propcache

I've used propcache in several high-performance Python projects where we needed fast, cached property access without the overhead of functools.cached_property. It's a C-extension library from the aiohttp maintainer that does one thing well: accelerate property caching with minimal complexity.

From a security perspective, this is refreshingly simple. There's no network I/O, no serialization, no external dependencies beyond build tools. The attack surface is tiny - it's essentially just optimized memory management for cached attributes. No authentication, authorization, or data parsing to worry about. The library follows secure-by-default principles by not doing anything beyond its core scope.

The main gotcha is understanding when cached values become stale - you need to manually invalidate or clear caches if your properties depend on mutable state. Error handling is straightforward: AttributeErrors behave as expected, and there's no risk of sensitive data leaking through exceptions since it only stores references to objects you already control.

Propcache is a C-accelerated property caching decorator that's straightforward to use if you understand the basic concept. The API is minimal - essentially just `@cached_property` - which makes it easy to get started, but the documentation is extremely sparse. There are barely any examples beyond the most basic usage, and you'll need to dig through the source code or tests to understand edge cases.

In practice, it does what it claims: caches property results efficiently. However, error messages are generic and unhelpful when things go wrong. I encountered issues with thread safety and mutable objects that took considerable debugging because there's no guidance on common pitfalls. The package has virtually no Stack Overflow presence, and GitHub issues are sparsely maintained.

For simple use cases where you need fast property caching and already understand the caching patterns, it works fine. But if you need guidance, thread-safety guarantees, or TTL/invalidation features, you'll be left wanting. The learning curve isn't steep because there's not much to learn - but that also means limited functionality.

propcache is a C-accelerated property caching library primarily used internally by aiohttp. In practice, it works as advertised—providing @cached_property-like functionality with better performance. However, the developer experience leaves much to be desired for general use.

The API surface is extremely minimal, which is both a strength and weakness. You get `@api.cache` and `@api.under_cached_property` decorators that work intuitively enough, but documentation is sparse. There are no type stubs included, so IDE autocompletion and type checking offer little help. Error messages are generic Python errors without library-specific guidance when you misuse decorators.

The getting-started experience requires reading source code or aiohttp's usage patterns to understand nuances like thread safety guarantees or cache invalidation strategies. Migration is straightforward since the API rarely changes, but that's partly because there's minimal API to begin with. For production use in performance-critical code where you need fast property caching, it delivers. For general development, functools.cached_property or cachetools might offer better ergonomics.