class HistoriesApiTestCase(api.ApiTestCase):
def setUp(self):
super(HistoriesApiTestCase, self).setUp()
self.dataset_populator = DatasetPopulator(self.galaxy_interactor)
self.dataset_collection_populator = DatasetCollectionPopulator(self.galaxy_interactor)
def test_create_history(self):
# Create a history.
create_response = self._create_history("TestHistory1")
created_id = create_response["id"]
# Make sure new history appears in index of user's histories.
index_response = self._get("histories").json()
indexed_history = [h for h in index_response if h["id"] == created_id][0]
self.assertEqual(indexed_history["name"], "TestHistory1")
def test_show_history(self):
history_id = self._create_history("TestHistoryForShow")["id"]
show_response = self._show(history_id)
self._assert_has_key(
show_response,
'id', 'name', 'annotation', 'size', 'contents_url',
'state', 'state_details', 'state_ids'
)
state_details = show_response["state_details"]
state_ids = show_response["state_ids"]
states = [
'discarded', 'empty', 'error', 'failed_metadata', 'new',
'ok', 'paused', 'queued', 'running', 'setting_metadata', 'upload'
]
assert isinstance(state_details, dict)
assert isinstance(state_ids, dict)
self._assert_has_keys(state_details, *states)
self._assert_has_keys(state_ids, *states)
def test_show_most_recently_used(self):
history_id = self._create_history("TestHistoryRecent")["id"]
show_response = self._get("histories/most_recently_used").json()
assert show_response["id"] == history_id
def test_index_order(self):
slightly_older_history_id = self._create_history("TestHistorySlightlyOlder")["id"]
newer_history_id = self._create_history("TestHistoryNewer")["id"]
index_response = self._get("histories").json()
assert index_response[0]["id"] == newer_history_id
assert index_response[1]["id"] == slightly_older_history_id
def test_delete(self):
# Setup a history and ensure it is in the index
history_id = self._create_history("TestHistoryForDelete")["id"]
index_response = self._get("histories").json()
assert index_response[0]["id"] == history_id
show_response = self._show(history_id)
assert not show_response["deleted"]
# Delete the history
self._delete("histories/%s" % history_id)
# Check can view it - but it is deleted
show_response = self._show(history_id)
assert show_response["deleted"]
# Verify it is dropped from history index
index_response = self._get("histories").json()
assert len(index_response) == 0 or index_response[0]["id"] != history_id
# Add deleted filter to index to view it
index_response = self._get("histories", {"deleted": "true"}).json()
assert index_response[0]["id"] == history_id
def test_purge(self):
history_id = self._create_history("TestHistoryForPurge")["id"]
data = {'purge': True}
self._delete("histories/%s" % history_id, data=data)
show_response = self._show(history_id)
assert show_response["deleted"]
assert show_response["purged"]
def test_undelete(self):
history_id = self._create_history("TestHistoryForDeleteAndUndelete")["id"]
self._delete("histories/%s" % history_id)
self._post("histories/deleted/%s/undelete" % history_id)
show_response = self._show(history_id)
assert not show_response["deleted"]
def test_update(self):
history_id = self._create_history("TestHistoryForUpdating")["id"]
self._update(history_id, {"name": "New Name"})
show_response = self._show(history_id)
assert show_response["name"] == "New Name"
unicode_name = u'桜ゲノム'
self._update(history_id, {"name": unicode_name})
show_response = self._show(history_id)
assert show_response["name"] == unicode_name, show_response
quoted_name = "'MooCow'"
self._update(history_id, {"name": quoted_name})
show_response = self._show(history_id)
assert show_response["name"] == quoted_name
self._update(history_id, {"deleted": True})
show_response = self._show(history_id)
assert show_response["deleted"], show_response
self._update(history_id, {"deleted": False})
show_response = self._show(history_id)
assert not show_response["deleted"]
self._update(history_id, {"published": True})
show_response = self._show(history_id)
assert show_response["published"]
self._update(history_id, {"genome_build": "hg18"})
show_response = self._show(history_id)
assert show_response["genome_build"] == "hg18"
self._update(history_id, {"annotation": "The annotation is cool"})
show_response = self._show(history_id)
assert show_response["annotation"] == "The annotation is cool"
self._update(history_id, {"annotation": unicode_name})
show_response = self._show(history_id)
assert show_response["annotation"] == unicode_name, show_response
self._update(history_id, {"annotation": quoted_name})
show_response = self._show(history_id)
assert show_response["annotation"] == quoted_name
def test_update_invalid_attribute(self):
history_id = self._create_history("TestHistoryForInvalidUpdating")["id"]
put_response = self._update(history_id, {"invalidkey": "moo"})
assert "invalidkey" not in put_response.json()
def test_update_invalid_types(self):
history_id = self._create_history("TestHistoryForUpdatingInvalidTypes")["id"]
for str_key in ["name", "annotation"]:
assert self._update(history_id, {str_key: False}).status_code == 400
for bool_key in ['deleted', 'importable', 'published']:
assert self._update(history_id, {bool_key: "a string"}).status_code == 400
assert self._update(history_id, {"tags": "a simple string"}).status_code == 400
assert self._update(history_id, {"tags": [True]}).status_code == 400
def test_invalid_keys(self):
invalid_history_id = "1234123412341234"
assert self._get("histories/%s" % invalid_history_id).status_code == 400
assert self._update(invalid_history_id, {"name": "new name"}).status_code == 400
assert self._delete("histories/%s" % invalid_history_id).status_code == 400
assert self._post("histories/deleted/%s/undelete" % invalid_history_id).status_code == 400
def test_create_anonymous_fails(self):
post_data = dict(name="CannotCreate")
