import contextlib
import io
import json
import os
import re
import shutil
import sys
import tempfile
import time
import traceback
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,
)

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.client.staging import StagingInterface
from galaxy.tool_util.parameters import (
    DataCollectionRequest,
    DataRequestHda,
    encode_test,
    input_models_from_json,
    TestCaseToolState,
    ToolParameterBundle,
)
from galaxy.tool_util.parser.interface import (
    AssertionList,
    TestCollectionDef,
    TestCollectionOutputDef,
    TestSourceTestOutputColllection,
    ToolSourceTestOutputs,
    XmlTestCollectionDefDict,
)
from galaxy.tool_util.verify.test_data import TestDataResolver
from galaxy.tool_util_models.tool_source import (
    JsonTestCollectionDefDict,
    JsonTestDatasetDefDict,
)
from galaxy.util import requests
from galaxy.util.bunch import Bunch
from galaxy.util.compression_utils import CompressedFile
from galaxy.util.hash_util import (
    memory_bound_hexdigest,
    parse_checksum_hash,
)
from . import verify
from ._types import (
    ExpandedToolInputs,
    ExpandedToolInputsJsonified,
    RawTestToolRequest,
    RequiredDataTablesT,
    RequiredFilesT,
    RequiredLocFileT,
    ToolTestDescriptionDict,
)
from .asserts import verify_assertions
from .wait import wait_on

log = getLogger(__name__)

UseLegacyApiT = Literal["always", "never", "if_needed"]
DEFAULT_USE_LEGACY_API: UseLegacyApiT = "always"

# 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 = 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", "?")


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]


class ValidToolTestDict(TypedDict):
    inputs: ExpandedToolInputs
    request: NotRequired[Optional[RawTestToolRequest]]
    request_schema: NotRequired[Optional[Dict[str, Any]]]
    outputs: ToolSourceTestOutputs
    output_collections: List[TestSourceTestOutputColllection]
    stdout: NotRequired[AssertionList]
    stderr: NotRequired[AssertionList]
    expect_exit_code: NotRequired[Optional[Union[str, int]]]
    expect_failure: NotRequired[bool]
    expect_test_failure: NotRequired[bool]
    maxseconds: NotRequired[Optional[int]]
    num_outputs: NotRequired[Optional[Union[str, int]]]
    command_line: NotRequired[AssertionList]
    command_version: NotRequired[AssertionList]
    required_files: NotRequired[RequiredFilesT]
    required_data_tables: NotRequired[RequiredDataTablesT]
    required_loc_files: NotRequired[RequiredLocFileT]
    error: Literal[False]
    tool_id: str
    tool_version: str
    test_index: int


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]


class PathOrLocation(NamedTuple):
    name: str
    path: Optional[str]
    location: Optional[str]


def stage_data_in_history(
    galaxy_interactor: "GalaxyInteractorApi",
    tool_id: str,
    all_test_data,
    history: str,
    force_path_paste=False,
    maxseconds=DEFAULT_TOOL_TEST_WAIT,
    tool_version=None,
    test_data_resolver: Optional[TestDataResolver] = None,
):
    assert tool_id, "Tool id not set"

    staging_interface = InteractorStagingInterface(galaxy_interactor, maxseconds=maxseconds, upload_async=UPLOAD_ASYNC)
    job = {}
    for test_data in all_test_data:
        test_dict = galaxy_interactor.remote_to_input(
            test_data=test_data, tool_id=tool_id, force_path_paste=force_path_paste, tool_version=tool_version
        )
        job[test_data["fname"]] = test_dict
    resolve_data = test_data_resolver.get_filename if test_data_resolver else None
    staging_interface.stage(
        "tool",
        history_id=history,
        job=job,
        use_path_paste=force_path_paste,
        resolve_data=resolve_data,
    )
    staging_interface.handle_jobs()
    galaxy_interactor.uploads = job
    return


