def run_workflow(self,
wdl_path: Path,
inputs: Optional[dict] = None,
expected: Optional[dict] = None,
**kwargs) -> dict:
"""
Run a WDL workflow on given inputs, and check that the output matches
given expected values.
Args:
wdl_path: The WDL script to execute.
inputs: Object that will be serialized to JSON and provided to Cromwell
as the workflow inputs.
expected: Dict mapping output parameter names to expected values.
kwargs: Additional keyword arguments, mostly for debugging:
* workflow_name: Name of the workflow to run.
* task_name: Name of the task to run if a workflow isn't defined.
* inputs_file: Path to the Cromwell inputs file to use. Inputs are
written to this file only if it doesn't exist.
Returns:
Dict of outputs.
Raises:
Exception: if there was an error executing Cromwell
AssertionError: if the actual outputs don't match the expected outputs
"""
wdl_doc = CLI.load(str(wdl_path),
path=[str(path) for path in self._import_dirs],
check_quant=kwargs.get("check_quant", True),
read_source=CLI.read_source)
namespace, is_task = get_target_name(wdl_doc=wdl_doc, **kwargs)
inputs_dict, inputs_file = read_write_inputs(
inputs_dict=inputs,
namespace=namespace if not is_task else None,
)
target, input_env, input_json = CLI.runner_input(
doc=wdl_doc,
inputs=[],
input_file=str(inputs_file) if inputs_file else None,
empty=[],
task=namespace if is_task else None)
logger = logging.getLogger("miniwdl-run")
logger.setLevel(CLI.NOTICE_LEVEL)
CLI.install_coloredlogs(logger)
# initialize Docker
client = docker.from_env()
try:
logger.debug("dockerd :: " + json.dumps(client.version())[1:-1])
_util.initialize_local_docker(logger, client)
finally:
client.close()
try:
if isinstance(target, Tree.Task):
entrypoint = runtime.run_local_task
else:
entrypoint = runtime.run_local_workflow
rundir, output_env = entrypoint(target,
input_env,
copy_input_files=kwargs.get(
"copy_input_files", False))
except Error.EvalError as err: # TODO: test errors
MiniwdlExecutor.log_source(logger, err)
raise
except Error.RuntimeError as err:
MiniwdlExecutor.log_source(logger, err)
if isinstance(err, runtime.error.RunFailed):
# This will be a workflow- or a task-level failure, depending on
# whether a workflow or task was executed. If it is workflow-level,
# we need to get the task-level error that caused the workflow to fail.
if isinstance(err.exe, Tree.Workflow):
err = err.__cause__
task_err = cast(runtime.error.RunFailed, err)
cause = task_err.__cause__
failed_task_exit_status = None
failed_task_stderr = None
if isinstance(cause, runtime.error.CommandFailed):
# If the task failed due to an error in the command, populate the
# command exit status and stderr.
cmd_err = cast(runtime.error.CommandFailed, cause)
failed_task_exit_status = cmd_err.exit_status
failed_task_stderr = MiniwdlExecutor.read_miniwdl_command_std(
cmd_err.stderr_file)
raise ExecutionFailedError(
"miniwdl",
namespace,
status="Failed",
inputs=task_err.exe.inputs,
failed_task=task_err.exe.name,
failed_task_exit_status=failed_task_exit_status,
failed_task_stderr=failed_task_stderr) from err
else:
raise
outputs = CLI.values_to_json(output_env, namespace=target.name)
if expected:
self._validate_outputs(outputs, expected, target.name)
return outputs
def run_workflow(self,
wdl_path: Path,
inputs: Optional[dict] = None,
expected: Optional[dict] = None,
**kwargs) -> dict:
"""
Run a WDL workflow on given inputs, and check that the output matches
given expected values.
Args:
wdl_path: The WDL script to execute.
inputs: Object that will be serialized to JSON and provided to Cromwell
as the workflow inputs.
expected: Dict mapping output parameter names to expected values.
kwargs: Additional keyword arguments, mostly for debugging:
* workflow_name: The name of the workflow in the WDL script. If None,
the name of the WDL script is used (without the .wdl extension).
* inputs_file: Path to the Cromwell inputs file to use. Inputs are
written to this file only if it doesn't exist.
* imports_file: Path to the WDL imports file to use. Imports are
written to this file only if it doesn't exist.
* java_args: Additional arguments to pass to Java runtime.
* cromwell_args: Additional arguments to pass to `cromwell run`.
Returns:
Dict of outputs.
Raises:
ExecutionFailedError: if there was an error executing Cromwell
AssertionError: if the actual outputs don't match the expected outputs
"""
target, is_task = get_target_name(wdl_path=wdl_path,
import_dirs=self._import_dirs,
**kwargs)
if is_task:
raise ValueError(
"Cromwell cannot execute tasks independently of a workflow")
inputs_dict, inputs_file = read_write_inputs(inputs_dict=inputs,
namespace=target)
imports_file = self._get_workflow_imports(kwargs.get("imports_file"))
inputs_arg = f"-i {inputs_file}" if inputs_file else ""
imports_zip_arg = f"-p {imports_file}" if imports_file else ""
java_args = kwargs.get("java_args", self.java_args) or ""
cromwell_args = kwargs.get("cromwell_args", self._cromwell_args) or ""
metadata_file = Path.cwd() / "metadata.json"
cmd = (
f"{self.java_bin} {java_args} -jar {self._cromwell_jar_file} run "
f"-m {metadata_file} {cromwell_args} {inputs_arg} {imports_zip_arg} "
f"{wdl_path}")
LOG.info(f"Executing cromwell command '{cmd}' with inputs "
f"{json.dumps(inputs_dict, default=str)}")
exe = subby.run(cmd, raise_on_error=False)
metadata = None
if metadata_file.exists():
with open(metadata_file, "rt") as inp:
metadata = json.load(inp)
if exe.ok:
if metadata:
assert metadata["status"] == "Succeeded"
outputs = metadata["outputs"]
else:
LOG.warning(
f"Cromwell command completed successfully but did not generate "
f"a metadata file at {metadata_file}")
outputs = self._get_cromwell_outputs(exe.output)
else:
error_kwargs = {
"executor": "cromwell",
"target": target,
"status": "Failed",
"inputs": inputs_dict,
"executor_stdout": exe.output,
"executor_stderr": exe.error,
}
if metadata:
failures = self._get_failures(metadata)
if failures:
error_kwargs.update({
"failed_task":
failures.failed_task,
"failed_task_exit_status":
failures.failed_task_exit_status,
"failed_task_stdout":
failures.failed_task_stdout,
"failed_task_stderr":
failures.failed_task_stderr
})
if failures.num_failed > 1:
error_kwargs["msg"] = \
f"cromwell failed on {failures.num_failed} instances of " \
f"{failures.failed_task} of {target}; only " \
f"showing output from the first failed task"
else:
error_kwargs[
"msg"] = f"cromwell failed on workflow {target}"
else:
error_kwargs["msg"] = \
f"Cromwell command failed but did not generate a metadata " \
f"file at {metadata_file}"
raise ExecutionFailedError(**error_kwargs)
if expected:
self._validate_outputs(outputs, expected, target)
return outputs
def run_workflow(
self,
wdl_path: Path,
inputs: Optional[dict] = None,
expected: Optional[dict] = None,
**kwargs,
) -> dict:
"""
Run a WDL workflow on given inputs, and check that the output matches
given expected values.
Args:
wdl_path: The WDL script to execute.
inputs: Object that will be serialized to JSON and provided to Cromwell
as the workflow inputs.
expected: Dict mapping output parameter names to expected values.
kwargs: Additional keyword arguments, mostly for debugging:
* workflow_name: The name of the workflow in the WDL script. If None,
the name of the WDL script is used (without the .wdl extension).
* inputs_file: Path to the Cromwell inputs file to use. Inputs are
written to this file only if it doesn't exist.
* imports_file: Path to the WDL imports file to use. Imports are
written to this file only if it doesn't exist.
* java_args: Additional arguments to pass to Java runtime.
* cromwell_args: Additional arguments to pass to `cromwell run`.
Returns:
Dict of outputs.
Raises:
ExecutionFailedError: if there was an error executing Cromwell
AssertionError: if the actual outputs don't match the expected outputs
"""
target, is_task = get_target_name(wdl_path=wdl_path,
import_dirs=self._import_dirs,
**kwargs)
if is_task:
raise ValueError(
"Cromwell cannot execute tasks independently of a workflow")
inputs_dict, _ = read_write_inputs(
inputs_file=kwargs.get("inputs_file"),
inputs_dict=inputs,
namespace=target,
write_formatted_inputs=False)
payload = {}
payload_files = []
def open_payload_file(path: Path, mode: str = "r") -> IO:
open_file = open(path, mode)
payload_files.append(open_file)
return open_file
try:
payload["workflowSource"] = open_payload_file(wdl_path)
if inputs_dict:
payload["workflowInputs"] = json.dumps(inputs_dict,
default=str)
imports_file = self._get_workflow_imports(
self._import_dirs, kwargs.get("imports_file"))
if imports_file:
payload["workflowDependencies"] = open_payload_file(
imports_file, "rb")
if self._cromwell_config_file:
if isinstance(inputs_dict, dict):
payload["workflowOptions"] = json.dumps(
self._cromwell_config_file, default=str)
else:
payload["workflowOptions"] = open_payload_file(
self._cromwell_config_file)
LOG.info(
f"Executing cromwell server '{self._cromwell_api_url}' with inputs "
f"{json.dumps(inputs_dict, default=str)}")
with requests.post(self._cromwell_api_url,
files=payload,
auth=self._auth) as resp:
status_object = self._resp_to_json(resp, target, inputs_dict)
run_id = status_object["id"]
LOG.info(
f"Executing on cromwell with id {run_id}. Waiting until terminal "
f"state is reached")
finally:
for fh in payload_files:
try:
fh.close()
except:
LOG.exception("Error closing file %s", fh)
self._poll_until_terminal(
run_id, target, inputs_dict,
kwargs.get("timeout", DEFAULT_POLLING_TIMEOUT))
metadata_url = f"{self._cromwell_api_url}/{run_id}/metadata"
outputs = None
with requests.get(metadata_url, auth=self._auth) as metadata_response:
metadata = self._resp_to_json(metadata_response, target,
inputs_dict)
if metadata["status"] == "Succeeded":
outputs = metadata["outputs"]
else:
error_kwargs = {
"executor": "cromwell",
"target": target,
"status": "Failed",
"inputs": inputs_dict,
}
self._parse_metadata_errors(metadata,
target=target,
error_kwargs=error_kwargs)
raise ExecutionFailedError(**error_kwargs)
if expected:
self._validate_outputs(outputs, expected, target)
return outputs