from arvados.errors import ApiError
import arvados_cwl.util
-from .arvcontainer import RunnerContainer
+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
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.
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.")