By Konstantinos Patronas —

Installing psycopg2 on AWS Lambda When Developing on ARM Macs

Developers working on M1/M2 Macs (ARM architecture) face a common challenge when deploying Python applications to AWS Lambda: the need to…

Installing psycopg2 on AWS Lambda When Developing on ARM Macs
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Developers working on M1/M2 Macs (ARM architecture) face a common challenge when deploying Python applications to AWS Lambda: the need to package libraries compiled for x86_64 architecture. This is particularly tricky with packages like psycopg2 that contain binary components. The traditional approach involves using Docker with x86_64 emulation, which can be time-consuming and error-prone.

A Simpler Solution

There’s a more straightforward approach using pip’s platform-specific installation capabilities. This method allows you to download and package the correct binary versions directly from your ARM Mac, without needing Docker.

Step-by-Step Guide

  1. Create a Project Directory

First, create a directory for your Lambda function:

mkdir my_lambda_project 
cd my_lambda_project

2. Install psycopg2
Use pip with specific flags to install the x86_64 version of psycopg2-binary:

pip install --platform manylinux2014_x86_64 --target ./package \ 
    --implementation cp --python-version 3.9 \ 
    --only-binary=:all: psycopg2-binary

Let’s break down these flags:

  • --platform manylinux2014_x86_64: Ensures compatibility with AWS Lambda’s x86_64 environment
  • --target ./package: Installs packages to a local directory
  • --implementation cp: Specifies CPython
  • --python-version 3.9: Matches Lambda’s Python runtime version
  • --only-binary=:all: Forces pip to use pre-built wheels
  • psycopg2-binary: The binary distribution of psycopg2

3. Create Your Lambda Function
Create your Lambda function code (e.g., lambda_function.py):

import psycopg2 
 
def lambda_handler(event, context): 
    # Your database connection code here 
    conn = psycopg2.connect( 
        host="your-database-host", 
        database="your-database", 
        user="your-username", 
        password="your-password" 
    ) 
    # Rest of your code...

4. Package Everything Together
Create a deployment package containing both your function and its dependencies:

cd package 
zip -r ../lambda_function.zip . 
cd .. 
zip lambda_function.zip lambda_function.py

Common Issues and Solutions

  1. Version Mismatch: If you encounter version compatibility issues, try specifying the exact version:
pip install --platform manylinux2014_x86_64 --target ./package \ 
    --implementation cp --python-version 3.9 \ 
    --only-binary=:all: psycopg2-binary==2.9.9

2. Dependency Conflicts: If you get dependency-related errors, you can add the — no-deps flag:

pip install --platform manylinux2014_x86_64 --target ./package \ 
    --implementation cp --python-version 3.9 \ 
    --only-binary=:all: --no-deps psycopg2-binary

3. Size Considerations: The resulting package will be relatively large due to included binaries. If you’re deploying frequently, consider using Lambda layers instead for rarely-changed dependencies.

Advantages Over Docker Method

This approach offers several benefits:

  • No need to set up and maintain Docker
  • Faster deployment preparation
  • Simpler workflow
  • Less room for error in the packaging process
  • Works directly from your ARM Mac

Conclusion

While working with binary dependencies on AWS Lambda from an ARM Mac traditionally required complex Docker setups, pip’s platform-specific installation capabilities offer a much simpler solution. This method ensures you get the correct architecture for your Lambda function while maintaining a straightforward development workflow on your ARM Mac.

Remember to always test your deployment package in a development Lambda environment before moving to production, as environment-specific issues can sometimes arise despite using the correct architecture binaries.

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