download_workflow(uploaded_workflow_id)
assert downloaded_workflow["name"] == "test_for_export"
steps = downloaded_workflow["steps"]
assert len(steps) == 3
assert "0" in steps
first_step = steps["0"]
self._assert_has_keys(first_step, "inputs", "outputs")
inputs = first_step["inputs"]
assert len(inputs) > 0, first_step
first_input = inputs[0]
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")
[docs] def test_export_format2(self):
uploaded_workflow_id = self.workflow_populator.simple_workflow("test_for_export_format2")
downloaded_workflow = self._download_workflow(uploaded_workflow_id, style="format2")
assert downloaded_workflow["class"] == "GalaxyWorkflow"
[docs] 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",
"inputs",
"outputs",
"config_form",
"annotation",
"post_job_actions",
"workflow_outputs",
"uuid",
"label",
)
[docs] @skip_without_tool("output_filter_with_input")
def test_export_editor_filtered_outputs(self):
template = """
class: GalaxyWorkflow
steps:
- tool_id: output_filter_with_input
state:
produce_out_1: {produce_out_1}
filter_text_1: {filter_text_1}
produce_collection: false
produce_paired_collection: false
"""
workflow_id = self._upload_yaml_workflow(template.format(produce_out_1="false", filter_text_1="false"))
downloaded_workflow = self._download_workflow(workflow_id, style="editor")
outputs = downloaded_workflow["steps"]["0"]["outputs"]
assert len(outputs) == 1
assert outputs[0]["name"] == "out_3"
workflow_id = self._upload_yaml_workflow(template.format(produce_out_1="true", filter_text_1="false"))
downloaded_workflow = self._download_workflow(workflow_id, style="editor")
outputs = downloaded_workflow["steps"]["0"]["outputs"]
assert len(outputs) == 2
assert outputs[0]["name"] == "out_1"
assert outputs[1]["name"] == "out_3"
workflow_id = self._upload_yaml_workflow(template.format(produce_out_1="true", filter_text_1="foo"))
downloaded_workflow = self._download_workflow(workflow_id, style="editor")
outputs = downloaded_workflow["steps"]["0"]["outputs"]
assert len(outputs) == 3
assert outputs[0]["name"] == "out_1"
assert outputs[1]["name"] == "out_2"
assert outputs[2]["name"] == "out_3"
[docs] @skip_without_tool("output_filter_exception_1")
def test_export_editor_filtered_outputs_exception_handling(self):
workflow_id = self._upload_yaml_workflow(
"""
class: GalaxyWorkflow
steps:
- tool_id: output_filter_exception_1
"""
)
downloaded_workflow = self._download_workflow(workflow_id, style="editor")
outputs = downloaded_workflow["steps"]["0"]["outputs"]
assert len(outputs) == 2
assert outputs[0]["name"] == "out_1"
assert outputs[1]["name"] == "out_2"
[docs] @skip_without_tool("collection_type_source")
def test_export_editor_collection_type_source(self):
workflow_id = self._upload_yaml_workflow(
"""
class: GalaxyWorkflow
inputs:
- id: text_input1
type: collection
collection_type: "list:paired"
steps:
- tool_id: collection_type_source
in:
input_collect: text_input1
"""
)
downloaded_workflow = self._download_workflow(workflow_id, style="editor")
steps = downloaded_workflow["steps"]
assert len(steps) == 2
# Non-subworkflow collection_type_source tools will be handled by the client,
# so collection_type should be None here.
assert steps["1"]["outputs"][0]["collection_type"] is None
[docs] @skip_without_tool("collection_type_source")
def test_export_editor_subworkflow_collection_type_source(self):
workflow_id = self._upload_yaml_workflow(
"""
class: GalaxyWorkflow
inputs:
outer_input: data
steps:
inner_workflow:
run:
class: GalaxyWorkflow
inputs:
inner_input:
type: collection
collection_type: "list:paired"
outputs:
workflow_output:
outputSource: collection_type_source/list_output
steps:
collection_type_source:
tool_id: collection_type_source
in:
input_collect: inner_input
in:
inner_input: outer_input
"""
)
downloaded_workflow = self._download_workflow(workflow_id, style="editor")
steps = downloaded_workflow["steps"]
assert len(steps) == 2
assert steps["1"]["type"] == "subworkflow"
assert steps["1"]["outputs"][0]["collection_type"] == "list:paired"
[docs] 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
[docs] 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)
[docs] 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_step = downloaded_workflow["steps"]["1"]
for runtime_input in runtime_step["inputs"]:
if runtime_input["name"] == "num_lines":
break
assert runtime_input["description"].startswith("runtime parameter for tool")
tool_state = json.loads(runtime_step["tool_state"])
assert "num_lines" in tool_state
self._assert_is_runtime_input(tool_state["num_lines"])
[docs] @skip_without_tool("cat1")
def test_run_workflow_by_index(self):
self.__run_cat_workflow(inputs_by="step_index")
[docs] @skip_without_tool("cat1")
def test_run_workflow_by_uuid(self):
self.__run_cat_workflow(inputs_by="step_uuid")
[docs] @skip_without_tool("cat1")
def test_run_workflow_by_uuid_implicitly(self):
self.__run_cat_workflow(inputs_by="uuid_implicitly")
[docs] @skip_without_tool("cat1")
def test_run_workflow_by_name(self):
self.__run_cat_workflow(inputs_by="name")
[docs] @skip_without_tool("cat1")
def test_run_workflow(self):
self.__run_cat_workflow(inputs_by="step_id")
[docs] @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:
multiple:
tool_id: multiple_versions
tool_version: "0.1"
state:
inttest: 0
"""
)
self.workflow_populator.invoke_workflow_and_wait(workflow_version_01, history_id=history_01_id)
with self.dataset_populator.test_history() as history_02_id:
workflow_version_02 = self._upload_yaml_workflow(
"""
class: GalaxyWorkflow
steps:
multiple:
tool_id: multiple_versions
tool_version: "0.2"
state:
inttest: 1
"""
)
self.workflow_populator.invoke_workflow_and_wait(workflow_version_02, history_id=history_02_id)
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, _, workflow_id = self._setup_workflow_run(workflow, inputs_by=inputs_by)
invocation_id = self.workflow_populator.invoke_workflow_and_wait(workflow_id, request=workflow_request).json()[
"id"
]
invocation = self._invocation_details(workflow_id, invocation_id)
assert invocation["state"] == "scheduled", invocation
[docs] @skip_without_tool("collection_creates_pair")
def test_workflow_run_output_collections(self) -> None:
with self.dataset_populator.test_history() as history_id:
self._run_workflow(WORKFLOW_WITH_OUTPUT_COLLECTION, history_id=history_id)
self.assertEqual("a\nc\nb\nd\n", self.dataset_populator.get_history_dataset_content(history_id, hid=0))
[docs] @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:
job_props:
tool_id: job_properties
state:
thebool: true
failbool: true
identifier:
tool_id: identifier_multiple_in_conditional
state:
outer_cond:
cond_param_outer: true
inner_cond:
cond_param_inner: true
input1:
$link: 0/out_file1
thedata: null
cat:
tool_id: cat1
in:
input1: identifier/output1
queries_0|input2: identifier/output1
"""
)
with self.dataset_populator.test_history() as history_id:
invocation_response = self.workflow_populator.invoke_workflow(workflow_id, history_id=history_id)
invocation_id = invocation_response.json()["id"]
self.workflow_populator.wait_for_workflow(workflow_id, invocation_id, history_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,
)
unpaused_dataset_1 = self.dataset_populator.get_history_dataset_details(
history_id, hid=5, wait=True, assert_ok=False
)
assert unpaused_dataset_1["state"] == "ok"
self.dataset_populator.wait_for_history(history_id, assert_ok=False)
unpaused_dataset_2 = self.dataset_populator.get_history_dataset_details(
history_id, hid=6, wait=True, assert_ok=False
)
assert unpaused_dataset_2["state"] == "ok"
[docs] @skip_without_tool("job_properties")
@skip_without_tool("collection_creates_list")
def test_workflow_resume_from_failed_step_with_hdca_input(self):
workflow_id = self._upload_yaml_workflow(
"""
class: GalaxyWorkflow
steps:
job_props:
tool_id: job_properties
state:
thebool: true
failbool: true
list_in_list_out:
tool_id: collection_creates_list
in:
input1: job_props/list_output
identifier:
tool_id: identifier_collection
in:
input1: list_in_list_out/list_output
"""
)
with self.dataset_populator.test_history() as history_id:
invocation_id = self.__invoke_workflow(workflow_id, history_id=history_id)
self.workflow_populator.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_colletion = self.dataset_populator.get_history_collection_details(
history_id, hid=7, wait=True, assert_ok=False
)
first_paused_element = paused_colletion["elements"][0]["object"]
assert first_paused_element["state"] == "paused", first_paused_element
dependent_dataset = self.dataset_populator.get_history_dataset_details(
history_id, hid=8, wait=True, assert_ok=False
)
assert dependent_dataset["state"] == "paused"
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,
)
paused_colletion = self.dataset_populator.get_history_collection_details(
history_id, hid=7, wait=True, assert_ok=False
)
first_paused_element = paused_colletion["elements"][0]["object"]
assert first_paused_element["state"] == "ok"
self.dataset_populator.wait_for_history(history_id, assert_ok=False)
dependent_dataset = self.dataset_populator.get_history_dataset_details(
history_id, hid=8, wait=True, assert_ok=False
)
assert dependent_dataset["name"].startswith("identifier_collection")
assert dependent_dataset["state"] == "ok"
[docs] @skip_without_tool("fail_identifier")
@skip_without_tool("identifier_collection")
def test_workflow_resume_with_mapped_over_input(self):
with self.dataset_populator.test_history() as history_id:
self._run_workflow(
"""
class: GalaxyWorkflow
inputs:
input_datasets: collection
steps:
fail_identifier_1:
tool_id: fail_identifier
state:
failbool: true
in:
input1: input_datasets
identifier:
tool_id: identifier_collection
in:
input1: fail_identifier_1/out_file1
test_data:
input_datasets:
collection_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=True,
)
history_contents = self.dataset_populator._get_contents_request(history_id=history_id).json()
first_input = history_contents[1]
assert first_input["history_content_type"] == "dataset"
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": first_input["id"]}]},
"failbool": "false",
"rerun_remap_job_id": failed_dataset["creating_job"],
}
run_dict = self.dataset_populator.run_tool(
tool_id="fail_identifier",
inputs=inputs,
history_id=history_id,
)
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
replaced_hda_id = run_dict["outputs"][0]["id"]
replaced_hda = self.dataset_populator.get_history_dataset_details(
history_id, dataset_id=replaced_hda_id, wait=True, assert_ok=False
)
assert not replaced_hda["visible"], replaced_hda
[docs] def test_workflow_resume_with_mapped_over_collection_input(self):
# Test that replacement and resume also works if the failed job re-run works on a input DCE
with self.dataset_populator.test_history() as history_id:
job_summary = self._run_workflow(
"""
class: GalaxyWorkflow
inputs:
input_collection: collection
steps:
- tool_id: collection_creates_list_of_pairs
state:
failbool: true
in:
input1:
source: input_collection
- tool_id: collection_creates_list_of_pairs
state:
failbool: false
in:
input1:
source: 1/list_output
test_data:
input_collection:
collection_type: "list:list:paired"
""",
history_id=history_id,
assert_ok=False,
wait=True,
)
invocation = self.workflow_populator.get_invocation(job_summary.invocation_id, step_details=True)
