Creating an AWS Lambda Layer for Python Libraries

AWS Lambda Layers offer a powerful solution for organizing, sharing, and managing code dependencies across multiple Lambda functions. In this guide, we’ll walk you through the process of creating an AWS Lambda Layer specifically for Python libraries. Additionally, we’ll discuss the required IAM policies and roles to ensure your Lambda functions can seamlessly access and use the layer.

Prerequisites

Before we delve into the solution, make sure you have the following prerequisites in place:

• An active AWS account.
• The AWS Command Line Interface (CLI) installed and properly configured.
• Python 3.8 or your desired Python version set up on your local development environment.

The Common Issue: ImportError

Imagine you’re working on an AWS Lambda function, and you encounter an error like this:

Unable to import module 'lambda_function': No module named 'python-decouple'

This error typically indicates that your Lambda function is unable to import the ‘python-decouple’ module due to missing dependencies. To overcome this issue, you can create an AWS Lambda Layer that includes the necessary Python library and its dependencies.

Packaging the Python Library

In this example, we’ll package the ‘python-decouple’ library as an AWS Lambda Layer. You can replace it with any other Python library of your choice. Here’s a step-by-step guide on how to do it:

1. Create a Directory and Install the Library

Start by creating a directory where you’ll prepare your Lambda Layer package:

mkdir python

Next, use pip to install the desired library into this directory:

python3.8 -m pip install python-decouple -t python/

This command will install the library into the ‘python’ directory.

2. Create a Zip Archive

After successfully installing the library, create a zip archive that contains the contents of the ‘python’ directory:

zip -r layer.zip python

This will result in a ‘layer.zip’ file containing the library and its dependencies.

Uploading the Layer to AWS Lambda

Now that you’ve packaged your Python library, it’s time to upload it to AWS Lambda as a Layer:

1. Log in to the AWS Console: Access the AWS Management Console and log in to your AWS account.

2. Open the AWS Lambda Service: Within the AWS Console, navigate to the AWS Lambda service.

3. Create a Layer: In the Lambda service dashboard, click on “Layers” in the left navigation pane.

• Click the “Create a layer” button.

4. Configure the Layer

• Provide a name for your layer.

• Upload the ‘layer.zip’ file you created earlier as the layer package.

• Specify a compatible runtime (e.g., Python 3.8).

5. Create the Layer: Click the “Create” button to create your AWS Lambda Layer.

IAM Policy and Role Requirements:To ensure that your Lambda functions can access the newly created layer, you’ll need to create an IAM policy like the one below:

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Sid": "LambdaGetLayerVersion",
            "Effect": "Allow",
            "Action": "lambda:GetLayerVersion",
            "Resource": "arn:aws:lambda:*:1234567890:layer:*:*"
        }
    ]
}

This policy allows Lambda functions to retrieve the necessary layer versions. Assign this policy to the IAM role associated with your Lambda functions to enable them to utilize the Lambda Layer effectively.

With these steps, you’ve not only addressed the ‘No module named’ error by packaging your Python library but also ensured that your Lambda functions have the necessary IAM policies and roles to access the layer seamlessly. Remember to replace ‘python-decouple’ with your specific library, and customize the Python version and other settings to match your project requirements. AWS Lambda Layers simplify code sharing and enhance your development workflow.

Visit AWS documentation for more details: https://docs.aws.amazon.com/lambda/latest/dg/chapter-layers.html

Tags: AWS Lambda, Lambda Layers, Python Libraries