# Using lower-level _api_url will cause key to not be injected.
histories_url = self._api_url("histories")
create_response = post(url=histories_url, data=post_data)
self._assert_status_code_is(create_response, 403)
def test_import_export(self):
history_name = "for_export_default"
history_id = self.dataset_populator.new_history(name=history_name)
self.dataset_populator.new_dataset(history_id, content="1 2 3")
deleted_hda = self.dataset_populator.new_dataset(history_id, content="1 2 3")
self.dataset_populator.delete_dataset(history_id, deleted_hda["id"])
deleted_details = self.dataset_populator.get_history_dataset_details(history_id, id=deleted_hda["id"])
assert deleted_details["deleted"]
imported_history_id = self._reimport_history(history_id, history_name, wait_on_history_length=2)
def upload_job_check(job):
assert job["tool_id"] == "upload1"
def check_discarded(hda):
assert hda["deleted"]
assert hda["state"] == "discarded", hda
assert hda["purged"] is True
self._check_imported_dataset(history_id=imported_history_id, hid=1, job_checker=upload_job_check)
self._check_imported_dataset(history_id=imported_history_id, hid=2, has_job=False, hda_checker=check_discarded, job_checker=upload_job_check)
imported_content = self.dataset_populator.get_history_dataset_content(
history_id=imported_history_id,
hid=1,
)
assert imported_content == "1 2 3\n"
def test_import_1901_histories(self):
f = open(self.test_data_resolver.get_filename("exports/1901_two_datasets.tgz"), 'rb')
import_data = dict(archive_source='', archive_file=f)
self._import_history_and_wait(import_data, "API Test History", wait_on_history_length=2)
def test_import_export_include_deleted(self):
history_name = "for_export_include_deleted"
history_id = self.dataset_populator.new_history(name=history_name)
self.dataset_populator.new_dataset(history_id, content="1 2 3")
deleted_hda = self.dataset_populator.new_dataset(history_id, content="1 2 3")
self.dataset_populator.delete_dataset(history_id, deleted_hda["id"])
imported_history_id = self._reimport_history(history_id, history_name, wait_on_history_length=2, export_kwds={"include_deleted": "True"})
self._assert_history_length(imported_history_id, 2)
def upload_job_check(job):
assert job["tool_id"] == "upload1"
def check_ok(hda):
assert hda["state"] == "ok", hda
assert hda["deleted"] is True, hda
self._check_imported_dataset(history_id=imported_history_id, hid=1, job_checker=upload_job_check)
self._check_imported_dataset(history_id=imported_history_id, hid=2, hda_checker=check_ok, job_checker=upload_job_check)
imported_content = self.dataset_populator.get_history_dataset_content(
history_id=imported_history_id,
hid=1,
)
assert imported_content == "1 2 3\n"
def test_import_metadata_regeneration(self):
history_name = "for_import_metadata_regeneration"
history_id = self.dataset_populator.new_history(name=history_name)
self.dataset_populator.new_dataset(history_id, content=open(self.test_data_resolver.get_filename("1.bam"), 'rb'), file_type='bam', wait=True)
imported_history_id = self._reimport_history(history_id, history_name)
self._assert_history_length(imported_history_id, 1)
self._check_imported_dataset(history_id=imported_history_id, hid=1)
import_bam_metadata = self.dataset_populator.get_history_dataset_details(
history_id=imported_history_id,
hid=1,
)
# The cleanup() method of the __IMPORT_HISTORY__ job (which is executed
# after the job has entered its final state):
# - creates a new dataset with 'ok' state and adds it to the history
# - starts a __SET_METADATA__ job to regenerate the dataset metadata, if
# needed
# We need to wait a bit for the creation of the __SET_METADATA__ job.
time.sleep(1)
self.dataset_populator.wait_for_history_jobs(imported_history_id, assert_ok=True)
bai_metadata = import_bam_metadata["meta_files"][0]
assert bai_metadata["file_type"] == "bam_index"
api_url = bai_metadata["download_url"].split("api/", 1)[1]
bai_response = self._get(api_url)
self._assert_status_code_is(bai_response, 200)
assert len(bai_response.content) > 4
def test_import_export_collection(self):
history_name = "for_export_with_collections"
history_id = self.dataset_populator.new_history(name=history_name)
self.dataset_collection_populator.create_list_in_history(history_id, contents=["Hello", "World"], direct_upload=True)
imported_history_id = self._reimport_history(history_id, history_name, wait_on_history_length=3)
self._assert_history_length(imported_history_id, 3)
def check_elements(elements):
assert len(elements) == 2
element0 = elements[0]["object"]
element1 = elements[1]["object"]
for element in [element0, element1]:
assert not element["visible"]
assert not element["deleted"]
assert element["state"] == "ok"
assert element0["hid"] == 2
assert element1["hid"] == 3
self._check_imported_collection(imported_history_id, hid=1, collection_type="list", elements_checker=check_elements)
def test_import_export_nested_collection(self):
history_name = "for_export_with_nested_collections"
history_id = self.dataset_populator.new_history(name=history_name)
self.dataset_collection_populator.create_list_of_pairs_in_history(history_id)
imported_history_id = self._reimport_history(history_id, history_name, wait_on_history_length=3)
self._assert_history_length(imported_history_id, 3)
def check_elements(elements):
assert len(elements) == 1
element0 = elements[0]["object"]
self._assert_has_keys(element0, "elements", "collection_type")
child_elements = element0["elements"]
assert len(child_elements) == 2
assert element0["collection_type"] == "paired"
self._check_imported_collection(imported_history_id, hid=1, collection_type="list:paired", elements_checker=check_elements)
def _reimport_history(self, history_id, history_name, wait_on_history_length=None, export_kwds={}):
# Ensure the history is ready to go...
self.dataset_populator.wait_for_history(history_id, assert_ok=True)
return self.dataset_populator.reimport_history(
history_id, history_name, wait_on_history_length=wait_on_history_length, export_kwds=export_kwds, url=self.url, api_key=self.galaxy_interactor.api_key
)
def _import_history_and_wait(self, import_data, history_name, wait_on_history_length=None):
imported_history_id = self.dataset_populator.import_history_and_wait_for_name(import_data, history_name)
if wait_on_history_length:
self.dataset_populator.wait_on_history_length(imported_history_id, wait_on_history_length)
return imported_history_id
def _assert_history_length(self, history_id, n):
contents_response = self._get("histories/%s/contents" % history_id)
self._assert_status_code_is(contents_response, 200)
contents = contents_response.json()
assert len(contents) == n, contents
def _check_imported_dataset(self, history_id, hid, has_job=True, hda_checker=None, job_checker=None):
imported_dataset_metadata = self.dataset_populator.get_history_dataset_details(
history_id=history_id,
hid=hid,
)
assert imported_dataset_metadata["history_content_type"] == "dataset"
assert imported_dataset_metadata["history_id"] == history_id
if hda_checker is not None:
hda_checker(imported_dataset_metadata)
assert "creating_job" in imported_dataset_metadata
job_id = imported_dataset_metadata["creating_job"]
if has_job:
assert job_id
job_details = self.dataset_populator.get_job_details(job_id, full=True)
assert job_details.status_code == 200, job_details.content
job = job_details.json()
assert 'history_id' in job, job
assert job['history_id'] == history_id, job
if job_checker is not None:
job_checker(job)
def _check_imported_collection(self, history_id, hid, collection_type=None, elements_checker=None):