# TODO: return steps sorted by order_index ? Why don't we do that ??
invocation["steps"].sort(key=lambda step: step["order_index"])
failed_step = invocation["steps"][1]
assert failed_step["jobs"][0]["state"] == "error"
failed_hdca_id = failed_step["output_collections"]["list_output"]["id"]
failed_hdca = self.dataset_populator.get_history_collection_details(
history_id=history_id, content_id=failed_hdca_id, assert_ok=False
)
assert (
failed_hdca["elements"][0]["object"]["elements"][0]["object"]["elements"][0]["object"]["state"]
== "error"
)
paused_step = invocation["steps"][2]
# job not created, input in error state
assert paused_step["jobs"][0]["state"] == "paused"
input_hdca = self.dataset_populator.get_history_collection_details(
history_id=history_id, content_id=job_summary.inputs["input_collection"]["id"], assert_ok=False
)
# now re-run errored job
inputs = {
"input1": {"values": [{"src": "dce", "id": input_hdca["elements"][0]["id"]}]},
"failbool": "false",
"rerun_remap_job_id": failed_step["jobs"][0]["id"],
}
run_response = self.dataset_populator.run_tool(
tool_id="collection_creates_list_of_pairs",
inputs=inputs,
history_id=history_id,
)
assert not run_response["output_collections"][0]["visible"]
self.dataset_populator.wait_for_job(paused_step["jobs"][0]["id"])
invocation = self.workflow_populator.get_invocation(job_summary.invocation_id, step_details=True)
rerun_step = invocation["steps"][1]
assert rerun_step["jobs"][0]["state"] == "ok"
replaced_hdca = self.dataset_populator.get_history_collection_details(
history_id=history_id, content_id=failed_hdca_id, assert_ok=False
)
assert (
replaced_hdca["elements"][0]["object"]["elements"][0]["object"]["elements"][0]["object"]["state"]
== "ok"
)
[docs] @skip_without_tool("multi_data_optional")
def test_workflow_list_list_multi_data_map_over(self):
# Test that a list:list is reduced to list with a multiple="true" data input
workflow_id = self._upload_yaml_workflow(
"""
class: GalaxyWorkflow
inputs:
input_datasets: collection
steps:
multi_data_optional:
tool_id: multi_data_optional
in:
input1: input_datasets
"""
)
with self.dataset_populator.test_history() as history_id:
hdca_id = self.dataset_collection_populator.create_list_of_list_in_history(history_id).json()
self.dataset_populator.wait_for_history(history_id, assert_ok=True)
inputs = {
"0": self._ds_entry(hdca_id),
}
invocation_id = self.__invoke_workflow(workflow_id, inputs=inputs, history_id=history_id)
self.workflow_populator.wait_for_invocation_and_jobs(history_id, workflow_id, invocation_id)
output_collection = self.dataset_populator.get_history_collection_details(history_id, hid=6)
assert output_collection["collection_type"] == "list"
assert output_collection["job_source_type"] == "ImplicitCollectionJobs"
[docs] @skip_without_tool("cat_list")
@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:
fetch_response = self.dataset_collection_populator.create_list_in_history(
history_id, contents=["a\nb\nc\nd\n", "e\nf\ng\nh\n"]
).json()
hdca1 = self.dataset_collection_populator.wait_for_fetched_collection(fetch_response)
self.dataset_populator.wait_for_history(history_id, assert_ok=True)
inputs = {
"0": self._ds_entry(hdca1),
}
invocation_id = self.__invoke_workflow(workflow_id, inputs=inputs, history_id=history_id)
self.workflow_populator.wait_for_invocation_and_jobs(history_id, workflow_id, invocation_id)
self.assertEqual(
"a\nc\nb\nd\ne\ng\nf\nh\n", self.dataset_populator.get_history_dataset_content(history_id, hid=0)
)
[docs] @skip_without_tool("cat_list")
@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, f"Expected 7 history items, got {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)
[docs] @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
inputs:
test_input_1: data
test_input_2: data
test_input_3: data
steps:
split_up:
tool_id: collection_split_on_column
in:
input1: test_input_2
min_repeat:
tool_id: min_repeat
in:
queries_0|input: test_input_1
queries2_0|input2: 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(workflow_id, inputs=inputs, history_id=history_id)
self.workflow_populator.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")
[docs] @skip_without_tool("cat")
@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
inputs:
text_input1: data
text_input2: data
steps:
cat_inputs:
tool_id: cat1
in:
input1: text_input1
queries_0|input2: text_input2
split_up_1:
tool_id: collection_split_on_column
in:
input1: cat_inputs/out_file1
split_up_2:
tool_id: collection_split_on_column
in:
input1: split_up_1/split_output
cat_output:
tool_id: cat
in:
input1: 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(workflow_id, inputs=inputs, history_id=history_id)
self.workflow_populator.wait_for_invocation_and_jobs(history_id, workflow_id, invocation_id)
[docs] @skip_without_tool("cat1")
@skip_without_tool("__FLATTEN__")
def test_workflow_input_tags(self):
workflow = self.workflow_populator.load_workflow_from_resource(name="test_workflow_with_input_tags")
workflow_id = self.workflow_populator.create_workflow(workflow)
downloaded_workflow = self._download_workflow(workflow_id)
count = 0
tag_test = ["tag1", "tag2"]
for step in downloaded_workflow["steps"]:
current = json.loads(downloaded_workflow["steps"][step]["tool_state"])
assert current["tag"] == tag_test[count]
count += 1
[docs] @skip_without_tool("column_param")
def test_empty_file_data_column_specified(self):
# Regression test for https://github.com/galaxyproject/galaxy/pull/10981
with self.dataset_populator.test_history() as history_id:
self._run_jobs(
"""class: GalaxyWorkflow
steps:
empty_output:
tool_id: empty_output
outputs:
out_file1:
change_datatype: tabular
column_param:
tool_id: column_param
in:
input1: empty_output/out_file1
state:
col: 2
col_names: 'B'
""",
history_id=history_id,
)
[docs] @skip_without_tool("column_param_list")
def test_comma_separated_columns(self):
# Regression test for https://github.com/galaxyproject/galaxy/pull/10981
with self.dataset_populator.test_history() as history_id:
self._run_jobs(
"""class: GalaxyWorkflow
steps:
empty_output:
tool_id: empty_output
outputs:
out_file1:
change_datatype: tabular
column_param_list:
tool_id: column_param_list
in:
input1: empty_output/out_file1
state:
col: '2,3'
col_names: 'B'
""",
history_id=history_id,
)
[docs] @skip_without_tool("column_param_list")
def test_comma_separated_columns_with_trailing_newline(self):
# Tests that workflows with weird tool state continue to run.
# In this case the newline may have been added by the workflow editor
# text field that is used for data_column parameters
with self.dataset_populator.test_history() as history_id:
job_summary = self._run_workflow(
"""class: GalaxyWorkflow
steps:
empty_output:
tool_id: empty_output
outputs:
out_file1:
change_datatype: tabular
column_param_list:
tool_id: column_param_list
in:
input1: empty_output/out_file1
state:
col: '2,3\n'
col_names: 'B\n'
""",
history_id=history_id,
)
job = self.dataset_populator.get_job_details(job_summary.jobs[0]["id"], full=True).json()
assert "col 2,3" in job["command_line"]
assert 'echo "col_names B" >>' in job["command_line"]
[docs] @skip_without_tool("column_param")
def test_runtime_data_column_parameter(self):
with self.dataset_populator.test_history() as history_id:
self._run_workflow_with_runtime_data_column_parameter(history_id)
[docs] @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
inputs:
input_fastqs: collection
reference: data
steps:
map_over_mapper:
tool_id: mapper
in:
input1: input_fastqs
reference: reference
pileup:
tool_id: pileup
in:
input1: map_over_mapper/out_file1
reference: reference
test_data:
input_fastqs:
collection_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,
)
[docs] def test_run_subworkflow_simple(self) -> None:
with self.dataset_populator.test_history() as history_id:
summary = self._run_workflow(
WORKFLOW_NESTED_SIMPLE,
test_data="""
outer_input:
value: 1.bed
type: File
""",
history_id=history_id,
)
invocation_id = summary.invocation_id
content = self.dataset_populator.get_history_dataset_content(history_id)
self.assertEqual(
"chrX\t152691446\t152691471\tCCDS14735.1_cds_0_0_chrX_152691447_f\t0\t+\nchrX\t152691446\t152691471\tCCDS14735.1_cds_0_0_chrX_152691447_f\t0\t+\n",
content,
)
steps = self.workflow_populator.get_invocation(invocation_id)["steps"]
assert sum(1 for step in steps if step["subworkflow_invocation_id"] is None) == 3
subworkflow_invocation_id = [
step["subworkflow_invocation_id"] for step in steps if step["subworkflow_invocation_id"]
][0]
subworkflow_invocation = self.workflow_populator.get_invocation(subworkflow_invocation_id)
assert [step for step in subworkflow_invocation["steps"] if step["order_index"] == 0][0][
"workflow_step_label"
] == "inner_input"
assert [step for step in subworkflow_invocation["steps"] if step["order_index"] == 1][0][
"workflow_step_label"
] == "random_lines"
bco = self.workflow_populator.get_biocompute_object(invocation_id)
self.workflow_populator.validate_biocompute_object(bco)
[docs] @skip_without_tool("random_lines1")
def test_run_subworkflow_runtime_parameters(self):
with self.dataset_populator.test_history() as history_id:
self._run_jobs(
WORKFLOW_NESTED_RUNTIME_PARAMETER,
test_data="""
step_parameters:
'1':
'1|num_lines': 2
outer_input:
value: 1.bed
type: File
""",
history_id=history_id,
)
content = self.dataset_populator.get_history_dataset_content(history_id)
assert len([x for x in content.split("\n") if x]) == 2
[docs] @skip_without_tool("cat")
def test_run_subworkflow_replacement_parameters(self):
with self.dataset_populator.test_history() as history_id:
test_data = """
replacement_parameters:
replaceme: moocow
outer_input:
value: 1.bed
type: File
"""
self._run_jobs(WORKFLOW_NESTED_REPLACEMENT_PARAMETER, test_data=test_data, history_id=history_id)
details = self.dataset_populator.get_history_dataset_details(history_id)
assert details["name"] == "moocow suffix"
[docs] @skip_without_tool("create_2")
def test_placements_from_text_inputs(self):
with self.dataset_populator.test_history() as history_id:
run_def = """
class: GalaxyWorkflow
inputs: []
steps:
create_2:
tool_id: create_2
state:
sleep_time: 0
outputs:
out_file1:
rename: "${replaceme} name"
out_file2:
rename: "${replaceme} name 2"
test_data:
replacement_parameters:
replaceme: moocow
"""
self._run_jobs(run_def, history_id=history_id)
details = self.dataset_populator.get_history_dataset_details(history_id)
assert details["name"] == "moocow name 2"
run_def = """
class: GalaxyWorkflow
inputs:
replaceme: text
steps:
create_2:
tool_id: create_2
state:
sleep_time: 0
outputs:
out_file1:
rename: "${replaceme} name"
out_file2:
rename: "${replaceme} name 2"
test_data:
replaceme:
value: moocow
type: raw
"""
self._run_jobs(run_def, history_id=history_id)
details = self.dataset_populator.get_history_dataset_details(history_id)
assert details["name"] == "moocow name 2", details["name"]
[docs] @skip_without_tool("random_lines1")
def test_run_runtime_parameters_after_pause(self):
with self.dataset_populator.test_history() as history_id:
