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Source code for galaxy.tool_util.verify.interactor
import contextlib
import io
import json
import os
import re
import shutil
import sys
import tarfile
import tempfile
import time
import urllib.parse
import zipfile
from json import dumps
from logging import getLogger
from typing import (
Any,
Callable,
cast,
Dict,
Generator,
List,
NamedTuple,
Optional,
Union,
)
import requests
from packaging.version import Version
from requests import Response
from requests.cookies import RequestsCookieJar
from typing_extensions import (
Literal,
NotRequired,
Protocol,
TypedDict,
)
from galaxy import util
from galaxy.tool_util.parser.interface import (
AssertionList,
TestCollectionDef,
TestCollectionOutputDef,
)
from galaxy.util.bunch import Bunch
from galaxy.util.hash_util import (
memory_bound_hexdigest,
parse_checksum_hash,
)
from . import verify
from .asserts import verify_assertions
from .wait import wait_on
log = getLogger(__name__)
# Off by default because it can pound the database pretty heavily
# and result in sqlite errors on larger tests or larger numbers of
# tests.
VERBOSE_ERRORS = util.asbool(os.environ.get("GALAXY_TEST_VERBOSE_ERRORS", False))
UPLOAD_ASYNC = util.asbool(os.environ.get("GALAXY_TEST_UPLOAD_ASYNC", True))
ERROR_MESSAGE_DATASET_SEP = "--------------------------------------"
DEFAULT_TOOL_TEST_WAIT = int(os.environ.get("GALAXY_TEST_DEFAULT_WAIT", 86400))
CLEANUP_TEST_HISTORIES = "GALAXY_TEST_NO_CLEANUP" not in os.environ
DEFAULT_TARGET_HISTORY = os.environ.get("GALAXY_TEST_HISTORY_ID", None)
DEFAULT_FTYPE = "auto"
# This following default dbkey was traditionally hg17 before Galaxy 18.05,
# restore this behavior by setting GALAXY_TEST_DEFAULT_DBKEY to hg17.
DEFAULT_DBKEY = os.environ.get("GALAXY_TEST_DEFAULT_DBKEY", "?")
[docs]class OutputsDict(dict):
"""Ordered dict that can also be accessed by index.
>>> out = OutputsDict()
>>> out['item1'] = 1
>>> out['item2'] = 2
>>> out[1] == 2 == out['item2']
True
"""
def __getitem__(self, item):
if isinstance(item, int):
return self[list(self.keys())[item]]
else:
return super().__getitem__(item)
JobDataT = Dict[str, Any]
JobDataCallbackT = Callable[[JobDataT], None]
[docs]class ValidToolTestDict(TypedDict):
inputs: Any
outputs: Any
output_collections: List[Dict[str, Any]]
stdout: NotRequired[AssertionList]
stderr: NotRequired[AssertionList]
expect_exit_code: NotRequired[int]
expect_failure: NotRequired[bool]
expect_test_failure: NotRequired[bool]
maxseconds: NotRequired[int]
num_outputs: NotRequired[int]
command_line: NotRequired[AssertionList]
command_version: NotRequired[AssertionList]
required_files: NotRequired[List[Any]]
required_data_tables: NotRequired[List[Any]]
required_loc_files: NotRequired[List[str]]
error: Literal[False]
tool_id: str
tool_version: str
test_index: int
[docs]class InvalidToolTestDict(TypedDict):
error: Literal[True]
tool_id: str
tool_version: str
test_index: int
inputs: Any
exception: str
maxseconds: Optional[int]
ToolTestDict = Union[ValidToolTestDict, InvalidToolTestDict]
ToolTestDictsT = List[ToolTestDict]
[docs]def stage_data_in_history(
galaxy_interactor: "GalaxyInteractorApi",
tool_id: str,
all_test_data,
history=None,
force_path_paste=False,
maxseconds=DEFAULT_TOOL_TEST_WAIT,
tool_version=None,
):
# Upload any needed files
upload_waits = []
assert tool_id
if UPLOAD_ASYNC:
for test_data in all_test_data:
upload_waits.append(
galaxy_interactor.stage_data_async(
test_data,
history,
tool_id,
force_path_paste=force_path_paste,
maxseconds=maxseconds,
tool_version=tool_version,
)
)
for upload_wait in upload_waits:
upload_wait()
else:
for test_data in all_test_data:
upload_wait = galaxy_interactor.stage_data_async(
test_data,
history,
tool_id,
force_path_paste=force_path_paste,
maxseconds=maxseconds,
tool_version=tool_version,
)
upload_wait()
[docs]class RunToolResponse(NamedTuple):
inputs: Dict[str, Any]
outputs: OutputsDict
output_collections: Dict[str, Any]
jobs: List[Dict[str, Any]]
[docs]class GalaxyInteractorApi:
# api_key and cookies can also be manually set by UsesApiTestCaseMixin._different_user()
api_key: Optional[str]
cookies: Optional[RequestsCookieJar]
keep_outputs_dir: Optional[str]
[docs] def __init__(self, **kwds):
self.api_url = f"{kwds['galaxy_url'].rstrip('/')}/api"
self.cookies = None
self.master_api_key = kwds["master_api_key"]
self.api_key = self._get_user_key(
kwds.get("api_key"), kwds.get("master_api_key"), test_user=kwds.get("test_user")
)
if kwds.get("user_api_key_is_admin_key", False):
self.master_api_key = self.api_key
self.keep_outputs_dir = kwds.get("keep_outputs_dir", None)
self.download_attempts = kwds.get("download_attempts", 1)
self.download_sleep = kwds.get("download_sleep", 1)
# Local test data directories.
self.test_data_directories = kwds.get("test_data") or []
self._target_galaxy_version = None
self.uploads = {}
@property
def target_galaxy_version(self):
if self._target_galaxy_version is None:
self._target_galaxy_version = Version(self._get("version").json()["version_major"])
return self._target_galaxy_version
@property
def supports_test_data_download(self):
return self.target_galaxy_version >= Version("19.01")
def _get_user_key(
self, user_key: Optional[str], admin_key: Optional[str], test_user: Optional[str] = None
) -> Optional[str]:
if not test_user:
test_user = "test@bx.psu.edu"
if user_key:
return user_key
test_user_response = self.ensure_user_with_email(test_user)
if not admin_key:
raise Exception("Must specify either a user key or admin key to interact with the Galaxy API")
return self._post(f"users/{test_user_response['id']}/api_key", key=admin_key).json()
[docs] def get_tests_summary(self):
response = self._get("tools/tests_summary")
assert response.status_code == 200, f"Non 200 response from tool tests available API. [{response.content}]"
return response.json()
[docs] def get_tool_tests(self, tool_id: str, tool_version: Optional[str] = None) -> ToolTestDictsT:
url = f"tools/{tool_id}/test_data"
params = {"tool_version": tool_version} if tool_version else None
response = self._get(url, data=params)
assert response.status_code == 200, f"Non 200 response from tool test API. [{response.content}]"
return response.json()
[docs] def verify_output_collection(
self, output_collection_def, output_collection_id, history, tool_id, tool_version=None
):
data_collection = self._get(
f"dataset_collections/{output_collection_id}", data={"instance_type": "history"}
).json()
def verify_dataset(element, element_attrib, element_outfile):
hda = element["object"]
try:
self.verify_output_dataset(
history,
hda_id=hda["id"],
outfile=element_outfile,
attributes=element_attrib,
tool_id=tool_id,
tool_version=tool_version,
)
except AssertionError as e:
raise AssertionError(
f"Collection element {element.get('element_identifier', '')} of collection {output_collection_def.name}: {e}"
)
verify_collection(output_collection_def, data_collection, verify_dataset)
[docs] def verify_output(self, history_id, jobs, output_data, output_testdef, tool_id, maxseconds, tool_version=None):
outfile = output_testdef.outfile
attributes = output_testdef.attributes
name = output_testdef.name
expected_count = attributes.get("count")
self.wait_for_jobs(history_id, jobs, maxseconds)
hid = self.__output_id(output_data)