class RunToolResponse(NamedTuple):
    inputs: Dict[str, Any]
    outputs: OutputsDict
    output_collections: Dict[str, Any]
    jobs: List[Dict[str, Any]]


class InteractorStagingInterface(StagingInterface):

    def __init__(self, galaxy_interactor: "GalaxyInteractorApi", maxseconds: Optional[int], upload_async: bool) -> None:
        super().__init__()
        self.galaxy_interactor = galaxy_interactor
        self.maxseconds = maxseconds or DEFAULT_TOOL_TEST_WAIT
        self.upload_async = upload_async
        self.job_responses: List[Dict[str, Any]] = []

    def _post(self, api_path: str, payload: Dict[str, Any]) -> Dict[str, Any]:
        response = self.galaxy_interactor._post(api_path, payload, json=True)
        assert response.status_code == 200, f"Staging failed: {response.text}"
        return response.json()

    def _handle_job(self, job_response: Dict[str, Any]):
        if not self.upload_async:
            return self.galaxy_interactor.wait_for_job(
                job_response["id"], job_response["history_id"], maxseconds=self.maxseconds
            )
        else:
            self.job_responses.append(job_response)
        return

    def handle_jobs(self):
        for job_response in self.job_responses:
            self.galaxy_interactor.wait_for_job(job_response["id"], job_response["history_id"], self.maxseconds)

    @property
    def use_fetch_api(self):
        return True


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]

    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()

    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()

    def get_tool_inputs(self, tool_id: str, tool_version: Optional[str] = None) -> ToolParameterBundle:
        url = f"tools/{tool_id}/inputs"
        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 inputs API. [{response.content}]"
        raw_inputs_array = response.json()
        tool_parameter_bundle = input_models_from_json(raw_inputs_array)
        return tool_parameter_bundle

    def get_tool_tests(self, tool_id: str, tool_version: Optional[str] = None) -> List[ToolTestDescriptionDict]:
        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()

    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)

    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")
        min_count = attributes.get("min")
        max_count = attributes.get("max")
        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}'"
            )
        if min_count is not None and min_count > found_datasets:
            raise AssertionError(
                f"Output '{name}': expected to have at least '{min_count}' datasets, but it had '{found_datasets}'"
            )
        if max_count is not None and max_count < found_datasets:
            raise AssertionError(
                f"Output '{name}': expected to have at most '{max_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)}")

    def wait_for_jobs(self, history_id, jobs, maxseconds):
        for job in jobs:
            self.wait_for_job(job["id"], history_id, maxseconds)

    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 = get_metadata_to_test(attributes)

        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)
            compare_expected_metadata_to_api_response(metadata, dataset)

    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)

    def wait_on_tool_request(self, tool_request_id: str):
        def state():
            state_response = self._get(f"tool_requests/{tool_request_id}/state")
            state_response.raise_for_status()
            return state_response.json()

        def is_ready():
            is_complete = state() in ["submitted", "failed"]
            return True if is_complete else None

        self.wait_for(is_ready, "waiting for tool request to submit")
        return state() == "submitted"

    def get_tool_request(self, tool_request_id: str):
        response_raw = self._get(f"tool_requests/{tool_request_id}")
        response_raw.raise_for_status()
        return response_raw.json()

    def wait_for(self, func: Callable, what: str = "tool test run", **kwd) -> None:
        walltime_exceeded = int(kwd.get("maxseconds", DEFAULT_TOOL_TEST_WAIT))
        return wait_on(func, what, walltime_exceeded)

    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")

    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", "show_own": "true"})
        response = self._get(f"histories?{filters}")
        try:
            return response.json()[-1]
        except IndexError:
            return None

    @contextlib.contextmanager
    def test_history(
        self,
        require_new: bool = True,
        cleanup_callback: Optional[Callable[[str], None]] = None,
        name: Optional[str] = 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(name)
        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)

    def new_history(self, history_name: Optional[str] = None, publish_history: bool = False) -> str:
        history_name = history_name or "test_history"
        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

    def publish_history(self, history_id: str) -> None:
        response = self._put(f"histories/{history_id}", json.dumps({"published": True}))
        response.raise_for_status()

