diff options
Diffstat (limited to 'bh20seqanalyzer')
| -rw-r--r-- | bh20seqanalyzer/main.py | 131 |
1 files changed, 131 insertions, 0 deletions
diff --git a/bh20seqanalyzer/main.py b/bh20seqanalyzer/main.py new file mode 100644 index 0000000..78e32c9 --- /dev/null +++ b/bh20seqanalyzer/main.py @@ -0,0 +1,131 @@ +import argparse +import arvados +import arvados.collection +import time +import subprocess +import tempfile +import json +import logging +import ruamel.yaml +from bh20sequploader.qc_metadata import qc_metadata + +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): + 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.yaml" not in col: + logging.warn("Upload '%s' missing metadata.yaml", collection["name"]) + valid = False + else: + metadata_content = ruamel.yaml.round_trip_load(col.open("metadata.yaml")) + valid = qc_metadata(metadata_content) and valid + + 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) |