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Source code for galaxy_test.base.populators

import contextlib
import json
import os
import random
import string
import unittest
from collections import namedtuple
from functools import wraps
from io import StringIO
from operator import itemgetter

try:
    from nose.tools import nottest
except ImportError:
    def nottest(x):
        return x
import requests
import yaml
from gxformat2 import (
    convert_and_import_workflow,
    ImporterGalaxyInterface,
)
from gxformat2._yaml import ordered_load
from pkg_resources import resource_string

from galaxy.tool_util.client.staging import InteractorStaging
from galaxy.tool_util.verify.test_data import TestDataResolver
from galaxy.tool_util.verify.wait import (
    TimeoutAssertionError,
    wait_on as tool_util_wait_on,
)
from galaxy.util import unicodify
from . import api_asserts


# Simple workflow that takes an input and call cat wrapper on it.
workflow_str = unicodify(resource_string(__name__, "data/test_workflow_1.ga"))
# Simple workflow that takes an input and filters with random lines twice in a
# row - first grabbing 8 lines at random and then 6.
workflow_random_x2_str = unicodify(resource_string(__name__, "data/test_workflow_2.ga"))


DEFAULT_TIMEOUT = 60  # Secs to wait for state to turn ok

SKIP_FLAKEY_TESTS_ON_ERROR = os.environ.get("GALAXY_TEST_SKIP_FLAKEY_TESTS_ON_ERROR", None)


[docs]def flakey(method): @wraps(method) def wrapped_method(test_case, *args, **kwargs): try: method(test_case, *args, **kwargs) except unittest.SkipTest: raise except Exception: if SKIP_FLAKEY_TESTS_ON_ERROR: raise unittest.SkipTest("Error encountered during test marked as @flakey.") else: raise return wrapped_method
[docs]def skip_without_tool(tool_id): """Decorate an API test method as requiring a specific tool. Have test framework skip the test case if the tool is unavailable. """ def method_wrapper(method): def get_tool_ids(api_test_case): index = api_test_case.galaxy_interactor.get("tools", data=dict(in_panel=False)) tools = index.json() # In panels by default, so flatten out sections... tool_ids = [itemgetter("id")(_) for _ in tools] return tool_ids @wraps(method) def wrapped_method(api_test_case, *args, **kwargs): _raise_skip_if(tool_id not in get_tool_ids(api_test_case)) return method(api_test_case, *args, **kwargs) return wrapped_method return method_wrapper
[docs]def skip_without_datatype(extension): """Decorate an API test method as requiring a specific datatype. Have test framework skip the test case if the datatype is unavailable. """ def has_datatype(api_test_case): index_response = api_test_case.galaxy_interactor.get("datatypes") assert index_response.status_code == 200, "Failed to fetch datatypes for target Galaxy." datatypes = index_response.json() assert isinstance(datatypes, list) return extension in datatypes def method_wrapper(method): @wraps(method) def wrapped_method(api_test_case, *args, **kwargs): _raise_skip_if(not has_datatype(api_test_case)) method(api_test_case, *args, **kwargs) return wrapped_method return method_wrapper
[docs]def is_site_up(url): try: response = requests.get(url, timeout=10) return response.status_code == 200 except Exception: return False
[docs]def skip_if_site_down(url): def method_wrapper(method): @wraps(method) def wrapped_method(api_test_case, *args, **kwargs): _raise_skip_if(not is_site_up(url), f"Test depends on [{url}] being up and it appears to be down.") method(api_test_case, *args, **kwargs) return wrapped_method return method_wrapper
skip_if_toolshed_down = skip_if_site_down("https://toolshed.g2.bx.psu.edu") skip_if_github_down = skip_if_site_down("https://github.com/")
[docs]def summarize_instance_history_on_error(method): @wraps(method) def wrapped_method(api_test_case, *args, **kwds): try: method(api_test_case, *args, **kwds) except Exception: api_test_case.dataset_populator._summarize_history(api_test_case.history_id) raise return wrapped_method
[docs]@nottest def uses_test_history(**test_history_kwd): """Can override require_new and cancel_executions using kwds to decorator. """ def method_wrapper(method): @wraps(method) def wrapped_method(api_test_case, *args, **kwds): with api_test_case.dataset_populator.test_history(**test_history_kwd) as history_id: method(api_test_case, history_id, *args, **kwds) return wrapped_method return method_wrapper
def _raise_skip_if(check, *args): if check: from nose.plugins.skip import SkipTest raise SkipTest(*args) # Deprecated mixin, use dataset populator instead. # TODO: Rework existing tests to target DatasetPopulator in a setup method instead.
[docs]class TestsDatasets: def _new_dataset(self, history_id, content='TestData123', **kwds): return DatasetPopulator(self.galaxy_interactor).new_dataset(history_id, content=content, **kwds) def _wait_for_history(self, history_id, assert_ok=False): return DatasetPopulator(self.galaxy_interactor).wait_for_history(history_id, assert_ok=assert_ok) def _new_history(self, **kwds): return DatasetPopulator(self.galaxy_interactor).new_history(**kwds) def _upload_payload(self, history_id, content, **kwds): return DatasetPopulator(self.galaxy_interactor).upload_payload(history_id, content, **kwds) def _run_tool_payload(self, tool_id, inputs, history_id, **kwds): return DatasetPopulator(self.galaxy_interactor).run_tool_payload(tool_id, inputs, history_id, **kwds)
[docs]class BaseDatasetPopulator: """ Abstract description of API operations optimized for testing Galaxy - implementations must implement _get, _post and _delete. """
[docs] def new_dataset(self, history_id, content=None, wait=False, **kwds): run_response = self.new_dataset_request(history_id, content=content, wait=wait, **kwds) assert run_response.status_code == 200, "Failed to create new dataset with response: %s" % run_response.content return run_response.json()["outputs"][0]
[docs] def new_dataset_request(self, history_id, content=None, wait=False, **kwds): if content is None and "ftp_files" not in kwds: content = "TestData123" payload = self.upload_payload(history_id, content=content, **kwds) run_response = self.tools_post(payload) if wait: self.wait_for_tool_run(history_id, run_response, assert_ok=kwds.get('assert_ok', True)) return run_response
[docs] def fetch(self, payload, assert_ok=True, timeout=DEFAULT_TIMEOUT, wait=None): tool_response = self._post("tools/fetch", data=payload) if wait is None: wait = assert_ok if wait: job = self.check_run(tool_response) self.wait_for_job(job["id"], timeout=timeout) if assert_ok: job = tool_response.json()["jobs"][0] details = self.get_job_details(job["id"]).json() assert details["state"] == "ok", details return tool_response
[docs] def wait_for_tool_run(self, history_id, run_response, timeout=DEFAULT_TIMEOUT, assert_ok=True): job = self.check_run(run_response) self.wait_for_job(job["id"], timeout=timeout) self.wait_for_history(history_id, assert_ok=assert_ok, timeout=timeout) return run_response
[docs] def check_run(self, run_response): run = run_response.json() assert run_response.status_code == 200, run job = run["jobs"][0] return job