imported_collection_metadata = self.dataset_populator.get_history_collection_details(
history_id=history_id,
hid=hid,
)
assert imported_collection_metadata["history_content_type"] == "dataset_collection"
assert imported_collection_metadata["history_id"] == history_id
assert "collection_type" in imported_collection_metadata
assert "elements" in imported_collection_metadata
if collection_type is not None:
assert imported_collection_metadata["collection_type"] == collection_type, imported_collection_metadata
if elements_checker is not None:
elements_checker(imported_collection_metadata["elements"])
def test_create_tag(self):
post_data = dict(name="TestHistoryForTag")
history_id = self._post("histories", data=post_data).json()["id"]
tag_data = dict(value="awesometagvalue")
tag_url = "histories/%s/tags/awesometagname" % history_id
tag_create_response = self._post(tag_url, data=tag_data)
self._assert_status_code_is(tag_create_response, 200)
def _show(self, history_id):
return self._get("histories/%s" % history_id).json()
def _update(self, history_id, data):
update_url = self._api_url("histories/%s" % history_id, use_key=True)
put_response = put(update_url, json=data)
return put_response
def _create_history(self, name):
post_data = dict(name=name)
create_response = self._post("histories", data=post_data).json()
self._assert_has_keys(create_response, "name", "id")
self.assertEqual(create_response["name"], name)
return create_response
class LibrariesApiTestCase(api.ApiTestCase, TestsDatasets):
def setUp(self):
super(LibrariesApiTestCase, self).setUp()
self.dataset_populator = DatasetPopulator(self.galaxy_interactor)
self.dataset_collection_populator = DatasetCollectionPopulator(
self.galaxy_interactor)
self.library_populator = LibraryPopulator(self.galaxy_interactor)
def test_create(self):
data = dict(name="CreateTestLibrary")
create_response = self._post("libraries", data=data, admin=True)
self._assert_status_code_is(create_response, 200)
library = create_response.json()
self._assert_has_keys(library, "name")
assert library["name"] == "CreateTestLibrary"
def test_delete(self):
library = self.library_populator.new_library("DeleteTestLibrary")
create_response = self._delete("libraries/%s" % library["id"],
admin=True)
self._assert_status_code_is(create_response, 200)
library = create_response.json()
self._assert_has_keys(library, "deleted")
assert library["deleted"] is True
# Test undeleting
data = dict(undelete=True)
create_response = self._delete("libraries/%s" % library["id"],
data=data,
admin=True)
library = create_response.json()
self._assert_status_code_is(create_response, 200)
assert library["deleted"] is False
def test_nonadmin(self):
# Anons can't create libs
data = dict(name="CreateTestLibrary")
create_response = self._post("libraries",
data=data,
admin=False,
anon=True)
self._assert_status_code_is(create_response, 403)
# Anons can't delete libs
library = self.library_populator.new_library("AnonDeleteTestLibrary")
create_response = self._delete("libraries/%s" % library["id"],
admin=False,
anon=True)
self._assert_status_code_is(create_response, 403)
# Anons can't update libs
data = dict(name="ChangedName",
description="ChangedDescription",
synopsis='ChangedSynopsis')
create_response = self._patch("libraries/%s" % library["id"],
data=data,
admin=False,
anon=True)
self._assert_status_code_is(create_response, 403)
def test_update(self):
library = self.library_populator.new_library("UpdateTestLibrary")
data = dict(name='ChangedName',
description='ChangedDescription',
synopsis='ChangedSynopsis')
create_response = self._patch("libraries/%s" % library["id"],
data=data,
admin=True)
self._assert_status_code_is(create_response, 200)
library = create_response.json()
self._assert_has_keys(library, 'name', 'description', 'synopsis')
assert library['name'] == 'ChangedName'
assert library['description'] == 'ChangedDescription'
assert library['synopsis'] == 'ChangedSynopsis'
def test_create_private_library_permissions(self):
library = self.library_populator.new_library("PermissionTestLibrary")
library_id = library["id"]
role_id = self.library_populator.user_private_role_id()
self.library_populator.set_permissions(library_id, role_id)
create_response = self._create_folder(library)
self._assert_status_code_is(create_response, 200)
def test_create_dataset_denied(self):
library = self.library_populator.new_private_library(
"ForCreateDatasets")
folder_response = self._create_folder(library)
self._assert_status_code_is(folder_response, 200)
folder_id = folder_response.json()[0]['id']
history_id = self.dataset_populator.new_history()
hda_id = self.dataset_populator.new_dataset(history_id,
content="1 2 3")['id']
with self._different_user():
payload = {'from_hda_id': hda_id}
create_response = self._post("folders/%s/contents" % folder_id,
payload)
self._assert_status_code_is(create_response, 403)
def test_show_private_dataset_permissions(self):
library, library_dataset = self.library_populator.new_library_dataset_in_private_library(
"ForCreateDatasets", wait=True)
with self._different_user():
response = self.library_populator.show_ldda(
library["id"], library_dataset["id"])
# TODO: this should really be 403 and a proper JSON exception.
self._assert_status_code_is(response, 400)
def test_create_dataset(self):
library, library_dataset = self.library_populator.new_library_dataset_in_private_library(
"ForCreateDatasets", wait=True)
self._assert_has_keys(library_dataset, "peek", "data_type")
assert library_dataset["peek"].find("create_test") >= 0
assert library_dataset["file_ext"] == "txt", library_dataset[
"file_ext"]
def test_fetch_upload_to_folder(self):
history_id, library, destination = self._setup_fetch_to_folder(
"flat_zip")
items = [{"src": "files", "dbkey": "hg19", "info": "my cool bed"}]
targets = [{"destination": destination, "items": items}]
payload = {
"history_id": history_id, # TODO: Shouldn't be needed :(
"targets": json.dumps(targets),
"__files": {
"files_0|file_data":
open(self.test_data_resolver.get_filename("4.bed"))
},
}
self.dataset_populator.fetch(payload)
dataset = self.library_populator.get_library_contents_with_path(
library["id"], "/4.bed")
assert dataset["file_size"] == 61, dataset
assert dataset["genome_build"] == "hg19", dataset
assert dataset["misc_info"] == "my cool bed", dataset
assert dataset["file_ext"] == "bed", dataset
def test_fetch_zip_to_folder(self):
history_id, library, destination = self._setup_fetch_to_folder(
"flat_zip")
bed_test_data_path = self.test_data_resolver.get_filename("4.bed.zip")
targets = [{
"destination": destination,
"items_from": "archive",
"src": "files",
}]
payload = {
"history_id": history_id, # TODO: Shouldn't be needed :(
"targets": json.dumps(targets),
"__files": {
"files_0|file_data": open(bed_test_data_path, 'rb')
}
}
self.dataset_populator.fetch(payload)
dataset = self.library_populator.get_library_contents_with_path(
library["id"], "/4.bed")
assert dataset["file_size"] == 61, dataset
def test_fetch_single_url_to_folder(self):
history_id, library, destination = self._setup_fetch_to_folder(
"single_url")
items = [{
"src": "url",
"url":
"https://raw.githubusercontent.com/galaxyproject/galaxy/dev/test-data/4.bed",
"MD5": "37b59762b59fff860460522d271bc111"
}]
targets = [{
"destination": destination,
"items": items,
}]
payload = {
"history_id": history_id, # TODO: Shouldn't be needed :(
"targets": json.dumps(targets),
"validate_hashes": True
}
self.dataset_populator.fetch(payload)
dataset = self.library_populator.get_library_contents_with_path(
library["id"], "/4.bed")
assert dataset["file_size"] == 61, dataset
def test_fetch_failed_validation(self):
# Exception handling is really rough here - we should be creating a dataset in error instead
# of just failing the job like this.
history_id, library, destination = self._setup_fetch_to_folder(
"single_url")
items = [{
"src": "url",
"url":
"https://raw.githubusercontent.com/galaxyproject/galaxy/dev/test-data/4.bed",
"MD5": "37b59762b59fff860460522d271bc112"
}]
targets = [{
"destination": destination,
"items": items,
}]
payload = {
"history_id": history_id, # TODO: Shouldn't be needed :(
"targets": json.dumps(targets),
"validate_hashes": True
}
tool_response = self.dataset_populator.fetch(payload, assert_ok=False)
job = self.dataset_populator.check_run(tool_response)
self.dataset_populator.wait_for_job(job["id"])
job = tool_response.json()["jobs"][0]
details = self.dataset_populator.get_job_details(job["id"]).json()
assert details["state"] == "error", details
def test_fetch_url_archive_to_folder(self):
history_id, library, destination = self._setup_fetch_to_folder(
"single_url")
targets = [{
"destination":
destination,
"items_from":
"archive",
"src":
"url",
"url":
"https://raw.githubusercontent.com/galaxyproject/galaxy/dev/test-data/4.bed.zip",
}]
payload = {
"history_id": history_id, # TODO: Shouldn't be needed :(
"targets": json.dumps(targets),
}
self.dataset_populator.fetch(payload)
dataset = self.library_populator.get_library_contents_with_path(
library["id"], "/4.bed")
assert dataset["file_size"] == 61, dataset
@unittest.skip # reference URLs changed, checksums now invalid.
def test_fetch_bagit_archive_to_folder(self):
history_id, library, destination = self._setup_fetch_to_folder(
"bagit_archive")
example_bag_path = self.test_data_resolver.get_filename(
"example-bag.zip")
targets = [{
"destination": destination,
"items_from": "bagit_archive",
"src": "files",
}]
payload = {
"history_id": history_id, # TODO: Shouldn't be needed :(
"targets": json.dumps(targets),
"__files": {
"files_0|file_data": open(example_bag_path)
},
}
self.dataset_populator.fetch(payload)
dataset = self.library_populator.get_library_contents_with_path(
library["id"], "/README.txt")
assert dataset["file_size"] == 66, dataset
dataset = self.library_populator.get_library_contents_with_path(
library["id"], "/bdbag-profile.json")
assert dataset["file_size"] == 723, dataset
def _setup_fetch_to_folder(self, test_name):
return self.library_populator.setup_fetch_to_folder(test_name)
def test_create_dataset_in_folder(self):
library = self.library_populator.new_private_library(
"ForCreateDatasets")
folder_response = self._create_folder(library)
self._assert_status_code_is(folder_response, 200)
folder_id = folder_response.json()[0]['id']
history_id = self.dataset_populator.new_history()
hda_id = self.dataset_populator.new_dataset(history_id,
content="1 2 3")['id']
payload = {'from_hda_id': hda_id}
create_response = self._post("folders/%s/contents" % folder_id,
payload)
self._assert_status_code_is(create_response, 200)
self._assert_has_keys(create_response.json(), "name", "id")
def test_update_dataset_in_folder(self):
ld = self._create_dataset_in_folder_in_library("ForUpdateDataset")
data = {
'name': 'updated_name',
'file_ext': 'fastq',
'misc_info': 'updated_info',
'genome_build': 'updated_genome_build'
}
create_response = self._patch("libraries/datasets/%s" %
ld.json()["id"],
data=data)
self._assert_status_code_is(create_response, 200)
self._assert_has_keys(create_response.json(), "name", "file_ext",
"misc_info", "genome_build")
def test_invalid_update_dataset_in_folder(self):
ld = self._create_dataset_in_folder_in_library(
"ForInvalidUpdateDataset")
data = {'file_ext': 'nonexisting_type'}
create_response = self._patch("libraries/datasets/%s" %
ld.json()["id"],
data=data)
self._assert_status_code_is(create_response, 400)
assert 'This Galaxy does not recognize the datatype of:' in create_response.json(
)['err_msg']
def test_detect_datatype_of_dataset_in_folder(self):
ld = self._create_dataset_in_folder_in_library("ForDetectDataset")
# Wait for metadata job to finish.
time.sleep(2)
data = {'file_ext': 'data'}
create_response = self._patch("libraries/datasets/%s" %
ld.json()["id"],
data=data)
self._assert_status_code_is(create_response, 200)
self._assert_has_keys(create_response.json(), "file_ext")
assert create_response.json()["file_ext"] == "data"
# Wait for metadata job to finish.
time.sleep(2)
data = {'file_ext': 'auto'}
create_response = self._patch("libraries/datasets/%s" %
ld.json()["id"],
data=data)
self._assert_status_code_is(create_response, 200)
self._assert_has_keys(create_response.json(), "file_ext")
assert create_response.json()["file_ext"] == "txt"
def test_create_datasets_in_library_from_collection(self):
library = self.library_populator.new_private_library(
"ForCreateDatasetsFromCollection")
folder_response = self._create_folder(library)
self._assert_status_code_is(folder_response, 200)
folder_id = folder_response.json()[0]['id']
history_id = self.dataset_populator.new_history()
hdca_id = self.dataset_collection_populator.create_list_in_history(
history_id, contents=["xxx", "yyy"],
direct_upload=True).json()["outputs"][0]["id"]
payload = {
'from_hdca_id': hdca_id,
'create_type': 'file',
'folder_id': folder_id
}
create_response = self._post("libraries/%s/contents" % library['id'],
payload)
self._assert_status_code_is(create_response, 200)
def test_create_datasets_in_folder_from_collection(self):
library = self.library_populator.new_private_library(
"ForCreateDatasetsFromCollection")
history_id = self.dataset_populator.new_history()
hdca_id = self.dataset_collection_populator.create_list_in_history(
history_id, contents=["xxx", "yyy"],
direct_upload=True).json()["outputs"][0]["id"]
folder_response = self._create_folder(library)
self._assert_status_code_is(folder_response, 200)
folder_id = folder_response.json()[0]['id']
payload = {'from_hdca_id': hdca_id}
create_response = self._post("folders/%s/contents" % folder_id,
payload)
self._assert_status_code_is(create_response, 200)
assert len(create_response.json()) == 2
# Also test that anything different from a flat dataset collection list
# is refused
hdca_pair_id = self.dataset_collection_populator.create_list_of_pairs_in_history(
history_id).json()["outputs"][0]['id']
payload = {'from_hdca_id': hdca_pair_id}
create_response = self._post("folders/%s/contents" % folder_id,
payload)
self._assert_status_code_is(create_response, 501)
assert create_response.json(
)['err_msg'] == 'Cannot add nested collections to library. Please flatten your collection first.'
def _create_folder(self, library):
create_data = dict(
folder_id=library["root_folder_id"],
create_type="folder",
name="New Folder",
)
return self._post("libraries/%s/contents" % library["id"],
data=create_data)
def _create_dataset_in_folder_in_library(self, library_name):
library = self.library_populator.new_private_library(library_name)
folder_response = self._create_folder(library)
self._assert_status_code_is(folder_response, 200)
folder_id = folder_response.json()[0]['id']
history_id = self.dataset_populator.new_history()
hda_id = self.dataset_populator.new_dataset(history_id,
content="1 2 3")['id']
payload = {
'from_hda_id': hda_id,
'create_type': 'file',
'folder_id': folder_id
}
ld = self._post("libraries/%s/contents" % folder_id, payload)
return ld
class JobsApiTestCase(api.ApiTestCase):
def setUp(self):
super(JobsApiTestCase, self).setUp()
self.dataset_populator = DatasetPopulator(self.galaxy_interactor)
self.dataset_collection_populator = DatasetCollectionPopulator(
self.galaxy_interactor)
@uses_test_history(require_new=True)
def test_index(self, history_id):
# Create HDA to ensure at least one job exists...
self.__history_with_new_dataset(history_id)
jobs = self.__jobs_index()
assert "upload1" in map(itemgetter("tool_id"), jobs)
@uses_test_history(require_new=True)
def test_system_details_admin_only(self, history_id):
self.__history_with_new_dataset(history_id)
jobs = self.__jobs_index(admin=False)
job = jobs[0]
self._assert_not_has_keys(job, "command_line", "external_id")
jobs = self.__jobs_index(admin=True)
job = jobs[0]
self._assert_has_keys(job, "command_line", "external_id")
@uses_test_history(require_new=True)
def test_index_state_filter(self, history_id):
# Initial number of ok jobs
original_count = len(self.__uploads_with_state("ok"))
# Run through dataset upload to ensure num uplaods at least greater
# by 1.
self.__history_with_ok_dataset(history_id)
# Verify number of ok jobs is actually greater.
count_increased = False
for i in range(10):
new_count = len(self.__uploads_with_state("ok"))
if original_count < new_count:
count_increased = True
break
time.sleep(.1)
if not count_increased:
template = "Jobs in ok state did not increase (was %d, now %d)"
message = template % (original_count, new_count)
raise AssertionError(message)
@uses_test_history(require_new=True)
def test_index_date_filter(self, history_id):
self.__history_with_new_dataset(history_id)
two_weeks_ago = (datetime.datetime.utcnow() -
datetime.timedelta(7)).isoformat()
last_week = (datetime.datetime.utcnow() -
datetime.timedelta(7)).isoformat()
next_week = (datetime.datetime.utcnow() +
datetime.timedelta(7)).isoformat()
today = datetime.datetime.utcnow().isoformat()
tomorrow = (datetime.datetime.utcnow() +
datetime.timedelta(1)).isoformat()
jobs = self.__jobs_index(data={
"date_range_min": today[0:10],
"date_range_max": tomorrow[0:10]
})
assert len(jobs) > 0
today_job_id = jobs[0]["id"]
jobs = self.__jobs_index(data={
"date_range_min": two_weeks_ago,
"date_range_max": last_week
})
assert today_job_id not in map(itemgetter("id"), jobs)
jobs = self.__jobs_index(data={
"date_range_min": last_week,
"date_range_max": next_week
})
assert today_job_id in map(itemgetter("id"), jobs)
@uses_test_history(require_new=True)
def test_index_history(self, history_id):
self.__history_with_new_dataset(history_id)
jobs = self.__jobs_index(data={"history_id": history_id})
assert len(jobs) > 0
with self.dataset_populator.test_history() as other_history_id:
jobs = self.__jobs_index(data={"history_id": other_history_id})
assert len(jobs) == 0
@uses_test_history(require_new=True)
def test_index_multiple_states_filter(self, history_id):
# Initial number of ok jobs
original_count = len(self.__uploads_with_state("ok", "new"))
# Run through dataset upload to ensure num uplaods at least greater
# by 1.
self.__history_with_ok_dataset(history_id)
# Verify number of ok jobs is actually greater.
new_count = len(self.__uploads_with_state("new", "ok"))
assert original_count < new_count, new_count
@uses_test_history(require_new=True)
def test_show(self, history_id):
# Create HDA to ensure at least one job exists...
self.__history_with_new_dataset(history_id)
jobs_response = self._get("jobs")
first_job = jobs_response.json()[0]
self._assert_has_key(first_job, 'id', 'state', 'exit_code',
'update_time', 'create_time')
job_id = first_job["id"]
show_jobs_response = self._get("jobs/%s" % job_id)
self._assert_status_code_is(show_jobs_response, 200)
job_details = show_jobs_response.json()
self._assert_has_key(job_details, 'id', 'state', 'exit_code',
'update_time', 'create_time')
show_jobs_response = self._get("jobs/%s" % job_id, {"full": True})
self._assert_status_code_is(show_jobs_response, 200)
job_details = show_jobs_response.json()
self._assert_has_key(job_details, 'id', 'state', 'exit_code',
'update_time', 'create_time', 'stdout', 'stderr',
'job_messages')
@uses_test_history(require_new=True)
def test_show_security(self, history_id):
self.__history_with_new_dataset(history_id)
jobs_response = self._get("jobs", data={"history_id": history_id})
job = jobs_response.json()[0]
job_id = job["id"]
show_jobs_response = self._get("jobs/%s" % job_id, admin=False)
self._assert_not_has_keys(show_jobs_response.json(), "command_line",
"external_id")
# TODO: Re-activate test case when API accepts privacy settings
# with self._different_user():
# show_jobs_response = self._get( "jobs/%s" % job_id, admin=False )
# self._assert_status_code_is( show_jobs_response, 200 )
show_jobs_response = self._get("jobs/%s" % job_id, admin=True)
self._assert_has_keys(show_jobs_response.json(), "command_line",
"external_id")
def _run_detect_errors(self, history_id, inputs):
payload = self.dataset_populator.run_tool_payload(
tool_id='detect_errors_aggressive',
inputs=inputs,
history_id=history_id,
)
return self._post("tools", data=payload).json()
@skip_without_tool("detect_errors_aggressive")
def test_unhide_on_error(self):
with self.dataset_populator.test_history() as history_id:
inputs = {'error_bool': 'true'}
run_response = self._run_detect_errors(history_id=history_id,
inputs=inputs)
job_id = run_response['jobs'][0]["id"]
self.dataset_populator.wait_for_job(job_id)
job = self.dataset_populator.get_job_details(job_id).json()
assert job['state'] == 'error'
dataset = self.dataset_populator.get_history_dataset_details(
history_id=history_id,
dataset_id=run_response['outputs'][0]['id'],
assert_ok=False)
assert dataset['visible']
@skip_without_tool("detect_errors_aggressive")
def test_no_unhide_on_error_if_mapped_over(self):
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")]).json()
inputs = {
'error_bool': 'true',
'dataset': {
'batch': True,
'values': [{
'src': 'hdca',
'id': hdca1['id']
}],
}
}
run_response = self._run_detect_errors(history_id=history_id,
inputs=inputs)
job_id = run_response['jobs'][0]["id"]
self.dataset_populator.wait_for_job(job_id)
job = self.dataset_populator.get_job_details(job_id).json()