# TODO: Twill version verifies dataset is 'ok' in here.
try:
self.verify_output_dataset(
history_id=history_id,
hda_id=hid,
outfile=outfile,
attributes=attributes,
tool_id=tool_id,
tool_version=tool_version,
)
except AssertionError as e:
raise AssertionError(f"Output {name}: {str(e)}")
primary_datasets = attributes.get("primary_datasets", {})
job_id = self._dataset_provenance(history_id, hid)["job_id"]
outputs = self._get(f"jobs/{job_id}/outputs").json()
found_datasets = 0
for output in outputs:
if output["name"] == name or output["name"].startswith(f"__new_primary_file_{name}|"):
found_datasets += 1
if expected_count is not None and expected_count != found_datasets:
raise AssertionError(
f"Output '{name}': expected to have '{expected_count}' datasets, but it had '{found_datasets}'"
)
for designation, (primary_outfile, primary_attributes) in primary_datasets.items():
primary_output = None
for output in outputs:
if output["name"] == f"__new_primary_file_{name}|{designation}__":
primary_output = output
break
if not primary_output:
raise Exception(
f"Failed to find primary dataset with designation [{designation}] for output with name [{name}]"
)
primary_hda_id = primary_output["dataset"]["id"]
try:
self.verify_output_dataset(
history_id,
primary_hda_id,
primary_outfile,
primary_attributes,
tool_id=tool_id,
tool_version=tool_version,
)
except AssertionError as e:
raise AssertionError(f"Primary output {name}: {str(e)}")
[docs] def wait_for_jobs(self, history_id, jobs, maxseconds):
for job in jobs:
self.wait_for_job(job["id"], history_id, maxseconds)
[docs] def verify_output_dataset(self, history_id, hda_id, outfile, attributes, tool_id, tool_version=None):
fetcher = self.__dataset_fetcher(history_id)
test_data_downloader = self.__test_data_downloader(tool_id, tool_version, attributes)
verify_hid(
outfile,
hda_id=hda_id,
attributes=attributes,
dataset_fetcher=fetcher,
test_data_downloader=test_data_downloader,
keep_outputs_dir=self.keep_outputs_dir,
)
self._verify_metadata(history_id, hda_id, attributes)
def _verify_metadata(self, history_id, hid, attributes):
"""Check dataset metadata.
ftype on output maps to `file_ext` on the hda's API description, `name`, `info`,
`dbkey` and `tags` all map to the API description directly. Other metadata attributes
are assumed to be datatype-specific and mapped with a prefix of `metadata_`.
"""
metadata = attributes.get("metadata", {}).copy()
for key in metadata.copy().keys():
if key not in ["name", "info", "tags", "created_from_basename"]:
new_key = f"metadata_{key}"
metadata[new_key] = metadata[key]
del metadata[key]
elif key == "info":
metadata["misc_info"] = metadata["info"]
del metadata["info"]
expected_file_type = attributes.get("ftype", None)
if expected_file_type:
metadata["file_ext"] = expected_file_type
if metadata:
def wait_for_content():
response = self._get(f"histories/{history_id}/contents/{hid}")
try:
response.raise_for_status()
return response.json()
except requests.exceptions.HTTPError:
return None
dataset = wait_on(wait_for_content, desc="dataset metadata", timeout=10)
for key, value in metadata.items():
try:
dataset_value = dataset.get(key, None)
def compare(val, expected):
if str(val) != str(expected):
raise Exception(
f"Dataset metadata verification for [{key}] failed, expected [{value}] but found [{dataset_value}]. Dataset API value was [{dataset}]." # noqa: B023
)
if isinstance(dataset_value, list):
value = str(value).split(",")
if len(value) != len(dataset_value):
raise Exception(
f"Dataset metadata verification for [{key}] failed, expected [{value}] but found [{dataset_value}], lists differ in length. Dataset API value was [{dataset}]."
)
for val, expected in zip(dataset_value, value):
compare(val, expected)
else:
compare(dataset_value, value)
except KeyError:
raise Exception(f"Failed to verify dataset metadata, metadata key [{key}] was not found.")
[docs] def wait_for_job(self, job_id: str, history_id: Optional[str] = None, maxseconds=DEFAULT_TOOL_TEST_WAIT) -> None:
self.wait_for(lambda: self.__job_ready(job_id, history_id), maxseconds=maxseconds)
[docs] def wait_for(self, func: Callable, what: str = "tool test run", **kwd) -> None:
walltime_exceeded = int(kwd.get("maxseconds", DEFAULT_TOOL_TEST_WAIT))
wait_on(func, what, walltime_exceeded)
[docs] def get_job_stdio(self, job_id: str) -> Dict[str, Any]:
return self.__get_job_stdio(job_id).json()
def __get_job(self, job_id: str) -> Response:
return self._get(f"jobs/{job_id}")
def __get_job_stdio(self, job_id: str) -> Response:
return self._get(f"jobs/{job_id}?full=true")
[docs] def get_history(self, history_name: str = "test_history") -> Optional[Dict[str, Any]]:
# Return the most recent non-deleted history matching the provided name
filters = urllib.parse.urlencode({"q": "name", "qv": history_name, "order": "update_time"})
response = self._get(f"histories?{filters}")
try:
return response.json()[-1]
except IndexError:
return None
[docs] @contextlib.contextmanager
def test_history(
self, require_new: bool = True, cleanup_callback: Optional[Callable[[str], None]] = None
) -> Generator[str, None, None]:
history_id = None
if not require_new:
history_id = DEFAULT_TARGET_HISTORY
cleanup = CLEANUP_TEST_HISTORIES
history_id = history_id or self.new_history()
try:
yield history_id
except Exception:
self._summarize_history(history_id)
raise
finally:
if cleanup and cleanup_callback is not None:
cleanup_callback(history_id)
[docs] def new_history(self, history_name: str = "test_history", publish_history: bool = False) -> str:
create_response = self._post("histories", {"name": history_name})
try:
create_response.raise_for_status()
except Exception as e:
raise Exception(f"Error occurred while creating history with name '{history_name}': {e}")
history_id = create_response.json()["id"]
if publish_history:
self.publish_history(history_id)
return history_id
[docs] def publish_history(self, history_id: str) -> None:
response = self._put(f"histories/{history_id}", json.dumps({"published": True}))
response.raise_for_status()
[docs] def test_data_path(self, tool_id, filename, tool_version=None):
version_fragment = f"&tool_version={tool_version}" if tool_version else ""
response = self._get(f"tools/{tool_id}/test_data_path?filename={filename}{version_fragment}", admin=True)
result = response.json()
if response.status_code in [200, 404]:
return result
raise Exception(result["err_msg"])
[docs] def test_data_download(self, tool_id, filename, mode="file", is_output=True, tool_version=None):
result = None
local_path = None
if self.supports_test_data_download:
version_fragment = f"&tool_version={tool_version}" if tool_version else ""
response = self._get(f"tools/{tool_id}/test_data_download?filename={filename}{version_fragment}")
if response.status_code == 200:
if mode == "file":
result = response.content
elif mode == "directory":
prefix = os.path.basename(filename)
path = tempfile.mkdtemp(prefix=prefix)
fileobj = io.BytesIO(response.content)
if zipfile.is_zipfile(fileobj):
with zipfile.ZipFile(fileobj) as contents:
contents.extractall(path=path)
else:
# Galaxy < 21.01
with tarfile.open(fileobj=fileobj) as tar_contents:
tar_contents.extractall(path=path)
result = path
else:
# We can only use local data
local_path = self.test_data_path(tool_id, filename, tool_version=tool_version)
if result is None and (local_path is None or not os.path.exists(local_path)):
local_path = self._find_in_test_data_directories(filename)
if result is None and local_path is not None and os.path.exists(local_path):
if mode == "file":
with open(local_path, mode="rb") as f:
result = f.read()
elif mode == "directory":
# Make a copy, since we are going to clean up the returned path
path = tempfile.mkdtemp()
shutil.copytree(local_path, path)
result = path
if result is None:
if is_output:
raise AssertionError(
f"Test output file ({filename}) is missing. If you are using planemo, try adding --update_test_data to generate it."