[docs] def wait_for_history(self, history_id, assert_ok=False, timeout=DEFAULT_TIMEOUT): try: return wait_on_state(lambda: self._get("histories/%s" % history_id), desc="history state", assert_ok=assert_ok, timeout=timeout) except AssertionError: self._summarize_history(history_id) raise
[docs] def wait_for_history_jobs(self, history_id, assert_ok=False, timeout=DEFAULT_TIMEOUT): def has_active_jobs(): active_jobs = self.active_history_jobs(history_id) if len(active_jobs) == 0: return True else: return None try: wait_on(has_active_jobs, "active jobs", timeout=timeout) except TimeoutAssertionError as e: jobs = self.history_jobs(history_id) message = f"Failed waiting on active jobs to complete, current jobs are [{jobs}]. {e}" raise TimeoutAssertionError(message) if assert_ok: return self.wait_for_history(history_id, assert_ok=True, timeout=timeout)
[docs] def wait_for_job(self, job_id, assert_ok=False, timeout=DEFAULT_TIMEOUT): return wait_on_state(lambda: self.get_job_details(job_id), desc="job state", assert_ok=assert_ok, timeout=timeout)
[docs] def get_job_details(self, job_id, full=False): return self._get(f"jobs/{job_id}?full={full}")
[docs] def cancel_history_jobs(self, history_id, wait=True): active_jobs = self.active_history_jobs(history_id) for active_job in active_jobs: self.cancel_job(active_job["id"])
[docs] def history_jobs(self, history_id): query_params = {"history_id": history_id, "order_by": "create_time"} jobs_response = self._get("jobs", query_params) assert jobs_response.status_code == 200 return jobs_response.json()
[docs] def active_history_jobs(self, history_id): all_history_jobs = self.history_jobs(history_id) active_jobs = [j for j in all_history_jobs if j["state"] in ["new", "upload", "waiting", "queued", "running"]] return active_jobs
[docs] def cancel_job(self, job_id): return self._delete("jobs/%s" % job_id)
[docs] def delete_history(self, history_id): delete_response = self._delete(f"histories/{history_id}") delete_response.raise_for_status()
[docs] def delete_dataset(self, history_id, content_id): delete_response = self._delete(f"histories/{history_id}/contents/{content_id}") return delete_response
[docs] def create_tool_from_path(self, tool_path): tool_directory = os.path.dirname(os.path.abspath(tool_path)) payload = dict( src="from_path", path=tool_path, tool_directory=tool_directory, ) return self._create_tool_raw(payload)
[docs] def create_tool(self, representation, tool_directory=None): if isinstance(representation, dict): representation = json.dumps(representation) payload = dict( representation=representation, tool_directory=tool_directory, ) return self._create_tool_raw(payload)
def _create_tool_raw(self, payload): try: create_response = self._post("dynamic_tools", data=payload, admin=True) except TypeError: create_response = self._post("dynamic_tools", data=payload) assert create_response.status_code == 200, create_response.text return create_response.json()
[docs] def list_dynamic_tools(self): list_response = self._get("dynamic_tools", admin=True) assert list_response.status_code == 200, list_response return list_response.json()
[docs] def show_dynamic_tool(self, uuid): show_response = self._get("dynamic_tools/%s" % uuid, admin=True) assert show_response.status_code == 200, show_response return show_response.json()
[docs] def deactivate_dynamic_tool(self, uuid): delete_response = self._delete("dynamic_tools/%s" % uuid, admin=True) return delete_response.json()
def _summarize_history(self, history_id): pass
[docs] @contextlib.contextmanager def test_history(self, **kwds): cleanup = "GALAXY_TEST_NO_CLEANUP" not in os.environ def wrap_up(): cancel_executions = kwds.get("cancel_executions", True) if cleanup and cancel_executions: self.cancel_history_jobs(history_id) require_new = kwds.get("require_new", True) try: history_id = None if not require_new: history_id = kwds.get("GALAXY_TEST_HISTORY_ID", None) history_id = history_id or self.new_history() yield history_id wrap_up() except Exception: self._summarize_history(history_id) wrap_up() raise
[docs] def new_history(self, **kwds): name = kwds.get("name", "API Test History") create_history_response = self._post("histories", data=dict(name=name)) assert "id" in create_history_response.json(), create_history_response.text history_id = create_history_response.json()["id"] return history_id
[docs] def upload_payload(self, history_id, content=None, **kwds): name = kwds.get("name", "Test_Dataset") dbkey = kwds.get("dbkey", "?") file_type = kwds.get("file_type", 'txt') upload_params = { 'files_0|NAME': name, 'dbkey': dbkey, 'file_type': file_type, } if dbkey is None: del upload_params["dbkey"] if content is None: upload_params["files_0|ftp_files"] = kwds.get("ftp_files") elif hasattr(content, 'read'): upload_params["files_0|file_data"] = content else: upload_params['files_0|url_paste'] = content if "to_posix_lines" in kwds: upload_params["files_0|to_posix_lines"] = kwds["to_posix_lines"] if "space_to_tab" in kwds: upload_params["files_0|space_to_tab"] = kwds["space_to_tab"] if "auto_decompress" in kwds: upload_params["files_0|auto_decompress"] = kwds["auto_decompress"] upload_params.update(kwds.get("extra_inputs", {})) return self.run_tool_payload( tool_id='upload1', inputs=upload_params, history_id=history_id, upload_type='upload_dataset' )
[docs] def get_remote_files(self, target="ftp"): return self._get("remote_files", data={"target": target}).json()
[docs] def run_tool_payload(self, tool_id, inputs, history_id, **kwds): # Remove files_%d|file_data parameters from inputs dict and attach # as __files dictionary. for key, value in list(inputs.items()): if key.startswith("files_") and key.endswith("|file_data"): if "__files" not in kwds: kwds["__files"] = {} kwds["__files"][key] = value del inputs[key] return dict( tool_id=tool_id, inputs=json.dumps(inputs), history_id=history_id, **kwds )
[docs] def run_tool(self, tool_id, inputs, history_id, assert_ok=True, **kwds): payload = self.run_tool_payload(tool_id, inputs, history_id, **kwds) tool_response = self.tools_post(payload) if assert_ok: api_asserts.assert_status_code_is(tool_response, 200) return tool_response.json() else: return tool_response
[docs] def tools_post(self, payload, url="tools"): tool_response = self._post(url, data=payload) return tool_response
[docs] def get_history_dataset_content(self, history_id, wait=True, filename=None, type='text', raw=False, **kwds): dataset_id = self.__history_content_id(history_id, wait=wait, **kwds) data = {} if filename: data["filename"] = filename if raw: data['raw'] = True display_response = self._get_contents_request(history_id, "/%s/display" % dataset_id, data=data) assert display_response.status_code == 200, display_response.text if type == 'text': return display_response.text else: return display_response.content
[docs] def get_history_dataset_details(self, history_id, **kwds): dataset_id = self.__history_content_id(history_id, **kwds) details_response = self.get_history_dataset_details_raw(history_id, dataset_id) details_response.raise_for_status() return details_response.json()