    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"])

    def test_data_download(self, tool_id, filename, mode="file", is_output=True, tool_version=None, path_only=False):
        result: Optional[Union[str, bytes]] = None
        local_path: Optional[str] = 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":
                    if path_only:
                        pardir = tempfile.mkdtemp()
                        path = os.path.join(pardir, os.path.basename(filename))
                        with open(path, "wb") as out:
                            out.write(response.content)
                        return out.name
                    else:
                        return 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 CompressedFile.open_tar(fileobj) as tar_contents:
                            tar_contents.extractall(path=path)
                    result = path
                    if path_only:
                        return result
        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":
                if path_only:
                    return local_path
                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

    def remote_to_input(
        self, test_data, tool_id: str, force_path_paste: bool = False, tool_version: Optional[str] = None
    ):
        fname = test_data["fname"]
        tags = test_data.get("tags")
        tool_input = {
            "format": test_data["ftype"],
            "dbkey": test_data["dbkey"],
            "class": test_data.get("class", "File"),
            # Match legacy test behavior
            "decompress": util.string_as_bool(test_data.get("decompress", True)),
        }
        if tags:
            if isinstance(tags, str):
                tags = tags.split(",")
            tool_input["tags"] = tags

        metadata = test_data.get("metadata", {})
        if not hasattr(metadata, "items"):
            raise Exception(f"Invalid metadata description found for input [{fname}] - [{metadata}]")
        tool_input["metadata"] = metadata

        composite_data = test_data["composite_data"]
        if composite_data:
            tool_input["composite_data"] = [
                self._get_path_or_location(
                    fname=fname_,
                    test_data={},
                    tool_id=tool_id,
                    tool_version=tool_version,
                    force_path_paste=force_path_paste,
                ).path
                for fname_ in composite_data
            ]
        else:
            assert fname, "File path is required and cannot be empty string"
            path_or_location = self._get_path_or_location(
                fname,
                test_data,
                tool_id,
                tool_version=tool_version,
                mode="file" if tool_input["class"].lower() == "file" else "directory",
            )
            if path_or_location.path:
                tool_input["path"] = path_or_location.path
            if path_or_location.location:
                tool_input["location"] = path_or_location.location
            tool_input["name"] = os.path.basename(path_or_location.name)
        return tool_input

    def _get_path_or_location(
        self,
        fname: str,
        test_data: Dict[str, Any],
        tool_id: str,
        tool_version: Optional[str] = None,
        force_path_paste: bool = False,
        mode: Literal["file", "directory"] = "file",
    ) -> PathOrLocation:
        file_name = None
        file_name_exists = False
        location = self._ensure_valid_location_in(test_data)
        if fname and force_path_paste:
            file_name = self.test_data_path(tool_id, fname, tool_version=tool_version)
            file_name_exists = os.path.exists(file_name)
        if not file_name_exists and location is not None:
            return PathOrLocation(name=location, location=location, path=None)
        else:
            if force_path_paste:
                if file_name is None:
                    file_name = self.test_data_path(tool_id, fname, tool_version=tool_version)
                return PathOrLocation(name=fname, location=f"file://{file_name}", path=None)
            else:
                path = self.test_data_download(
                    tool_id, fname, is_output=False, tool_version=tool_version, mode=mode, path_only=True
                )
                assert isinstance(path, str)
                # Downloaded directories contain root directory
                if path and mode == "directory":
                    path = os.path.join(path, fname)
                return PathOrLocation(name=fname, location=None, path=path)

    def _ensure_valid_location_in(self, test_data: dict) -> Optional[str]:
        location: Optional[str] = test_data.get("location")
        if location and not util.is_url(location):
            raise ValueError(f"Invalid `location` URL: `{location}`")
        return location

    def run_tool(
        self,
        testdef: "ToolTestDescription",
        history_id: str,
        resource_parameters: Optional[Dict[str, Any]] = None,
        use_legacy_api: UseLegacyApiT = DEFAULT_USE_LEGACY_API,
    ) -> 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 {}
        request = testdef.request
        request_schema = testdef.request_schema
        submit_with_legacy_api = use_legacy_api == "always" or (use_legacy_api == "if_needed" and request is None)
        if submit_with_legacy_api:
            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

