Rancero to Inherit Development of inhouse Cache
We're excited to announce that Rancero is inheriting development and future support for inhouse, a zero-dependency, in-process TTL cache for Python.
inhouse is designed for developers who need fast, simple caching without the overhead of external infrastructure like Redis. A single decorator is all it takes. No complex configuration, and no separate services to deploy.
Why use inhouse?
- Zero external dependencies — No Redis, no databases, no infrastructure to manage. inhouse runs entirely in-process.
- Stampede-safe — Per-key singleflight ensures concurrent cache misses on the same key coalesce into one computation, preventing thundering herds.
- LRU-bounded — Automatically evicts least-recently-used entries when
max_sizeis exceeded, keeping memory under control. - TTL with lazy expiry — Expired entries are cleaned on read, with an optional background sweeper for proactive cleanup.
- Thread-safe — Safe for use with both sync and async callables.
- FastAPI-ready — Built-in
@fastapi_cachedecorator with Request/Response-aware cache keys, background expiry sweeper, and clean lifespan shutdown.
How it benefits developers
inhouse eliminates the friction of setting up and maintaining external caching infrastructure. It's ideal for single-node applications, prototypes, and services where latency and simplicity matter. With inhouse, you add caching in one line of code and get production-grade features like stampede protection, deterministic cache keys, and configurable TTL policies, all without leaving your application process.
"For when Redis is a meeting you don't want to have."
inhouse will be included in the Rancero platform natively, and we're committed to supporting and developing the library with community contributions.
For full documentation, visit our inhouse Cache documentation. We will own/maintain formal documentation for inhouse Cache moving forward.
Try it out: The package is published on PyPI as inhouse-cache. Imports use inhouse (e.g. from inhouse import MemoryStore).
Core:
pip install inhouse-cache
With FastAPI helpers (fastapi_cache, lifespan sweeper):
pip install inhouse-cache[fastapi]