[docs] def get_history_dataset_details_raw(self, history_id, dataset_id): details_response = self._get_contents_request(history_id, f"/datasets/{dataset_id}") return details_response
[docs] def get_history_dataset_extra_files(self, history_id, **kwds): dataset_id = self.__history_content_id(history_id, **kwds) details_response = self._get_contents_request(history_id, "/%s/extra_files" % dataset_id) assert details_response.status_code == 200, details_response.content return details_response.json()
[docs] def get_history_collection_details(self, history_id, **kwds): hdca_id = self.__history_content_id(history_id, **kwds) details_response = self._get_contents_request(history_id, "/dataset_collections/%s" % hdca_id) assert details_response.status_code == 200, details_response.content return details_response.json()
[docs] def run_collection_creates_list(self, history_id, hdca_id): inputs = { "input1": {"src": "hdca", "id": hdca_id}, } self.wait_for_history(history_id, assert_ok=True) return self.run_tool("collection_creates_list", inputs, history_id)
[docs] def run_exit_code_from_file(self, history_id, hdca_id): exit_code_inputs = { "input": {'batch': True, 'values': [{"src": "hdca", "id": hdca_id}]}, } response = self.run_tool("exit_code_from_file", exit_code_inputs, history_id, assert_ok=False).json() self.wait_for_history(history_id, assert_ok=False) return response
def __history_content_id(self, history_id, wait=True, **kwds): if wait: assert_ok = kwds.get("assert_ok", True) self.wait_for_history(history_id, assert_ok=assert_ok) # kwds should contain a 'dataset' object response, a 'dataset_id' or # the last dataset in the history will be fetched. if "dataset_id" in kwds: history_content_id = kwds["dataset_id"] elif "content_id" in kwds: history_content_id = kwds["content_id"] elif "dataset" in kwds: history_content_id = kwds["dataset"]["id"] else: hid = kwds.get("hid", None) # If not hid, just grab last dataset history_contents = self._get_contents_request(history_id).json() if hid: history_content_id = None for history_item in history_contents: if history_item["hid"] == hid: history_content_id = history_item["id"] if history_content_id is None: raise Exception(f"Could not find content with HID [{hid}] in [{history_contents}]") else: # No hid specified - just grab most recent element. history_content_id = history_contents[-1]["id"] return history_content_id def _get_contents_request(self, history_id, suffix="", data=None): if data is None: data = {} url = "histories/%s/contents" % history_id if suffix: url = f"{url}{suffix}" return self._get(url, data=data)
[docs] def ds_entry(self, history_content): src = 'hda' if 'history_content_type' in history_content and history_content['history_content_type'] == "dataset_collection": src = 'hdca' return dict(src=src, id=history_content["id"])
[docs] def dataset_storage_info(self, dataset_id): storage_response = self.galaxy_interactor.get(f"datasets/{dataset_id}/storage") storage_response.raise_for_status() return storage_response.json()
[docs] def get_roles(self): roles_response = self.galaxy_interactor.get("roles", admin=True) assert roles_response.status_code == 200 return roles_response.json()
[docs] def user_email(self): users_response = self.galaxy_interactor.get("users") users = users_response.json() assert len(users) == 1 return users[0]["email"]
[docs] def user_id(self): users_response = self.galaxy_interactor.get("users") users = users_response.json() assert len(users) == 1 return users[0]["id"]
[docs] def user_private_role_id(self): user_email = self.user_email() roles = self.get_roles() users_roles = [r for r in roles if r["name"] == user_email] assert len(users_roles) == 1, f"Did not find exactly one role for email {user_email} - {users_roles}" role = users_roles[0] assert "id" in role, role return role["id"]
[docs] def create_role(self, user_ids, description=None): payload = { "name": self.get_random_name(prefix="testpop"), "description": description or "Test Role", "user_ids": user_ids, } role_response = self.galaxy_interactor.post("roles", data=payload, admin=True, json=True) assert role_response.status_code == 200 return role_response.json()
[docs] def create_quota(self, quota_payload): quota_response = self.galaxy_interactor.post("quotas", data=quota_payload, admin=True) quota_response.raise_for_status() return quota_response.json()
[docs] def get_quotas(self): quota_response = self.galaxy_interactor.get("quotas", admin=True) quota_response.raise_for_status() return quota_response.json()
[docs] def make_private(self, history_id, dataset_id): role_id = self.user_private_role_id() # Give manage permission to the user. payload = { "access": json.dumps([role_id]), "manage": json.dumps([role_id]), } url = f"histories/{history_id}/contents/{dataset_id}/permissions" update_response = self.galaxy_interactor._put(url, payload, admin=True) assert update_response.status_code == 200, update_response.content return update_response.json()
[docs] def validate_dataset(self, history_id, dataset_id): url = f"histories/{history_id}/contents/{dataset_id}/validate" update_response = self.galaxy_interactor._put(url, {}) assert update_response.status_code == 200, update_response.content return update_response.json()
[docs] def validate_dataset_and_wait(self, history_id, dataset_id): self.validate_dataset(history_id, dataset_id) def validated(): metadata = self.get_history_dataset_details(history_id, dataset_id=dataset_id) validated_state = metadata['validated_state'] if validated_state == 'unknown': return else: return validated_state return wait_on( validated, "dataset validation" )
[docs] def setup_history_for_export_testing(self, history_name): history_id = self.new_history(name=history_name) self.new_dataset(history_id, content="1 2 3") deleted_hda = self.new_dataset(history_id, content="1 2 3", wait=True) self.delete_dataset(history_id, deleted_hda["id"]) deleted_details = self.get_history_dataset_details(history_id, id=deleted_hda["id"]) assert deleted_details["deleted"] return history_id
[docs] def prepare_export(self, history_id, data): url = "histories/%s/exports" % history_id put_response = self._put(url, data) put_response.raise_for_status() if put_response.status_code == 202: def export_ready_response(): put_response = self._put(url) if put_response.status_code == 202: return None return put_response put_response = wait_on(export_ready_response, desc="export ready") api_asserts.assert_status_code_is(put_response, 200) return put_response else: job_desc = put_response.json() assert "job_id" in job_desc return self.wait_for_job(job_desc["job_id"])
[docs] def export_url(self, history_id, data, check_download=True): put_response = self.prepare_export(history_id, data) response = put_response.json() api_asserts.assert_has_keys(response, "download_url") download_url = response["download_url"] if check_download: self.get_export_url(download_url) return download_url
[docs] def get_export_url(self, export_url): full_download_url = f"{export_url}?key={self._api_key}" download_response = self._get(full_download_url) api_asserts.assert_status_code_is(download_response, 200) return download_response