            # 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]
        else:
            assert request is not None, "Request not set"
            assert request_schema is not None, "Request schema not set"
            parameters = request_schema["parameters"]

            def adapt_datasets(test_input: JsonTestDatasetDefDict) -> DataRequestHda:
                # if path is not set it might be a composite file with a path,
                # e.g. composite_shapefile
                test_input_path = test_input.get("path", "")
                return DataRequestHda(**self.uploads[test_input_path])

            def adapt_collections(test_input: JsonTestCollectionDefDict) -> DataCollectionRequest:
                test_collection_def = TestCollectionDef.from_dict(test_input)
                hdca_id = self._create_collection(history_id, test_collection_def)
                return DataCollectionRequest(src="hdca", id=hdca_id)

            test_case_state = TestCaseToolState(input_state=request)
            inputs_tree = encode_test(
                test_case_state, input_models_from_json(parameters), adapt_datasets, adapt_collections
            ).input_state

        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

        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,
                use_legacy_api=submit_with_legacy_api,
            )
            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)
        if not submit_with_legacy_api:
            tool_request_id = submit_response_object["tool_request_id"]
            successful = self.wait_on_tool_request(tool_request_id)
            if not successful:
                request = self.get_tool_request(tool_request_id) or {}
                raise RunToolException(
                    f"Tool request failure - state {request.get('state')}, message: {request.get('state_message')}",
                    inputs_tree,
                )
            job_refs = self.jobs_for_tool_request(tool_request_id)
            outputs = OutputsDict()
            output_collections = {}
            if len(job_refs) != 1:
                raise Exception(
                    f"Found incorrect number of jobs for tool request - was expecting a single job {job_refs}"
                )
            assert len(job_refs) == 1, job_refs
            job_id = job_refs[0]["id"]
            jobs = [self.__get_job(job_id).json()]
            job_outputs = self.job_outputs(job_id)
            for job_output in job_outputs:
                if "dataset" in job_output:
                    outputs[job_output["name"]] = job_output["dataset"]
                else:
                    output_collections[job_output["name"]] = job_output["dataset_collection_instance"]
        else:
            outputs = self.__dictify_outputs(submit_response_object)
            output_collections = self.__dictify_output_collections(submit_response_object)
            jobs = submit_response_object["jobs"]
        try:
            return RunToolResponse(
                inputs=inputs_tree,
                outputs=outputs,
                output_collections=output_collections,
                jobs=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,
        )
        if collection_def.fields:
            create_payload["fields"] = collection_def.fields
        create_response = self._post("dataset_collections", data=create_payload, json=True)
        create_response.raise_for_status()
        return create_response.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:
                    if isinstance(tags, str):
                        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 output_hid(self, output_data):
        return output_data["id"]

    def delete_history(self, history: str) -> None:
        self._delete(f"histories/{history}")

    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: Optional[str] = dataset.get("id")
            if dataset_id is None:
                print("| *TEST FRAMEWORK ERROR - NO DATASET ID*")
                continue

            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)