workflow_run_description = f"""{WORKFLOW_RUNTIME_PARAMETER_AFTER_PAUSE}
test_data:
step_parameters:
'2':
'num_lines': 2
input1:
value: 1.bed
type: File
"""
job_summary = self._run_workflow(workflow_run_description, history_id=history_id, wait=False)
uploaded_workflow_id, invocation_id = job_summary.workflow_id, job_summary.invocation_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=1, 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)
content = self.dataset_populator.get_history_dataset_content(history_id)
assert len([x for x in content.split("\n") if x]) == 2
[docs] def test_run_subworkflow_auto_labels(self):
def run_test(workflow_text):
with self.dataset_populator.test_history() as history_id:
test_data = """
outer_input:
value: 1.bed
type: File
"""
summary = self._run_workflow(workflow_text, test_data=test_data, history_id=history_id)
jobs = summary.jobs
assert len(jobs) == 4, "4 jobs expected, got %d jobs" % len(jobs)
content = self.dataset_populator.get_history_dataset_content(history_id)
self.assertEqual(
"chrX\t152691446\t152691471\tCCDS14735.1_cds_0_0_chrX_152691447_f\t0\t+\nchrX\t152691446\t152691471\tCCDS14735.1_cds_0_0_chrX_152691447_f\t0\t+\n",
content,
)
run_test(NESTED_WORKFLOW_AUTO_LABELS_MODERN_SYNTAX)
[docs] @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
inputs:
test_input_1: data
test_input_2: data
steps:
first_cat:
tool_id: cat1
in:
input1: test_input_1
zip_it:
tool_id: "__ZIP_COLLECTION__"
in:
input_forward: first_cat/out_file1
input_reverse: test_input_2
concat_pair:
tool_id: collection_paired_test
in:
f1: 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(workflow_id, inputs=inputs, history_id=history_id)
self.workflow_populator.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")
[docs] @skip_without_tool("collection_paired_test")
def test_workflow_flatten(self):
with self.dataset_populator.test_history() as history_id:
self._run_jobs(
"""
class: GalaxyWorkflow
steps:
nested:
tool_id: collection_creates_dynamic_nested
state:
sleep_time: 0
foo: 'dummy'
flatten:
tool_id: '__FLATTEN__'
state:
input:
$link: nested/list_output
join_identifier: '-'
""",
test_data={},
history_id=history_id,
)
details = self.dataset_populator.get_history_collection_details(history_id, hid=14)
assert details["collection_type"] == "list"
elements = details["elements"]
identifiers = [e["element_identifier"] for e in elements]
assert len(identifiers) == 6
assert "oe1-ie1" in identifiers
[docs] @skip_without_tool("collection_paired_test")
def test_workflow_flatten_with_mapped_over_execution(self):
with self.dataset_populator.test_history() as history_id:
self._run_jobs(
r"""
class: GalaxyWorkflow
inputs:
input_fastqs: collection
steps:
split_up:
tool_id: collection_split_on_column
in:
input1: input_fastqs
flatten:
tool_id: '__FLATTEN__'
in:
input: split_up/split_output
join_identifier: '-'
test_data:
input_fastqs:
collection_type: list
elements:
- identifier: samp1
content: "0\n1"
""",
history_id=history_id,
)
history = self._get(f"histories/{history_id}/contents").json()
flattened_collection = history[-1]
assert flattened_collection["history_content_type"] == "dataset_collection"
assert flattened_collection["collection_type"] == "list"
assert flattened_collection["element_count"] == 2
nested_collection = self.dataset_populator.get_history_collection_details(history_id, hid=3)
assert nested_collection["collection_type"] == "list:list"
assert nested_collection["element_count"] == 1
assert nested_collection["elements"][0]["object"]["populated"]
assert nested_collection["elements"][0]["object"]["element_count"] == 2
[docs] @skip_without_tool("cat")
def test_workflow_invocation_report_1(self):
test_data = """
input_1:
value: 1.bed
type: File
"""
with self.dataset_populator.test_history() as history_id:
summary = self._run_workflow(
"""
class: GalaxyWorkflow
inputs:
input_1: data
outputs:
output_1:
outputSource: first_cat/out_file1
steps:
first_cat:
tool_id: cat
in:
input1: input_1
""",
test_data=test_data,
history_id=history_id,
)
workflow_id = summary.workflow_id
invocation_id = summary.invocation_id
report_json = self.workflow_populator.workflow_report_json(workflow_id, invocation_id)
assert "markdown" in report_json
self._assert_has_keys(report_json, "markdown", "render_format")
assert report_json["render_format"] == "markdown"
markdown_content = report_json["markdown"]
assert "## Workflow Outputs" in markdown_content
assert "## Workflow Inputs" in markdown_content
assert "## About This Report" not in markdown_content
[docs] @skip_without_tool("cat")
def test_workflow_invocation_report_custom(self):
with self.dataset_populator.test_history() as history_id:
summary = self._run_workflow(
WORKFLOW_WITH_CUSTOM_REPORT_1, test_data=WORKFLOW_WITH_CUSTOM_REPORT_1_TEST_DATA, history_id=history_id
)
workflow_id = summary.workflow_id
invocation_id = summary.invocation_id
downloaded_workflow = self._download_workflow(workflow_id)
assert "report" in downloaded_workflow
report_config = downloaded_workflow["report"]
assert "markdown" in report_config
report_json = self.workflow_populator.workflow_report_json(workflow_id, invocation_id)
assert "markdown" in report_json, f"markdown not in report json {report_json}"
self._assert_has_keys(report_json, "markdown", "render_format")
assert report_json["render_format"] == "markdown"
markdown_content = report_json["markdown"]
assert "## Workflow Outputs" in markdown_content
assert "\n```galaxy\nhistory_dataset_display(history_dataset_id=" in markdown_content
assert "## Workflow Inputs" in markdown_content
assert "## About This Report" in markdown_content
[docs] @skip_without_tool("cat1")
def test_export_invocation_bco(self):
with self.dataset_populator.test_history() as history_id:
summary = self._run_workflow(WORKFLOW_SIMPLE, test_data={"input1": "hello world"}, history_id=history_id)
invocation_id = summary.invocation_id
bco = self.workflow_populator.get_biocompute_object(invocation_id)
self.workflow_populator.validate_biocompute_object(bco)
self.assertEqual(bco["provenance_domain"]["name"], "Simple Workflow")
[docs] @skip_without_tool("__APPLY_RULES__")
def test_workflow_run_apply_rules(self):
with self.dataset_populator.test_history() as history_id:
self._run_workflow(
WORKFLOW_WITH_RULES_1,
history_id=history_id,
wait=True,
assert_ok=True,
round_trip_format_conversion=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)
[docs] def test_filter_failed_mapping(self):
with self.dataset_populator.test_history() as history_id:
summary = self._run_workflow(
"""
class: GalaxyWorkflow
inputs:
input_c: collection
steps:
mixed_collection:
tool_id: exit_code_from_file
state:
input:
$link: input_c
filtered_collection:
tool_id: "__FILTER_FAILED_DATASETS__"
state:
input:
$link: mixed_collection/out_file1
cat:
tool_id: cat1
state:
input1:
$link: filtered_collection
""",
test_data="""
input_c:
collection_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("__DATA_FETCH__")) == 1, 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
[docs] def test_workflow_request(self):
workflow = self.workflow_populator.load_workflow(name="test_for_queue")
workflow_request, history_id, workflow_id = self._setup_workflow_run(workflow)
run_workflow_response = self.workflow_populator.invoke_workflow_raw(
workflow_id, workflow_request, assert_ok=True
)
invocation_id = run_workflow_response.json()["id"]
self.workflow_populator.wait_for_invocation_and_jobs(history_id, workflow_id, invocation_id)
[docs] def test_workflow_new_autocreated_history(self):
workflow = self.workflow_populator.load_workflow(name="test_for_new_autocreated_history")
workflow_request, history_id, workflow_id = self._setup_workflow_run(workflow)
del workflow_request[
"history"
] # Not passing a history param means asking for a new history to be automatically created
run_workflow_dict = self.workflow_populator.invoke_workflow_raw(
workflow_id, workflow_request, assert_ok=True
).json()
new_history_id = run_workflow_dict["history_id"]
assert history_id != new_history_id
invocation_id = run_workflow_dict["id"]
self.workflow_populator.wait_for_invocation_and_jobs(new_history_id, workflow_id, invocation_id)
[docs] def test_workflow_output_dataset(self):
with self.dataset_populator.test_history() as history_id:
summary = self._run_workflow(WORKFLOW_SIMPLE, test_data={"input1": "hello world"}, history_id=history_id)
workflow_id = summary.workflow_id
invocation_id = summary.invocation_id
invocation_response = self._get(f"workflows/{workflow_id}/invocations/{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()
[docs] @skip_without_tool("cat")
def test_workflow_output_dataset_collection(self):
with self.dataset_populator.test_history() as history_id:
summary = self._run_workflow_with_output_collections(history_id)
workflow_id = summary.workflow_id
invocation_id = summary.invocation_id
invocation_response = self._get(f"workflows/{workflow_id}/invocations/{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"
[docs] def test_workflow_input_as_output(self):
with self.dataset_populator.test_history() as history_id:
summary = self._run_workflow_with_inputs_as_outputs(history_id)
workflow_id = summary.workflow_id
invocation_id = summary.invocation_id
invocation_response = self._get(f"workflows/{workflow_id}/invocations/{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
assert len(invocation["output_values"]) == 1
assert "wf_output_param" in invocation["output_values"]
assert invocation["output_values"]["wf_output_param"] == "A text variable", invocation["output_values"]
output_content = self.dataset_populator.get_history_dataset_content(
history_id, content_id=invocation["outputs"]["wf_output_1"]["id"]
)
assert output_content == "hello world\n"
[docs] def test_subworkflow_output_as_output(self):
with self.dataset_populator.test_history() as history_id:
summary = self._run_workflow(
"""
class: GalaxyWorkflow
inputs:
input1: data
outputs:
wf_output_1:
outputSource: nested_workflow/inner_output
steps:
nested_workflow:
run:
class: GalaxyWorkflow
inputs:
inner_input: data
outputs:
inner_output:
outputSource: inner_input
steps: []
in:
inner_input: input1
""",
test_data={"input1": "hello world"},
history_id=history_id,
)
workflow_id = summary.workflow_id
invocation_id = summary.invocation_id
invocation_response = self._get(f"workflows/{workflow_id}/invocations/{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, content_id=invocation["outputs"]["wf_output_1"]["id"]
)
assert output_content == "hello world\n"
[docs] @skip_without_tool("cat")
def test_workflow_input_mapping(self):
with self.dataset_populator.test_history() as history_id:
summary = self._run_workflow(
"""
class: GalaxyWorkflow
inputs:
input1: data
outputs:
wf_output_1:
outputSource: first_cat/out_file1
steps:
first_cat:
tool_id: cat
in:
input1: input1
""",
test_data="""
input1:
collection_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(f"workflows/{workflow_id}/invocations/{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"
[docs] @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_workflow(