)
else:
raise AssertionError(f"Test input file ({filename}) cannot be found.")
return result
def _find_in_test_data_directories(self, filename: str) -> Optional[str]:
local_path = None
for test_data_directory in self.test_data_directories:
local_path = os.path.join(test_data_directory, filename)
if os.path.exists(local_path):
break
return local_path
def __output_id(self, output_data):
# Allow data structure coming out of tools API - {id: <id>, output_name: <name>, etc...}
# or simple id as comes out of workflow API.
try:
output_id = output_data.get("id")
except AttributeError:
output_id = output_data
return output_id
[docs] def stage_data_async(
self,
test_data: Dict[str, Any],
history_id: str,
tool_id: str,
force_path_paste: bool = False,
maxseconds: int = DEFAULT_TOOL_TEST_WAIT,
tool_version: Optional[str] = None,
) -> Callable[[], None]:
fname = test_data["fname"]
tool_input = {
"file_type": test_data["ftype"],
"dbkey": test_data["dbkey"],
}
metadata = test_data.get("metadata", {})
if not hasattr(metadata, "items"):
raise Exception(f"Invalid metadata description found for input [{fname}] - [{metadata}]")
for name, value in test_data.get("metadata", {}).items():
tool_input[f"files_metadata|{name}"] = value
composite_data = test_data["composite_data"]
if composite_data:
files = {}
for i, file_name in enumerate(composite_data):
if force_path_paste:
file_path = self.test_data_path(tool_id, file_name, tool_version=tool_version)
tool_input.update({f"files_{i}|url_paste": f"file://{file_path}"})
else:
file_content = self.test_data_download(
tool_id, file_name, is_output=False, tool_version=tool_version
)
files[f"files_{i}|file_data"] = file_content
tool_input.update(
{
f"files_{i}|type": "upload_dataset",
}
)
name = test_data["name"]
else:
file_name = None
file_name_exists = False
location = self._ensure_valid_location_in(test_data)
if fname:
file_name = self.test_data_path(tool_id, fname, tool_version=tool_version)
file_name_exists = os.path.exists(f"{file_name}")
upload_from_location = not file_name_exists and location is not None
name = os.path.basename(location if upload_from_location else fname)
tool_input.update(
{
"files_0|NAME": name,
"files_0|type": "upload_dataset",
}
)
files = {}
if upload_from_location:
tool_input.update({"files_0|url_paste": location})
elif force_path_paste:
file_name = self.test_data_path(tool_id, fname, tool_version=tool_version)
tool_input.update({"files_0|url_paste": f"file://{file_name}"})
else:
file_content = self.test_data_download(tool_id, fname, is_output=False, tool_version=tool_version)
files = {"files_0|file_data": file_content}
submit_response_object = self.__submit_tool(
history_id, "upload1", tool_input, extra_data={"type": "upload_dataset"}, files=files
)
submit_response = ensure_tool_run_response_okay(submit_response_object, f"upload dataset {name}")
assert (
"outputs" in submit_response
), f"Invalid response from server [{submit_response}], expecting outputs in response."
outputs = submit_response["outputs"]
assert len(outputs) > 0, f"Invalid response from server [{submit_response}], expecting an output dataset."
dataset = outputs[0]
hid = dataset["id"]
self.uploads[os.path.basename(fname)] = self.uploads[fname] = self.uploads[name] = {"src": "hda", "id": hid}
assert (
"jobs" in submit_response
), f"Invalid response from server [{submit_response}], expecting jobs in response."
jobs = submit_response["jobs"]
assert len(jobs) > 0, f"Invalid response from server [{submit_response}], expecting a job."
return lambda: self.wait_for_job(jobs[0]["id"], history_id, maxseconds=maxseconds)
def _ensure_valid_location_in(self, test_data: dict) -> Optional[str]:
location: Optional[str] = test_data.get("location")
has_valid_location = location and util.is_url(location)
if location and not has_valid_location:
raise ValueError(f"Invalid `location` URL: `{location}`")
return location
[docs] def run_tool(self, testdef, history_id, resource_parameters=None) -> RunToolResponse:
# We need to handle the case where we've uploaded a valid compressed file since the upload
# tool will have uncompressed it on the fly.
resource_parameters = resource_parameters or {}
inputs_tree = testdef.inputs.copy()
for key, value in inputs_tree.items():
values = [value] if not isinstance(value, list) else value
new_values = []
for value in values:
if isinstance(value, TestCollectionDef):
hdca_id = self._create_collection(history_id, value)
new_values = [dict(src="hdca", id=hdca_id)]
elif value in self.uploads:
new_values.append(self.uploads[value])
else:
new_values.append(value)
inputs_tree[key] = new_values
if resource_parameters:
inputs_tree["__job_resource|__job_resource__select"] = "yes"
for key, value in resource_parameters.items():
inputs_tree[f"__job_resource|{key}"] = value
# HACK: Flatten single-value lists. Required when using expand_grouping
for key, value in inputs_tree.items():
if isinstance(value, list) and len(value) == 1:
inputs_tree[key] = value[0]
submit_response = None
for _ in range(DEFAULT_TOOL_TEST_WAIT):
submit_response = self.__submit_tool(
history_id, tool_id=testdef.tool_id, tool_input=inputs_tree, tool_version=testdef.tool_version
)
if _are_tool_inputs_not_ready(submit_response):
print("Tool inputs not ready yet")
time.sleep(1)
continue
else:
break
submit_response_object = ensure_tool_run_response_okay(submit_response, "execute tool", inputs_tree)
try:
return RunToolResponse(
inputs=inputs_tree,
outputs=self.__dictify_outputs(submit_response_object),
output_collections=self.__dictify_output_collections(submit_response_object),
jobs=submit_response_object["jobs"],
)
except KeyError:
message = (
f"Error creating a job for these tool inputs - {submit_response_object.get('err_msg', 'unknown error')}"
)
raise RunToolException(message, inputs_tree)
def _create_collection(self, history_id, collection_def):
create_payload = dict(
name=collection_def.name,
element_identifiers=self._element_identifiers(collection_def),
collection_type=collection_def.collection_type,
history_id=history_id,
)
return self._post("dataset_collections", data=create_payload, json=True).json()["id"]
def _element_identifiers(self, collection_def):
element_identifiers = []
for element_dict in collection_def.elements:
element_identifier = element_dict["element_identifier"]
element_def = element_dict["element_definition"]
if isinstance(element_def, TestCollectionDef):
subelement_identifiers = self._element_identifiers(element_def)
element = dict(
name=element_identifier,
src="new_collection",
collection_type=element_def.collection_type,
element_identifiers=subelement_identifiers,
)
else:
element = self.uploads[element_def["value"]].copy()
element["name"] = element_identifier
tags = element_def.get("attributes").get("tags")
if tags:
element["tags"] = tags.split(",")
element_identifiers.append(element)
return element_identifiers
def __dictify_output_collections(self, submit_response) -> Dict[str, Any]:
output_collections_dict = {}
for output_collection in submit_response["output_collections"]:
output_collections_dict[output_collection["output_name"]] = output_collection
return output_collections_dict
def __dictify_outputs(self, datasets_object) -> OutputsDict:
# Convert outputs list to a dictionary that can be accessed by
# output_name so can be more flexible about ordering of outputs
# but also allows fallback to legacy access as list mode.
outputs_dict = OutputsDict()
for output in datasets_object["outputs"]:
outputs_dict[output.get("output_name")] = output
return outputs_dict
def __job_ready(self, job_id: str, history_id: Optional[str] = None):
if job_id is None:
raise ValueError("__job_ready passed empty job_id")
try:
return self._state_ready(job_id, error_msg="Job in error state.")
