Basic usage:

  from zoocache import cacheable, invalidate, add_deps

  @cacheable
  def get_product_page(pid: int, sid: int):
      product = db.get_product(pid)
      add_deps([f"product:{pid}"])

      stock = db.get_stock(sid, pid)
      add_deps([f"store:{sid}:stock"])

      return render(product, stock)

  get_product_page(42, 1)   # computes and caches
  get_product_page(42, 1)   # cache hit

  invalidate("product:42")  # product info changed
  invalidate("store:1")     # clears ALL store:1:* (stock, prices, etc)

Internally it's a prefix trie with HLC for distributed consistency, a SingleFlight to avoid thundering herds, and MsgPack+LZ4 serialization. The core is Rust via PyO3. Supports in-memory, LMDB, and Redis backends.

It's a fairly niche tool, if simple TTL or lru_cache covers your use case, you don't need this. It's more for when you have complex data relationships and need precise, immediate invalidation.

Source: https://github.com/albertobadia/zoocache

Hope you find it useful. Happy to receive feedback, PRs, or discuss design tradeoffs.