[docs] def import_history(self, import_data): files = {} archive_file = import_data.pop("archive_file", None) if archive_file: files["archive_file"] = archive_file import_response = self._post("histories", data=import_data, files=files) api_asserts.assert_status_code_is(import_response, 200)
[docs] def import_history_and_wait_for_name(self, import_data, history_name): def history_names(): return {h["name"]: h for h in self.get_histories()} import_name = "imported from archive: %s" % history_name assert import_name not in history_names() self.import_history(import_data) def has_history_with_name(): histories = history_names() return histories.get(import_name, None) imported_history = wait_on(has_history_with_name, desc="import history") imported_history_id = imported_history["id"] self.wait_for_history(imported_history_id) return imported_history_id
[docs] def rename_history(self, history_id, new_name): update_url = "histories/%s" % history_id put_response = self._put(update_url, {"name": new_name}) return put_response
[docs] def get_histories(self): history_index_response = self._get("histories") api_asserts.assert_status_code_is(history_index_response, 200) return history_index_response.json()
[docs] def wait_on_history_length(self, history_id, wait_on_history_length): def history_has_length(): history_length = self.history_length(history_id) return None if history_length != wait_on_history_length else True wait_on(history_has_length, desc="import history population")
[docs] def history_length(self, history_id): contents_response = self._get("histories/%s/contents" % history_id) api_asserts.assert_status_code_is(contents_response, 200) contents = contents_response.json() return len(contents)
[docs] def reimport_history(self, history_id, history_name, wait_on_history_length, export_kwds, url, api_key): # Export the history. download_path = self.export_url(history_id, export_kwds, check_download=True) # Create download for history full_download_url = f"{url}{download_path}?key={api_key}" import_data = dict(archive_source=full_download_url, archive_type="url") imported_history_id = self.import_history_and_wait_for_name(import_data, history_name) if wait_on_history_length: self.wait_on_history_length(imported_history_id, wait_on_history_length) return imported_history_id
[docs] def get_random_name(self, prefix=None, suffix=None, len=10): # stolen from navigates_galaxy.py return '{}{}{}'.format( prefix or '', ''.join(random.choice(string.ascii_lowercase + string.digits) for _ in range(len)), suffix or '', )
[docs]class DatasetPopulator(BaseDatasetPopulator):
[docs] def __init__(self, galaxy_interactor): self.galaxy_interactor = galaxy_interactor
@property def _api_key(self): return self.galaxy_interactor.api_key def _post(self, route, data=None, files=None, admin=False): return self.galaxy_interactor.post(route, data, files=files, admin=admin) def _put(self, route, data=None): return self.galaxy_interactor.put(route, data) def _get(self, route, data=None, admin=False): if data is None: data = {} return self.galaxy_interactor.get(route, data=data, admin=admin) def _delete(self, route, data=None, admin=False): if data is None: data = {} return self.galaxy_interactor.delete(route, data=data, admin=admin) def _summarize_history(self, history_id): self.galaxy_interactor._summarize_history(history_id)
[docs] def wait_for_dataset(self, history_id, dataset_id, assert_ok=False, timeout=DEFAULT_TIMEOUT): return wait_on_state(lambda: self._get(f"histories/{history_id}/contents/{dataset_id}"), desc="dataset state", assert_ok=assert_ok, timeout=timeout)
[docs]class BaseWorkflowPopulator:
[docs] def load_workflow(self, name, content=workflow_str, add_pja=False): workflow = json.loads(content) workflow["name"] = name if add_pja: tool_step = workflow["steps"]["2"] tool_step["post_job_actions"]["RenameDatasetActionout_file1"] = dict( action_type="RenameDatasetAction", output_name="out_file1", action_arguments=dict(newname="foo ${replaceme}"), ) return workflow
[docs] def load_random_x2_workflow(self, name): return self.load_workflow(name, content=workflow_random_x2_str)
[docs] def load_workflow_from_resource(self, name, filename=None): if filename is None: filename = "data/%s.ga" % name content = unicodify(resource_string(__name__, filename)) return self.load_workflow(name, content=content)
[docs] def simple_workflow(self, name, **create_kwds): workflow = self.load_workflow(name) return self.create_workflow(workflow, **create_kwds)
[docs] def import_workflow_from_path(self, from_path): data = dict( from_path=from_path ) import_response = self._post("workflows", data=data) api_asserts.assert_status_code_is(import_response, 200) return import_response.json()["id"]
[docs] def create_workflow(self, workflow, **create_kwds): upload_response = self.create_workflow_response(workflow, **create_kwds) uploaded_workflow_id = upload_response.json()["id"] return uploaded_workflow_id
[docs] def create_workflow_response(self, workflow, **create_kwds): data = dict( workflow=json.dumps(workflow), **create_kwds ) upload_response = self._post("workflows/upload", data=data) return upload_response
[docs] def upload_yaml_workflow(self, has_yaml, **kwds): round_trip_conversion = kwds.get("round_trip_format_conversion", False) client_convert = kwds.pop("client_convert", not round_trip_conversion) kwds["convert"] = client_convert workflow = convert_and_import_workflow(has_yaml, galaxy_interface=self, **kwds) workflow_id = workflow["id"] if round_trip_conversion: workflow_yaml_wrapped = self.download_workflow(workflow_id, style="format2_wrapped_yaml") assert "yaml_content" in workflow_yaml_wrapped, workflow_yaml_wrapped round_trip_converted_content = workflow_yaml_wrapped["yaml_content"] workflow_id = self.upload_yaml_workflow(round_trip_converted_content, client_convert=False, round_trip_conversion=False) return workflow_id
[docs] def wait_for_invocation(self, workflow_id, invocation_id, timeout=DEFAULT_TIMEOUT, assert_ok=True): url = f"workflows/{workflow_id}/usage/{invocation_id}" def workflow_state(): return self._get(url) return wait_on_state(workflow_state, desc="workflow invocation state", timeout=timeout, assert_ok=assert_ok)
[docs] def history_invocations(self, history_id): history_invocations_response = self._get("invocations", {"history_id": history_id}) api_asserts.assert_status_code_is(history_invocations_response, 200) return history_invocations_response.json()
[docs] def wait_for_history_workflows(self, history_id, assert_ok=True, timeout=DEFAULT_TIMEOUT, expected_invocation_count=None): if expected_invocation_count is not None: def invocation_count(): invocations = self.history_invocations(history_id) if len(invocations) == expected_invocation_count: return True wait_on(invocation_count, "%s history invocations" % expected_invocation_count) for invocation in self.history_invocations(history_id): workflow_id = invocation["workflow_id"] invocation_id = invocation["id"] self.wait_for_workflow(workflow_id, invocation_id, history_id, timeout=timeout, assert_ok=assert_ok)