except Exception:
if VERBOSE_ERRORS and history_id is not None:
self._summarize_history(history_id)
raise
def _summarize_history(self, history_id: str):
if history_id is None:
raise ValueError("_summarize_history passed empty history_id")
print(f"Problem in history with id {history_id} - summary of history's datasets and jobs below.")
try:
history_contents = self.__contents(history_id)
except Exception:
print("*TEST FRAMEWORK FAILED TO FETCH HISTORY DETAILS*")
return
for history_content in history_contents:
dataset = history_content
print(ERROR_MESSAGE_DATASET_SEP)
dataset_id = dataset.get("id", None)
print(f"| {dataset['hid']} - {dataset['name']} (HID - NAME) ")
if history_content["history_content_type"] == "dataset_collection":
history_contents_json = self._get(
f"histories/{history_id}/contents/dataset_collections/{history_content['id']}"
).json()
print(f"| Dataset Collection: {history_contents_json}")
print("|")
continue
try:
dataset_info = self._dataset_info(history_id, dataset_id)
print("| Dataset State:")
print(self.format_for_summary(dataset_info.get("state"), "Dataset state is unknown."))
print("| Dataset Blurb:")
print(self.format_for_summary(dataset_info.get("misc_blurb", ""), "Dataset blurb was empty."))
print("| Dataset Info:")
print(self.format_for_summary(dataset_info.get("misc_info", ""), "Dataset info is empty."))
print("| Peek:")
print(self.format_for_summary(dataset_info.get("peek", ""), "Peek unavailable."))
except Exception:
print("| *TEST FRAMEWORK ERROR FETCHING DATASET DETAILS*")
try:
provenance_info = self._dataset_provenance(history_id, dataset_id)
print("| Dataset Job Standard Output:")
print(self.format_for_summary(provenance_info.get("stdout", ""), "Standard output was empty."))
print("| Dataset Job Standard Error:")
print(self.format_for_summary(provenance_info.get("stderr", ""), "Standard error was empty."))
except Exception:
print("| *TEST FRAMEWORK ERROR FETCHING JOB DETAILS*")
print("|")
try:
jobs_json = self._get(f"jobs?history_id={history_id}").json()
for job_json in jobs_json:
print(ERROR_MESSAGE_DATASET_SEP)
print(f"| Job {job_json['id']}")
print("| State: ")
print(self.format_for_summary(job_json.get("state", ""), "Job state is unknown."))
print("| Update Time:")
print(self.format_for_summary(job_json.get("update_time", ""), "Job update time is unknown."))
print("| Create Time:")
print(self.format_for_summary(job_json.get("create_time", ""), "Job create time is unknown."))
print("|")
print(ERROR_MESSAGE_DATASET_SEP)
except Exception:
print(ERROR_MESSAGE_DATASET_SEP)
print("*TEST FRAMEWORK FAILED TO FETCH HISTORY JOBS*")
print(ERROR_MESSAGE_DATASET_SEP)
[docs] def format_for_summary(self, blob, empty_message, prefix="| "):
contents = "\n".join(f"{prefix}{line.strip()}" for line in io.StringIO(blob).readlines() if line.rstrip("\n\r"))
return contents or f"{prefix}*{empty_message}*"
def _dataset_provenance(self, history_id, id):
provenance = self._get(f"histories/{history_id}/contents/{id}/provenance").json()
return provenance
def _dataset_info(self, history_id, id):
dataset_json = self._get(f"histories/{history_id}/contents/{id}").json()
return dataset_json
def __contents(self, history_id):
history_contents_response = self._get(f"histories/{history_id}/contents")
history_contents_response.raise_for_status()
return history_contents_response.json()
def _state_ready(self, job_id: str, error_msg: str):
state_str = self.__get_job(job_id).json()["state"]
if state_str == "ok":
return True
elif state_str == "error":
job_json = self.get_job_stdio(job_id)
raise Exception(
f"{error_msg}. tool_id: {job_json['tool_id']}, exit_code: {job_json['exit_code']}, stderr: {job_json['stderr']}."
)
return None
def __submit_tool(self, history_id, tool_id, tool_input, extra_data=None, files=None, tool_version=None):
extra_data = extra_data or {}
data = dict(
history_id=history_id, tool_id=tool_id, inputs=dumps(tool_input), tool_version=tool_version, **extra_data
)
return self._post("tools", files=files, data=data)
[docs] def ensure_user_with_email(self, email, password=None):
admin_key = self.master_api_key
all_users_response = self._get("users", key=admin_key)
try:
all_users_response.raise_for_status()
except requests.exceptions.HTTPError as e:
raise Exception(
f"Failed to verify user with email [{email}] exists - perhaps you're targetting the wrong Galaxy server or using an incorrect admin API key. HTTP error: {e}"
)
all_users = all_users_response.json()
try:
test_user = [user for user in all_users if user["email"] == email][0]
except IndexError:
username = re.sub(r"[^a-z-\d]", "--", email.lower())
password = password or "testpass"
