import argparse import arvados import arvados.collection import time import subprocess import tempfile import json import logging logging.basicConfig(format="[%(asctime)s] %(levelname)s %(message)s", datefmt="%Y-%m-%d %H:%M:%S", level=logging.INFO) logging.getLogger("googleapiclient.discovery").setLevel(logging.WARN) def validate_upload(api, collection, validated_project, latest_result_uuid): col = arvados.collection.Collection(collection["uuid"]) # validate the collection here. Check metadata, etc. valid = True if "sequence.fasta" not in col: valid = False logging.warn("Upload '%s' missing sequence.fasta", collection["name"]) if "metadata.jsonld" not in col: logging.warn("Upload '%s' missing metadata.jsonld", collection["name"]) valid = False dup = api.collections().list(filters=[["owner_uuid", "=", validated_project], ["portable_data_hash", "=", col.portable_data_hash()]]).execute() if dup["items"]: # This exact collection has been uploaded before. valid = False logging.warn("Upload '%s' is duplicate" % collection["name"]) if valid: logging.info("Added '%s' to validated sequences" % collection["name"]) # Move it to the "validated" project to be included in the next analysis api.collections().update(uuid=collection["uuid"], body={"owner_uuid": validated_project}).execute() else: # It is invalid, delete it. logging.warn("Deleting '%s'" % collection["name"]) api.collections().delete(uuid=collection["uuid"]).execute() return valid def start_analysis(api, analysis_project, workflow_uuid, validated_project): project = api.groups().create(body={ "group_class": "project", "name": "Pangenome analysis", "owner_uuid": analysis_project, }, ensure_unique_name=True).execute() validated = arvados.util.list_all(api.collections().list, filters=[["owner_uuid", "=", validated_project]]) with tempfile.NamedTemporaryFile() as tmp: inputobj = { "inputReads": [] } for v in validated: inputobj["inputReads"].append({ "class": "File", "location": "keep:%s/sequence.fasta" % v["portable_data_hash"] }) tmp.write(json.dumps(inputobj, indent=2).encode('utf-8')) tmp.flush() cmd = ["arvados-cwl-runner", "--submit", "--no-wait", "--debug", "--project-uuid=%s" % project["uuid"], "arvwf:%s" % workflow_uuid, tmp.name] logging.info("Running %s" % ' '.join(cmd)) comp = subprocess.run(cmd, capture_output=True) if comp.returncode != 0: logging.error(comp.stderr.decode('utf-8')) def copy_most_recent_result(api, analysis_project, latest_result_uuid): most_recent_analysis = api.groups().list(filters=[['owner_uuid', '=', analysis_project]], order="created_at desc", limit=1).execute() for m in most_recent_analysis["items"]: cr = api.container_requests().list(filters=[['owner_uuid', '=', m["uuid"]], ["requesting_container_uuid", "=", None]]).execute() if cr["items"] and cr["items"][0]["output_uuid"]: wf = cr["items"][0] src = api.collections().get(uuid=wf["output_uuid"]).execute() dst = api.collections().get(uuid=latest_result_uuid).execute() if src["portable_data_hash"] != dst["portable_data_hash"]: logging.info("Copying latest result from '%s' to %s", m["name"], latest_result_uuid) api.collections().update(uuid=latest_result_uuid, body={"manifest_text": src["manifest_text"], "description": "latest result from %s %s" % (m["name"], wf["uuid"])}).execute() break def main(): parser = argparse.ArgumentParser(description='Analyze collections uploaded to a project') parser.add_argument('--uploader-project', type=str, default='lugli-j7d0g-n5clictpuvwk8aa', help='') parser.add_argument('--analysis-project', type=str, default='lugli-j7d0g-y4k4uswcqi3ku56', help='') parser.add_argument('--validated-project', type=str, default='lugli-j7d0g-5ct8p1i1wrgyjvp', help='') parser.add_argument('--workflow-uuid', type=str, default='lugli-7fd4e-mqfu9y3ofnpnho1', help='') parser.add_argument('--latest-result-uuid', type=str, default='lugli-4zz18-z513nlpqm03hpca', help='') args = parser.parse_args() api = arvados.api() logging.info("Starting up, monitoring %s for uploads" % (args.uploader_project)) while True: new_collections = api.collections().list(filters=[['owner_uuid', '=', args.uploader_project]]).execute() at_least_one_new_valid_seq = False for c in new_collections["items"]: at_least_one_new_valid_seq = validate_upload(api, c, args.validated_project) or at_least_one_new_valid_seq if at_least_one_new_valid_seq: start_analysis(api, args.analysis_project, args.workflow_uuid, args.validated_project) copy_most_recent_result(api, args.analysis_project, args.latest_result_uuid) time.sleep(10)