"""
class: GalaxyWorkflow
inputs:
text_input: data
outputs:
wf_output_1:
outputSource: split_up/paired_output
steps:
split_up:
tool_id: collection_creates_pair
in:
input1: text_input
""",
test_data="""
text_input:
collection_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(f"workflows/{workflow_id}/invocations/{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"
self.workflow_populator.wait_for_invocation_and_jobs(history_id, workflow_id, invocation_id)
jobs_summary_response = self._get(f"workflows/{workflow_id}/invocations/{invocation_id}/jobs_summary")
self._assert_status_code_is(jobs_summary_response, 200)
jobs_summary = jobs_summary_response.json()
assert "states" in jobs_summary
invocation_states = jobs_summary["states"]
assert invocation_states and "ok" in invocation_states, jobs_summary
assert invocation_states["ok"] == 2, jobs_summary
assert jobs_summary["model"] == "WorkflowInvocation", jobs_summary
jobs_summary_response = self._get(f"workflows/{workflow_id}/invocations/{invocation_id}/step_jobs_summary")
self._assert_status_code_is(jobs_summary_response, 200)
jobs_summary = jobs_summary_response.json()
assert len(jobs_summary) == 1
collection_summary = jobs_summary[0]
assert "states" in collection_summary
collection_states = collection_summary["states"]
assert collection_states and "ok" in collection_states, collection_states
assert collection_states["ok"] == 2, collection_summary
assert collection_summary["model"] == "ImplicitCollectionJobs", collection_summary
[docs] def test_workflow_run_input_mapping_with_subworkflows(self):
with self.dataset_populator.test_history() as history_id:
test_data = """
outer_input:
collection_type: list
name: the_dataset_list
elements:
- identifier: el1
value: 1.fastq
type: File
- identifier: el2
value: 1.fastq
type: File
"""
summary = self._run_workflow(WORKFLOW_NESTED_SIMPLE, test_data=test_data, history_id=history_id)
workflow_id = summary.workflow_id
invocation_id = summary.invocation_id
invocation_response = self._get(f"workflows/{workflow_id}/invocations/{invocation_id}")
self._assert_status_code_is(invocation_response, 200)
invocation_response = self._get(f"workflows/{workflow_id}/invocations/{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"
[docs] @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_workflow(
"""
class: GalaxyWorkflow
inputs:
outer_input: data
outputs:
outer_output:
outputSource: second_cat/out_file1
steps:
first_cat:
tool_id: cat1
in:
input1: outer_input
nested_workflow:
run:
class: GalaxyWorkflow
inputs:
inner_input: data
outputs:
workflow_output:
outputSource: random_lines/out_file1
steps:
random_lines:
tool_id: random_lines1
state:
num_lines: 2
input:
$link: inner_input
seed_source:
seed_source_selector: set_seed
seed: asdf
in:
inner_input: first_cat/out_file1
split:
tool_id: split
in:
input1: nested_workflow/workflow_output
second_cat:
tool_id: cat_list
in:
input1: split/output
test_data:
outer_input:
value: 1.bed
type: File
""",
history_id=history_id,
wait=True,
round_trip_format_conversion=True,
)
self.assertEqual(
"chr6\t108722976\t108723115\tCCDS5067.1_cds_0_0_chr6_108722977_f\t0\t+\nchrX\t152691446\t152691471\tCCDS14735.1_cds_0_0_chrX_152691447_f\t0\t+\n",
self.dataset_populator.get_history_dataset_content(history_id),
)
# self.assertEqual("chr16\t142908\t143003\tCCDS10397.1_cds_0_0_chr16_142909_f\t0\t+\nchrX\t152691446\t152691471\tCCDS14735.1_cds_0_0_chrX_152691447_f\t0\t+\n", self.dataset_populator.get_history_dataset_content(history_id))
[docs] @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:
outer_input: data
outputs:
outer_output:
outputSource: second_cat/out_file1
steps:
first_cat:
tool_id: cat1
in:
input1: outer_input
nested_workflow:
run:
class: GalaxyWorkflow
inputs:
inner_input: data
outputs:
workflow_output:
outputSource: inner_cat/out_file1
steps:
random_lines:
tool_id: random_lines1
in:
input: inner_input
num_lines:
default: 2
seed_source|seed_source_selector:
default: set_seed
seed_source|seed:
default: asdf
split:
tool_id: split
in:
input1: random_lines/out_file1
inner_cat:
tool_id: cat1
in:
input1: split/output
in:
inner_input: first_cat/out_file1
second_cat:
tool_id: cat_list
in:
input1: nested_workflow/workflow_output
""",
test_data="""
outer_input:
value: 1.bed
type: File
""",
history_id=history_id,
wait=True,
round_trip_format_conversion=True,
)
self.assertEqual(
"chr6\t108722976\t108723115\tCCDS5067.1_cds_0_0_chr6_108722977_f\t0\t+\nchrX\t152691446\t152691471\tCCDS14735.1_cds_0_0_chrX_152691447_f\t0\t+\n",
self.dataset_populator.get_history_dataset_content(history_id),
)
[docs] @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:
outer_input: data
outputs:
outer_output:
outputSource: second_cat/out_file1
steps:
first_cat:
tool_id: cat1
in:
input1: outer_input
nested_workflow:
run:
class: GalaxyWorkflow
inputs:
inner_input: data
outputs:
workflow_output:
outputSource: split/output
steps:
random_lines:
tool_id: random_lines1
state:
num_lines: 2
input:
$link: inner_input
seed_source:
seed_source_selector: set_seed
seed: asdf
split:
tool_id: split
in:
input1: random_lines/out_file1
in:
inner_input: first_cat/out_file1
second_cat:
tool_id: cat_list
in:
input1: nested_workflow/workflow_output
""",
test_data="""
outer_input:
value: 1.bed
type: File
""",
history_id=history_id,
wait=True,
round_trip_format_conversion=True,
)
self.assertEqual(
"chr6\t108722976\t108723115\tCCDS5067.1_cds_0_0_chr6_108722977_f\t0\t+\nchrX\t152691446\t152691471\tCCDS14735.1_cds_0_0_chrX_152691447_f\t0\t+\n",
self.dataset_populator.get_history_dataset_content(history_id),
)
[docs] @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:
input1: data
outputs:
count_list:
outputSource: count_list/out_file1
steps:
empty_list:
tool_id: empty_list
in:
input1: input1
random_lines:
tool_id: random_lines1
state:
num_lines: 2
input:
$link: empty_list/output
seed_source:
seed_source_selector: set_seed
seed: asdf
count_list:
tool_id: count_list
in:
input1: 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))
[docs] @skip_without_tool("random_lines1")
def test_change_datatype_collection_map_over(self):
with self.dataset_populator.test_history() as history_id:
jobs_summary = self._run_workflow(
"""
class: GalaxyWorkflow
inputs:
text_input1: collection
steps:
map_over:
tool_id: random_lines1
in:
input: text_input1
outputs:
out_file1:
change_datatype: csv
""",
test_data="""
text_input1:
collection_type: "list:paired"
""",
history_id=history_id,
)
hdca = self.dataset_populator.get_history_collection_details(history_id=jobs_summary.history_id, hid=4)
assert hdca["collection_type"] == "list:paired"
assert len(hdca["elements"][0]["object"]["elements"]) == 2
forward, reverse = hdca["elements"][0]["object"]["elements"]
assert forward["object"]["file_ext"] == "csv"
assert reverse["object"]["file_ext"] == "csv"
[docs] @skip_without_tool("collection_type_source_map_over")
def test_mapping_and_subcollection_mapping(self):
with self.dataset_populator.test_history() as history_id:
jobs_summary = self._run_workflow(
"""
class: GalaxyWorkflow
inputs:
text_input1: collection
steps:
map_over:
tool_id: collection_type_source_map_over
in:
input_collect: text_input1
""",
test_data="""
text_input1:
collection_type: "list:paired"
""",
history_id=history_id,
)
hdca = self.dataset_populator.get_history_collection_details(history_id=jobs_summary.history_id, hid=1)
assert hdca["collection_type"] == "list:paired"
assert len(hdca["elements"][0]["object"]["elements"]) == 2
[docs] @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_workflow(
"""
class: GalaxyWorkflow
inputs:
input1: data
outputs:
count_multi_file:
outputSource: count_multi_file/out_file1
steps:
empty_list:
tool_id: empty_list
in:
input1: input1
random_lines:
tool_id: random_lines1
state:
num_lines: 2
input:
$link: empty_list/output
seed_source:
seed_source_selector: set_seed
seed: asdf
count_multi_file:
tool_id: count_multi_file
in:
input1: random_lines/out_file1
""",
test_data="""
input1:
value: 1.bed
type: File
""",
history_id=history_id,
wait=True,
round_trip_format_conversion=True,
)
self.assertEqual("0\n", self.dataset_populator.get_history_dataset_content(history_id))
[docs] @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(f"histories/{history_id}")
invocation_cancelled = self._wait_for_invocation_state(uploaded_workflow_id, invocation_id, "cancelled")
assert invocation_cancelled, "Workflow state is not cancelled..."
[docs] @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(f"histories/{history_id}")
invocation_cancelled = self._wait_for_invocation_state(uploaded_workflow_id, invocation_id, "cancelled")
assert invocation_cancelled, "Workflow state is not cancelled..."
[docs] @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)
[docs] @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..."
[docs] @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")
fetch_response = self.dataset_collection_populator.create_list_in_history(
history_id, contents=["1\n2\n3", "4\n5\n6"]
).json()
hdca1 = self.dataset_collection_populator.wait_for_fetched_collection(fetch_response)
index_map = {
"0": self._ds_entry(hda1),
"1": self._ds_entry(hdca1),
}
invocation_id = self.__invoke_workflow(uploaded_workflow_id, inputs=index_map, history_id=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)
self.__review_paused_steps(uploaded_workflow_id, invocation_id, order_index=4, action=True)
self.workflow_populator.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)
)
[docs] @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(f"workflows/{uploaded_workflow_id}/usage/{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"
[docs] @skip_without_tool("cat")
def test_pause_outputs_with_deleted_inputs(self):
self._deleted_inputs_workflow(purge=False)
[docs] @skip_without_tool("cat")
def test_error_outputs_with_purged_inputs(self):
self._deleted_inputs_workflow(purge=True)
def _deleted_inputs_workflow(self, purge):
# We run a workflow on a collection with a deleted element.
with self.dataset_populator.test_history() as history_id:
workflow_id = self._upload_yaml_workflow(
"""
class: GalaxyWorkflow
inputs:
input1:
type: collection
collection_type: list
steps:
first_cat:
tool_id: cat
in:
input1: input1
second_cat:
tool_id: cat
in:
input1: first_cat/out_file1
"""
)
DELETED = 0
PAUSED_1 = 1
PAUSED_2 = 2
fetch_response = self.dataset_collection_populator.create_list_in_history(
history_id, contents=[("sample1-1", "1 2 3")], wait=True
).json()
hdca1 = self.dataset_collection_populator.wait_for_fetched_collection(fetch_response)
deleted_id = hdca1["elements"][DELETED]["object"]["id"]
self.dataset_populator.delete_dataset(
history_id=history_id, content_id=deleted_id, purge=purge, wait_for_purge=True
)
label_map = {"input1": self._ds_entry(hdca1)}
workflow_request = dict(
history=f"hist_id={history_id}",
ds_map=self.workflow_populator.build_ds_map(workflow_id, label_map),
)
r = self.workflow_populator.invoke_workflow_raw(workflow_id, workflow_request)
self._assert_status_code_is(r, 200)
invocation_id = r.json()["id"]