    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: str, id: str) -> Dict[str, Any]:
        provenance = self._get(f"histories/{history_id}/contents/{id}/provenance").json()
        return provenance

    def _dataset_info(self, history_id: str, id: str) -> Dict[str, Any]:
        dataset_json = self._get(f"histories/{history_id}/contents/{id}").json()
        return dataset_json

    def jobs_for_tool_request(self, tool_request_id: str) -> List[Dict[str, Any]]:
        job_list_response = self._get(f"tool_requests/{tool_request_id}")
        job_list_response.raise_for_status()
        return job_list_response.json()["jobs"]

    def job_outputs(self, job_id: str) -> List[Dict[str, Any]]:
        outputs = self._get(f"jobs/{job_id}/outputs")
        outputs.raise_for_status()
        return outputs.json()

    def __contents(self, history_id: str) -> List[Dict[str, Any]]:
        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: str,
        tool_id: str,
        tool_input: Optional[dict],
        extra_data: Optional[dict] = None,
        files: Optional[dict] = None,
        tool_version: Optional[str] = None,
        use_legacy_api: bool = True,
    ):
        extra_data = extra_data or {}
        if use_legacy_api:
            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)
        else:
            assert files is None
            data = dict(
                history_id=history_id, tool_id=tool_id, inputs=tool_input, tool_version=tool_version, **extra_data
            )
            submit_tool_request_response = self._post("jobs", data=data, json=True)
            return submit_tool_request_response

    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, f"Failed to fetch url '{url}'"
            response.raise_for_status()
            return response.content

        return fetcher

    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 _options(
        self,
        path: str,
        data: 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, as_json=json, headers=headers)
        kwd["timeout"] = kwd.pop("timeout", util.DEFAULT_SOCKET_TIMEOUT)
        return requests.options(url, **kwd)

    def _delete(self, path, data=None, key=None, headers=None, admin=False, anon=False, json=False, params=None):
        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, params=params, 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)

    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
        )


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: Dict[str, Any] = {
        "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


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


class RunToolException(Exception):
    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.
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,
    )


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)

    actual_element_count = len(data_collection["elements"])
    if output_collection_def.count and output_collection_def.count != actual_element_count:
        message = f"Output collection '{name}': expected to have {output_collection_def.count} elements, but it had {actual_element_count}."
        raise AssertionError(message)
    if output_collection_def.min and output_collection_def.min > actual_element_count:
        message = f"Output collection '{name}': expected to have at least {output_collection_def.min} elements, but it had {actual_element_count}."
        raise AssertionError(message)
    if output_collection_def.max and output_collection_def.max < actual_element_count:
        message = f"Output collection '{name}': expected to have at most {output_collection_def.max} 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
            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", {}))
            expected_count = element_attrib.get("count")
            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}"
                )
            max = element_attrib.get("max")
            if max is not None and max < element_count:
                raise AssertionError(
                    f"Element '{element_identifier}': expected to have at most {max} elements, but it had {element_count}"
                )
            min = element_attrib.get("min")
            if min is not None and min > element_count:
                raise AssertionError(
                    f"Element '{element_identifier}': expected to have at least {min} 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)

    if output_collection_def.element_tests:
        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)


class TestConfig(Protocol):
    def get_test_config(self, job_data: Dict[str, Any]) -> Optional[Dict[str, Any]]: ...


class NullClientTestConfig(TestConfig):
    def get_test_config(self, job_data):
        return None


class DictClientTestConfig(TestConfig):
    def __init__(self, tools):
        self._tools = tools or {}

    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


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,
    use_legacy_api: UseLegacyApiT = DEFAULT_USE_LEGACY_API,
    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[List[ToolTestDescriptionDict]] = None,  # extension point only for tests
    test_data_resolver: Optional[TestDataResolver] = None,
):
    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: ToolTestDescriptionDict = tool_test_dicts[test_index]
    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(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_exc_info = 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,
                test_data_resolver=test_data_resolver,
            )
        except Exception:
            input_staging_exc_info = sys.exc_info()
            raise
        try:
            tool_response = galaxy_interactor.run_tool(
                testdef, test_history, resource_parameters=resource_parameters, use_legacy_api=use_legacy_api
            )
            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_exc_info:
                job_data["execution_problem"] = (
                    f"Input staging problem: {''.join(traceback.format_exception(*input_staging_exc_info))}"
                )
                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


class JobOutputsError(AssertionError):
    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


