import boto3 import warnings import os from joblib import load warnings.filterwarnings('ignore') def lambda_handler(event, context): payload = event values_for_model = payload["5008807"].values() values_for_model = list(values_for_model) AWS_S3_BUCKET = "engel-tests-20851" #ACCESS_KEY_ID = os.getenv("AWS_ACCESS_KEY_ID") #SECRET_ACCESS_KEY = os.getenv("AWS_SECRET_ACCESS_KEY") s3_client = boto3.client( "s3" #aws_access_key_id=ACCESS_KEY_ID, #aws_secret_access_key=SECRET_ACCESS_KEY, ) filename = "model_risk.joblib" s3_client.download_file(AWS_S3_BUCKET, filename, '/tmp/' + filename) my_model = load('/tmp/model_risk.joblib') prediction_result = my_model.predict([values_for_model]) list_result = prediction_result.tolist() list_final = list_result[0] output = { "risk_prediction": list_final } return output event_local_example = { "5008807" : { "1" : 32, "2" : 12, "3" : 2, "4" : 119, "5" : 45 } } result = lambda_handler(event_local_example, context=None) print(result)