[docs] def wait_for_workflow(self, workflow_id, invocation_id, history_id, assert_ok=True, timeout=DEFAULT_TIMEOUT): """ Wait for a workflow invocation to completely schedule and then history to be complete. """ self.wait_for_invocation(workflow_id, invocation_id, timeout=timeout, assert_ok=assert_ok) self.dataset_populator.wait_for_history_jobs(history_id, assert_ok=assert_ok, timeout=timeout)
[docs] def get_invocation(self, invocation_id): r = self._get("invocations/%s" % invocation_id) r.raise_for_status() return r.json()
[docs] def get_biocompute_object(self, invocation_id): bco_response = self._get("invocations/%s/biocompute" % invocation_id) bco_response.raise_for_status() return bco_response.json()
[docs] def validate_biocompute_object(self, bco, expected_schema_version='https://w3id.org/ieee/ieee-2791-schema/2791object.json'): # TODO: actually use jsonref and jsonschema to validate this someday api_asserts.assert_has_keys(bco, "object_id", "spec_version", "etag", "provenance_domain", "usability_domain", "description_domain", "execution_domain", "parametric_domain", "io_domain", "error_domain") assert bco['spec_version'] == expected_schema_version api_asserts.assert_has_keys(bco['description_domain'], "keywords", "xref", "platform", "pipeline_steps") api_asserts.assert_has_keys(bco['execution_domain'], "script_access_type", "script", "script_driver", "software_prerequisites", "external_data_endpoints", "environment_variables") for p in bco['parametric_domain']: api_asserts.assert_has_keys(p, "param", "value", "step") api_asserts.assert_has_keys(bco['io_domain'], "input_subdomain", "output_subdomain")
[docs] def invoke_workflow_raw(self, workflow_id, request): url = "workflows/%s/usage" % (workflow_id) invocation_response = self._post(url, data=request) return invocation_response
[docs] def invoke_workflow(self, history_id, workflow_id, inputs=None, request=None, assert_ok=True): if inputs is None: inputs = {} if request is None: request = {} request["history"] = "hist_id=%s" % history_id, if inputs: request["inputs"] = json.dumps(inputs) request["inputs_by"] = 'step_index' invocation_response = self.invoke_workflow_raw(workflow_id, request) if assert_ok: api_asserts.assert_status_code_is(invocation_response, 200) invocation_id = invocation_response.json()["id"] return invocation_id else: return invocation_response
[docs] def workflow_report_json(self, workflow_id, invocation_id): response = self._get(f"workflows/{workflow_id}/invocations/{invocation_id}/report") api_asserts.assert_status_code_is(response, 200) return response.json()
[docs] def download_workflow(self, workflow_id, style=None, history_id=None): params = {} if style is not None: params["style"] = style if history_id is not None: params['history_id'] = history_id response = self._get("workflows/%s/download" % workflow_id, data=params) api_asserts.assert_status_code_is(response, 200) if style != "format2": return response.json() else: return ordered_load(response.text)
[docs] def update_workflow(self, workflow_id, workflow_object): data = dict( workflow=workflow_object ) raw_url = 'workflows/%s' % workflow_id put_response = self.galaxy_interactor._put(raw_url, data=json.dumps(data)) return put_response
[docs] def refactor_workflow(self, workflow_id, actions, dry_run=None, style=None): data = dict( actions=actions, ) if style is not None: data["style"] = style if dry_run is not None: data["dry_run"] = dry_run raw_url = 'workflows/%s/refactor' % workflow_id put_response = self.galaxy_interactor._put(raw_url, data=json.dumps(data)) return put_response
[docs] @contextlib.contextmanager def export_for_update(self, workflow_id): workflow_object = self.download_workflow(workflow_id) yield workflow_object put_respose = self.update_workflow(workflow_id, workflow_object) put_respose.raise_for_status()
[docs] def run_workflow(self, has_workflow, test_data=None, history_id=None, wait=True, source_type=None, jobs_descriptions=None, expected_response=200, assert_ok=True, client_convert=None, round_trip_format_conversion=False, raw_yaml=False): """High-level wrapper around workflow API, etc. to invoke format 2 workflows.""" workflow_populator = self if client_convert is None: client_convert = not round_trip_format_conversion workflow_id = workflow_populator.upload_yaml_workflow(has_workflow, source_type=source_type, client_convert=client_convert, round_trip_format_conversion=round_trip_format_conversion, raw_yaml=raw_yaml) if test_data is None: if jobs_descriptions is None: assert source_type != "path" jobs_descriptions = yaml.safe_load(has_workflow) test_data = jobs_descriptions.get("test_data", {}) if not isinstance(test_data, dict): test_data = yaml.safe_load(test_data) parameters = test_data.pop('step_parameters', {}) replacement_parameters = test_data.pop("replacement_parameters", {}) inputs, label_map, has_uploads = load_data_dict(history_id, test_data, self.dataset_populator, self.dataset_collection_populator) workflow_request = dict( history="hist_id=%s" % history_id, workflow_id=workflow_id, ) workflow_request["inputs"] = json.dumps(label_map) workflow_request["inputs_by"] = 'name' if parameters: workflow_request["parameters"] = json.dumps(parameters) workflow_request["parameters_normalized"] = True if replacement_parameters: workflow_request["replacement_params"] = json.dumps(replacement_parameters) if has_uploads: self.dataset_populator.wait_for_history(history_id, assert_ok=True) invocation_response = workflow_populator.invoke_workflow_raw(workflow_id, workflow_request) api_asserts.assert_status_code_is(invocation_response, expected_response) invocation = invocation_response.json() if expected_response != 200: assert not assert_ok return invocation invocation_id = invocation.get('id') if invocation_id: # Wait for workflow to become fully scheduled and then for all jobs # complete. if wait: workflow_populator.wait_for_workflow(workflow_id, invocation_id, history_id, assert_ok=assert_ok) jobs = self.dataset_populator.history_jobs(history_id) return RunJobsSummary( history_id=history_id, workflow_id=workflow_id, invocation_id=invocation_id, inputs=inputs, jobs=jobs, invocation=invocation, workflow_request=workflow_request )
[docs] def dump_workflow(self, workflow_id, style=None): raw_workflow = self.download_workflow(workflow_id, style=style) if style == "format2_wrapped_yaml": print(raw_workflow["yaml_content"]) else: print(json.dumps(raw_workflow, sort_keys=True, indent=2))
RunJobsSummary = namedtuple('RunJobsSummary', ['history_id', 'workflow_id', 'invocation_id', 'inputs', 'jobs', 'invocation', 'workflow_request'])
[docs]class WorkflowPopulator(BaseWorkflowPopulator, ImporterGalaxyInterface):
[docs] def __init__(self, galaxy_interactor): self.galaxy_interactor = galaxy_interactor self.dataset_populator = DatasetPopulator(galaxy_interactor) self.dataset_collection_populator = DatasetCollectionPopulator(galaxy_interactor)
def _post(self, route, data=None, admin=False): if data is None: data = {} return self.galaxy_interactor.post(route, data, admin=admin) def _get(self, route, data=None): if data is None: data = {} return self.galaxy_interactor.get(route, data=data) # Required for ImporterGalaxyInterface interface - so we can recurisvely import # nested workflows.