assert job['state'] == 'error'
dataset = self.dataset_populator.get_history_dataset_details(
history_id=history_id,
dataset_id=run_response['outputs'][0]['id'],
assert_ok=False)
assert not dataset['visible']
@skip_without_tool('empty_output')
def test_common_problems(self):
with self.dataset_populator.test_history() as history_id:
empty_run_response = self.dataset_populator.run_tool(
tool_id='empty_output',
inputs={},
history_id=history_id,
)
empty_hda = empty_run_response["outputs"][0]
cat_empty_twice_run_response = self.dataset_populator.run_tool(
tool_id='cat1',
inputs={
'input1': {
'src': 'hda',
'id': empty_hda['id']
},
'queries_0|input2': {
'src': 'hda',
'id': empty_hda['id']
}
},
history_id=history_id,
)
empty_output_job = empty_run_response["jobs"][0]
cat_empty_job = cat_empty_twice_run_response["jobs"][0]
empty_output_common_problems_response = self._get(
'jobs/%s/common_problems' % empty_output_job["id"]).json()
cat_empty_common_problems_response = self._get(
'jobs/%s/common_problems' % cat_empty_job["id"]).json()
self._assert_has_keys(empty_output_common_problems_response,
"has_empty_inputs", "has_duplicate_inputs")
self._assert_has_keys(cat_empty_common_problems_response,
"has_empty_inputs", "has_duplicate_inputs")
assert not empty_output_common_problems_response["has_empty_inputs"]
assert cat_empty_common_problems_response["has_empty_inputs"]
assert not empty_output_common_problems_response[
"has_duplicate_inputs"]
assert cat_empty_common_problems_response["has_duplicate_inputs"]
@skip_without_tool('detect_errors_aggressive')
def test_report_error(self):
with self.dataset_populator.test_history() as history_id:
payload = self.dataset_populator.run_tool_payload(
tool_id='detect_errors_aggressive',
inputs={'error_bool': 'true'},
history_id=history_id,
)
run_response = self._post("tools", data=payload).json()
job_id = run_response['jobs'][0]["id"]
dataset_id = run_response['outputs'][0]['id']
response = self._post('jobs/%s/error' % job_id,
data={'dataset_id': dataset_id})
assert response.status_code == 200
@skip_without_tool('detect_errors_aggressive')
def test_report_error_anon(self):
# Need to get a cookie and use that for anonymous tool runs
cookies = requests.get(self.url).cookies
payload = json.dumps({
"tool_id": "detect_errors_aggressive",
"inputs": {
"error_bool": "true"
}
})
run_response = requests.post("%s/tools" %
self.galaxy_interactor.api_url,
data=payload,
cookies=cookies).json()
job_id = run_response['jobs'][0]["id"]
dataset_id = run_response['outputs'][0]['id']
response = requests.post('%s/jobs/%s/error' %
(self.galaxy_interactor.api_url, job_id),
params={
'email': '*****@*****.**',
'dataset_id': dataset_id
},
cookies=cookies)
assert response.status_code == 200
@uses_test_history(require_new=True)
def test_deleting_output_keep_running_until_all_deleted(self, history_id):
job_state, outputs = self._setup_running_two_output_job(
history_id, 120)
self._hack_to_skip_test_if_state_ok(job_state)
# Delete one of the two outputs and make sure the job is still running.
self._raw_update_history_item(history_id, outputs[0]["id"],
{"deleted": True})
self._hack_to_skip_test_if_state_ok(job_state)
time.sleep(1)
self._hack_to_skip_test_if_state_ok(job_state)
state = job_state().json()["state"]
assert state == "running", state
# Delete the second output and make sure the job is cancelled.
self._raw_update_history_item(history_id, outputs[1]["id"],
{"deleted": True})
final_state = wait_on_state(job_state, assert_ok=False, timeout=15)
assert final_state in ["deleted_new", "deleted"], final_state
@uses_test_history(require_new=True)
def test_purging_output_keep_running_until_all_purged(self, history_id):
job_state, outputs = self._setup_running_two_output_job(
history_id, 120)
# Pretty much right away after the job is running, these paths should be populated -
# if they are grab them and make sure they are deleted at the end of the job.
dataset_1 = self._get_history_item_as_admin(history_id,
outputs[0]["id"])
dataset_2 = self._get_history_item_as_admin(history_id,
outputs[1]["id"])
if "file_name" in dataset_1:
output_dataset_paths = [
dataset_1["file_name"], dataset_2["file_name"]
]
# This may or may not exist depending on if the test is local or not.
output_dataset_paths_exist = os.path.exists(
output_dataset_paths[0])
else:
output_dataset_paths = []
output_dataset_paths_exist = False
self._hack_to_skip_test_if_state_ok(job_state)
current_state = job_state().json()["state"]
assert current_state == "running", current_state
# Purge one of the two outputs and make sure the job is still running.
self._raw_update_history_item(history_id, outputs[0]["id"],
{"purged": True})
time.sleep(1)
self._hack_to_skip_test_if_state_ok(job_state)
current_state = job_state().json()["state"]
assert current_state == "running", current_state
# Purge the second output and make sure the job is cancelled.
self._raw_update_history_item(history_id, outputs[1]["id"],
{"purged": True})
final_state = wait_on_state(job_state, assert_ok=False, timeout=15)
assert final_state in ["deleted_new", "deleted"], final_state
def paths_deleted():
if not os.path.exists(
output_dataset_paths[0]) and not os.path.exists(
output_dataset_paths[1]):
return True
if output_dataset_paths_exist:
wait_on(paths_deleted, "path deletion")
@uses_test_history(require_new=True)
def test_purging_output_cleaned_after_ok_run(self, history_id):
job_state, outputs = self._setup_running_two_output_job(history_id, 10)
# Pretty much right away after the job is running, these paths should be populated -
# if they are grab them and make sure they are deleted at the end of the job.
dataset_1 = self._get_history_item_as_admin(history_id,
outputs[0]["id"])
dataset_2 = self._get_history_item_as_admin(history_id,
outputs[1]["id"])
if "file_name" in dataset_1:
output_dataset_paths = [
dataset_1["file_name"], dataset_2["file_name"]
]
# This may or may not exist depending on if the test is local or not.
output_dataset_paths_exist = os.path.exists(
output_dataset_paths[0])
else:
output_dataset_paths = []
output_dataset_paths_exist = False
if not output_dataset_paths_exist:
# Given this Galaxy configuration - there is nothing more to be tested here.
# Consider throwing a skip instead.
return
# Purge one of the two outputs and wait for the job to complete.
self._raw_update_history_item(history_id, outputs[0]["id"],
{"purged": True})
wait_on_state(job_state, assert_ok=True)
if output_dataset_paths_exist:
time.sleep(.5)
# Make sure the non-purged dataset is on disk and the purged one is not.
assert os.path.exists(output_dataset_paths[1])
assert not os.path.exists(output_dataset_paths[0])
def _hack_to_skip_test_if_state_ok(self, job_state):
from nose.plugins.skip import SkipTest
if job_state().json()["state"] == "ok":
message = "Job state switch from running to ok too quickly - the rest of the test requires the job to be in a running state. Skipping test."