# If remote user middleware is enabled - this endpoint consumes
# ``remote_user_email`` otherwise it requires ``email``, ``password``
# and ``username``.
data = dict(
remote_user_email=email,
email=email,
password=password,
username=username,
)
test_user = self._post("users", data, key=admin_key, json=True).json()
return test_user
def __test_data_downloader(self, tool_id, tool_version=None, attributes: Optional[dict] = None):
location = None
checksum = attributes.get("checksum") if attributes else None
def test_data_download_from_galaxy(filename, mode="file"):
return self.test_data_download(tool_id, filename, mode=mode, tool_version=tool_version)
def test_data_download_from_location(filename: str):
# try to find the file in the test data directories first
local_path = self._find_in_test_data_directories(filename)
if local_path and os.path.exists(local_path):
with open(local_path, mode="rb") as f:
return f.read()
# if not found, try to download it from the location to the test data directory
# to be reused in subsequent tests
if local_path:
util.download_to_file(location, local_path)
self._verify_checksum(local_path, checksum)
with open(local_path, mode="rb") as f:
return f.read()
# otherwise, download it to a temporary file
with tempfile.NamedTemporaryFile() as file_handle:
util.download_to_file(location, file_handle.name)
self._verify_checksum(file_handle.name, checksum)
return file_handle.file.read()
if attributes:
location = self._ensure_valid_location_in(attributes)
if location:
return test_data_download_from_location
return test_data_download_from_galaxy
def _verify_checksum(self, file_path: str, checksum: Optional[str] = None):
if checksum is None:
return
hash_function, expected_hash_value = parse_checksum_hash(checksum)
calculated_hash_value = memory_bound_hexdigest(hash_func_name=hash_function, path=file_path)
if calculated_hash_value != expected_hash_value:
raise AssertionError(
f"Failed to verify checksum with [{hash_function}] - expected [{expected_hash_value}] got [{calculated_hash_value}]"
)
def __dataset_fetcher(self, history_id):
def fetcher(hda_id, base_name=None):
url = f"histories/{history_id}/contents/{hda_id}/display?raw=true"
if base_name:
url += f"&filename={base_name}"
response = None
for _ in range(self.download_attempts):
response = self._get(url)
if response.status_code == 500:
print(f"Retrying failed download with status code {response.status_code}")
time.sleep(self.download_sleep)
continue
else:
break
assert response
response.raise_for_status()
return response.content
return fetcher
[docs] def api_key_header(
self, key: Optional[str], admin: bool, anon: bool, headers: Optional[Dict[str, Optional[str]]]
) -> Dict[str, Optional[str]]:
header = headers or {}
if not anon:
if not key:
key = self.api_key if not admin else self.master_api_key
header["x-api-key"] = key
return header
def _post(
self,
path: str,
data: Optional[Dict[str, Any]] = None,
files: Optional[Dict[str, Any]] = None,
key: Optional[str] = None,
headers: Optional[Dict[str, Optional[str]]] = None,
admin: bool = False,
anon: bool = False,
json: bool = False,
) -> Response:
headers = self.api_key_header(key=key, admin=admin, anon=anon, headers=headers)
url = self.get_api_url(path)
kwd = self._prepare_request_params(data=data, files=files, as_json=json, headers=headers)
kwd["timeout"] = kwd.pop("timeout", util.DEFAULT_SOCKET_TIMEOUT)
return requests.post(url, **kwd)
def _delete(self, path, data=None, key=None, headers=None, admin=False, anon=False, json=False):
headers = self.api_key_header(key=key, admin=admin, anon=anon, headers=headers)
url = self.get_api_url(path)
kwd = self._prepare_request_params(data=data, as_json=json, headers=headers)
kwd["timeout"] = kwd.pop("timeout", util.DEFAULT_SOCKET_TIMEOUT)
return requests.delete(url, **kwd)
def _patch(self, path, data=None, key=None, headers=None, admin=False, anon=False, json=False):
headers = self.api_key_header(key=key, admin=admin, anon=anon, headers=headers)
url = self.get_api_url(path)
kwd = self._prepare_request_params(data=data, as_json=json, headers=headers)
kwd["timeout"] = kwd.pop("timeout", util.DEFAULT_SOCKET_TIMEOUT)
return requests.patch(url, **kwd)
def _put(self, path, data=None, key=None, headers=None, admin=False, anon=False, json=False):
headers = self.api_key_header(key=key, admin=admin, anon=anon, headers=headers)
url = self.get_api_url(path)
kwd = self._prepare_request_params(data=data, as_json=json, headers=headers)
kwd["timeout"] = kwd.pop("timeout", util.DEFAULT_SOCKET_TIMEOUT)
return requests.put(url, **kwd)
def _get(self, path, data=None, key=None, headers=None, admin=False, anon=False, allow_redirects=True):
headers = self.api_key_header(key=key, admin=admin, anon=anon, headers=headers)
url = self.get_api_url(path)
kwargs: Dict[str, Any] = {}
if self.cookies:
kwargs["cookies"] = self.cookies
# no data for GET
return requests.get(
url,
params=data,
headers=headers,
timeout=util.DEFAULT_SOCKET_TIMEOUT,
allow_redirects=allow_redirects,
**kwargs,
)
def _head(self, path, data=None, key=None, headers=None, admin=False, anon=False):
headers = self.api_key_header(key=key, admin=admin, anon=anon, headers=headers)
url = self.get_api_url(path)
kwargs: Dict[str, Any] = {}
if self.cookies:
kwargs["cookies"] = self.cookies
# no data for HEAD
return requests.head(url, params=data, headers=headers, timeout=util.DEFAULT_SOCKET_TIMEOUT, **kwargs)
[docs] def get_api_url(self, path: str) -> str:
if path.startswith("http"):
return path
elif path.startswith("/api/"):
path = path[len("/api/") :]
return urllib.parse.urljoin(f"{self.api_url}/", path)
def _prepare_request_params(
self,
data: Optional[Dict[str, Any]] = None,
files: Optional[Dict[str, Any]] = None,
as_json: bool = False,
params: Optional[Dict[str, Any]] = None,
headers: Optional[Dict[str, Optional[str]]] = None,
) -> Dict[str, Any]:
"""Handle some Galaxy conventions and work around requests issues.
This is admittedly kind of hacky, so the interface may change frequently - be
careful on reuse.
If ``as_json`` is True, use post payload using request's json parameter instead
of the data parameter (i.e. assume the contents is a json-ified blob instead of
form parameters with individual parameters json-ified if needed). requests doesn't
allow files to be specified with the json parameter - so rewrite the parameters
to handle that if as_json is True with specified files.
"""
return prepare_request_params(
data=data, files=files, as_json=as_json, params=params, headers=headers, cookies=self.cookies
)
[docs]def prepare_request_params(
data: Optional[Dict[str, Any]] = None,
files: Optional[Dict[str, Any]] = None,
as_json: bool = False,
params: Optional[Dict[str, Any]] = None,
headers: Optional[Dict[str, Optional[str]]] = None,
cookies: Optional[RequestsCookieJar] = None,
) -> Dict[str, Any]:
params = params or {}
data = data or {}
# handle encoded files
if files is None:
# if not explicitly passed, check __files... convention used in tool testing
# and API testing code
files = data.get("__files")
if files is not None:
del data["__files"]
# files doesn't really work with json, so dump the parameters
# and do a normal POST with request's data parameter.
if files and as_json:
as_json = False
new_items = {}
for key, val in data.items():
if isinstance(val, dict) or isinstance(val, list):
new_items[key] = dumps(val)
data.update(new_items)
kwd = {
"files": files,
}
if headers:
kwd["headers"] = headers
if as_json:
kwd["json"] = data or None
kwd["params"] = params
else:
data.update(params)
kwd["data"] = data
if cookies:
kwd["cookies"] = cookies
return kwd
[docs]def ensure_tool_run_response_okay(submit_response_object, request_desc, inputs=None):
if submit_response_object.status_code != 200:
message = None
dynamic_param_error = False
try:
err_response = submit_response_object.json()
if "param_errors" in err_response:
param_errors = err_response["param_errors"]
if "dbkey" in param_errors:
dbkey_err_obj = param_errors["dbkey"]
dbkey_val = dbkey_err_obj.get("parameter_value")
message = f"Invalid dbkey specified [{dbkey_val}]"
for value in param_errors.values():
if isinstance(value, dict) and value.get("is_dynamic"):
dynamic_param_error = True
if message is None:
message = err_response.get("err_msg") or None
except Exception:
# invalid JSON content.
pass
if message is None:
message = f"Request to {request_desc} failed - invalid JSON content returned from Galaxy server [{submit_response_object.text}]"
raise RunToolException(message, inputs, dynamic_param_error=dynamic_param_error)
submit_response = submit_response_object.json()
return submit_response
def _are_tool_inputs_not_ready(submit_response):
if submit_response.status_code != 400:
return False
try:
submit_json = submit_response.json()
return submit_json.get("err_code") == 400015
except Exception:
return False
[docs]class RunToolException(Exception):
[docs] def __init__(self, message, inputs=None, dynamic_param_error=False):
super().__init__(message)
self.inputs = inputs
self.dynamic_param_error = dynamic_param_error
# Galaxy specific methods - rest of this can be used with arbitrary files and such.
[docs]def verify_hid(
filename: Optional[str],
hda_id: str,
attributes: Dict[str, Any],
test_data_downloader,
dataset_fetcher=None,
keep_outputs_dir: Optional[str] = None,
):
assert dataset_fetcher is not None
def verify_extra_files(extra_files):
_verify_extra_files_content(
extra_files,
hda_id,
dataset_fetcher=dataset_fetcher,
test_data_downloader=test_data_downloader,
keep_outputs_dir=keep_outputs_dir,
)
data = dataset_fetcher(hda_id)
item_label = ""
verify(
item_label,
data,
attributes=attributes,
filename=filename,
get_filecontent=test_data_downloader,
keep_outputs_dir=keep_outputs_dir,
verify_extra_files=verify_extra_files,
)
[docs]def verify_collection(output_collection_def, data_collection, verify_dataset):
name = output_collection_def.name
expected_collection_type = output_collection_def.collection_type
if expected_collection_type:
collection_type = data_collection["collection_type"]
if expected_collection_type != collection_type:
message = f"Output collection '{name}': expected to be of type [{expected_collection_type}], was of type [{collection_type}]."
