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Python utils and decorators for cаching with TTL, maxsize and file-based storage.

Project description

Status

WORK IN PROGRESS

Caching

Build Status Coverage Status Python Versions

Python utils and decorators for cаching with TTL, maxsize and file-based storage.

Installation

pip install caching

Usage

from caching import Cache

# File-based cache with unlimited ttl and maximum of 128 cached results
@Cache(ttl=-1, maxsize=128, filepath='/tmp/mycache')
def long_running_function(a, b, *args, c=None, **kwargs):
    pass

# Memory-based cache with limited ttl and maxsize and "least recently used"
# cache replacement policy.
@Cache(ttl=60, maxsize=128, policy='LRU')
def long_running_function(a, b, *args, c=None, **kwargs):
    pass

Advanced usage

from caching import Cache

# One cache for many functions

cache = Cache(filepath='/tmp/mycache', ttl=3600, maxsize=1024)

@cache
def pow(x, y):
    return x**y

@cache
def factorial(n):
    if n == 0:
        return 1
    return n * factorial(n-1)


# Caching the last result and returning it only in case of errors

@Cache(maxsize=1, only_on_errors=(ConnectionError, TimeoutError))
def api_request():
    """Request some remote resource which sometimes become unavailable.
    If this functions raises ConnectionError or TimeoutError, then the
    last cached result will be returned, if available."""


# Custom cache key function

@Cache(key=lambda x: x[0])
def toupper(a):
    global call_count
    call_count += 1
    return str(a).upper()

call_count = 0

# The key function returns the same result for both 'aaa' and 'azz'
# so the cached result from the first call is returned in the second call
assert toupper('aaa') == toupper('azz') == 'AAA'
assert call_count == 1


# Using cache as a key-value store

cache = Cache()

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.

  • [x] FIFO, LRU and LFU cache replacement policies.

  • [x] Customizable cache key function.

  • [ ] Multiprocessing- and thread-safe.

  • [ ] Pluggable external caching backends (see Redis example).

Project details


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Source Distribution

caching-py35-0.1.dev8.linux-x86_64.tar.gz (10.5 kB view hashes)

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