# AWS Chalice — Serverless Python Microframework for AWS Lambda

> Chalice is a Python microframework by AWS for building serverless applications on AWS Lambda and API Gateway. It provides a Flask-like API for defining routes and event handlers that deploy automatically to AWS with a single command.

## Install

Save in your project root:

# AWS Chalice — Serverless Python Microframework for AWS Lambda

## Quick Use
```bash
pip install chalice
chalice new-project my-api
cd my-api
# Edit app.py with your routes
chalice deploy
```

## Introduction
AWS Chalice is a framework for writing serverless Python applications that run on AWS Lambda. It provides a decorator-based API similar to Flask for defining REST endpoints, scheduled tasks, and event handlers. Chalice handles the packaging, IAM policy generation, and deployment to AWS automatically.

## What Chalice Does
- Defines REST API routes with Python decorators that map to API Gateway endpoints
- Automatically generates IAM policies based on the AWS services your code accesses
- Packages and deploys Lambda functions with a single `chalice deploy` command
- Supports event sources including S3, SQS, SNS, CloudWatch Events, and WebSockets
- Provides local testing with `chalice local` for rapid development without deploying

## Architecture Overview
Chalice analyzes your Python code to determine which AWS services you use and automatically generates the minimum IAM policy required. During deployment, it creates a Lambda function with your application code, sets up API Gateway routes, and configures event source mappings. The runtime routes incoming requests to the correct handler based on the URL path and HTTP method. Chalice uses AWS SAM or Terraform under the hood for infrastructure management.

## Self-Hosting & Configuration
- Requires Python 3.8+ and AWS credentials configured via `aws configure` or environment variables
- Project configuration lives in `.chalice/config.json` for stage-specific settings
- Set environment variables, memory size, timeout, and Lambda layers per deployment stage
- Use `chalice package` to export a SAM or Terraform template for CI/CD pipelines
- Manage dependencies in `requirements.txt`; Chalice bundles them into the deployment package

## Key Features
- Flask-like decorator syntax makes serverless development feel familiar to Python web developers
- Automatic IAM policy generation eliminates manual permission configuration
- Local development server for testing routes without deploying to AWS
- Built-in support for WebSocket APIs, scheduled events, and pure Lambda functions
- Terraform and SAM export for integration with existing infrastructure-as-code workflows

## Comparison with Similar Tools
- **Serverless Framework** — language-agnostic with YAML configuration; more flexible but more verbose for Python
- **AWS SAM** — lower-level; gives more control over CloudFormation resources but requires more boilerplate
- **Zappa** — deploys Django/Flask apps to Lambda; wraps existing WSGI apps rather than providing a native serverless API
- **FastAPI + Mangum** — run FastAPI on Lambda via an adapter; good for existing FastAPI apps but not serverless-first
- **SST** — TypeScript-first with broader AWS construct support; better for teams already using TypeScript

## FAQ
**Q: Can I use Chalice with an existing Flask or Django app?**
A: Chalice is its own framework, not a wrapper. For existing apps, consider Zappa or Mangum instead.

**Q: How does automatic IAM policy generation work?**
A: Chalice uses static analysis to detect boto3 calls in your code and generates a policy with only the permissions those calls require.

**Q: Does Chalice support container-based Lambda functions?**
A: Chalice primarily targets zip-based Lambda deployments. For container images, use SAM or CDK directly.

**Q: Can I deploy to multiple AWS accounts or regions?**
A: Yes. Use stage-specific configuration in `.chalice/config.json` to target different accounts and regions per stage.

## Sources
- https://github.com/aws/chalice
- https://aws.github.io/chalice/


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Author: AI Open Source