DEFAULT_NUM_OUTPUTS: Optional[int] = None
DEFAULT_OUTPUT_COLLECTIONS: List[TestSourceTestOutputColllection] = []
DEFAULT_REQUIRED_FILES: RequiredFilesT = []
DEFAULT_REQUIRED_DATA_TABLES: RequiredDataTablesT = []
DEFAULT_REQUIRED_LOC_FILES: RequiredLocFileT = []
DEFAULT_COMMAND_LINE: Optional[AssertionList] = []
DEFAULT_COMMAND_VERSION: Optional[AssertionList] = []
DEFAULT_STDOUT: Optional[AssertionList] = []
DEFAULT_STDERR: Optional[AssertionList] = []
DEFAULT_OUTPUTS: ToolSourceTestOutputs = []
DEFAULT_EXPECT_EXIT_CODE: Optional[int] = None
DEFAULT_EXPECT_FAILURE: bool = False
DEFAULT_EXPECT_TEST_FAILURE: bool = False
DEFAULT_EXCEPTION: Optional[str] = None


def adapt_tool_source_dict(processed_dict: ToolTestDict) -> ToolTestDescriptionDict:
    """Convert the dictionaries parsed from tool sources (ToolTestDict) to a ToolTestDescriptionDict.

    ToolTestDescription is used inside and outside of Galaxy, so convert the dictionaries to the format
    produced by ToolTestDescription.to_dict() and then construct a ToolTestDescription from that.
    """
    test_index: int = _get_test_index(processed_dict)
    name = _get_test_name(processed_dict, test_index)
    error_in_test_definition = processed_dict["error"]

    exception: Optional[str] = DEFAULT_EXCEPTION
    output_collections: List[TestSourceTestOutputColllection] = []
    num_outputs: Optional[int] = DEFAULT_NUM_OUTPUTS
    required_files: RequiredFilesT = DEFAULT_REQUIRED_FILES
    required_data_tables: RequiredDataTablesT = DEFAULT_REQUIRED_DATA_TABLES
    required_loc_files: RequiredLocFileT = DEFAULT_REQUIRED_LOC_FILES
    command_line: Optional[AssertionList] = DEFAULT_COMMAND_LINE
    command_version: Optional[AssertionList] = DEFAULT_COMMAND_VERSION
    stdout: Optional[AssertionList] = DEFAULT_STDERR
    stderr: Optional[AssertionList] = DEFAULT_STDERR
    outputs: ToolSourceTestOutputs = DEFAULT_OUTPUTS
    expect_exit_code: Optional[int] = DEFAULT_EXPECT_EXIT_CODE
    expect_failure: bool = DEFAULT_EXPECT_FAILURE
    expect_test_failure: bool = DEFAULT_EXPECT_TEST_FAILURE
    inputs: ExpandedToolInputsJsonified = {}
    maxseconds: Optional[int] = None
    request: Optional[Dict[str, Any]] = None
    request_schema: Optional[Dict[str, Any]] = None

    if not error_in_test_definition:
        processed_test_dict = cast(ValidToolTestDict, processed_dict)
        maxseconds = processed_test_dict.get("maxseconds")
        output_collections = processed_test_dict.get("output_collections", [])
        if "num_outputs" in processed_test_dict and processed_test_dict["num_outputs"]:
            num_outputs = int(processed_test_dict["num_outputs"])

