Here is what i want to do :
Local environment
Serverless framework version 1.22.0
Python 2.7
Here is my serverless.yml file
service: aws-python # NOTE: update this with your service name
provider:
name: aws
runtime: python2.7
stage: dev
region: us-east-1
iamRoleStatements:
- Effect: "Allow"
Action:
- s3:*
- "ses:SendEmail"
- "ses:SendRawEmail"
- "s3:PutBucketNotification"
Resource: "*"
functions:
csvfile:
handler: handler.csvfile
description: send mail whenever a csv file is uploaded on S3
events:
- s3:
bucket: mine2
event: s3:ObjectCreated:*
rules:
- suffix: .csv
and here is my lambda function :
import json
import boto3
import botocore
import logging
import sys
import traceback
import csv
from botocore.exceptions import ClientError
from pprint import pprint
from time import strftime, gmtime
from json import dumps, loads, JSONEncoder, JSONDecoder
#setup simple logging for INFO
logger = logging.getLogger()
logger.setLevel(logging.INFO)
from botocore.exceptions import ClientError
def csvfile(event, context):
"""Send email whenever a csvfile is uploaded to S3 """
body = {}
emailcontent = ''
status_code = 200
#set email information
email_from = '****@*****.com'
email_to = '****@****.com'
email_subject = 'new file is uploaded'
try:
s3 = boto3.resource(u's3')
s3 = boto3.client('s3')
for record in event['Records']:
filename = record['s3']['object']['key']
filesize = record['s3']['object']['size']
source = record['requestParameters']['sourceIPAddress']
eventTime = record['eventTime']
# get a handle on the bucket that holds your file
bucket = s3.Bucket(u'mine2')
# get a handle on the object you want (i.e. your file)
obj = bucket.Object(key= event[u'Records'][0][u's3'][u'object'][u'key'])
# get the object
response = obj.get()
# read the contents of the file and split it into a list of lines
lines = response[u'Body'].read().split()
# now iterate over those lines
for row in csv.DictReader(lines):
print(row)
emailcontent = emailcontent + '\n' + row
except Exception as e:
print(traceback.format_exc())
status_code = 500
body["message"] = json.dumps(e)
email_body = "File Name: " + filename + "\n" + "File Size: " + str(filesize) + "\n" + "Upload Time: " + eventTime + "\n" + "User Details: " + source + "\n" + "content of the csv file :" + emailcontent
ses = boto3.client('ses')
ses.send_email(Source = email_from,
Destination = {'ToAddresses': [email_to,],},
Message = {'Subject': {'Data': email_subject}, 'Body':{'Text' : {'Data': email_body}}}
)
print('Function execution Completed')
i don't know what i did wrong, cause the part when i just get info about the file works fine, it's when i add the reading part that the lambda function doesn't return anything
Reading objects without downloading them Similarly, if you want to upload and read small pieces of textual data such as quotes, tweets, or news articles, you can do that using the S3 resource method put(), as demonstrated in the example below (Gist).
Go to the S3 console, click your bucket, go to the Properties tab, click Events. A list of triggers on the bucket will be displayed.
In this tutorial, the S3 trigger invokes a function to create a thumbnail image for each image file that is uploaded to your S3 bucket. This tutorial requires a moderate level of AWS and Lambda domain knowledge. You use the AWS Command Line Interface (AWS CLI) to create resources, and you create a .
I suggest to add to your IAM policy also the access to Cloudwatch.
Actually your lambda function is not returning anything, but you can see your log output in Cloudwatch. I really recommend to use logger.info(message)
instead of print
when you are setting up logger
.
I hope that this helps to debug your function.
Except the part of sending, this is how I will rewrite it (just tested in the AWS console):
import logging
import boto3
logger = logging.getLogger()
logger.setLevel(logging.INFO)
s3 = boto3.client('s3')
def lambda_handler(event, context):
email_content = ''
# retrieve bucket name and file_key from the S3 event
bucket_name = event['Records'][0]['s3']['bucket']['name']
file_key = event['Records'][0]['s3']['object']['key']
logger.info('Reading {} from {}'.format(file_key, bucket_name))
# get the object
obj = s3.get_object(Bucket=bucket_name, Key=file_key)
# get lines inside the csv
lines = obj['Body'].read().split(b'\n')
for r in lines:
logger.info(r.decode())
email_content = email_content + '\n' + r.decode()
logger.info(email_content)
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