[docs] def import_workflow(self, workflow, **kwds): workflow_str = json.dumps(workflow, indent=4) data = { 'workflow': workflow_str, } data.update(**kwds) upload_response = self._post("workflows", data=data) assert upload_response.status_code == 200, upload_response.content return upload_response.json()
[docs] def import_tool(self, tool): """ Import a workflow via POST /api/workflows or comparable interface into Galaxy. """ upload_response = self._import_tool_response(tool) assert upload_response.status_code == 200, upload_response return upload_response.json()
def _import_tool_response(self, tool): tool_str = json.dumps(tool, indent=4) data = { 'representation': tool_str } upload_response = self._post("dynamic_tools", data=data, admin=True) return upload_response
[docs]class LibraryPopulator:
[docs] def __init__(self, galaxy_interactor): self.galaxy_interactor = galaxy_interactor self.dataset_populator = DatasetPopulator(galaxy_interactor)
[docs] def get_libraries(self): get_response = self.galaxy_interactor.get("libraries") return get_response.json()
[docs] def new_private_library(self, name): library = self.new_library(name) library_id = library["id"] role_id = self.user_private_role_id() self.set_permissions(library_id, role_id) return library
[docs] def new_library(self, name): data = dict(name=name) create_response = self.galaxy_interactor.post("libraries", data=data, admin=True) return create_response.json()
[docs] def set_permissions(self, library_id, role_id=None): if role_id: perm_list = json.dumps(role_id) else: perm_list = json.dumps([]) permissions = dict( LIBRARY_ACCESS_in=perm_list, LIBRARY_MODIFY_in=perm_list, LIBRARY_ADD_in=perm_list, LIBRARY_MANAGE_in=perm_list, ) response = self.galaxy_interactor.post("libraries/%s/permissions" % library_id, data=permissions, admin=True) api_asserts.assert_status_code_is(response, 200)
[docs] def user_email(self): # deprecated - use DatasetPopulator return self.dataset_populator.user_email()
[docs] def user_private_role_id(self): # deprecated - use DatasetPopulator return self.dataset_populator.user_private_role_id()
[docs] def create_dataset_request(self, library, **kwds): upload_option = kwds.get("upload_option", "upload_file") create_data = { "folder_id": kwds.get("folder_id", library["root_folder_id"]), "create_type": "file", "files_0|NAME": kwds.get("name", "NewFile"), "upload_option": upload_option, "file_type": kwds.get("file_type", "auto"), "db_key": kwds.get("db_key", "?"), } if kwds.get("link_data"): create_data["link_data_only"] = "link_to_files" if upload_option == "upload_file": files = { "files_0|file_data": kwds.get("file", StringIO(kwds.get("contents", "TestData"))), } elif upload_option == "upload_paths": create_data["filesystem_paths"] = kwds["paths"] files = {} elif upload_option == "upload_directory": create_data["server_dir"] = kwds["server_dir"] files = {} return create_data, files
[docs] def new_library_dataset(self, name, **create_dataset_kwds): library = self.new_private_library(name) payload, files = self.create_dataset_request(library, **create_dataset_kwds) dataset = self.raw_library_contents_create(library["id"], payload, files=files).json()[0] return self.wait_on_library_dataset(library, dataset)
[docs] def wait_on_library_dataset(self, library, dataset): def show(): return self.galaxy_interactor.get("libraries/{}/contents/{}".format(library["id"], dataset["id"])) wait_on_state(show, assert_ok=True, timeout=DEFAULT_TIMEOUT) return show().json()
[docs] def raw_library_contents_create(self, library_id, payload, files=None): if files is None: files = {} url_rel = "libraries/%s/contents" % library_id return self.galaxy_interactor.post(url_rel, payload, files=files)
[docs] def show_ldda(self, library_id, library_dataset_id): return self.galaxy_interactor.get(f"libraries/{library_id}/contents/{library_dataset_id}")
[docs] def new_library_dataset_in_private_library(self, library_name="private_dataset", wait=True): library = self.new_private_library(library_name) payload, files = self.create_dataset_request(library, file_type="txt", contents="create_test") create_response = self.galaxy_interactor.post("libraries/%s/contents" % library["id"], payload, files=files) api_asserts.assert_status_code_is(create_response, 200) library_datasets = create_response.json() assert len(library_datasets) == 1 library_dataset = library_datasets[0] if wait: def show(): return self.show_ldda(library["id"], library_dataset["id"]) wait_on_state(show, assert_ok=True) library_dataset = show().json() return library, library_dataset
[docs] def get_library_contents_with_path(self, library_id, path): all_contents_response = self.galaxy_interactor.get("libraries/%s/contents" % library_id) api_asserts.assert_status_code_is(all_contents_response, 200) all_contents = all_contents_response.json() matching = [c for c in all_contents if c["name"] == path] if len(matching) == 0: raise Exception(f"Failed to find library contents with path [{path}], contents are {all_contents}") get_response = self.galaxy_interactor.get(matching[0]["url"]) api_asserts.assert_status_code_is(get_response, 200) return get_response.json()
[docs] def setup_fetch_to_folder(self, test_name): history_id = self.dataset_populator.new_history() library = self.new_private_library(test_name) folder_id = library["root_folder_id"][1:] destination = {"type": "library_folder", "library_folder_id": folder_id} return history_id, library, destination
[docs]class BaseDatasetCollectionPopulator:
[docs] def create_list_from_pairs(self, history_id, pairs, name="Dataset Collection from pairs"): return self.create_nested_collection(history_id=history_id, collection=pairs, collection_type='list:paired', name=name)
[docs] def nested_collection_identifiers(self, history_id, collection_type): rank_types = list(reversed(collection_type.split(":"))) assert len(rank_types) > 0 rank_type_0 = rank_types[0] if rank_type_0 == "list": identifiers = self.list_identifiers(history_id) else: identifiers = self.pair_identifiers(history_id) nested_collection_type = rank_type_0 for i, rank_type in enumerate(reversed(rank_types[1:])): name = "test_level_%d" % (i + 1) if rank_type == "list" else "paired" identifiers = [dict( src="new_collection", name=name, collection_type=nested_collection_type, element_identifiers=identifiers, )] nested_collection_type = f"{rank_type}:{nested_collection_type}" return identifiers
[docs] def create_nested_collection(self, history_id, collection_type, name=None, collection=None, element_identifiers=None): """Create a nested collection either from collection or using collection_type).""" assert collection_type is not None name = name or "Test %s" % collection_type if collection is not None: assert element_identifiers is None element_identifiers = [] for i, pair in enumerate(collection): element_identifiers.append(dict( name="test%d" % i, src="hdca", id=pair )) if element_identifiers is None: element_identifiers = self.nested_collection_identifiers(history_id, collection_type) payload = dict( instance_type="history", history_id=history_id, element_identifiers=json.dumps(element_identifiers), collection_type=collection_type, name=name, ) return self.__create(payload)
