Computing with Python functions.
- python
- parallel-computing
- caching
- multiprocessing
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Computing with Python functions.
Extensible memoizing collections and decorators
Build real-time apps (Blazor included) with less than 1% of extra code responsible for real-time updates. Host 10-1000x faster APIs relying on transparent and nearly 100% consistent caching. We call it DREAM, or Distributed REActive Memoization, and it's here to turn real-time on!
Memoize functions - an optimization technique used to speed up consecutive function calls by caching the result of calls with identical input
Quick development library (AutoMapper, LinQ, IOC Dependency Injection, MemoryCache, Scheduled tasks, Json and Yml Config and Options pattern, Serializers, etc) with crossplatform support for Delphi/Firemonkey (Windows,Linux,OSX/IOS/Android) and freepascal (Windows/Linux).
The wise choice for Ruby memoization
Memoize promise-returning & async functions
A method caching macro for elixir using CAS on ETS.
Cache values in your Web Extension and clear them on expiration. Also includes a memoize-like API to cache any function results automatically
Memoize promise-returning functions. Includes cache expire and prefetch.
A Common Lisp function caching / memoization library
🚀 Schema based, typed Redis caching/memoize framework for Go