AWS Lambda function with non-standard AWS Python libraries required on Mac (Big Sur)

  1. Install PyCharm, pip3, zsh
  • 2. Create a folder where would contain the zip file to upload AWS afterward. It’s recommended to be the same function name to be deployed to AWS function. Eg. lambda_function
    Add main python function file – which would be used to execute the code in AWS once uploaded – to the folder, this file will use the non-standard libraries to be installed. In my case: file, with following content:
  • 3. Create environment variable called venv3, using this command
    virtualenv venv3

  • 4. Activate environment venv3, using this command
  • source venv3/bin/activate

  • 5. Install the packages which are being used in the python function code, eg.:
  • pip3 install s3fs jmespath s3transfer six python-dateutil docutils simple-salesforce

    Important note: using pip3 instead of pip, otw the function won’t work and come up with this kind of error when running:

    Here is how the folder structure looks like after the packages installation:

  • 6. Prepare and zip the folder containing necessary files
  • Go to the right folder first:

    cd venv3/lib/python3.8/site-packages/

    Zip the files and folder, in my case:

    zip -r9 ${OLDPWD}/ dateutil docutils jmespath s3fs s3transfer fsspec

  • 7. Add the main function py file to the recently zipped file
  • Go back to root first

    cd $OLDPWD

    Add file to the zip

    zip -g

  • 8. Upload the final zip file to AWS function:
  • If the zip file is less than 10 MB, you can upload it directly using .zip option, otw upload it to s3 and use its URI. For large size file, you cannot see the Code inline to edit, but to change your code locally and upload it to test again.

    My case: zip file is greater than 30MB

    Take a look at your function handler name, which normally cause the compiling error like above


    If everything is fine, but time out for long running task, you may encounter such error message:

    What you need to do is increase the time out of the lambda function, max 15 mins. Default: 3 secs.

    Max time it recalls the function in case of time out is 3, and ends afterwards.

    Final design

    Sample code for copy function:

    import json
    import boto3
    import os
    import botocore
    s3 = boto3.resource('s3')
    # lambda function to copy file from 1 s3 to another s3
    def lambda_handler(event, context):
        #specify source bucket
        #get object that has been uploaded
        file_name = event['Records'][0]['s3']['object']['key']
        #specify the target folder for files copied
        #specify the source of listening files to make decision
        source_bucket_to_listen = 'dns-ticketek'
        bucket = s3.Bucket(source_bucket_to_listen)
        key = bucket.Object(file_name)
        #print('==File size==', key.content_length)
        #specify destination bucket
        #specify from where file needs to be copied
        copy_object = {'Bucket':source_bucket_name,'Key':file_name}
        #response_contents = s3_client.list_objects_v2(Bucket=source_bucket_name).get('Contents')
        #write copy statement
        ##This worked
        #for rc in response_contents:
            #'Size' returns in bytes
            #If file size larger than or equal to 500KB
            #filename = rc.get('Key')
            #print('==File name==' + filename + ' and size: ', rc.get('Size'))
            #if rc.get('Size') >= 500*1024:
        if key.content_length >= 500*1024:
            #print(f"Key: {rc.get('Key')}")
            #Copy to the big file name folder
            s3.Object(dest_bucket_bigfilename,dest_bucket_bffolder + '/' + os.path.basename(file_name)).copy_from(CopySource=copy_object)
        elif key.content_length < 500*1024:
            #Copy normal files to destination folder
            s3.Object(destination_bucket_name,destination_bucket_folder + '/' + os.path.basename(file_name)).copy_from(CopySource=copy_object)
        return {
            'statusCode': 3000,
            'body': json.dumps('File has been successfully copied')

    Sample code for file split lambda function:

    import os
    import boto3
    import s3fs
    import base64
    import json
    import sys
    import csv
    from botocore.exceptions import ClientError
    s3_client = boto3.client('s3')
    # S3 bucket info
    s3 = s3fs.S3FileSystem(anon=False)
    s3_res = boto3.resource('s3')
    # added
    # s3_res = boto3.resource('s3')
    ##Important! Need to configure the lambda function time out to 14mins
    def lambda_handler(event, context):
        output = []
        print("Received event: \n" + str(event))
        for record in event['Records']:
            # specify source bucket
            source_bucket_name = event['Records'][0]['s3']['bucket']['name']
            # get object that has been uploaded
            file2processname = event['Records'][0]['s3']['object']['key']
            print("==file2processname==: \n", file2processname)
            #print("==file2processnamecut==: \n" + file2processname[14:len(file2processname)])
            file2processnamecut = file2processname[14:len(file2processname)]
            #input_file = 'test-lambda012/dns-firehose-7-2021-05-11-03-21-46-71799d22-d2b6-4721-b4ff-2e138497af8b'
            #input_file_tmp = 'test-lambda012/tmp2readfull'
            #input_file = 'dnsbigfile/dnsbigfile/' + file2processname
            input_file = 'dnsbigfile/dnsbigfile/' + file2processnamecut
            print("Input file: \n" + input_file)
            #Create empty file named after recently landed file plus _tmp suffix
            ##s3_client.put_object(Bucket='dnsbigfile', Key='dnsbigfile/' + file2processname + '_tmp')
            #file2processtmp = file2processname + '_tmp'
            file2processtmp = file2processnamecut + '_tmp'
            print("file2processtmp==" + file2processtmp)
            #input_file_tmp = 'dnsbigfile/dnsbigfile/tmp2readfull'
            input_file_tmp = 'dnsbigfile/dnsbigfile/' + file2processtmp
            print("Input file tmp: \n" + input_file_tmp)
            response_contents = s3_client.list_objects_v2(Bucket=source_bucket_name).get('Contents')
            for rc in response_contents:
                # 'Size' returns in bytes
                # If file size larger than or equal to 500KB
                filename = rc.get('Key')
                if rc.get('Size') >= 500*1024:
                    # Read the file, write to temp file with \n added
                    f =,'r')
                    a =
                    #print("==File Content== \n" + a.replace("}{", "}\n{"))
                    g =, 'w')
                    g.write(a.replace("}{", "}\n{"))
                    # Split the temp file just added the \n between }{ into several files, each line per file
                    num = sum(1 for line in
                    print("==Total lines counted in file:==", num)
                    # This is to avoid max size limit
                    maxInt = sys.maxsize
                    while True:
                        # decrease the maxInt value by factor 10
                        # as long as the OverflowError occurs.
                        except OverflowError:
                            maxInt = int(maxInt / 10)
                    ## Split the ready file
                    sorting = True
                    num_of_lines_each = 1
                    hold_lines = []
                    with, 'r') as csvfile:
                        for row in csvfile:
                    outer_count = 1
                    line_count = 0
                    while sorting:
                        count = 0
                        increment = (outer_count - 1) * num_of_lines_each
                        left = len(hold_lines) - increment
                        #file_name = 'test-lambda012/tmp2read_full_' + str(outer_count * num_of_lines_each) + '.csv'
                        file_name = input_file_tmp + '_' + str(outer_count * num_of_lines_each) + '.csv'
                        hold_new_lines = []
                        if left < num_of_lines_each:
                            while count < left:
                                count += 1
                                line_count += 1
                            sorting = False
                            while count < num_of_lines_each:
                                count += 1
                                line_count += 1
                        outer_count += 1
                        with, 'w') as next_file:
                            for row in hold_new_lines:
            ## Move all split files to dns2import, move to dnsfilessplit first to test
            response_contents2 = s3_client.list_objects_v2(Bucket='dnsbigfile').get('Contents')
            # destination_bucket_name = 'dnsfilessplit'
            # destination_bucket_folder = 'dnsfilessplit'
            destination_bucket_name = 'dns2import'
            destination_bucket_folder = 'dns2import'
            strcontained = '_tmp_'
            for rc2 in response_contents2:
                filename = rc2.get('Key')
                filesize = rc2.get('Size')
                if filename.find(strcontained) != -1:
                    copy_object = {'Bucket': 'dnsbigfile', 'Key': filename}
                    print("==File to copy:==" + filename)
                    s3_client.copy_object(CopySource=copy_object, Bucket=destination_bucket_name, Key=filename)
                    s3_res.Object(destination_bucket_name, destination_bucket_folder + '/' + os.path.basename(filename)).copy_from(CopySource=copy_object)
                    s3_res.Object(destination_bucket_name, filename).delete()
                    #Delete the file after copying it to the target folder
                    s3_res.Object('dnsbigfile', filename).delete()
                    ## To do: delete the big file after done reading successfully
                elif filesize >= 500*1024:
                    s3_res.Object('dnsbigfile', filename).delete()

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