# If this starts failing we may have prevented running workflows on collections with deleted members,
# in which case we can disable this test.
self.workflow_populator.wait_for_invocation_and_jobs(
workflow_id, history_id, invocation_id, assert_ok=False
)
contents = self.__history_contents(history_id)
datasets = [content for content in contents if content["history_content_type"] == "dataset"]
assert datasets[DELETED]["deleted"]
state = "error" if purge else "paused"
assert datasets[PAUSED_1]["state"] == state
assert datasets[PAUSED_2]["state"] == "paused"
[docs] def test_run_with_implicit_connection(self):
with self.dataset_populator.test_history() as history_id:
run_summary = self._run_workflow(
"""
class: GalaxyWorkflow
inputs:
test_input: data
steps:
first_cat:
tool_id: cat1
in:
input1: test_input
the_pause:
type: pause
in:
input: first_cat/out_file1
second_cat:
tool_id: cat1
in:
input1: the_pause
third_cat:
tool_id: random_lines1
in:
$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,
round_trip_format_conversion=True,
)
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.workflow_populator.wait_for_invocation_and_jobs(history_id, workflow_id, invocation_id)
self._assert_history_job_count(history_id, 4)
[docs] def test_run_with_optional_data_specified_to_multi_data(self):
with self.dataset_populator.test_history() as history_id:
self._run_workflow(
WORKFLOW_OPTIONAL_TRUE_INPUT_DATA,
test_data="""
input1:
value: 1.bed
type: File
""",
history_id=history_id,
wait=True,
assert_ok=True,
)
content = self.dataset_populator.get_history_dataset_content(history_id)
assert "CCDS989.1_cds_0_0_chr1_147962193_r" in content
[docs] def test_run_with_optional_data_unspecified_to_multi_data(self):
with self.dataset_populator.test_history() as history_id:
self._run_jobs(
WORKFLOW_OPTIONAL_TRUE_INPUT_DATA, test_data={}, history_id=history_id, wait=True, assert_ok=True
)
content = self.dataset_populator.get_history_dataset_content(history_id)
assert "No input selected" in content
[docs] def test_run_with_optional_data_unspecified_survives_delayed_step(self):
with self.dataset_populator.test_history() as history_id:
self._run_workflow(
WORKFLOW_OPTIONAL_INPUT_DELAYED_SCHEDULING,
history_id=history_id,
wait=True,
assert_ok=True,
)
[docs] def test_run_subworkflow_with_optional_data_unspecified(self):
with self.dataset_populator.test_history() as history_id:
subworkflow = yaml.safe_load(
"""
class: GalaxyWorkflow
inputs:
required: data
steps:
nested_workflow:
in:
required: required
test_data:
required:
value: 1.bed
type: File
"""
)
subworkflow["steps"]["nested_workflow"]["run"] = yaml.safe_load(WORKFLOW_OPTIONAL_INPUT_DELAYED_SCHEDULING)
self._run_workflow(
subworkflow,
history_id=history_id,
wait=True,
assert_ok=True,
)
[docs] def test_run_with_non_optional_data_unspecified_fails_invocation(self):
with self.dataset_populator.test_history() as history_id:
error = self._run_jobs(
WORKFLOW_OPTIONAL_FALSE_INPUT_DATA,
test_data={},
history_id=history_id,
wait=False,
assert_ok=False,
expected_response=400,
)
self._assert_failed_on_non_optional_input(error, "input1")
[docs] def test_run_with_optional_collection_specified(self):
with self.dataset_populator.test_history() as history_id:
self._run_jobs(
WORKFLOW_OPTIONAL_TRUE_INPUT_COLLECTION,
test_data="""
input1:
collection_type: paired
name: the_dataset_pair
elements:
- identifier: forward
value: 1.fastq
type: File
- identifier: reverse
value: 1.fastq
type: File
""",
history_id=history_id,
wait=True,
assert_ok=True,
)
content = self.dataset_populator.get_history_dataset_content(history_id)
assert "GAATTGATCAGGACATAGGACAACTGTAGGCACCAT" in content
[docs] def test_run_with_optional_collection_unspecified(self):
with self.dataset_populator.test_history() as history_id:
self._run_jobs(
WORKFLOW_OPTIONAL_TRUE_INPUT_COLLECTION, test_data={}, history_id=history_id, wait=True, assert_ok=True
)
content = self.dataset_populator.get_history_dataset_content(history_id)
assert "No input specified." in content
[docs] def test_run_with_non_optional_collection_unspecified_fails_invocation(self):
with self.dataset_populator.test_history() as history_id:
error = self._run_jobs(
WORKFLOW_OPTIONAL_FALSE_INPUT_COLLECTION,
test_data={},
history_id=history_id,
wait=False,
assert_ok=False,
expected_response=400,
)
self._assert_failed_on_non_optional_input(error, "input1")
def _assert_failed_on_non_optional_input(self, error, input_name):
assert "err_msg" in error
err_msg = error["err_msg"]
assert input_name in err_msg
assert "is not optional and no input" in err_msg
[docs] def test_run_with_validated_parameter_connection_optional(self):
with self.dataset_populator.test_history() as history_id:
self._run_workflow(
"""
class: GalaxyWorkflow
inputs:
text_input: text
steps:
validation:
tool_id: validation_repeat
state:
r2:
- text:
$link: text_input
""",
test_data="""
text_input:
value: "abd"
type: raw
""",
history_id=history_id,
wait=True,
round_trip_format_conversion=True,
)
jobs = self._history_jobs(history_id)
assert len(jobs) == 1
[docs] def test_run_with_int_parameter(self):
with self.dataset_populator.test_history() as history_id:
failed = False
try:
self._run_jobs(
WORKFLOW_PARAMETER_INPUT_INTEGER_REQUIRED,
test_data="""
data_input:
value: 1.bed
type: File
""",
history_id=history_id,
wait=True,
assert_ok=True,
)
except AssertionError as e:
assert "(int_input) is not optional" in str(e)
failed = True
assert failed
run_response = self._run_workflow(
WORKFLOW_PARAMETER_INPUT_INTEGER_REQUIRED,
test_data="""
data_input:
value: 1.bed
type: File
int_input:
value: 1
type: raw
""",
history_id=history_id,
wait=True,
assert_ok=True,
)
# self.dataset_populator.wait_for_history(history_id, assert_ok=True)
content = self.dataset_populator.get_history_dataset_content(history_id)
assert len(content.splitlines()) == 1, content
invocation = self.workflow_populator.get_invocation(run_response.invocation_id)
assert invocation["input_step_parameters"]["int_input"]["parameter_value"] == 1
run_response = self._run_workflow(
WORKFLOW_PARAMETER_INPUT_INTEGER_OPTIONAL,
test_data="""
data_input:
value: 1.bed
type: File
""",
history_id=history_id,
wait=True,
assert_ok=True,
)
invocation = self.workflow_populator.get_invocation(run_response.invocation_id)
# Optional step parameter without default value will not be recorded.
assert "int_input" not in invocation["input_step_parameters"]
[docs] def test_run_with_int_parameter_nested(self):
with self.dataset_populator.test_history() as history_id:
workflow = self.workflow_populator.load_workflow_from_resource("test_subworkflow_with_integer_input")
workflow_id = self.workflow_populator.create_workflow(workflow)
hda: dict = self.dataset_populator.new_dataset(history_id, content="1 2 3")
workflow_request = {
"history_id": history_id,
"inputs_by": "name",
"inputs": json.dumps(
{
"input_dataset": {"src": "hda", "id": hda["id"]},
"int_parameter": 1,
}
),
}
self.workflow_populator.invoke_workflow_and_wait(workflow_id, request=workflow_request)
[docs] def test_run_with_validated_parameter_connection_default_values(self):
with self.dataset_populator.test_history() as history_id:
self._run_jobs(
WORKFLOW_PARAMETER_INPUT_INTEGER_DEFAULT,
test_data="""
data_input:
value: 1.bed
type: File
""",
history_id=history_id,
wait=True,
assert_ok=True,
)
self.dataset_populator.wait_for_history(history_id, assert_ok=True)
content = self.dataset_populator.get_history_dataset_content(history_id)
assert len(content.splitlines()) == 3, content
[docs] def test_run_with_validated_parameter_connection_invalid(self):
with self.dataset_populator.test_history() as history_id:
self._run_jobs(
"""
class: GalaxyWorkflow
inputs:
text_input: text
steps:
validation:
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,
)
[docs] def test_run_with_text_input_connection(self):
with self.dataset_populator.test_history() as history_id:
self._run_jobs(
"""
class: GalaxyWorkflow
inputs:
data_input: data
text_input: text
steps:
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("chrX\t152691446\t152691471\tCCDS14735.1_cds_0_0_chrX_152691447_f\t0\t+\n", content)
[docs] def test_run_with_numeric_input_connection(self):
history_id = self.dataset_populator.new_history()
self._run_jobs(
"""
class: GalaxyWorkflow
steps:
- label: forty_two
tool_id: expression_forty_two
state: {}
- label: consume_expression_parameter
tool_id: cheetah_casting
state:
floattest: 3.14
inttest:
$link: forty_two/out1
test_data: {}
""",
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)
lines = content.split("\n")
assert len(lines) == 4
str_43 = lines[0]
str_4point14 = lines[2]
assert lines[3] == ""
assert int(str_43) == 43
assert abs(float(str_4point14) - 4.14) < 0.0001
[docs] @skip_without_tool("param_value_from_file")
def test_expression_tool_map_over(self):
history_id = self.dataset_populator.new_history()
self._run_jobs(
"""
class: GalaxyWorkflow
inputs:
text_input1: collection
steps:
- label: param_out
tool_id: param_value_from_file
in:
input1: text_input1
- label: consume_expression_parameter
tool_id: validation_default
in:
input1: param_out/text_param
outputs:
out_file1:
rename: "replaced_param_collection"
test_data:
text_input1:
collection_type: list
elements:
- identifier: A
content: A
- identifier: B
content: B
""",
history_id=history_id,
)
history_contents = self._get(f"histories/{history_id}/contents").json()
collection = [
c
for c in history_contents
if c["history_content_type"] == "dataset_collection" and c["name"] == "replaced_param_collection"
][0]
collection_details = self._get(collection["url"]).json()
assert collection_details["element_count"] == 2
elements = collection_details["elements"]
assert elements[0]["element_identifier"] == "A"
assert elements[1]["element_identifier"] == "B"
element_a_content = self.dataset_populator.get_history_dataset_content(
history_id, dataset=elements[0]["object"]
)
element_b_content = self.dataset_populator.get_history_dataset_content(
history_id, dataset=elements[1]["object"]
)
assert element_a_content.strip() == "A"
assert element_b_content.strip() == "B"
[docs] @skip_without_tool("create_input_collection")
def test_workflow_optional_input_text_parameter_reevaluation(self):
with self.dataset_populator.test_history() as history_id:
self._run_jobs(
"""
class: GalaxyWorkflow
inputs:
text_input:
type: text
optional: true
default: ''
steps:
create_collection:
tool_id: create_input_collection
nested_workflow:
in:
inner_input: create_collection/output
inner_text_input: text_input
run:
class: GalaxyWorkflow
inputs:
inner_input:
type: data_collection_input
inner_text_input:
type: text
optional: true
default: ''
steps:
apply:
tool_id: __APPLY_RULES__
in:
input: inner_input
state:
rules:
rules:
- type: add_column_metadata
value: identifier0
mapping:
- type: list_identifiers
columns: [0]
echo:
cat1:
in:
input1: apply/output
outputs:
out_file1:
rename: "#{inner_text_input} suffix"
""",
history_id=history_id,
)
[docs] @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_one, self.dataset_populator.test_history() as history_id_two:
workflow_request, _, workflow_id = self._setup_workflow_run(workflow, history_id=history_id_one)
invocation_id = self.workflow_populator.invoke_workflow_and_wait(
workflow_id, request=workflow_request
).json()["id"]
invocation_1 = self.workflow_populator.get_invocation(invocation_id)
# 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"])
for key, input_values in invocation_1["inputs"].items():
copy_payload = {"content": input_values["id"], "source": "hda", "type": "dataset"}
copy_response = self._post(f"histories/{history_id_two}/contents", data=copy_payload, json=True).json()
new_ds_map[key]["id"] = copy_response["id"]
new_workflow_request["ds_map"] = json.dumps(new_ds_map, sort_keys=True)
new_workflow_request["history"] = f"hist_id={history_id_two}"
new_workflow_request["use_cached_job"] = True
# We run the workflow again, it should not produce any new outputs
new_workflow_response = self.workflow_populator.invoke_workflow_raw(
workflow_id, new_workflow_request, assert_ok=True
).json()
invocation_id = new_workflow_response["id"]
self.workflow_populator.wait_for_invocation_and_jobs(history_id_two, workflow_id, invocation_id)
