fastcache

C implementation of Python 3 functools.lru_cache. Provides speedup of 10-30x over standard library. Passes test suite from standard library for lru_cache.

Provides 2 Least Recently Used caching function decorators:

clru_cache - built-in (faster) >>> from fastcache import clru_cache, version >>> version '1.1.0' >>> @clru_cache(maxsize=325, typed=False) ... def fib(n): ... """Terrible Fibonacci number generator.""" ... return n if n < 2 else fib(n-1) + fib(n-2) ... >>> fib(300) 222232244629420445529739893461909967206666939096499764990979600 >>> fib.cache_info() CacheInfo(hits=298, misses=301, maxsize=325, currsize=301) >>> print(fib.doc) Terrible Fibonacci number generator. >>> fib.cache_clear() >>> fib.cache_info() CacheInfo(hits=0, misses=0, maxsize=325, currsize=0) >>> fib.wrapped(300) 222232244629420445529739893461909967206666939096499764990979600 >>> type(fib) >>> <class 'fastcache.clru_cache'>

lru_cache - python wrapper around clru_cache >>> from fastcache import lru_cache >>> @lru_cache(maxsize=128, typed=False) ... def f(a, b): ... pass ... >>> type(f) >>> <class 'function'>

(c)lru_cache(maxsize=128, typed=False, state=None, unhashable='error')

  Least-recently-used cache decorator.

  If *maxsize* is set to None, the LRU features are disabled and the cache
  can grow without bound.

  If *typed* is True, arguments of different types will be cached separately.
  For example, f(3.0) and f(3) will be treated as distinct calls with
  distinct results.

  If *state* is a list or dict, the items will be incorporated into the
  argument hash.

  The result of calling the cached function with unhashable (mutable)
  arguments depends on the value of *unhashable*:

      If *unhashable* is 'error', a TypeError will be raised.

      If *unhashable* is 'warning', a UserWarning will be raised, and
      the wrapped function will be called with the supplied arguments.
      A miss will be recorded in the cache statistics.

      If *unhashable* is 'ignore', the wrapped function will be called
      with the supplied arguments. A miss will will be recorded in
      the cache statistics.

  View the cache statistics named tuple (hits, misses, maxsize, currsize)
  with f.cache_info().  Clear the cache and statistics with f.cache_clear().
  Access the underlying function with f.__wrapped__.

  See:  http://en.wikipedia.org/wiki/Cache_algorithms#Least_Recently_Used