raise AssertionError(message)
expected_element_count = output_collection_def.count
if expected_element_count:
actual_element_count = len(data_collection["elements"])
if expected_element_count != actual_element_count:
message = f"Output collection '{name}': expected to have {expected_element_count} elements, but it had {actual_element_count}."
raise AssertionError(message)
def get_element(elements, id):
for element in elements:
if element["element_identifier"] == id:
return element
return False
def verify_elements(element_objects, element_tests):
expected_sort_order = {}
eo_ids = [_["element_identifier"] for _ in element_objects]
for element_identifier, element_test in element_tests.items():
if isinstance(element_test, dict):
element_outfile, element_attrib = None, element_test
else:
element_outfile, element_attrib = element_test
expected_count = element_attrib.get("count")
if "expected_sort_order" in element_attrib:
expected_sort_order[element_attrib["expected_sort_order"]] = element_identifier
element = get_element(element_objects, element_identifier)
if not element:
message = f"Output collection '{name}': failed to find identifier '{element_identifier}' in the tool generated elements {eo_ids}"
raise AssertionError(message)
element_type = element["element_type"]
if element_type != "dataset_collection":
element_count = 1
verify_dataset(element, element_attrib, element_outfile)
else:
elements = element["object"]["elements"]
element_count = len(elements)
verify_elements(elements, element_attrib.get("elements", {}))
if expected_count is not None and expected_count != element_count:
raise AssertionError(
f"Element '{element_identifier}': expected to have {expected_count} elements, but it had {element_count}"
)
if len(expected_sort_order) > 0:
generated_sort_order = [_["element_identifier"] for _ in element_objects]
i = 0
for element_index in sorted(expected_sort_order.keys()):
identifier = expected_sort_order[element_index]
try:
i = generated_sort_order[i:].index(identifier) + 1
except ValueError:
message = f"Output collection '{name}': identifier '{identifier}' found out of order, expected order of {expected_sort_order} for the tool generated collection elements {eo_ids}"
raise AssertionError(message)
verify_elements(data_collection["elements"], output_collection_def.element_tests)
def _verify_composite_datatype_file_content(
file_name,
hda_id,
base_name=None,
attributes=None,
dataset_fetcher=None,
test_data_downloader=None,
keep_outputs_dir: Optional[str] = None,
mode="file",
):
assert dataset_fetcher is not None
data = dataset_fetcher(hda_id, base_name)
item_label = f"History item {hda_id}"
try:
verify(
item_label,
data,
attributes=attributes,
filename=file_name,
get_filecontent=test_data_downloader,
keep_outputs_dir=keep_outputs_dir,
mode=mode,
)
except AssertionError as err:
errmsg = f"Composite file ({base_name}) of {item_label} different than expected, difference:\n"
errmsg += util.unicodify(err)
raise AssertionError(errmsg)
def _verify_extra_files_content(
extra_files: List[Dict[str, Any]], hda_id: str, dataset_fetcher, test_data_downloader, keep_outputs_dir
):
files_list = []
cleanup_directories = []
for extra_file_dict in extra_files:
extra_file_type = extra_file_dict["type"]
extra_file_name = extra_file_dict["name"]
extra_file_attributes = extra_file_dict["attributes"]
extra_file_value = extra_file_dict["value"]
if extra_file_type == "file":
files_list.append((extra_file_name, extra_file_value, extra_file_attributes, extra_file_type))
elif extra_file_type == "directory":
extracted_path = test_data_downloader(extra_file_value, mode="directory")
cleanup_directories.append(extracted_path)
for root, _directories, files in util.path.safe_walk(extracted_path):
for filename in files:
filename = os.path.join(root, filename)
filename = os.path.relpath(filename, extracted_path)
files_list.append(
(filename, os.path.join(extracted_path, filename), extra_file_attributes, extra_file_type)
)
else:
raise ValueError(f"unknown extra_files type: {extra_file_type}")
try:
for filename, filepath, attributes, extra_file_type in files_list:
_verify_composite_datatype_file_content(
filepath,
hda_id,
base_name=filename,
attributes=attributes,
dataset_fetcher=dataset_fetcher,
test_data_downloader=test_data_downloader,
keep_outputs_dir=keep_outputs_dir,
mode=extra_file_type,
)
finally:
for path in cleanup_directories:
shutil.rmtree(path)
[docs]class DictClientTestConfig(TestConfig):
[docs] def get_test_config(self, job_data):
# TODO: allow short ids, allow versions below outer id instead of key concatenation.
tool_id = job_data.get("tool_id")
tool_version = job_data.get("tool_version")
tool_test_config = None
tool_version_test_config = None
is_default = False
if tool_id in self._tools:
tool_test_config = self._tools[tool_id]
if tool_test_config is None:
tool_id = f"{tool_id}/{tool_version}"
if tool_id in self._tools:
tool_version_test_config = self._tools[tool_id]
else:
if tool_version in tool_test_config:
tool_version_test_config = tool_test_config[tool_version]
elif "default" in tool_test_config:
tool_version_test_config = tool_test_config["default"]
is_default = True
if tool_version_test_config:
test_index = job_data.get("test_index")
if test_index in tool_version_test_config:
return tool_version_test_config[test_index]
elif str(test_index) in tool_version_test_config:
return tool_version_test_config[str(test_index)]
if "default" in tool_version_test_config:
return tool_version_test_config["default"]
elif is_default:
return tool_version_test_config
return None
[docs]def verify_tool(
tool_id: str,
galaxy_interactor: "GalaxyInteractorApi",
resource_parameters: Optional[Dict[str, Any]] = None,
register_job_data: Optional[JobDataCallbackT] = None,
test_index: int = 0,
tool_version: Optional[str] = None,
quiet: bool = False,
test_history: Optional[str] = None,
no_history_cleanup: bool = False,
publish_history: bool = False,
force_path_paste: bool = False,
maxseconds: int = DEFAULT_TOOL_TEST_WAIT,
client_test_config: Optional[TestConfig] = None,
skip_with_reference_data: bool = False,
skip_on_dynamic_param_errors: bool = False,
_tool_test_dicts: Optional[ToolTestDictsT] = None, # extension point only for tests
):
if resource_parameters is None:
resource_parameters = {}
if client_test_config is None:
client_test_config = NullClientTestConfig()
tool_test_dicts = _tool_test_dicts or galaxy_interactor.get_tool_tests(tool_id, tool_version=tool_version)
tool_test_dict = tool_test_dicts[test_index]
if "test_index" not in tool_test_dict:
tool_test_dict["test_index"] = test_index
if "tool_id" not in tool_test_dict:
tool_test_dict["tool_id"] = tool_id
if tool_version is None and "tool_version" in tool_test_dict:
tool_version = tool_test_dict.get("tool_version")
job_data: JobDataT = {
"tool_id": tool_id,
"tool_version": tool_version,
"test_index": test_index,
}
client_config = client_test_config.get_test_config(job_data)
skip_message = None
if client_config is not None:
job_data.update(client_config)
skip_message = job_data.get("skip")
if not skip_message and skip_with_reference_data:
required_data_tables = tool_test_dict.get("required_data_tables")
required_loc_files = tool_test_dict.get("required_loc_files")