# get_history_dataset_details defaults to last item in history, so since we've done
# wait_for_invocation_and_jobs - this will be the output of the cat1 job for both histories
# (the only job in the loaded workflow).
first_wf_output_hda = self.dataset_populator.get_history_dataset_details(history_id=history_id_one)
second_wf_output_hda = self.dataset_populator.get_history_dataset_details(history_id=history_id_two)
first_wf_output = self._get(f"datasets/{first_wf_output_hda['id']}").json()
second_wf_output = self._get(f"datasets/{second_wf_output_hda['id']}").json()
assert (
first_wf_output["file_name"] == second_wf_output["file_name"]
), f"first output:\n{first_wf_output}\nsecond output:\n{second_wf_output}"
[docs] @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:
test_data = """
outer_input:
value: 1.bed
type: File
"""
run_jobs_summary = self._run_workflow(
WORKFLOW_NESTED_SIMPLE, test_data=test_data, history_id=history_id_one
)
workflow_id = run_jobs_summary.workflow_id
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(f"histories/{history_id_two}/contents", data=copy_payload, json=True)
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"] = f"hist_id={history_id_two}"
workflow_request["inputs"] = json.dumps(inputs)
self.workflow_populator.invoke_workflow_and_wait(workflow_id, request=run_jobs_summary.workflow_request)
# 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,
)
[docs] def test_cannot_run_inaccessible_workflow(self):
workflow = self.workflow_populator.load_workflow(name="test_for_run_cannot_access")
workflow_request, _, workflow_id = self._setup_workflow_run(workflow)
with self._different_user():
run_workflow_response = self._post(f"workflows/{workflow_id}/invocations", data=workflow_request)
self._assert_status_code_is(run_workflow_response, 403)
[docs] def test_400_on_invalid_workflow_id(self):
workflow = self.workflow_populator.load_workflow(name="test_for_run_does_not_exist")
workflow_request, _, _ = self._setup_workflow_run(workflow)
run_workflow_response = self._post(f"workflows/{self._random_key()}/invocations", data=workflow_request)
self._assert_status_code_is(run_workflow_response, 400)
[docs] 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, workflow_id = self._setup_workflow_run(workflow)
with self._different_user():
other_history_id = self.dataset_populator.new_history()
workflow_request["history"] = f"hist_id={other_history_id}"
run_workflow_response = self._post(f"workflows/{workflow_id}/invocations", data=workflow_request)
self._assert_status_code_is(run_workflow_response, 403)
[docs] def test_cannot_run_bootstrap_admin_workflow(self):
workflow = self.workflow_populator.load_workflow(name="test_bootstrap_admin_cannot_run")
workflow_request, *_ = self._setup_workflow_run(workflow)
run_workflow_response = self._post("workflows", data=workflow_request, key=self.master_api_key, json=True)
self._assert_status_code_is(run_workflow_response, 400)
[docs] @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()
hdca1 = self.dataset_collection_populator.wait_for_fetched_collection(hdca1)
hdca2 = self.dataset_collection_populator.wait_for_fetched_collection(hdca2)
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(
ds_map=self.workflow_populator.build_ds_map(workflow_id, label_map),
)
self.workflow_populator.invoke_workflow_and_wait(
workflow_id, history_id=history_id, request=workflow_request
)
self.assertEqual(
"1 2 3\n4 5 6\n7 8 9\n0 a b\n", self.dataset_populator.get_history_dataset_content(history_id)
)
[docs] 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 _ 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
[docs] def test_empty_create(self):
response = self._post("workflows")
self._assert_status_code_is(response, 400)
self._assert_error_code_is(response, error_codes.error_codes_by_name["USER_REQUEST_MISSING_PARAMETER"])
[docs] 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.error_codes_by_name["USER_REQUEST_INVALID_PARAMETER"])
[docs] @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, workflow_id = self._setup_workflow_run(workflow, inputs_by="step_index")
workflow_request["replacement_params"] = dumps(dict(replaceme="was replaced"))
run_workflow_response = self.workflow_populator.invoke_workflow_raw(
workflow_id, workflow_request, assert_ok=True
)
invocation_id = run_workflow_response.json()["id"]
self.workflow_populator.wait_for_invocation_and_jobs(history_id, workflow_id, invocation_id, assert_ok=True)
content = self.dataset_populator.get_history_dataset_details(history_id, wait=True, assert_ok=True)
assert content["name"] == "foo was replaced"
[docs] @skip_without_tool("output_filter")
def test_optional_workflow_output(self):
with self.dataset_populator.test_history() as history_id:
run_object = self._run_workflow(
"""
class: GalaxyWorkflow
inputs: []
outputs:
wf_output_1:
outputSource: output_filter/out_1
steps:
output_filter:
tool_id: output_filter
state:
produce_out_1: False
filter_text_1: '1'
produce_collection: False
""",
test_data={},
history_id=history_id,
wait=False,
)
self.workflow_populator.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"
[docs] @skip_without_tool("output_filter_with_input_optional")
def test_workflow_optional_input_filtering(self):
with self.dataset_populator.test_history() as history_id:
test_data = """
input1:
collection_type: list
elements:
- identifier: A
content: A
"""
run_object = self._run_workflow(
"""
class: GalaxyWorkflow
inputs:
input1:
type: collection
collection_type: list
outputs:
wf_output_1:
outputSource: output_filter/out_1
steps:
output_filter:
tool_id: output_filter_with_input_optional
in:
input_1: input1
""",
test_data=test_data,
history_id=history_id,
wait=False,
)
self.workflow_populator.wait_for_invocation_and_jobs(
history_id, run_object.workflow_id, run_object.invocation_id
)
contents = self.__history_contents(history_id)
assert len(contents) == 4
for content in contents:
if content["history_content_type"] == "dataset":
assert content["state"] == "ok"
else:
print(content)
assert content["populated_state"] == "ok"
[docs] @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:
input1:
type: collection
collection_type: list
steps:
first_cat:
tool_id: cat
in:
input1: input1
outputs:
out_file1:
rename: "my new name"
""",
test_data="""
input1:
collection_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
[docs] @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:
input1:
type: collection
collection_type: list
steps:
first_cat:
tool_id: cat
in:
input1: input1
outputs:
out_file1:
rename: "#{input1} suffix"
""",
test_data="""
input1:
collection_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
[docs] @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:
input1: data
steps:
- tool_id: collection_creates_pair
in:
input1: 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["elements"][0]["object"]["visible"] is False
assert details1["name"] == "my new name", details1
assert details1["history_content_type"] == "dataset_collection"
[docs] @skip_without_tool("__BUILD_LIST__")
def test_run_build_list_hide_collection_output(self):
with self.dataset_populator.test_history() as history_id:
self._run_jobs(
"""
class: GalaxyWorkflow
inputs:
input1: data
steps:
- tool_id: __BUILD_LIST__
in:
datasets_0|input: input1
state:
datasets:
- id_cond:
id_select: id
outputs:
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=3, wait=True, assert_ok=True
)
assert details1["elements"][0]["object"]["visible"] is False
assert details1["name"] == "data 1 (as list)", details1
assert details1["visible"] is False
[docs] @skip_without_tool("__BUILD_LIST__")
def test_run_build_list_delete_intermediate_collection_output(self):
with self.dataset_populator.test_history() as history_id:
self._run_jobs(
"""
class: GalaxyWorkflow
inputs:
input1: data
steps:
- tool_id: __BUILD_LIST__
in:
datasets_0|input: input1
state:
datasets:
- id_cond:
id_select: id
outputs:
output:
delete_intermediate_datasets: 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=3, wait=True, assert_ok=True
)
assert details1["elements"][0]["object"]["visible"] is False
assert details1["name"] == "data 1 (as list)", details1
# FIXME: this doesn't work because the workflow is still being scheduled
# TODO: Implement a way to run PJAs that couldn't be run during/after the job
# after the workflow has run to completion
assert details1["deleted"] is False
[docs] @skip_without_tool("__BUILD_LIST__")
def test_run_build_list_change_datatype_collection_output(self):
with self.dataset_populator.test_history() as history_id:
self._run_jobs(
"""
class: GalaxyWorkflow
inputs:
input1: data
steps:
- tool_id: __BUILD_LIST__
in:
datasets_0|input: input1
state:
datasets:
- id_cond:
id_select: idx
outputs:
output:
change_datatype: txt
- tool_id: __BUILD_LIST__
in:
datasets_0|input: input1
state:
datasets:
- id_cond:
id_select: idx
""",
test_data="""
input1:
value: 1.fasta
type: File
file_type: fasta
name: fasta1
""",
history_id=history_id,
)
details1 = self.dataset_populator.get_history_collection_details(
history_id, hid=3, wait=True, assert_ok=True
)
assert details1["name"] == "data 1 (as list)", details1
assert details1["elements"][0]["object"]["visible"] is False
assert details1["elements"][0]["object"]["file_ext"] == "txt"
details2 = self.dataset_populator.get_history_collection_details(
history_id, hid=5, wait=True, assert_ok=True
)
# Also check that we don't overwrite the original HDA's datatype
assert details2["elements"][0]["object"]["file_ext"] == "fasta"
[docs] @skip_without_tool("__BUILD_LIST__")
def test_run_build_list_rename_collection_output(self):
with self.dataset_populator.test_history() as history_id:
self._run_jobs(
"""
class: GalaxyWorkflow
inputs:
input1: data
steps:
- tool_id: __BUILD_LIST__
in:
datasets_0|input: input1
state:
datasets:
- id_cond:
id_select: idx
outputs:
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=3, wait=True, assert_ok=True
)
assert details1["elements"][0]["object"]["visible"] is False
assert details1["name"] == "my new name", details1
assert details1["history_content_type"] == "dataset_collection"
[docs] @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:
create_2:
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"
[docs] @skip_without_tool("cat")
def test_run_rename_based_on_input(self):
with self.dataset_populator.test_history() as history_id:
self._run_jobs(WORKFLOW_RENAME_ON_INPUT, 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
[docs] @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:
input1: data
steps:
first_fail:
tool_id: fail_identifier
state:
failbool: true
input1:
$link: input1
outputs:
out_file1:
rename: "cat1 out"
cat:
tool_id: cat
in:
input1: 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,
)
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"] == f"{name} suffix"
[docs] @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:
input1: data
steps:
first_cat:
tool_id: cat
in:
input1: 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
[docs] @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:
input1: data
input2: data
steps:
first_cat:
tool_id: 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
[docs] @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:
fasta_input: data
fastq_input: data
steps:
mapping:
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
[docs] @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:
fasta_input: data
fastq_inputs: data
steps:
mapping:
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:
collection_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
[docs] @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:
input1: data
steps:
create_pair:
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
[docs] @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:
first_cat:
tool_id: cat
in:
input1: input1
outputs:
out_file1:
hide: true
""",
test_data="""
input1:
collection_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 not content["visible"]
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 not content["visible"]
[docs] @skip_without_tool("cat")
def test_tag_auto_propagation(self):
with self.dataset_populator.test_history() as history_id:
self._run_jobs(
"""
class: GalaxyWorkflow
inputs:
input1: data
steps:
first_cat:
tool_id: cat
in:
input1: input1
outputs:
out_file1:
add_tags:
- "name:treated1fb"
- "group:condition:treated"
- "group:type:single-read"
- "machine:illumina"
second_cat:
tool_id: cat
in:
input1: first_cat/out_file1
""",
test_data="""
input1:
value: 1.fasta
type: File
name: fasta1
""",
history_id=history_id,
round_trip_format_conversion=True,
)
details0 = self.dataset_populator.get_history_dataset_details(history_id, hid=2, wait=True, assert_ok=True)
tags = details0["tags"]
assert len(tags) == 4, details0
assert "name:treated1fb" in tags, tags
assert "group:condition:treated" in tags, tags
assert "group:type:single-read" in tags, tags
assert "machine:illumina" in tags, tags
details1 = self.dataset_populator.get_history_dataset_details(history_id, hid=3, wait=True, assert_ok=True)
tags = details1["tags"]
assert len(tags) == 1, details1
assert "name:treated1fb" in tags, tags
[docs] @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:
input1: data
steps:
create_pair:
tool_id: collection_creates_pair
in:
input1: input1
outputs:
paired_output:
add_tags:
- "name:foo"
""",
test_data="""
input1:
value: 1.fasta
type: File
name: fasta1
""",
history_id=history_id,
round_trip_format_conversion=True,
)
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
[docs] @skip_without_tool("cat")
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:
input1:
type: collection
collection_type: list
steps:
first_cat:
tool_id: cat
in:
input1: input1
outputs:
out_file1:
add_tags:
- "name:foo"
""",
test_data="""
input1:
collection_type: list
name: the_dataset_list
elements:
- identifier: el1
value: 1.fastq
type: File
""",
history_id=history_id,
round_trip_format_conversion=True,
)
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
[docs] @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:
input1: data
steps:
first_cat:
tool_id: cat
in:
input1: input1
outputs:
out_file1:
add_tags:
- "name:foo"
create_pair:
tool_id: collection_creates_pair
in:
input1: 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,
round_trip_format_conversion=True,
)
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
[docs] @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, workflow_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}})
self.workflow_populator.invoke_workflow_and_wait(workflow_id, request=workflow_request)
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.