        required_files = processed_test_dict.get("required_files", DEFAULT_REQUIRED_FILES)
        required_data_tables = processed_test_dict.get("required_data_tables", DEFAULT_REQUIRED_DATA_TABLES)
        required_loc_files = processed_test_dict.get("required_loc_files", DEFAULT_REQUIRED_LOC_FILES)
        command_line = processed_test_dict.get("command_line", DEFAULT_COMMAND_LINE)
        command_version = processed_test_dict.get("command_version", DEFAULT_COMMAND_VERSION)
        stdout = processed_test_dict.get("stdout", DEFAULT_STDOUT)
        stderr = processed_test_dict.get("stderr", DEFAULT_STDERR)
        outputs = processed_test_dict.get("outputs", DEFAULT_OUTPUTS)
        raw_expect_exit_code: Optional[Union[str, int]] = processed_test_dict.get(
            "expect_exit_code", DEFAULT_EXPECT_EXIT_CODE
        )
        if raw_expect_exit_code is not None:
            expect_exit_code = int(raw_expect_exit_code)

        expect_failure = processed_test_dict.get("expect_failure", DEFAULT_EXPECT_FAILURE)
        expect_test_failure = processed_test_dict.get("expect_test_failure", DEFAULT_EXPECT_TEST_FAILURE)
        inputs = processed_test_dict.get("inputs", {})
        request = processed_test_dict.get("request", None)
        request_schema = processed_test_dict.get("request_schema", None)
    else:
        invalid_test_dict = cast(InvalidToolTestDict, processed_dict)
        maxseconds = DEFAULT_TOOL_TEST_WAIT
        exception = invalid_test_dict.get("exception", DEFAULT_EXCEPTION)

    return ToolTestDescriptionDict(
        test_index=test_index,
        name=name,
        error=error_in_test_definition,
        maxseconds=maxseconds,
        tool_id=processed_dict["tool_id"],
        tool_version=processed_dict.get("tool_version"),
        exception=exception,
        num_outputs=num_outputs,
        required_files=required_files,
        required_data_tables=required_data_tables,
        required_loc_files=required_loc_files,
        command_line=command_line,
        command_version=command_version,
        stdout=stdout,
        stderr=stderr,
        outputs=outputs,
        output_collections=output_collections,
        expect_exit_code=expect_exit_code,
        expect_failure=expect_failure,
        expect_test_failure=expect_test_failure,
        inputs=inputs,
        request=request,
        request_schema=request_schema,
    )


def _get_test_index(test_dict: Union[ToolTestDict, ToolTestDescriptionDict]) -> int:
    assert "test_index" in test_dict, "Invalid processed test description, must have a 'test_index' for naming, etc.."
    return test_dict["test_index"]


def _get_test_name(test_dict: Union[ToolTestDict, ToolTestDescriptionDict], test_index: int) -> str:
    name = cast(str, test_dict.get("name", f"Test-{test_index + 1}"))
    return name


def expanded_inputs_from_json(expanded_inputs_json: ExpandedToolInputsJsonified) -> ExpandedToolInputs:
    loaded_inputs: ExpandedToolInputs = {}
    for key, value in expanded_inputs_json.items():
        if isinstance(value, dict) and value.get("model_class"):
            collection_def_dict = cast(XmlTestCollectionDefDict, value)
            loaded_inputs[key] = TestCollectionDef.from_dict(collection_def_dict)
        else:
            loaded_inputs[key] = value
    return loaded_inputs


def expanded_inputs_to_json(expanded_inputs: ExpandedToolInputs) -> ExpandedToolInputsJsonified:
    inputs_dict: ExpandedToolInputsJsonified = {}
    for key, value in expanded_inputs.items():
        if hasattr(value, "to_dict"):
            inputs_dict[key] = value.to_dict()
        else:
            inputs_dict[key] = value
    return inputs_dict


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
    tool_id: str
    tool_version: Optional[str]
    test_index: int
    num_outputs: Optional[int]
    stdout: Optional[AssertionList]
    stderr: Optional[AssertionList]
    command_line: Optional[AssertionList]
    command_version: Optional[AssertionList]
    required_files: RequiredFilesT
    required_data_tables: RequiredDataTablesT
    required_loc_files: RequiredLocFileT
    expect_exit_code: Optional[int]
    expect_failure: bool
    expect_test_failure: bool
    exception: Optional[str]
    inputs: ExpandedToolInputs
    request: Optional[Dict[str, Any]]
    request_schema: Optional[Dict[str, Any]]
    outputs: ToolSourceTestOutputs
    output_collections: List[TestCollectionOutputDef]
    maxseconds: Optional[int]

