Python utils and decorators for cаching with TTL, maxsize and file-based storage.
Project description
Status
WORK IN PROGRESS
Caching
Python utils and decorators for cаching with TTL, maxsize and file-based storage.
Installation
pip install caching
Usage
from caching import cache
@cache(ttl=60, maxsize=128, filepath='/tmp/mycache')
def long_running_function(a, b, *args, c=None, **kwargs):
pass
Advanced usage
from caching import Cache
# Set default parameters
cache = Cache(filepath='/tmp/mycache', ttl=3600, maxsize=1024)
# Use default parameters
@cache
def pow(x, y):
return x**y
# Override default parameters
@cache(filepath=None, ttl=-1, maxsize=10000)
def factorial(n):
if n == 0:
return 1
return n * factorial(n-1)
def cache_key(x):
return str(x)
@cache(ttl=-1, maxsize=10000, key=cache_key)
def toupper(a):
return str(a).upper()
# Using cache as a key-value store
try:
result = cache[1]
except KeyError:
result = calculate_result(1)
cache[1] = result
assert 1 in cache
assert cache[1] == result
assert cache.get(1, None) == result
assert cache.get(2, None) is None
# Cleanup
import os
cache = Cache(filepath='/tmp/mycache')
cache[1] = 'one'
assert 1 in cache
cache.clear() # empty the cache
assert 1 not in cache
assert list(cache.items()) == []
assert os.path.isfile('/tmp/mycache')
cache.remove() # Empty the cache and remove the underlying file
assert not os.path.isfile('/tmp/mycache')
Features
[x] Memory and file based cache.
[x] TTL and maxsize.
[x] Works with *args, **kwargs.
[x] Works with mutable function arguments of the following types: dict, list, set.
[ ] LRS (least recently stored), LRU and LFU cache.
[ ] Multiprocessing- and thread-safe.
[ ] Customizable cache key function.
[ ] Pluggable external caching backends (see Redis example).
Project details
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