#!/usr/bin/env python
+# Crunch script integration for running arvados-cwl-runner (importing
+# arvados_cwl module) inside a crunch job.
+#
+# This gets the job record, transforms the script parameters into a valid CWL
+# input object, then executes the CWL runner to run the underlying workflow or
+# tool. When the workflow completes, record the output object in an output
+# collection for this runner job.
+
import arvados
import arvados_cwl
import arvados.collection
from arvados.api import OrderedJsonModel
from cwltool.process import adjustFiles
+# Print package versions
+logging.info(cwltool.main.versionstring())
+
api = arvados.api("v1")
try:
job_order_object = arvados.current_job()['script_parameters']
- print job_order_object
-
def keeppath(v):
if arvados.util.keep_locator_pattern.match(v):
return "file://%s/%s" % (os.environ['TASK_KEEPMOUNT'], v)
t = cwltool.main.load_tool(job_order_object, False, True, runner.arvMakeTool, True)
- np = argparse.Namespace()
- np.project_uuid = arvados.current_job()["owner_uuid"]
- np.enable_reuse = True
- np.submit = False
- np.debug = True
- outputObj = runner.arvExecutor(t, job_order_object, "", np, cwl_runner_job={"uuid": arvados.current_job()["uuid"], "state": arvados.current_job()["state"]})
+ args = argparse.Namespace()
+ args.project_uuid = arvados.current_job()["owner_uuid"]
+ args.enable_reuse = True
+ args.submit = False
+ args.debug = True
+ args.quiet = False
+ args.ignore_docker_for_reuse = False
+ outputObj = runner.arvExecutor(t, job_order_object, "", args, cwl_runner_job={"uuid": arvados.current_job()["uuid"], "state": arvados.current_job()["state"]})
files = {}
def capture(path):