from arvados.errors import ApiError
import arvados_cwl.util
-from .arvcontainer import RunnerContainer
-from .runner import Runner, upload_docker, upload_job_order, upload_workflow_deps
+from .arvcontainer import RunnerContainer, cleanup_name_for_collection
+from .runner import Runner, upload_docker, upload_job_order, upload_workflow_deps, make_builder
from .arvtool import ArvadosCommandTool, validate_cluster_target, ArvadosExpressionTool
from .arvworkflow import ArvadosWorkflow, upload_workflow
from .fsaccess import CollectionFsAccess, CollectionFetcher, collectionResolver, CollectionCache, pdh_size
with SourceLine(obj, i, UnsupportedRequirement, logger.isEnabledFor(logging.DEBUG)):
self.check_features(v, parentfield=parentfield)
- def make_output_collection(self, name, storage_classes, tagsString, outputObj):
+ def make_output_collection(self, name, storage_classes, tagsString, output_properties, outputObj):
outputObj = copy.deepcopy(outputObj)
files = []
res = str(json.dumps(outputObj, sort_keys=True, indent=4, separators=(',',': '), ensure_ascii=False))
f.write(res)
- final.save_new(name=name, owner_uuid=self.project_uuid, storage_classes=storage_classes, ensure_unique_name=True)
+
+ final.save_new(name=name, owner_uuid=self.project_uuid, storage_classes=storage_classes,
+ ensure_unique_name=True, properties=output_properties)
logger.info("Final output collection %s \"%s\" (%s)", final.portable_data_hash(),
final.api_response()["name"],
self.api.containers().update(uuid=current['uuid'],
body={
'output': self.final_output_collection.portable_data_hash(),
+ 'output_properties': self.final_output_collection.get_properties(),
}).execute(num_retries=self.num_retries)
self.api.collections().update(uuid=self.final_output_collection.manifest_locator(),
body={
self.project_uuid = runtimeContext.project_uuid
# Upload local file references in the job order.
- job_order = upload_job_order(self, "%s input" % runtimeContext.name,
- updated_tool, job_order, runtimeContext)
+ with Perf(metrics, "upload_job_order"):
+ job_order = upload_job_order(self, "%s input" % runtimeContext.name,
+ updated_tool, job_order, runtimeContext)
# the last clause means: if it is a command line tool, and we
# are going to wait for the result, and always_submit_runner
loadingContext = self.loadingContext.copy()
loadingContext.do_validate = False
+ loadingContext.disable_js_validation = True
if submitting:
loadingContext.do_update = False
# Document may have been auto-updated. Reload the original
# document with updating disabled because we want to
# submit the document with its original CWL version, not
# the auto-updated one.
- tool = load_tool(updated_tool.tool["id"], loadingContext)
+ with Perf(metrics, "load_tool original"):
+ tool = load_tool(updated_tool.tool["id"], loadingContext)
else:
tool = updated_tool
# Upload direct dependencies of workflow steps, get back mapping of files to keep references.
# Also uploads docker images.
- merged_map = upload_workflow_deps(self, tool, runtimeContext)
+ logger.info("Uploading workflow dependencies")
+ with Perf(metrics, "upload_workflow_deps"):
+ merged_map = upload_workflow_deps(self, tool, runtimeContext)
# Recreate process object (ArvadosWorkflow or
# ArvadosCommandTool) because tool document may have been
loadingContext.loader = tool.doc_loader
loadingContext.avsc_names = tool.doc_schema
loadingContext.metadata = tool.metadata
- tool = load_tool(tool.tool, loadingContext)
+ with Perf(metrics, "load_tool"):
+ tool = load_tool(tool.tool, loadingContext)
if runtimeContext.update_workflow or runtimeContext.create_workflow:
# Create a pipeline template or workflow record and exit.
runtimeContext.tmpdir_prefix = "tmp"
runtimeContext.work_api = self.work_api
+ if not self.output_name:
+ self.output_name = "Output from workflow %s" % runtimeContext.name
+
+ self.output_name = cleanup_name_for_collection(self.output_name)
+
if self.work_api == "containers":
if self.ignore_docker_for_reuse:
raise Exception("--ignore-docker-for-reuse not supported with containers API.")
if workbench2 or workbench1:
logger.info("Output at %scollections/%s", workbench2 or workbench1, tool.final_output)
else:
- if self.output_name is None:
- self.output_name = "Output of %s" % (shortname(tool.tool["id"]))
if self.output_tags is None:
self.output_tags = ""
else:
storage_classes = runtimeContext.storage_classes.strip().split(",")
- self.final_output, self.final_output_collection = self.make_output_collection(self.output_name, storage_classes, self.output_tags, self.final_output)
+ output_properties = {}
+ output_properties_req, _ = tool.get_requirement("http://arvados.org/cwl#OutputCollectionProperties")
+ if output_properties_req:
+ builder = make_builder(job_order, tool.hints, tool.requirements, runtimeContext, tool.metadata)
+ for pr in output_properties_req["outputProperties"]:
+ output_properties[pr["propertyName"]] = builder.do_eval(pr["propertyValue"])
+
+ self.final_output, self.final_output_collection = self.make_output_collection(self.output_name, storage_classes,
+ self.output_tags, output_properties,
+ self.final_output)
self.set_crunch_output()
if runtimeContext.compute_checksum: