"""The AWS Lambda emmaa-queries definition.
This file contains the function that will be run when Lambda is triggered. It
must be placed on s3, which can either be done manually (not recommended) or
by running:
$ python update_lambda.py model_queries.py emmaa-queries
in this directory.
"""
import boto3
from datetime import datetime
JOB_DEF = 'emmaa_jobdef'
QUEUE = 'emmaa-models-update-test'
PROJECT = 'aske'
PURPOSE = 'update-emmaa-queries'
BRANCH = 'origin/master'
[docs]def lambda_handler(event, context):
"""Create a batch job to run queries for model.
This function is designed to be placed on lambda, taking the event and
context arguments that are passed. Event parameter is used here to pass
name of the model.
This Lambda function is configured to be invoked by emmaa-after-update
Lambda function.
Parameters
----------
event : dict
A dictionary containing metadata regarding the triggering event. In
this case the dictionary contains 'model' key.
context : object
This is an object containing potentially useful context provided by
Lambda. See the documentation cited above for details.
Returns
-------
ret : dict
A dict containing 'statusCode', with a valid HTTP status code, and any
other data to be returned to Lambda.
"""
batch = boto3.client('batch')
model_name = event['model']
core_command = 'bash scripts/git_and_run.sh'
if BRANCH is not None:
core_command += f' --branch {BRANCH}'
core_command += (' python scripts/answer_queries_from_s3.py'
f' --model {model_name}')
print(core_command)
cont_overrides = {
'command': ['python', '-m', 'indra.util.aws', 'run_in_batch',
'--project', PROJECT, '--purpose', PURPOSE,
core_command]
}
now_str = datetime.utcnow().strftime('%Y%m%d_%H%M%S')
ret = batch.submit_job(jobName=f'{model_name}_queries_{now_str}',
jobQueue=QUEUE, jobDefinition=JOB_DEF,
containerOverrides=cont_overrides)
job_id = ret['jobId']
return {'statusCode': 200, 'result': 'SUCCESS', 'job_id': job_id}