action-lambda-python-zip

GitHub Action to make zip deployment to AWS Lambda with pip requirements in a separate layer and additional custom layers.

Forked from:

Description

This action automatically installs requirements, zips and deploys the code including the dependencies as a separate layer.

Python 3.7 is supported

Pre-requisites

In order for the Action to have access to the code, you must use the actions/checkout@master job before it.

File Structure

This example workflow assumes your requirements.txt is in the root directory and that your functions are in folders with their function name as the directory name. Custom layers are assumed to be in a directory that matches their custom_layer_N_path value.

The below workflow would publish code to layers (pip and any custom layers) and functions (first_function and second_function), and finally also attach the layers to those updated functions.

For any custom layers, before the files are copied and zipped and uploaded to AWS, any custom script can be executed if it is placed inside the layer folder and named predeploy.sh

Environment variables

Storing credentials as a Github secret is strongly recommended.

• AWS Credentials AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY are required.

Inputs

• requirements_txt The name/path for the requirements.txt file. Defaults to requirements.txt.
• pip_layer_arn The ARN for the Lambda layer the dependencies should be pushed to without the version (version will be automatically updated on AWS).
• custom_layer_1_path Something like a folder of utils which holds all your utility code.
• custom_layer_1_arn The ARN for the Lambda layer where this utility code will go.
• custom_layer_2_path Same as above if you need more layers.
• custom_layer_2_arn Same as above if you need more layers.
• custom_layer_3_path Same as above if you need more layers.
• custom_layer_3_arn Same as above if you need more layers.
• custom_layer_4_path Same as above if you need more layers.
• custom_layer_4_arn Same as above if you need more layers.
• public_layer_1_arn The ARN of an external public Lambda layer in case you need one (e.g. https://github.com/keithrozario/Klayers).
• public_layer_2_arn Same as above if you need more layers.
• public_layer_3_arn Same as above if you need more layers.
• public_layer_4_arn Same as above if you need more layers.
• lambda_function_names The Lambda function names comma separated.
• aws_region

Example Workflow

on:
  push:
    branches:
      - master
jobs:
  build:
    runs-on: ubuntu-latest

    steps:
    - uses: actions/checkout@master
    - name: Deploy code to Lambda
      uses: seattleagainstslavery/[email protected]
      with:
        pip_layer_arn: 'YOUR_UNIQUE_ARN:layer:LAYER_NAME'
        custom_layer_1_path: 'utils'
        custom_layer_1_arn: 'YOUR_UNIQUE_ARN:layer:LAYER_NAME'
        lambda_function_names: 'first_function,second_function'
        aws_region: 'us-east-2'
      env:
        AWS_ACCESS_KEY_ID: ${{ secrets.AWS_ACCESS_KEY_ID }}
        AWS_SECRET_ACCESS_KEY: ${{ secrets.AWS_SECRET_ACCESS_KEY }}