lambda_function.py

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)