[docs] def create_list_of_pairs_in_history(self, history_id, **kwds): return self.upload_collection(history_id, "list:paired", elements=[ { "name": "test0", "elements": [ {"src": "pasted", "paste_content": "TestData123", "name": "forward"}, {"src": "pasted", "paste_content": "TestData123", "name": "reverse"}, ] } ])
[docs] def create_list_of_list_in_history(self, history_id, **kwds): # create_nested_collection will generate nested collection from just datasets, # this function uses recursive generation of history hdcas. collection_type = kwds.pop('collection_type', 'list:list') collection_types = collection_type.split(':') list = self.create_list_in_history(history_id, **kwds).json()['id'] current_collection_type = 'list' for collection_type in collection_types[1:]: current_collection_type = f"{current_collection_type}:{collection_type}" response = self.create_nested_collection(history_id=history_id, collection_type=current_collection_type, name=current_collection_type, collection=[list]) list = response.json()['id'] return response
[docs] def create_pair_in_history(self, history_id, **kwds): payload = self.create_pair_payload( history_id, instance_type="history", **kwds ) return self.__create(payload)
[docs] def create_list_in_history(self, history_id, **kwds): payload = self.create_list_payload( history_id, instance_type="history", **kwds ) return self.__create(payload)
[docs] def upload_collection(self, history_id, collection_type, elements, **kwds): payload = self.__create_payload_fetch(history_id, collection_type, contents=elements, **kwds) return self.__create(payload)
[docs] def create_list_payload(self, history_id, **kwds): return self.__create_payload(history_id, identifiers_func=self.list_identifiers, collection_type="list", **kwds)
[docs] def create_pair_payload(self, history_id, **kwds): return self.__create_payload(history_id, identifiers_func=self.pair_identifiers, collection_type="paired", **kwds)
def __create_payload(self, *args, **kwds): direct_upload = kwds.pop("direct_upload", False) if direct_upload: return self.__create_payload_fetch(*args, **kwds) else: return self.__create_payload_collection(*args, **kwds) def __create_payload_fetch(self, history_id, collection_type, **kwds): files = [] contents = None if "contents" in kwds: contents = kwds["contents"] del kwds["contents"] elements = [] if contents is None: if collection_type == "paired": contents = [("forward", "TestData123"), ("reverse", "TestData123")] elif collection_type == "list": contents = ["TestData123", "TestData123", "TestData123"] else: raise Exception("Unknown collection_type %s" % collection_type) if isinstance(contents, list): for i, contents_level in enumerate(contents): # If given a full collection definition pass as is. if isinstance(contents_level, dict): elements.append(contents_level) continue element = {"src": "pasted", "ext": "txt"} # Else older style list of contents or element ID and contents, # convert to fetch API. if isinstance(contents_level, tuple): # (element_identifier, contents) element_identifier = contents_level[0] dataset_contents = contents_level[1] else: dataset_contents = contents_level if collection_type == "list": element_identifier = "data%d" % i elif collection_type == "paired" and i == 0: element_identifier = "forward" else: element_identifier = "reverse" element["name"] = element_identifier element["paste_content"] = dataset_contents elements.append(element) name = kwds.get("name", "Test Dataset Collection") files_request_part = {} for i, content in enumerate(files): files_request_part["files_%d|file_data" % i] = StringIO(content) targets = [{ "destination": {"type": "hdca"}, "elements": elements, "collection_type": collection_type, "name": name, }] payload = dict( history_id=history_id, targets=json.dumps(targets), __files=files_request_part, ) return payload
[docs] def wait_for_fetched_collection(self, fetch_response): self.dataset_populator.wait_for_job(fetch_response["jobs"][0]["id"], assert_ok=True) initial_dataset_collection = fetch_response["outputs"][0] dataset_collection = self.dataset_populator.get_history_collection_details(initial_dataset_collection["history_id"], hid=initial_dataset_collection["hid"]) return dataset_collection
def __create_payload_collection(self, history_id, identifiers_func, collection_type, **kwds): contents = None if "contents" in kwds: contents = kwds["contents"] del kwds["contents"] if "element_identifiers" not in kwds: kwds["element_identifiers"] = json.dumps(identifiers_func(history_id, contents=contents)) if "name" not in kwds: kwds["name"] = "Test Dataset Collection" payload = dict( history_id=history_id, collection_type=collection_type, **kwds ) return payload
[docs] def pair_identifiers(self, history_id, contents=None): hda1, hda2 = self.__datasets(history_id, count=2, contents=contents) element_identifiers = [ dict(name="forward", src="hda", id=hda1["id"]), dict(name="reverse", src="hda", id=hda2["id"]), ] return element_identifiers
[docs] def list_identifiers(self, history_id, contents=None): count = 3 if contents is None else len(contents) # Contents can be a list of strings (with name auto-assigned here) or a list of # 2-tuples of form (name, dataset_content). if contents and isinstance(contents[0], tuple): hdas = self.__datasets(history_id, count=count, contents=[c[1] for c in contents]) def hda_to_identifier(i, hda): return dict(name=contents[i][0], src="hda", id=hda["id"]) else: hdas = self.__datasets(history_id, count=count, contents=contents) def hda_to_identifier(i, hda): return dict(name="data%d" % (i + 1), src="hda", id=hda["id"]) element_identifiers = [hda_to_identifier(i, hda) for (i, hda) in enumerate(hdas)] return element_identifiers
def __create(self, payload): # Create a colleciton - either from existing datasets using collection creation API # or from direct uploads with the fetch API. Dispatch on "targets" keyword in payload # to decide which to use. if "targets" not in payload: return self._create_collection(payload) else: return self.dataset_populator.fetch(payload) def __datasets(self, history_id, count, contents=None): datasets = [] for i in range(count): new_kwds = {} if contents: new_kwds["content"] = contents[i] datasets.append(self.dataset_populator.new_dataset(history_id, **new_kwds)) return datasets
[docs] def wait_for_dataset_collection(self, create_payload, assert_ok=False, timeout=DEFAULT_TIMEOUT): for element in create_payload["elements"]: if element['element_type'] == 'hda': self.dataset_populator.wait_for_dataset(history_id=element['object']['history_id'], dataset_id=element['object']['id'], assert_ok=assert_ok, timeout=timeout) elif element['element_type'] == 'dataset_collection': self.wait_for_dataset_collection(element['object'], assert_ok=assert_ok, timeout=timeout)
