I built a rate limiter that survives process restarts — no Redis required

Every time I needed rate limiting in a Python service, the answer was the same: add Redis. Just to count requests.

So I built Flint. Embedded, persistent, zero infrastructure.

pythonimport flint

limiter = flint.Limiter(data_dir=".flint")

limiter.limit("api:user-42", rate=100, per="1m")

if limiter.allow("api:user-42"):

process_request()

Counters persist in .flint/ and survive restarts. Something no in-memory solution does.

What makes it different

SlowAPI resets on restart. Redis requires infrastructure. nginx only works at HTTP layer.

Flint is persistent, embedded, and works anywhere — including AI APIs with cost-based limiting:

pythonresult = limiter.check("ai:user-42", cost=250)

FastAPI middleware, Prometheus export, millisecond precision, and atomic multi-limit checks included.

Core is Rust via PyO3. Token bucket check: ~560µs.

bashpip install flint-limiter

GitHub: https://github.com/BuildByNexora/Flint