# TODO: actually hit the API and see if these tables are available.
if required_data_tables:
skip_message = f"Skipping test because of required data tables ({required_data_tables})"
if required_loc_files:
skip_message = f"Skipping test because of required loc files ({required_loc_files})"
if skip_message and register_job_data:
job_data["status"] = "skip"
register_job_data(job_data)
return
tool_test_dict.setdefault("maxseconds", maxseconds)
testdef = ToolTestDescription(cast(ToolTestDict, tool_test_dict))
_handle_def_errors(testdef)
created_history = False
if test_history is None:
created_history = True
history_name = f"Tool Test History for {tool_id}/{tool_version}-{test_index}"
test_history = galaxy_interactor.new_history(history_name=history_name, publish_history=publish_history)
# Upload data to test_history, run the tool and check the outputs - record
# API input, job info, tool run exception, as well as exceptions related to
# job output checking and register they with the test plugin so it can
# record structured information.
tool_inputs = None
job_stdio = None
job_output_exceptions = None
tool_execution_exception: Optional[Exception] = None
input_staging_exception = None
expected_failure_occurred = False
begin_time = time.time()
try:
try:
stage_data_in_history(
galaxy_interactor,
tool_id,
testdef.test_data(),
history=test_history,
force_path_paste=force_path_paste,
maxseconds=maxseconds,
tool_version=tool_version,
)
except Exception as e:
input_staging_exception = e
raise
try:
tool_response = galaxy_interactor.run_tool(testdef, test_history, resource_parameters=resource_parameters)
data_list, jobs, tool_inputs = tool_response.outputs, tool_response.jobs, tool_response.inputs
data_collection_list = tool_response.output_collections
except RunToolException as e:
tool_inputs = e.inputs
tool_execution_exception = e
if not testdef.expect_failure:
raise e
else:
expected_failure_occurred = True
except Exception as e:
tool_execution_exception = e
raise e
if not expected_failure_occurred:
try:
job_stdio = _verify_outputs(
testdef, test_history, jobs, data_list, data_collection_list, galaxy_interactor, quiet=quiet
)
except JobOutputsError as e:
job_stdio = e.job_stdio
job_output_exceptions = e.output_exceptions
raise e
except Exception as e:
job_output_exceptions = [e]
raise e
finally:
if register_job_data is not None:
end_time = time.time()
job_data["time_seconds"] = end_time - begin_time
if tool_inputs is not None:
job_data["inputs"] = tool_inputs
if job_stdio is not None:
job_data["job"] = job_stdio
status = "success"
if job_output_exceptions:
job_data["output_problems"] = [util.unicodify(_) for _ in job_output_exceptions]
status = "failure"
if tool_execution_exception:
job_data["execution_problem"] = util.unicodify(tool_execution_exception)
dynamic_param_error = getattr(tool_execution_exception, "dynamic_param_error", False)
job_data["dynamic_param_error"] = dynamic_param_error
if not expected_failure_occurred:
if skip_on_dynamic_param_errors and dynamic_param_error:
status = "skip"
else:
status = "error"
if input_staging_exception:
job_data["execution_problem"] = f"Input staging problem: {util.unicodify(input_staging_exception)}"
status = "error"
job_data["status"] = status
register_job_data(job_data)
if created_history and not no_history_cleanup:
galaxy_interactor.delete_history(test_history)
def _handle_def_errors(testdef):
# If the test generation had an error, raise
if testdef.error:
if testdef.exception:
if isinstance(testdef.exception, Exception):
raise testdef.exception
else:
raise Exception(testdef.exception)
else:
raise Exception("Test parse failure")
def _verify_outputs(testdef, history, jobs, data_list, data_collection_list, galaxy_interactor, quiet=False):
assert len(jobs) == 1, "Test framework logic error, somehow tool test resulted in more than one job."
job = jobs[0]
found_exceptions: List[Exception] = []
def register_exception(e: Exception):
if not found_exceptions and not quiet:
# Only print this stuff out once.
for stream in ["stdout", "stderr"]:
if stream in job_stdio:
print(_format_stream(job_stdio[stream], stream=stream, format=True), file=sys.stderr)
found_exceptions.append(e)
if testdef.expect_failure:
if testdef.outputs:
raise Exception("Cannot specify outputs in a test expecting failure.")
maxseconds = testdef.maxseconds
# Wait for the job to complete and register expections if the final
# status was not what test was expecting.
job_failed = False
try:
galaxy_interactor.wait_for_job(job["id"], history, maxseconds)
except Exception as e:
job_failed = True
if not testdef.expect_failure:
found_exceptions.append(e)
job_stdio = galaxy_interactor.get_job_stdio(job["id"])
if testdef.num_outputs is not None:
expected = testdef.num_outputs
actual = len(data_list) + len(data_collection_list)
if expected != actual:
message = f"Incorrect number of outputs - expected {expected}, found {actual} (dataset(s): {','.join(data_list.keys())} collection(s): {' '.join(data_collection_list.keys())})"
error = AssertionError(message)
register_exception(error)
if not job_failed and testdef.expect_failure:
error = AssertionError("Expected job to fail but Galaxy indicated the job successfully completed.")
register_exception(error)
expect_exit_code = testdef.expect_exit_code
if expect_exit_code is not None:
exit_code = job_stdio["exit_code"]
if str(expect_exit_code) != str(exit_code):
error = AssertionError(f"Expected job to complete with exit code {expect_exit_code}, found {exit_code}")
register_exception(error)
for output_index, output_dict in enumerate(testdef.outputs):
# Get the correct hid
name = output_dict["name"]
outfile = output_dict["value"]
attributes = output_dict["attributes"]
output_testdef = Bunch(name=name, outfile=outfile, attributes=attributes)
output_data = None
try:
output_data = data_list[name]
except (TypeError, KeyError):
# Legacy - fall back on ordered data list access if data_list is
# just a list (case with twill variant or if output changes its
# name).
try:
if hasattr(data_list, "values"):
output_data = list(data_list.values())[output_index]
else:
output_data = data_list[len(data_list) - len(testdef.outputs) + output_index]
except IndexError:
error = AssertionError(
f"Tool did not produce an output with name '{name}' (or at index {output_index})"
)
register_exception(error)
if output_data:
try:
galaxy_interactor.verify_output(
history,
jobs,
output_data,
output_testdef=output_testdef,
tool_id=job["tool_id"],
maxseconds=maxseconds,
tool_version=testdef.tool_version,
)
except Exception as e:
register_exception(e)
other_checks = {
"command_line": "Command produced by the job",
"command_version": "Tool version indicated during job execution",
"stdout": "Standard output of the job",
"stderr": "Standard error of the job",
}
# TODO: Only hack the stdio like this for older profile, for newer tool profiles
# add some syntax for asserting job messages maybe - or just drop this because exit
# code and regex on stdio can be tested directly - so this is really testing Galaxy
# core handling more than the tool.
job_messages = job_stdio.get("job_messages") or []
stdout_prefix = ""
stderr_prefix = ""
for job_message in job_messages:
message_type = job_message.get("type")
if message_type == "regex" and job_message.get("stream") == "stderr":
stderr_prefix += f"{job_message.get('desc') or ''}\n"
elif message_type == "regex" and job_message.get("stream") == "stdout":
stdout_prefix += f"{job_message.get('desc') or ''}\n"
elif message_type == "exit_code":
stderr_prefix += f"{job_message.get('desc') or ''}\n"
else:
raise Exception(f"Unknown job message type [{message_type}] in [{job_message}]")
for what, description in other_checks.items():
if getattr(testdef, what, None) is not None:
try:
raw_data = job_stdio[what]
assertions = getattr(testdef, what)
if what == "stdout":
data = stdout_prefix + raw_data
elif what == "stderr":
data = stderr_prefix + raw_data
else:
data = raw_data
verify_assertions(data, assertions)
except AssertionError as err:
errmsg = f"{description} different than expected\n"
errmsg += util.unicodify(err)
register_exception(AssertionError(errmsg))
for output_collection_def in testdef.output_collections:
try:
name = output_collection_def.name
# TODO: data_collection_list is clearly a bad name for dictionary.
if name not in data_collection_list:
message = (
f"Failed to find output [{name}], tool outputs include [{','.join(data_collection_list.keys())}]"
)
raise AssertionError(message)
# Data collection returned from submission, elements may have been populated after
# the job completed so re-hit the API for more information.
data_collection_id = data_collection_list[name]["id"]
galaxy_interactor.verify_output_collection(
output_collection_def, data_collection_id, history, job["tool_id"]
)
except Exception as e:
register_exception(e)
if found_exceptions and not testdef.expect_test_failure:
raise JobOutputsError(found_exceptions, job_stdio)
elif not found_exceptions and testdef.expect_test_failure:
register_exception(AssertionError("Expected job to miss at least one test assumption but all were met."))
raise JobOutputsError(found_exceptions, job_stdio)
else:
return job_stdio
def _format_stream(output, stream, format):
output = output or ""
if format:
msg = f"---------------------- >> begin tool {stream} << -----------------------\n"
msg += f"{output}\n"
msg += f"----------------------- >> end tool {stream} << ------------------------\n"
else:
msg = output
return msg
[docs]class JobOutputsError(AssertionError):
[docs] def __init__(self, output_exceptions, job_stdio):
big_message = "\n".join(map(util.unicodify, output_exceptions))
super().__init__(big_message)
self.job_stdio = job_stdio
self.output_exceptions = output_exceptions
[docs]class ToolTestDescriptionDict(TypedDict):
name: str
inputs: Any
outputs: Any
output_collections: List[Dict[str, Any]]
stdout: Optional[AssertionList]
stderr: Optional[AssertionList]
expect_exit_code: Optional[int]
expect_failure: bool
expect_test_failure: bool
num_outputs: Optional[int]
command_line: Optional[AssertionList]
command_version: Optional[AssertionList]
required_files: List[Any]
required_data_tables: List[Any]
required_loc_files: List[str]
error: bool
tool_id: str
tool_version: Optional[str]
test_index: int
exception: Optional[str]
[docs]class ToolTestDescription:
"""
Encapsulates information about a tool test, and allows creation of a
dynamic TestCase class (the unittest framework is very class oriented,
doing dynamic tests in this way allows better integration)
"""
name: str
num_outputs: Optional[int]
stdout: Optional[AssertionList]
stderr: Optional[AssertionList]
command_line: Optional[AssertionList]
command_version: Optional[AssertionList]
required_files: List[Any]
required_data_tables: List[Any]
required_loc_files: List[str]
expect_exit_code: Optional[int]
expect_failure: bool
expect_test_failure: bool
exception: Optional[str]
[docs] def __init__(self, processed_test_dict: ToolTestDict):
assert (
"test_index" in processed_test_dict
), "Invalid processed test description, must have a 'test_index' for naming, etc.."
test_index = processed_test_dict["test_index"]
name = cast(str, processed_test_dict.get("name", f"Test-{test_index + 1}"))
error_in_test_definition = processed_test_dict["error"]
if not error_in_test_definition:
processed_test_dict = cast(ValidToolTestDict, processed_test_dict)
maxseconds = int(processed_test_dict.get("maxseconds") or DEFAULT_TOOL_TEST_WAIT or 86400)
output_collections = processed_test_dict.get("output_collections", [])
else:
processed_test_dict = cast(InvalidToolTestDict, processed_test_dict)
maxseconds = DEFAULT_TOOL_TEST_WAIT
output_collections = []
self.test_index = test_index
assert (
"tool_id" in processed_test_dict
), "Invalid processed test description, must have a 'tool_id' for naming, etc.."
self.tool_id = processed_test_dict["tool_id"]
self.tool_version = processed_test_dict.get("tool_version")
self.name = name
self.maxseconds = maxseconds
self.required_files = cast(List[Any], processed_test_dict.get("required_files", []))
self.required_data_tables = cast(List[Any], processed_test_dict.get("required_data_tables", []))
self.required_loc_files = cast(List[str], processed_test_dict.get("required_loc_files", []))
inputs = processed_test_dict.get("inputs", {})
loaded_inputs = {}
for key, value in inputs.items():
if isinstance(value, dict) and value.get("model_class"):
loaded_inputs[key] = TestCollectionDef.from_dict(value)
else:
loaded_inputs[key] = value
self.inputs = loaded_inputs
self.outputs = processed_test_dict.get("outputs", [])
self.num_outputs = cast(Optional[int], processed_test_dict.get("num_outputs", None))
self.error = processed_test_dict.get("error", False)
self.exception = cast(Optional[str], processed_test_dict.get("exception", None))
self.output_collections = [TestCollectionOutputDef.from_dict(d) for d in output_collections]
self.command_line = cast(Optional[AssertionList], processed_test_dict.get("command_line", None))
self.command_version = cast(Optional[AssertionList], processed_test_dict.get("command_version", None))
self.stdout = cast(Optional[AssertionList], processed_test_dict.get("stdout", None))
self.stderr = cast(Optional[AssertionList], processed_test_dict.get("stderr", None))
self.expect_exit_code = cast(Optional[int], processed_test_dict.get("expect_exit_code", None))
self.expect_failure = cast(bool, processed_test_dict.get("expect_failure", False))
self.expect_test_failure = cast(bool, processed_test_dict.get("expect_test_failure", False))
[docs] def test_data(self):
"""
Iterator over metadata representing the required files for upload.
"""
return test_data_iter(self.required_files)
[docs] def to_dict(self) -> ToolTestDescriptionDict:
inputs_dict = {}
for key, value in self.inputs.items():
if hasattr(value, "to_dict"):
inputs_dict[key] = value.to_dict()
else:
inputs_dict[key] = value
return {
"inputs": inputs_dict,
"outputs": self.outputs,
"output_collections": [_.to_dict() for _ in self.output_collections],
"num_outputs": self.num_outputs,
"command_line": self.command_line,
"command_version": self.command_version,
"stdout": self.stdout,
"stderr": self.stderr,
"expect_exit_code": self.expect_exit_code,
"expect_failure": self.expect_failure,
"expect_test_failure": self.expect_test_failure,
"name": self.name,
"test_index": self.test_index,
"tool_id": self.tool_id,
"tool_version": self.tool_version,
"required_files": self.required_files,
"required_data_tables": self.required_data_tables,
"required_loc_files": self.required_loc_files,
"error": self.error,
"exception": self.exception,
}
[docs]def test_data_iter(required_files):
for fname, extra in required_files:
data_dict = dict(
fname=fname,
metadata=extra.get("metadata", {}),
composite_data=extra.get("composite_data", []),
ftype=extra.get("ftype", DEFAULT_FTYPE),
dbkey=extra.get("dbkey", DEFAULT_DBKEY),
location=extra.get("location", None),
)
edit_attributes = extra.get("edit_attributes", [])
# currently only renaming is supported
for edit_att in edit_attributes:
if edit_att.get("type", None) == "name":
new_name = edit_att.get("value", None)
assert new_name, "You must supply the new dataset name as the value tag of the edit_attributes tag"
data_dict["name"] = new_name
else:
raise Exception(f"edit_attributes type ({edit_att.get('type', None)}) is unimplemented")
yield data_dict