[docs]class DatasetCollectionPopulator(BaseDatasetCollectionPopulator):
[docs] def __init__(self, galaxy_interactor): self.galaxy_interactor = galaxy_interactor self.dataset_populator = DatasetPopulator(galaxy_interactor)
def _create_collection(self, payload): create_response = self.galaxy_interactor.post("dataset_collections", data=payload) return create_response
[docs]def load_data_dict(history_id, test_data, dataset_populator, dataset_collection_populator): """Load a dictionary as inputs to a workflow (test data focused).""" def open_test_data(test_dict, mode="rb"): test_data_resolver = TestDataResolver() filename = test_data_resolver.get_filename(test_dict["value"]) return open(filename, mode) def read_test_data(test_dict): return open_test_data(test_dict, mode="r").read() inputs = {} label_map = {} has_uploads = False for key, value in test_data.items(): is_dict = isinstance(value, dict) if is_dict and ("elements" in value or value.get("type", None) in ["list:paired", "list", "paired"]): elements_data = value.get("elements", []) elements = [] for element_data in elements_data: # Adapt differences between test_data dict and fetch API description. if "name" not in element_data: identifier = element_data["identifier"] element_data["name"] = identifier input_type = element_data.get("type", "raw") content = None if input_type == "File": content = read_test_data(element_data) else: content = element_data["content"] if content is not None: element_data["src"] = "pasted" element_data["paste_content"] = content elements.append(element_data) # TODO: make this collection_type collection_type = value["type"] new_collection_kwds = {} if "name" in value: new_collection_kwds["name"] = value["name"] if collection_type == "list:paired": fetch_response = dataset_collection_populator.create_list_of_pairs_in_history(history_id, contents=elements, **new_collection_kwds).json() elif collection_type == "list": fetch_response = dataset_collection_populator.create_list_in_history(history_id, contents=elements, direct_upload=True, **new_collection_kwds).json() else: fetch_response = dataset_collection_populator.create_pair_in_history(history_id, contents=elements or None, direct_upload=True, **new_collection_kwds).json() hdca_output = fetch_response["outputs"][0] hdca = dataset_populator.ds_entry(hdca_output) hdca["hid"] = hdca_output["hid"] label_map[key] = hdca inputs[key] = hdca has_uploads = True elif is_dict and "type" in value: input_type = value["type"] if input_type == "File": content = open_test_data(value) new_dataset_kwds = { "content": content } if "name" in value: new_dataset_kwds["name"] = value["name"] if "file_type" in value: new_dataset_kwds["file_type"] = value["file_type"] hda = dataset_populator.new_dataset(history_id, **new_dataset_kwds) label_map[key] = dataset_populator.ds_entry(hda) has_uploads = True elif input_type == "raw": label_map[key] = value["value"] inputs[key] = value["value"] elif not is_dict: has_uploads = True hda = dataset_populator.new_dataset(history_id, content=value) label_map[key] = dataset_populator.ds_entry(hda) inputs[key] = hda else: raise ValueError("Invalid test_data def %s" % test_data) return inputs, label_map, has_uploads
[docs]def stage_inputs(galaxy_interactor, history_id, job, use_path_paste=True, use_fetch_api=True, to_posix_lines=True): """Alternative to load_data_dict that uses production-style workflow inputs.""" inputs, datasets = InteractorStaging(galaxy_interactor, use_fetch_api=use_fetch_api).stage( "workflow", history_id=history_id, job=job, use_path_paste=use_path_paste, to_posix_lines=to_posix_lines ) return inputs, datasets
[docs]def stage_rules_example(galaxy_interactor, history_id, example): """Wrapper around stage_inputs for staging collections defined by rules spec DSL.""" input_dict = example["test_data"].copy() input_dict["collection_type"] = input_dict.pop("type") input_dict["class"] = "Collection" inputs, _ = stage_inputs(galaxy_interactor, history_id=history_id, job={"input": input_dict}) return inputs
[docs]def wait_on_state(state_func, desc="state", skip_states=None, ok_states=None, assert_ok=False, timeout=DEFAULT_TIMEOUT): def get_state(): response = state_func() assert response.status_code == 200, "Failed to fetch state update while waiting. [%s]" % response.content state = response.json()["state"] if state in skip_states: return None else: if assert_ok: assert state in ok_states, "Final state - %s - not okay." % state return state if skip_states is None: skip_states = ["running", "queued", "new", "ready", "stop", "stopped", "setting_metadata"] if ok_states is None: ok_states = ["ok", "scheduled"] try: return wait_on(get_state, desc=desc, timeout=timeout) except TimeoutAssertionError as e: response = state_func() raise TimeoutAssertionError(f"{e} Current response containing state [{response.json()}].")
[docs]class GiPostGetMixin: """Mixin for adapting Galaxy testing populators helpers to bioblend.""" @property def _api_key(self): return self._gi.key def _api_url(self): return self._gi.url def _get(self, route, data=None): if data is None: data = {} return self._gi.make_get_request(self._url(route), data=data) def _post(self, route, data=None): if data is None: data = {} data = data.copy() data['key'] = self._gi.key return requests.post(self._url(route), data=data) def _put(self, route, data=None): if data is None: data = {} data = data.copy() data['key'] = self._gi.key return requests.put(self._url(route), data=data) def _delete(self, route, data=None): if data is None: data = {} data = data.copy() data['key'] = self._gi.key return requests.delete(self._url(route), data=data) def _url(self, route): if route.startswith("/api/"): route = route[len("/api/"):] return self._api_url() + "/" + route
[docs]class GiDatasetPopulator(BaseDatasetPopulator, GiPostGetMixin): """Implementation of BaseDatasetPopulator backed by bioblend."""
[docs] def __init__(self, gi): """Construct a dataset populator from a bioblend GalaxyInstance.""" self._gi = gi
[docs]class GiDatasetCollectionPopulator(BaseDatasetCollectionPopulator, GiPostGetMixin): """Implementation of BaseDatasetCollectionPopulator backed by bioblend."""
[docs] def __init__(self, gi): """Construct a dataset collection populator from a bioblend GalaxyInstance.""" self._gi = gi self.dataset_populator = GiDatasetPopulator(gi) self.dataset_collection_populator = GiDatasetCollectionPopulator(gi)
def _create_collection(self, payload): create_response = self._post("dataset_collections", data=payload) return create_response
[docs]class GiWorkflowPopulator(BaseWorkflowPopulator, GiPostGetMixin): """Implementation of BaseWorkflowPopulator backed by bioblend."""
[docs] def __init__(self, gi): """Construct a workflow populator from a bioblend GalaxyInstance.""" self._gi = gi self.dataset_populator = GiDatasetPopulator(gi)
[docs]def wait_on(function, desc, timeout=DEFAULT_TIMEOUT): return tool_util_wait_on(function, desc, timeout)