AWS Lambda + Python - No module named pkg_resources

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06-10-2024

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"No module named pkg_resources" in AWS Lambda with Python: A Comprehensive Guide

Have you encountered the dreaded "No module named pkg_resources" error when running your Python code on AWS Lambda? This frustrating message often arises when you try to use libraries like setuptools or pip that rely on pkg_resources for package management.

This article will unravel the mystery behind this error, explain its causes, and guide you through effective solutions to get your Lambda function running smoothly.

Scenario and Original Code:

Imagine you're building a Lambda function to process data using a popular Python library. Your code might look like this:

import boto3
import pandas as pd

def lambda_handler(event, context):
    # Load data from S3
    data = pd.read_csv('s3://my-bucket/data.csv')
    
    # Process the data
    # ...
    
    return {
        'statusCode': 200,
        'body': 'Data processed successfully.'
    }

You've deployed your function, but you're met with the dreaded error:

"errorMessage": "Unable to import module 'pandas': No module named 'pkg_resources'",

Why is this happening?

The issue stems from the way Python packages are handled in Lambda. Here's a breakdown:

• Lambda's Environment: Lambda environments are designed for lightweight and isolated execution. They often don't come pre-installed with every single Python package you might need.
• pkg_resources and Package Management: pkg_resources is a core component of Python's package management system. It's used by libraries like setuptools and pip to install, manage, and resolve package dependencies.
• Missing pkg_resources: When you encounter the "No module named pkg_resources" error, it implies that pkg_resources hasn't been correctly installed or is missing from your Lambda environment.

Solutions:

Here are the most effective ways to resolve the "No module named pkg_resources" error in AWS Lambda:

1. Install setuptools (Recommended):

   • This is the most reliable and recommended approach. setuptools is a fundamental Python package manager, and installing it will automatically include pkg_resources.
   • Within your Lambda function's code: Include pip install setuptools as part of your function's initialization.

   import boto3
   import os
   import subprocess
   
   def lambda_handler(event, context):
       # Install setuptools if it's not already installed
       if 'setuptools' not in os.environ['LD_LIBRARY_PATH']:
           subprocess.check_call([
               'pip',
               'install',
               'setuptools'
           ])
   
       import pandas as pd 
       # ... rest of your code
   

2. Install pkg_resources Directly:

   • If you're specifically targeting pkg_resources, you can directly install it:
   • Within your Lambda function's code: Include pip install pkg_resources as part of your function's initialization.

   import boto3
   import os
   import subprocess
   
   def lambda_handler(event, context):
       # Install pkg_resources if it's not already installed
       if 'pkg_resources' not in os.environ['LD_LIBRARY_PATH']:
           subprocess.check_call([
               'pip',
               'install',
               'pkg_resources'
           ])
   
       import pandas as pd
       # ... rest of your code
   

3. Lambda Layers:

   • This method is recommended for long-term maintainability and code organization. Lambda layers allow you to package frequently used dependencies, like setuptools, into reusable components that can be shared across multiple Lambda functions.
   • Create a Layer: Create a Lambda layer containing the required Python packages (setuptools or pkg_resources).
   • Attach to Function: Attach the layer to your Lambda function during deployment.
   • This ensures that the required dependencies are present in your Lambda environment without having to install them repeatedly in each function.

Additional Insights:

• Dependency Management: It's good practice to explicitly list all your Python dependencies in a requirements.txt file. This helps you manage and track your project's dependencies more effectively.
• Virtual Environments: Consider using virtual environments (like venv) for managing dependencies locally. This helps avoid conflicts between different projects and ensures your Lambda environment is consistent.

Conclusion:

By understanding the underlying causes of the "No module named pkg_resources" error and implementing the solutions provided, you can successfully run your Python code on AWS Lambda without encountering this common issue. Remember to prioritize using setuptools for overall package management within your Lambda functions.