    @staticmethod
    def from_tool_source_dict(processed_test_dict: ToolTestDict) -> "ToolTestDescription":
        return ToolTestDescription(adapt_tool_source_dict(processed_test_dict))

    def __init__(self, json_dict: ToolTestDescriptionDict):
        self.test_index = _get_test_index(json_dict)
        self.name = _get_test_name(json_dict, self.test_index)
        self.error = json_dict["error"]
        self.exception = json_dict.get("exception", DEFAULT_EXCEPTION)
        output_collections = json_dict.get("output_collections", DEFAULT_OUTPUT_COLLECTIONS)
        self.output_collections = [TestCollectionOutputDef.from_dict(d) for d in output_collections]
        self.num_outputs = json_dict.get("num_outputs", DEFAULT_NUM_OUTPUTS)
        self.required_files = json_dict.get("required_files", DEFAULT_REQUIRED_FILES)
        self.required_data_tables = json_dict.get("required_data_tables", DEFAULT_REQUIRED_DATA_TABLES)
        self.required_loc_files = json_dict.get("required_loc_files", DEFAULT_REQUIRED_LOC_FILES)
        self.command_line = json_dict.get("command_line", DEFAULT_COMMAND_LINE)
        self.command_version = json_dict.get("command_version", DEFAULT_COMMAND_VERSION)
        self.stdout = json_dict.get("stdout", DEFAULT_STDOUT)
        self.stderr = json_dict.get("stderr", DEFAULT_STDERR)
        self.outputs = json_dict.get("outputs", DEFAULT_OUTPUTS)
        self.expect_exit_code = json_dict.get("expect_exit_code", DEFAULT_EXPECT_EXIT_CODE)
        self.expect_failure = json_dict.get("expect_failure", DEFAULT_EXPECT_FAILURE)
        self.expect_test_failure = json_dict.get("expect_test_failure", DEFAULT_EXPECT_TEST_FAILURE)
        self.inputs = expanded_inputs_from_json(json_dict.get("inputs", {}))
        self.request = json_dict.get("request", None)
        self.request_schema = json_dict.get("request_schema", None)
        self.tool_id = json_dict["tool_id"]
        self.tool_version = json_dict.get("tool_version")
        self.maxseconds = json_dict.get("maxseconds")

    def test_data(self):
        """
        Iterator over metadata representing the required files for upload.
        """
        return test_data_iter(self.required_files)

    def to_dict(self) -> ToolTestDescriptionDict:
        inputs = expanded_inputs_to_json(self.inputs)
        test_description_def: ToolTestDescriptionDict = {
            "inputs": inputs,
            "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,
            "request": self.request,
            "request_schema": self.request_schema,
            "error": self.error,
            "exception": self.exception,
        }
        if self.maxseconds is not None:
            test_description_def["maxseconds"] = self.maxseconds
        return ToolTestDescriptionDict(**test_description_def)


def test_data_iter(required_files):
    for fname, extra in required_files:
        default_ftype = DEFAULT_FTYPE if extra.get("class", "File").lower() != "directory" else "directory"
        data_dict = {
            "fname": fname,
            "class": extra.get("class", "File"),
            "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),
            "tags": extra.get("tags", []),
        }
        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


def compare_expected_metadata_to_api_response(metadata: dict, dataset: dict) -> None:
    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.")


def get_metadata_to_test(test_properties: dict) -> dict:
    """Fetch out metadata to test from test property dict and adapt it to keys the API produces."""
    metadata = test_properties.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 = test_properties.get("ftype", None)
    if expected_file_type:
        metadata["file_ext"] = expected_file_type
    return metadata
