Streamlining Python Application Deployment on AWS Lambda with the Serverless Framework: A Step-by-Step Guide

AWS Lambda, a serverless compute service, has revolutionized how developers build and deploy applications. The Serverless Framework makes managing deployments, configurations, and integrations with AWS services more accessible. This step-by-step guide will help you deploy Python applications on AWS Lambda using the Serverless Framework.

1. Installing the Serverless Framework and Setting Up AWS Credentials

Before starting, ensure you have Node.js and NPM installed on your system. Then, install the Serverless Framework globally:

npm install -g serverless

Next, set up your AWS credentials to allow the Serverless Framework to interact with AWS services. Use the following command to configure credentials:

aws configure

Provide your Access Key ID, Secret Access Key, and default region (e.g., us-east-1).

2. Creating a Serverless Project with Python 3 Template

To create a new Serverless project using the Python 3 template, run the following:

serverless create –template aws-python3 –path my-python-app

cd my-python-app

This command initializes a new project with a serverless.yml configuration file, a handler.py file for your Lambda function, and other necessary files.

3. Setting Up a Virtual Environment for Local Development

Virtual environments help isolate project dependencies. Set up a virtual environment in your project directory:

python3 -m venv venv

source venv/bin/activate # On Windows, use venv\Scripts\activate

Once activated, all installed Python packages will be scoped for this environment.

4. Packaging Python Dependencies for AWS Lambda Deployment

AWS Lambda requires all dependencies to be packaged along with your function. Install your project’s dependencies inside the virtual environment:

pip install -r requirements.txt

To include the dependencies in the deployment package, use the following command:

pip install -r requirements.txt –target .

This ensures all packages are available in the root directory of your project.

5. Customizing the Serverless Configuration for Python Requirements

The serverless.yml file is the heart of the Serverless Framework. Modify it to match your project’s requirements:

service: my-python-app

provider:

name: aws

runtime: python3.9

region: us-east-1

functions:

hello:

handler: handler.hello

events:

– http:

path: hello

method: get

plugins:

– serverless-python-requirements

custom:

pythonRequirements:

dockerizePip: true

This configuration specifies the Python runtime, a sample HTTP event trigger, and the serverless-python-requirements plugin for handling Python dependencies.

Install the required plugin:

npm install serverless-python-requirements

6. Deploying the Lambda Function and Integrating with AWS Services

Deploy your function to AWS using the following command:

serverless deploy

The framework will package your application, upload it to AWS, and configure necessary resources. Once deployed, you’ll see the function’s endpoint and AWS resource information.

To invoke the function locally, use:

serverless invoke local –function hello

To test the deployed function in AWS:

serverless invoke –function hello

If your function interacts with other AWS services, configure them in the serverless.yml file under the resources section. For example, you can define S3 buckets, DynamoDB tables, or API Gateway integrations.

Conclusion

Deploying Python applications on AWS Lambda with the Serverless Framework simplifies serverless application development. Following this guide, you’ve learned how to install the Serverless Framework, set up AWS credentials, configure your project, package dependencies, and deploy a Python Lambda function.

Leverage this approach to build scalable and efficient serverless applications while focusing on your core logic rather than infrastructure management.