aws lambda layer python dependencies

Published: 13 December 2023
on channel: pyGPT

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AWS Lambda Layers allow you to package and reuse code across multiple Lambda functions. This tutorial will guide you through creating a Lambda Layer with Python dependencies and then using that layer in a Lambda function.
AWS Account: Ensure you have an AWS account with the necessary permissions to create Lambda functions and layers.
AWS CLI: Install the AWS Command Line Interface (CLI) on your local machine. You can download it from here.
Python and pip: Make sure you have Python installed on your machine. This tutorial assumes you have Python 3.x installed.
Create a file named requirements.txt and list the Python packages you want to include in the Lambda Layer. For example:
This command installs the dependencies in the python directory.
Note the LayerVersionArn in the output; you'll need it for the Lambda function.
Create a file named lambda_function.py with the following content:
Replace YOUR-ROLE-ARN and YOUR-LAYER-ARN with the appropriate values. If you don't have a role, create one with the necessary Lambda and Layer permissions.
Invoke the Lambda function and check the response:
You should see the response from the Lambda function.
Congratulations! You've successfully created a Lambda Layer with Python dependencies and used it in a Lambda function. This approach allows you to share and manage common dependencies across multiple Lambda functions efficiently.
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