zanewalker
da496746bb
- Core rate limiting with multiple algorithms (sliding window, token bucket, etc.) - SQLite and memory backends - Decorator and dependency injection patterns - Middleware support - Example usage files
61 lines
1.5 KiB
Python
61 lines
1.5 KiB
Python
"""Quickstart example - minimal setup to get rate limiting working."""
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from __future__ import annotations
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from contextlib import asynccontextmanager
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from fastapi import FastAPI, Request
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from fastapi.responses import JSONResponse
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from fastapi_traffic import (
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MemoryBackend,
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RateLimitExceeded,
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RateLimiter,
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rate_limit,
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)
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from fastapi_traffic.core.limiter import set_limiter
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# Step 1: Create a backend and limiter
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backend = MemoryBackend()
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limiter = RateLimiter(backend)
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@asynccontextmanager
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async def lifespan(app: FastAPI):
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"""Lifespan context manager for startup/shutdown."""
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await limiter.initialize()
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set_limiter(limiter)
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yield
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await limiter.close()
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app = FastAPI(title="Quickstart Example", lifespan=lifespan)
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# Step 2: Add exception handler for rate limit errors
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@app.exception_handler(RateLimitExceeded)
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async def rate_limit_handler(request: Request, exc: RateLimitExceeded) -> JSONResponse:
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return JSONResponse(
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status_code=429,
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content={"error": "Too many requests", "retry_after": exc.retry_after},
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)
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# Step 3: Apply rate limiting to endpoints
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@app.get("/")
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@rate_limit(10, 60) # 10 requests per minute
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async def hello(request: Request) -> dict[str, str]:
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return {"message": "Hello, World!"}
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@app.get("/api/data")
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@rate_limit(100, 60) # 100 requests per minute
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async def get_data(request: Request) -> dict[str, str]:
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return {"data": "Some important data"}
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if __name__ == "__main__":
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import uvicorn
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uvicorn.run(app, host="0.0.0.0", port=8000)
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