raise SkipTest(message)
def _setup_running_two_output_job(self, history_id, sleep_time):
payload = self.dataset_populator.run_tool_payload(
tool_id='create_2',
inputs=dict(sleep_time=sleep_time, ),
history_id=history_id,
)
run_response = self._post("tools", data=payload).json()
outputs = run_response["outputs"]
jobs = run_response["jobs"]
assert len(outputs) == 2
assert len(jobs) == 1
def job_state():
jobs_response = self._get("jobs/%s" % jobs[0]["id"])
return jobs_response
# Give job some time to get up and running.
time.sleep(2)
running_state = wait_on_state(job_state,
skip_states=["queued", "new"],
assert_ok=False,
timeout=15)
assert running_state == "running", running_state
def job_state():
jobs_response = self._get("jobs/%s" % jobs[0]["id"])
return jobs_response
return job_state, outputs
def _raw_update_history_item(self, history_id, item_id, data):
update_url = self._api_url("histories/%s/contents/%s" %
(history_id, item_id),
use_key=True)
update_response = requests.put(update_url, json=data)
assert_status_code_is_ok(update_response)
return update_response
@skip_without_tool("cat_data_and_sleep")
@uses_test_history(require_new=True)
def test_resume_job(self, history_id):
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")
# Submit first job
payload = self.dataset_populator.run_tool_payload(
tool_id='cat_data_and_sleep',
inputs={
'sleep_time': 15,
'input1': {
'src': 'hda',
'id': hda2['id']
},
'queries_0|input2': {
'src': 'hda',
'id': hda2['id']
}
},
history_id=history_id,
)
run_response = self._post("tools", data=payload).json()
output = run_response["outputs"][0]
# Submit second job that waits on job1
payload = self.dataset_populator.run_tool_payload(
tool_id='cat1',
inputs={
'input1': {
'src': 'hda',
'id': hda1['id']
},
'queries_0|input2': {
'src': 'hda',
'id': output['id']
}
},
history_id=history_id,
)
run_response = self._post("tools", data=payload).json()
job_id = run_response['jobs'][0]['id']
output = run_response["outputs"][0]
# Delete second jobs input while second job is waiting for first job
delete_response = self._delete("histories/%s/contents/%s" %
(history_id, hda1['id']))
self._assert_status_code_is(delete_response, 200)
self.dataset_populator.wait_for_history_jobs(history_id,
assert_ok=False)
dataset_details = self._get("histories/%s/contents/%s" %
(history_id, output['id'])).json()
assert dataset_details['state'] == 'paused'
# Undelete input dataset
undelete_response = self._put("histories/%s/contents/%s" %
(history_id, hda1['id']),
data=json.dumps({'deleted': False}))
self._assert_status_code_is(undelete_response, 200)
resume_response = self._put("jobs/%s/resume" % job_id)
self._assert_status_code_is(resume_response, 200)
self.dataset_populator.wait_for_history_jobs(history_id,
assert_ok=True)
dataset_details = self._get("histories/%s/contents/%s" %
(history_id, output['id'])).json()
assert dataset_details['state'] == 'ok'
def _get_history_item_as_admin(self, history_id, item_id):
response = self._get("histories/%s/contents/%s?view=detailed" %
(history_id, item_id),
admin=True)
assert_status_code_is_ok(response)
return response.json()
@uses_test_history(require_new=True)
def test_search(self, history_id):
dataset_id = self.__history_with_ok_dataset(history_id)
# We first copy the datasets, so that the update time is lower than the job creation time
new_history_id = self.dataset_populator.new_history()
copy_payload = {
"content": dataset_id,
"source": "hda",
"type": "dataset"
}
copy_response = self._post("histories/%s/contents" % new_history_id,
data=copy_payload)
self._assert_status_code_is(copy_response, 200)
inputs = json.dumps({'input1': {'src': 'hda', 'id': dataset_id}})
self._job_search(tool_id='cat1', history_id=history_id, inputs=inputs)
# We test that a job can be found even if the dataset has been copied to another history
new_dataset_id = copy_response.json()['id']
copied_inputs = json.dumps(
{'input1': {
'src': 'hda',
'id': new_dataset_id
}})
search_payload = self._search_payload(history_id=history_id,
tool_id='cat1',
inputs=copied_inputs)
self._search(search_payload, expected_search_count=1)
# Now we delete the original input HDA that was used -- we should still be able to find the job
delete_respone = self._delete("histories/%s/contents/%s" %
(history_id, dataset_id))
self._assert_status_code_is(delete_respone, 200)
self._search(search_payload, expected_search_count=1)
# Now we also delete the copy -- we shouldn't find a job
delete_respone = self._delete("histories/%s/contents/%s" %
(new_history_id, new_dataset_id))
self._assert_status_code_is(delete_respone, 200)
self._search(search_payload, expected_search_count=0)
@uses_test_history(require_new=True)
def test_search_handle_identifiers(self, history_id):
# Test that input name and element identifier of a jobs' output must match for a job to be returned.
dataset_id = self.__history_with_ok_dataset(history_id)
inputs = json.dumps({'input1': {'src': 'hda', 'id': dataset_id}})
self._job_search(tool_id='identifier_single',
history_id=history_id,
inputs=inputs)
dataset_details = self._get("histories/%s/contents/%s" %
(history_id, dataset_id)).json()
dataset_details['name'] = 'Renamed Test Dataset'
dataset_update_response = self._put(
"histories/%s/contents/%s" % (history_id, dataset_id),
data=dict(name='Renamed Test Dataset'))
self._assert_status_code_is(dataset_update_response, 200)
assert dataset_update_response.json()['name'] == 'Renamed Test Dataset'
search_payload = self._search_payload(history_id=history_id,
tool_id='identifier_single',
inputs=inputs)
self._search(search_payload, expected_search_count=0)
@uses_test_history(require_new=True)
def test_search_delete_outputs(self, history_id):
dataset_id = self.__history_with_ok_dataset(history_id)
inputs = json.dumps({'input1': {'src': 'hda', 'id': dataset_id}})
tool_response = self._job_search(tool_id='cat1',
history_id=history_id,
inputs=inputs)
output_id = tool_response.json()['outputs'][0]['id']
delete_respone = self._delete("histories/%s/contents/%s" %
(history_id, output_id))
self._assert_status_code_is(delete_respone, 200)
search_payload = self._search_payload(history_id=history_id,
tool_id='cat1',
inputs=inputs)
self._search(search_payload, expected_search_count=0)
@uses_test_history(require_new=True)
def test_search_with_hdca_list_input(self, history_id):
list_id_a = self.__history_with_ok_collection(collection_type='list',
history_id=history_id)
list_id_b = self.__history_with_ok_collection(collection_type='list',
history_id=history_id)
inputs = json.dumps({
'f1': {
'src': 'hdca',
'id': list_id_a
},
'f2': {
'src': 'hdca',
'id': list_id_b
},
})
tool_response = self._job_search(tool_id='multi_data_param',
history_id=history_id,
inputs=inputs)
# We switch the inputs, this should not return a match
inputs_switched = json.dumps({
'f2': {
'src': 'hdca',
'id': list_id_a
},
'f1': {
'src': 'hdca',
