How do add python libraries to AWS Lambda?

Question

I just made my first function that fetches data from an excel sheet in Google Sheets. I got an error:

"errorMessage": "Unable to import module 'lambda_function': No module named 'googleapiclient'"

so i googled how to upload python modules (https://www.youtube.com/watch?v=HBt8MXHcaPI) and it said to create a virtual env in something like VSCode, pip install the libraries that i'll need, then zip them and add them as a layer to Lambda.

I did that, twice. (It just looked like a whole bunch of libraries were being installed, so i looked up how to remove all of them (pip freeze | xargs pip uninstall -y) and tried again). So here's the starting point and after doing pip install google-api-python-client

I guess i'm a little confused whether i should be zipping up literally all of that, or just the stuff that has google in the name. I tried it both ways and neither seemed to work. I'm still getting that error.

Answer 1

To use any 3rd party library in lambda you can use a lambda layer.

install the dependency using following command

pip3 install <your_package> -t .

zip the package

zip -r your_pkg_layer.zip .

create the layer in aws and upload the zip, after that add the layer to your lambda function

you can follow this blog in medium.

Answer 2

I recommend that you look at AWS SAM

AWS SAM is an extension of CloudFormation that simplifies the development of serverless applications.

To deploy a AWS Lambda function using AWS Serverless Application Model (SAM), you need to follow these steps:

• Create a SAM template: This is a YAML file that defines the AWS resources you want to deploy, including the Lambda function and its dependencies.

• Package the function: Package the function code and any dependencies into a .zip file. (For this you'll need a requirements.txt file with all the dependencies your code needs)

• Deploy the function: Use the AWS CLI command deploy to deploy the SAM template and function code to AWS. The command will create or update a CloudFormation stack, which creates or updates the specified AWS resources.

Example SAM template:

AWSTemplateFormatVersion: '2010-09-09'
Transform: AWS::Serverless-2016-10-31
Resources:
  MyFunction:
    Type: AWS::Serverless::Function
    Properties:
      Handler: main.handler
      Runtime: python3.8
      CodeUri: .
      Description: "This is my SAM function"
      MemorySize: 128
      Timeout: 3

Example AWS CLI command:

sam build --debug --template-file template.yaml
sam package --s3-bucket your_s3_bucket --s3-prefix sam-deployments \
                  --output-template-file packaged-template.yaml
sam deploy -t packaged-template.yaml --stack-name your_stack_name \
          --region your_aws_region --capabilities CAPABILITY_IAM 

A common folder structure for a Lambda project using AWS Serverless Application Model (SAM) would look something like this:

my-lambda-project/
├── main.py # Lambda function code
├── template.yaml # SAM template
├── requirements.txt # Python dependencies