downloaded_workflow = self._download_workflow(workflow_id)
pjas = list(downloaded_workflow["steps"]["2"]["post_job_actions"].values())
assert len(pjas) == 0, len(pjas)
[docs] @skip_without_tool("cat1")
def test_run_with_delayed_runtime_pja(self):
workflow_id = self._upload_yaml_workflow(
"""
class: GalaxyWorkflow
inputs:
test_input: data
steps:
first_cat:
tool_id: cat1
in:
input1: test_input
the_pause:
type: pause
in:
input: first_cat/out_file1
second_cat:
tool_id: cat1
in:
input1: the_pause
""",
round_trip_format_conversion=True,
)
downloaded_workflow = self._download_workflow(workflow_id)
uuid_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),
}
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(
workflow_id, inputs=inputs, request=workflow_request, history_id=history_id
)
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"]
[docs] @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:
input1: data
outputs:
wf_output_1:
outputSource: third_cat/out_file1
steps:
first_cat:
tool_id: cat1
in:
input1: input1
second_cat:
tool_id: cat1
in:
input1: first_cat/out_file1
third_cat:
tool_id: cat1
in:
input1: 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"]
[docs] @skip_without_tool("cat1")
def test_validated_post_job_action_validated(self):
with self.dataset_populator.test_history() as history_id:
self._run_jobs(
"""
class: GalaxyWorkflow
inputs:
input1: data
outputs:
wf_output_1:
outputSource: first_cat/out_file1
steps:
first_cat:
tool_id: cat1
in:
input1: input1
post_job_actions:
ValidateOutputsAction:
action_type: ValidateOutputsAction
""",
test_data={"input1": {"type": "File", "file_type": "fastqsanger", "value": "1.fastqsanger"}},
history_id=history_id,
)
hda2 = self.dataset_populator.get_history_dataset_details(history_id, hid=2)
assert hda2["validated_state"] == "ok"
[docs] @skip_without_tool("cat1")
def test_validated_post_job_action_unvalidated_default(self):
with self.dataset_populator.test_history() as history_id:
self._run_jobs(
WORKFLOW_SIMPLE,
test_data={"input1": {"type": "File", "file_type": "fastqsanger", "value": "1.fastqsanger"}},
history_id=history_id,
)
hda2 = self.dataset_populator.get_history_dataset_details(history_id, hid=2)
assert hda2["validated_state"] == "unknown"
[docs] @skip_without_tool("cat1")
def test_validated_post_job_action_invalid(self):
with self.dataset_populator.test_history() as history_id:
self._run_jobs(
"""
class: GalaxyWorkflow
inputs:
input1: data
outputs:
wf_output_1:
outputSource: first_cat/out_file1
steps:
first_cat:
tool_id: cat1
in:
input1: input1
post_job_actions:
ValidateOutputsAction:
action_type: ValidateOutputsAction
""",
test_data={"input1": {"type": "File", "file_type": "fastqcssanger", "value": "1.fastqsanger"}},
history_id=history_id,
)
hda2 = self.dataset_populator.get_history_dataset_details(history_id, hid=2)
assert hda2["validated_state"] == "invalid"
[docs] def test_value_restriction_with_select_and_text_param(self):
workflow_id = self.workflow_populator.upload_yaml_workflow(
"""
class: GalaxyWorkflow
inputs:
select_text:
type: text
restrictOnConnections: true
steps:
select:
tool_id: multi_select
in:
select_ex: select_text
tool_with_text_input:
tool_id: param_text_option
in:
text_param: select_text
"""
)
with self.dataset_populator.test_history() as history_id:
run_workflow = self._download_workflow(workflow_id, style="run", history_id=history_id)
options = run_workflow["steps"][0]["inputs"][0]["options"]
assert len(options) == 5
assert options[0] == ["Ex1", "--ex1", False]
[docs] @skip_without_tool("random_lines1")
def test_run_replace_params_by_tool(self):
workflow_request, history_id, workflow_id = self._setup_random_x2_workflow("test_for_replace_tool_params")
workflow_request["parameters"] = dumps(dict(random_lines1=dict(num_lines=5)))
self.workflow_populator.invoke_workflow_and_wait(workflow_id, request=workflow_request)
# 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)
[docs] @skip_without_tool("random_lines1")
def test_run_replace_params_by_uuid(self):
workflow_request, history_id, workflow_id = self._setup_random_x2_workflow("test_for_replace_")
workflow_request["parameters"] = dumps(
{
"58dffcc9-bcb7-4117-a0e1-61513524b3b1": dict(num_lines=4),
"58dffcc9-bcb7-4117-a0e1-61513524b3b2": dict(num_lines=3),
}
)
self.workflow_populator.invoke_workflow_and_wait(workflow_id, request=workflow_request)
# 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)
[docs] @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", wait=True)
hda2 = self.dataset_populator.new_dataset(history_id, content="4 5 6", wait=True)
hda3 = self.dataset_populator.new_dataset(history_id, content="7 8 9", wait=True)
hda4 = self.dataset_populator.new_dataset(history_id, content="10 11 12", wait=True)
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(f"workflows/{workflow_id}/usage", 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)
[docs] @skip_without_tool("cat1")
@skip_without_tool("addValue")
def test_run_batch_inputs(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")
inputs = {
"coolinput": {
"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"},
],
}
}
parameters = {
"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,
"inputs": dumps(inputs),
"inputs_by": "name",
"parameters_normalized": True,
"parameters": dumps(parameters),
}
invocation_response = self._post(f"workflows/{workflow_id}/usage", 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)
[docs] @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)
)
[docs] @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:
validation:
tool_id: validation_repeat
state:
r2:
- text: "abd"
"""
)
workflow_request = dict(
history=f"hist_id={history_id}", parameters=dumps(dict(validation_repeat={"r2_0|text": ""}))
)
url = f"workflows/{workflow_id}/invocations"
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)
[docs] @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)
[docs] @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:
validation:
tool_id: validation_repeat
state:
r2:
- text: ""
""",
history_id=history_id,
wait=False,
expected_response=400,
assert_ok=False,
)
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=f"hist_id={history_id}",
workflow_id=uploaded_workflow_id,
parameters=dumps(dict(validation_default=substitions)),
)
run_workflow_response = self.workflow_populator.invoke_workflow_raw(uploaded_workflow_id, workflow_request)
return run_workflow_response, history_id
[docs] def test_subworkflow_import_order_maintained(self):
summary = self._run_workflow(
"""
class: GalaxyWorkflow
inputs:
outer_input_1:
type: int
default: 1
position:
left: 0
top: 0
outer_input_2:
type: int
default: 2
position:
left: 100
top: 0
steps:
nested_workflow:
in:
inner_input_1: outer_input_1
inner_input_2: outer_input_2
run:
class: GalaxyWorkflow
inputs:
inner_input_1:
type: int
position:
left: 100
top: 0
inner_input_2:
type: int
position:
left: 0
top: 0
steps: []
outputs:
- label: nested_out_1
outputSource: inner_input_1/output
- label: nested_out_2
outputSource: inner_input_2/output
outputs:
- label: out_1
outputSource: nested_workflow/nested_out_1
- label: out_2
outputSource: nested_workflow/nested_out_2
""",
assert_ok=False,
wait=False,
)
self.workflow_populator.wait_for_invocation(summary.workflow_id, summary.invocation_id)
self.workflow_populator.wait_for_history_workflows(
summary.history_id, assert_ok=False, expected_invocation_count=2
)
invocation = self.workflow_populator.get_invocation(summary.invocation_id)
output_values = invocation["output_values"]
assert output_values["out_1"] == 1
assert output_values["out_2"] == 2
[docs] @skip_without_tool("random_lines1")
def test_run_replace_params_by_steps(self):
workflow_request, history_id, workflow_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
self.workflow_populator.invoke_workflow_and_wait(workflow_id, request=workflow_request)
# 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)
[docs] @skip_without_tool("random_lines1")
def test_run_replace_params_nested(self):
workflow_request, history_id, workflow_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
self.workflow_populator.invoke_workflow_and_wait(workflow_id, request=workflow_request)
self.assertEqual("2\n", self.dataset_populator.get_history_dataset_content(history_id))
[docs] @skip_without_tool("random_lines1")
def test_run_replace_params_nested_normalized(self):
workflow_request, history_id, workflow_id, steps = self._setup_random_x2_workflow_steps(
"test_for_replace_step_normalized_params_nested"
)
parameters = {
"num_lines": 1,
"seed_source|seed_source_selector": "set_seed",
"seed_source|seed": "moo",
}
params = dumps({str(steps[0]["id"]): parameters, str(steps[1]["id"]): parameters})
workflow_request["parameters"] = params
workflow_request["parameters_normalized"] = False
self.workflow_populator.invoke_workflow_and_wait(workflow_id, request=workflow_request)
self.assertEqual("2\n", self.dataset_populator.get_history_dataset_content(history_id))
[docs] @skip_without_tool("random_lines1")
def test_run_replace_params_over_default(self):
with self.dataset_populator.test_history() as history_id:
self._run_jobs(
WORKFLOW_ONE_STEP_DEFAULT,
test_data="""
step_parameters:
'1':
num_lines: 4
input:
value: 1.bed
type: File
""",
history_id=history_id,
wait=True,
assert_ok=True,
round_trip_format_conversion=True,
)
result = self.dataset_populator.get_history_dataset_content(history_id)
assert result.count("\n") == 4
[docs] @skip_without_tool("random_lines1")
def test_defaults_editor(self):
workflow_id = self._upload_yaml_workflow(WORKFLOW_ONE_STEP_DEFAULT, publish=True)
workflow_object = self._download_workflow(workflow_id, style="editor")
put_response = self._update_workflow(workflow_id, workflow_object)
assert put_response.status_code == 200
[docs] def test_empty_collection_sort(self):
self._run_workflow(
"""class: GalaxyWorkflow
inputs:
input: collection
filter_file: data
steps:
filter_collection:
tool_id: __FILTER_FROM_FILE__
in:
input: input
how|filter_source: filter_file
sort_collection_1:
tool_id: __SORTLIST__
in:
input: filter_collection/output_filtered
sort_collection_2:
tool_id: __SORTLIST__
in:
input: filter_collection/output_discarded
merge_collection:
tool_id: __MERGE_COLLECTION__
in:
inputs_0|input: sort_collection_1/output
inputs_1|input: sort_collection_2/output
test_data:
input:
collection_type: list
elements:
- identifier: i1
content: "0"
filter_file: i1
""",
wait=True,
assert_ok=True,
)
[docs] @skip_without_tool("random_lines1")
def test_run_replace_params_over_default_delayed(self):
with self.dataset_populator.test_history() as history_id:
run_summary = self._run_workflow(
"""
class: GalaxyWorkflow
inputs:
input: data
steps:
first_cat:
tool_id: cat1
in:
input1: input
the_pause:
type: pause
in:
input: first_cat/out_file1
randomlines:
tool_id: random_lines1
in:
input: the_pause
num_lines:
default: 6
""",
test_data="""
step_parameters:
'3':
num_lines: 4
input:
value: 1.bed
type: File
""",
history_id=history_id,
wait=False,
)
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)
workflow_id = run_summary.workflow_id
invocation_id = run_summary.invocation_id
self.__review_paused_steps(workflow_id, invocation_id, order_index=2, action=True)
self.workflow_populator.wait_for_invocation_and_jobs(history_id, workflow_id, invocation_id)
result = self.dataset_populator.get_history_dataset_content(history_id)
assert result.count("\n") == 4
[docs] 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")
[docs] def test_invocation_filtering(self):
with self._different_user(email=f"{uuid4()}@test.com"):
# new user, start with no invocations
assert not self._assert_invocation_for_url_is("invocations")
self._run_jobs(
"""
class: GalaxyWorkflow
inputs:
input:
type: data
optional: true
steps: []
""",
wait=False,
)
first_invocation = self._assert_invocation_for_url_is("invocations")
new_history_id = self.dataset_populator.new_history()
# new history has no invocations
assert not self._assert_invocation_for_url_is(f"invocations?history_id={new_history_id}")
self._run_jobs(
"""
class: GalaxyWorkflow
inputs:
input:
type: data
optional: true
steps: []
""",
history_id=new_history_id,
wait=False,
)
# new history has one invocation now
new_invocation = self._assert_invocation_for_url_is(f"invocations?history_id={new_history_id}")
# filter invocation by workflow instance id
self._assert_invocation_for_url_is(
f"invocations?workflow_id={first_invocation['workflow_id']}&instance=true", first_invocation
)
# limit to 1, newest invocation first by default
self._assert_invocation_for_url_is("invocations?limit=1", target_invocation=new_invocation)
# limit to 1, descending sort on date
self._assert_invocation_for_url_is(
"invocations?limit=1&sort_by=create_time&sort_desc=true", target_invocation=new_invocation
)
# limit to 1, ascending sort on date
self._assert_invocation_for_url_is(
"invocations?limit=1&sort_by=create_time&sort_desc=false", target_invocation=first_invocation
)
# limit to 1, ascending sort on date, offset 1
self._assert_invocation_for_url_is(
"invocations?limit=1&sort_by=create_time&sort_desc=false&offset=1", target_invocation=new_invocation
)
def _assert_invocation_for_url_is(self, route, target_invocation=None):
response = self._get(route)
self._assert_status_code_is(response, 200)
invocations = response.json()
if target_invocation:
assert len(invocations) == 1
assert invocations[0]["id"] == target_invocation["id"]
if invocations:
assert len(invocations) == 1
return invocations[0]
[docs] @skip_without_tool("cat1")
def test_only_own_invocations_indexed_and_accessible(self):
workflow_id, usage = self._run_workflow_once_get_invocation("test_usage_accessiblity")
with self._different_user():
usage_details_response = self._get(f"workflows/{workflow_id}/usage/{usage['id']}")
self._assert_status_code_is(usage_details_response, 403)
index_response = self._get(f"workflows/{workflow_id}/invocations")
self._assert_status_code_is(index_response, 200)
assert len(index_response.json()) == 0
invocation_ids = self._all_user_invocation_ids()
assert usage["id"] in invocation_ids
with self._different_user():
invocation_ids = self._all_user_invocation_ids()
assert usage["id"] not in invocation_ids
[docs] @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", "workflow_id", "history_id")