'id': list_id_b
},
})
search_payload = self._search_payload(history_id=history_id,
tool_id='multi_data_param',
inputs=inputs_switched)
self._search(search_payload, expected_search_count=0)
# We delete the ouput (this is a HDA, as multi_data_param reduces collections)
# and use the correct input job definition, the job should not be found
output_id = tool_response.json()['outputs'][0]['id']
delete_respone = self._delete("histories/%s/contents/%s" %
(history_id, output_id))
self._assert_status_code_is(delete_respone, 200)
search_payload = self._search_payload(history_id=history_id,
tool_id='multi_data_param',
inputs=inputs)
self._search(search_payload, expected_search_count=0)
@uses_test_history(require_new=True)
def test_search_delete_hdca_output(self, history_id):
list_id_a = self.__history_with_ok_collection(collection_type='list',
history_id=history_id)
inputs = json.dumps({
'input1': {
'src': 'hdca',
'id': list_id_a
},
})
tool_response = self._job_search(tool_id='collection_creates_list',
history_id=history_id,
inputs=inputs)
output_id = tool_response.json()['outputs'][0]['id']
# We delete a single tool output, no job should be returned
delete_respone = self._delete("histories/%s/contents/%s" %
(history_id, output_id))
self._assert_status_code_is(delete_respone, 200)
search_payload = self._search_payload(
history_id=history_id,
tool_id='collection_creates_list',
inputs=inputs)
self._search(search_payload, expected_search_count=0)
tool_response = self._job_search(tool_id='collection_creates_list',
history_id=history_id,
inputs=inputs)
output_collection_id = tool_response.json(
)['output_collections'][0]['id']
# We delete a collection output, no job should be returned
delete_respone = self._delete(
"histories/%s/contents/dataset_collections/%s" %
(history_id, output_collection_id))
self._assert_status_code_is(delete_respone, 200)
search_payload = self._search_payload(
history_id=history_id,
tool_id='collection_creates_list',
inputs=inputs)
self._search(search_payload, expected_search_count=0)
@uses_test_history(require_new=True)
def test_search_with_hdca_pair_input(self, history_id):
list_id_a = self.__history_with_ok_collection(collection_type='pair',
history_id=history_id)
inputs = json.dumps({
'f1': {
'src': 'hdca',
'id': list_id_a
},
'f2': {
'src': 'hdca',
'id': list_id_a
},
})
self._job_search(tool_id='multi_data_param',
history_id=history_id,
inputs=inputs)
# We test that a job can be found even if the collection has been copied to another history
new_history_id = self.dataset_populator.new_history()
copy_payload = {
"content": list_id_a,
"source": "hdca",
"type": "dataset_collection"
}
copy_response = self._post("histories/%s/contents" % new_history_id,
data=copy_payload)
self._assert_status_code_is(copy_response, 200)
new_list_a = copy_response.json()['id']
copied_inputs = json.dumps({
'f1': {
'src': 'hdca',
'id': new_list_a
},
'f2': {
'src': 'hdca',
'id': new_list_a
},
})
search_payload = self._search_payload(history_id=new_history_id,
tool_id='multi_data_param',
inputs=copied_inputs)
self._search(search_payload, expected_search_count=1)
# Now we delete the original input HDCA that was used -- we should still be able to find the job
delete_respone = self._delete(
"histories/%s/contents/dataset_collections/%s" %
(history_id, list_id_a))
self._assert_status_code_is(delete_respone, 200)
self._search(search_payload, expected_search_count=1)
# Now we also delete the copy -- we shouldn't find a job
delete_respone = self._delete(
"histories/%s/contents/dataset_collections/%s" %
(history_id, new_list_a))
self._assert_status_code_is(delete_respone, 200)
self._search(search_payload, expected_search_count=0)
@uses_test_history(require_new=True)
def test_search_with_hdca_list_pair_input(self, history_id):
list_id_a = self.__history_with_ok_collection(
collection_type='list:pair', history_id=history_id)
inputs = json.dumps({
'f1': {
'src': 'hdca',
'id': list_id_a
},
'f2': {
'src': 'hdca',
'id': list_id_a
},
})
self._job_search(tool_id='multi_data_param',
history_id=history_id,
inputs=inputs)
def _job_search(self, tool_id, history_id, inputs):
search_payload = self._search_payload(history_id=history_id,
tool_id=tool_id,
inputs=inputs)
empty_search_response = self._post("jobs/search", data=search_payload)
self._assert_status_code_is(empty_search_response, 200)
self.assertEqual(len(empty_search_response.json()), 0)
tool_response = self._post("tools", data=search_payload)
self.dataset_populator.wait_for_tool_run(history_id,
run_response=tool_response)
self._search(search_payload, expected_search_count=1)
return tool_response
def _search_payload(self, history_id, tool_id, inputs, state='ok'):
search_payload = dict(tool_id=tool_id,
inputs=inputs,
history_id=history_id,
state=state)
return search_payload
def _search(self, payload, expected_search_count=1):
# in case job and history aren't updated at exactly the same
# time give time to wait
for i in range(5):
search_count = self._search_count(payload)
if search_count == expected_search_count:
break
time.sleep(1)
assert search_count == expected_search_count, "expected to find %d jobs, got %d jobs" % (
expected_search_count, search_count)
return search_count
def _search_count(self, search_payload):
search_response = self._post("jobs/search", data=search_payload)
self._assert_status_code_is(search_response, 200)
search_json = search_response.json()
return len(search_json)
def __uploads_with_state(self, *states):
jobs_response = self._get("jobs", data=dict(state=states))
self._assert_status_code_is(jobs_response, 200)
jobs = jobs_response.json()
assert not [j for j in jobs if not j['state'] in states]
return [j for j in jobs if j['tool_id'] == 'upload1']
def __history_with_new_dataset(self, history_id):
dataset_id = self.dataset_populator.new_dataset(history_id)["id"]
return dataset_id
def __history_with_ok_dataset(self, history_id):
dataset_id = self.dataset_populator.new_dataset(history_id,
wait=True)["id"]
return dataset_id
def __history_with_ok_collection(self,
collection_type='list',
history_id=None):
if not history_id:
history_id = self.dataset_populator.new_history()
if collection_type == 'list':
fetch_response = self.dataset_collection_populator.create_list_in_history(
history_id, direct_upload=True).json()
elif collection_type == 'pair':
fetch_response = self.dataset_collection_populator.create_pair_in_history(
history_id, direct_upload=True).json()
elif collection_type == 'list:pair':
fetch_response = self.dataset_collection_populator.create_list_of_pairs_in_history(
history_id).json()
self.dataset_collection_populator.wait_for_fetched_collection(
fetch_response)
return fetch_response["outputs"][0]['id']
def __jobs_index(self, **kwds):
jobs_response = self._get("jobs", **kwds)
self._assert_status_code_is(jobs_response, 200)
jobs = jobs_response.json()
assert isinstance(jobs, list)
return jobs
