fastapi-cap 0.2.0

A robust, extensible, and production-ready rate limiting library for FastAPI, supporting multiple algorithms and Redis backend.

🚦 FastAPI-Cap

FastAPI-Cap is a robust, extensible, and high-performance rate limiting library for FastAPI applications.
It leverages Redis and optimized Lua scripts to provide a suite of industry-standard algorithms for controlling API traffic, preventing abuse, and ensuring reliable service delivery.

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✨ Features

• Multiple Algorithms: Fixed Window, Sliding Window (approximated & log-based), Token Bucket, Leaky Bucket, and GCRA.
• High Performance: Atomic operations via Redis Lua scripts.
• Distributed: Consistent limits across multiple API instances.
• Easy Integration: Use as FastAPI dependencies or decorators.
• Customizable: Plug in your own key extraction and limit handling logic.
• Battle-tested: Designed for real-world, production-grade FastAPI services.

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📦 Installation

pip install fastapi-cap

You also need a running Redis instance.
For local development, you can use Docker:

docker run -p 6379:6379 redis

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🚀 Quick Start

1. Initialize Redis Connection

from fastapi import FastAPI
from fastapicap import Cap

app = FastAPI()
Cap.init_app("redis://localhost:6379/0")

2. Apply a Rate Limiter to a Route

from fastapicap import RateLimiter
from fastapi import Depends

limiter = RateLimiter(limit=5, minutes=1)

@app.get("/limited", dependencies=[Depends(limiter)])
async def limited_endpoint():
    return {"message": "You are within the rate limit!"}

3. Combine Multiple Limiters

limiter_1s = RateLimiter(limit=1, seconds=1)
limiter_30m = RateLimiter(limit=30, minutes=1)

@app.get("/strict", dependencies=[Depends(limiter_1s), Depends(limiter_30m)])
async def strict_endpoint():
    return {"message": "You passed both rate limits!"}

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🧩 Supported Algorithms

• Fixed Window: Simple, aggressive limits.
• Sliding Window (Approximated): Smoother than fixed window, more efficient than log-based.
• Sliding Window (Log-based): Most accurate and fair, eliminates burst issues.
• Token Bucket: Allows bursts, enforces average rate.
• Leaky Bucket: Smooths out bursts, enforces constant output rate.
• GCRA: Precise, fair, and burstable rate limiting.

See the strategies overview for details and usage examples.

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⚙️ Customization

• Custom Key Function: Rate limit by user ID, API key, etc.
• Custom on_limit Handler: Return custom responses, log events, etc.

See Quickstart for details.

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📚 Documentation

• Quickstart Guide
• Strategy Overview
• Fixed Window
• Sliding Window (Approximated)
• Sliding Window (Log-based)
• Token Bucket
• Leaky Bucket
• GCRA

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🛡️ License

MIT License

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🤝 Contributing

Contributions, bug reports, and feature requests are welcome!
Please open an issue or submit a pull request.

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