philiprehberger-rate-limiter 0.2.1

In-memory rate limiter with sliding window and token bucket

philiprehberger-rate-limiter

In-memory rate limiter with sliding window and token bucket algorithms.

Installation

pip install philiprehberger-rate-limiter

Usage

Basic Rate Limiting

from philiprehberger_rate_limiter import RateLimiter, Algorithm

limiter = RateLimiter(
    requests=100,
    window_seconds=60,
    algorithm=Algorithm.SLIDING_WINDOW,
)

if limiter.allow("user-123"):
    handle_request()

Check Status

status = limiter.status("user-123")
print(f"Allowed: {status.allowed}")
print(f"Remaining: {status.remaining}/{status.limit}")
print(f"Resets at: {status.reset_at}")

Decorator

limiter = RateLimiter(10, 60)

@limiter.limit("10/minute")
def api_endpoint():
    return {"data": "ok"}

Algorithms

# Fixed window — resets at interval boundaries
RateLimiter(100, 60, Algorithm.FIXED_WINDOW)

# Sliding window (default) — rolling time window
RateLimiter(100, 60, Algorithm.SLIDING_WINDOW)

# Token bucket — smooth rate with burst capacity
RateLimiter(100, 60, Algorithm.TOKEN_BUCKET)

API

• RateLimiter(requests, window_seconds, algorithm=SLIDING_WINDOW) — Create a rate limiter
• limiter.allow(key) — Check if request is allowed
• limiter.status(key) — Get detailed LimitStatus
• limiter.reset(key) — Reset state for a key
• limiter.reset_all() — Reset state for all keys
• limiter.active_keys() — List all keys with active state
• limiter.limit(rate) — Decorator with rate string (e.g., "10/minute")

License

MIT