# Check invocations for this workflow invocation by history and regardless of history.
history_invocations_response = self._get("invocations", {"history_id": usage_details["history_id"]})
self._assert_status_code_is(history_invocations_response, 200)
assert len(history_invocations_response.json()) == 1
assert history_invocations_response.json()[0]["id"] == invocation_id
# Check history invocations for this workflow invocation.
invocation_ids = self._all_user_invocation_ids()
assert invocation_id in invocation_ids
# Wait for the invocation to be fully scheduled, so we have details on all steps.
self._wait_for_invocation_state(workflow_id, invocation_id, "scheduled")
usage_details = self._invocation_details(workflow_id, invocation_id)
invocation_steps = usage_details["steps"]
invocation_input_step, invocation_tool_step = {}, {}
for invocation_step in invocation_steps:
self._assert_has_keys(invocation_step, "workflow_step_id", "order_index", "id")
order_index = invocation_step["order_index"]
assert order_index in [0, 1, 2], order_index
if order_index == 0:
invocation_input_step = invocation_step
elif order_index == 2:
invocation_tool_step = invocation_step
# Tool steps have non-null job_ids (deprecated though they may be)
assert invocation_input_step.get("job_id", None) is None
job_id = invocation_tool_step.get("job_id", None)
assert job_id is not None
invocation_tool_step_id = invocation_tool_step["id"]
invocation_tool_step_response = self._get(
f"workflows/{workflow_id}/invocations/{invocation_id}/steps/{invocation_tool_step_id}"
)
self._assert_status_code_is(invocation_tool_step_response, 200)
self._assert_has_keys(invocation_tool_step_response.json(), "id", "order_index", "job_id")
assert invocation_tool_step_response.json()["job_id"] == job_id
[docs] def test_invocation_with_collection_mapping(self):
workflow_id, invocation_id = self._run_mapping_workflow()
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", "workflow_id")
invocation_steps = usage_details["steps"]
invocation_input_step, invocation_tool_step = None, None
for invocation_step in invocation_steps:
self._assert_has_keys(invocation_step, "workflow_step_id", "order_index", "id")
order_index = invocation_step["order_index"]
assert order_index in [0, 1]
if invocation_step["order_index"] == 0:
assert invocation_input_step is None
invocation_input_step = invocation_step
else:
assert invocation_tool_step is None
invocation_tool_step = invocation_step
assert invocation_input_step
assert invocation_tool_step
# Tool steps have non-null job_ids (deprecated though they may be)
assert invocation_input_step.get("job_id", None) is None
assert invocation_tool_step.get("job_id", None) is None
assert invocation_tool_step["state"] == "scheduled"
usage_details = self._invocation_details(workflow_id, invocation_id, legacy_job_state="true")
# Assert some high-level things about the structure of data returned.
self._assert_has_keys(usage_details, "inputs", "steps", "workflow_id")
invocation_steps = usage_details["steps"]
invocation_input_step = None
invocation_tool_steps = []
for invocation_step in invocation_steps:
self._assert_has_keys(invocation_step, "workflow_step_id", "order_index", "id")
order_index = invocation_step["order_index"]
assert order_index in [0, 1]
if invocation_step["order_index"] == 0:
assert invocation_input_step is None
invocation_input_step = invocation_step
else:
invocation_tool_steps.append(invocation_step)
assert len(invocation_tool_steps) == 2
assert invocation_tool_steps[0]["state"] == "ok"
def _run_mapping_workflow(self):
history_id = self.dataset_populator.new_history()
summary = self._run_workflow(
"""
class: GalaxyWorkflow
inputs:
input_c: collection
steps:
cat1:
tool_id: cat1
in:
input1: input_c
""",
test_data="""
input_c:
collection_type: list
elements:
- identifier: i1
content: "0"
- identifier: i2
content: "1"
""",
history_id=history_id,
wait=True,
assert_ok=True,
)
workflow_id = summary.workflow_id
invocation_id = summary.invocation_id
return workflow_id, invocation_id
[docs] @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(f"workflows/{other_id}/usage")
self._assert_status_code_is(response, 200)
assert len(response.json()) == 0
run_workflow_response = self.workflow_populator.invoke_workflow_raw(
workflow_id, workflow_request, assert_ok=True
)
run_workflow_dict = run_workflow_response.json()
invocation_id = run_workflow_dict["id"]
usage_details_response = self._get(f"workflows/{other_id}/usage/{invocation_id}")
self._assert_status_code_is(usage_details_response, 200)
[docs] @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)
response = self._get(f"workflows/{workflow_id}/usage")
self._assert_status_code_is(response, 200)
assert len(response.json()) == 0
run_workflow_response = self.workflow_populator.invoke_workflow_raw(
workflow_id, workflow_request, assert_ok=True
)
run_workflow_dict = run_workflow_response.json()
invocation_id = run_workflow_dict["id"]
usage_details_response = self._get(f"workflows/{workflow_id}/usage/{invocation_id}")
self._assert_status_code_is(usage_details_response, 200)
[docs] @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)
response = self._get(f"workflows/{workflow_id}/usage")
self._assert_status_code_is(response, 200)
assert len(response.json()) == 0
run_workflow_response = self.workflow_populator.invoke_workflow_raw(
workflow_id, workflow_request, assert_ok=True
)
run_workflow_dict = run_workflow_response.json()
invocation_id = run_workflow_dict["id"]
with self._different_user():
usage_details_response = self._get(f"workflows/{workflow_id}/usage/{invocation_id}")
self._assert_status_code_is(usage_details_response, 403)
[docs] def test_workflow_publishing(self):
workflow_id = self.workflow_populator.simple_workflow("dummy")
response = self._show_workflow(workflow_id)
assert not response["published"]
assert not response["importable"]
published_worklow = self._put(f"workflows/{workflow_id}", data={"published": True}, json=True).json()
assert published_worklow["published"]
importable_worklow = self._put(f"workflows/{workflow_id}", data={"importable": True}, json=True).json()
assert importable_worklow["importable"]
unpublished_worklow = self._put(f"workflows/{workflow_id}", data={"published": False}, json=True).json()
assert not unpublished_worklow["published"]
unimportable_worklow = self._put(f"workflows/{workflow_id}", data={"importable": False}, json=True).json()
assert not unimportable_worklow["importable"]
[docs] def test_workflow_from_path_requires_admin(self):
# There are two ways to import workflows from paths, just verify both require an admin.
workflow_directory = mkdtemp()
try:
workflow_path = os.path.join(workflow_directory, "workflow.yml")
with open(workflow_path, "w") as f:
f.write(WORKFLOW_NESTED_REPLACEMENT_PARAMETER)
import_response = self.workflow_populator.import_workflow_from_path_raw(workflow_path)
self._assert_status_code_is(import_response, 403)
self._assert_error_code_is(import_response, error_codes.error_codes_by_name["ADMIN_REQUIRED"])
path_as_uri = f"file://{workflow_path}"
import_data = dict(archive_source=path_as_uri)
import_response = self._post("workflows", data=import_data)
self._assert_status_code_is(import_response, 403)
self._assert_error_code_is(import_response, error_codes.error_codes_by_name["ADMIN_REQUIRED"])
finally:
shutil.rmtree(workflow_directory)
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(
workflow_id,
history_id=history_id,
inputs=index_map,
)
return workflow_id, invocation_id
def _wait_for_invocation_non_new(self, workflow_id, invocation_id):
target_state_reached = False
for _ in range(50):
invocation = self._invocation_details(workflow_id, invocation_id)
if invocation["state"] != "new":
target_state_reached = True
break
time.sleep(0.25)
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 _ in range(25):
invocation = self._invocation_details(workflow_id, invocation_id)
if invocation["state"] == target_state:
target_state_reached = True
break
time.sleep(0.5)
return target_state_reached
def _update_workflow(self, workflow_id, workflow_object):
return self.workflow_populator.update_workflow(workflow_id, workflow_object)
def _invocation_step_details(self, workflow_id, invocation_id, step_id):
invocation_step_response = self._get(f"workflows/{workflow_id}/usage/{invocation_id}/steps/{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 = f"workflows/{workflow_id}/usage/{invocation_id}/steps/{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 _setup_random_x2_workflow_steps(self, name: str):
workflow_request, history_id, workflow_id = self._setup_random_x2_workflow(name)
random_line_steps = self._random_lines_steps(workflow_request, workflow_id)
return workflow_request, history_id, workflow_id, random_line_steps
def _random_lines_steps(self, workflow_request: dict, workflow_id: str):
workflow_summary_response = self._get(f"workflows/{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: str):
workflow = self.workflow_populator.load_random_x2_workflow(name)
uploaded_workflow_id = self.workflow_populator.create_workflow(workflow)
workflow_inputs = self.workflow_populator.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=f"hist_id={history_id}",
ds_map=dumps(
{
key: self._ds_entry(hda1),
}
),
)
return workflow_request, history_id, uploaded_workflow_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 = f"histories/{history}/contents"
history_contents = self.__history_contents(history)
hda_summary = next(hc for hc in history_contents if hc["hid"] == hid)
hda_info_response = self._get(f"{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 = f"histories/{history_id}/contents"
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) -> str:
return self.workflow_populator.invoke_workflow_and_assert_ok(*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 _show_workflow(self, workflow_id):
show_response = self._get(f"workflows/{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",
)
def _all_user_invocation_ids(self):
all_invocations_for_user = self._get("invocations")
self._assert_status_code_is(all_invocations_for_user, 200)
invocation_ids = [i["id"] for i in all_invocations_for_user.json()]
return invocation_ids
[docs]class AdminWorkflowsApiTestCase(BaseWorkflowsApiTestCase):
require_admin_user = True
[docs] def test_import_export_dynamic_tools(self):
workflow_id = self._upload_yaml_workflow(
"""
class: GalaxyWorkflow
steps:
- type: input
label: input1
- tool_id: cat1
label: first_cat
state:
input1:
$link: 0
- label: embed1
run:
class: GalaxyTool
command: echo 'hello world 2' > $output1
outputs:
output1:
format: txt
- tool_id: cat1
state:
input1:
$link: first_cat/out_file1
queries:
- input2:
$link: embed1/output1
test_data:
input1: "hello world"
"""
)
downloaded_workflow = self._download_workflow(workflow_id)
response = self.workflow_populator.create_workflow_response(downloaded_workflow)
workflow_id = response.json()["id"]
history_id = self.dataset_populator.new_history()
hda1 = self.dataset_populator.new_dataset(history_id, content="Hello World Second!")
workflow_request = dict(
inputs_by="name",
inputs=json.dumps({"input1": self._ds_entry(hda1)}),
)
self.workflow_populator.invoke_workflow_and_wait(workflow_id, history_id=history_id, request=workflow_request)
self.assertEqual(
"Hello World Second!\nhello world 2\n",
self.dataset_populator.get_history_dataset_content(history_id),
)