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python-common-cache is a cache component based in memory. It is lightweight, simple, and customizable. Implementing a cache that fits your needs is as simple as installing and importing.

Features

Complex configuration code is not necessary. The default configuration is suited for most use cases but there is also support for customized configuration in regards to: eviction strategy, cleanup strategy, and whether to enable thread pool and so on.
Fine-grained control of expiration time. Each cache instance has a global expiration time but can also set the local expiration time of the key by using put(key, value, expire).
Supports building a multi-level cache system using the cache_loader(key) and the cache_writer(key, value). The cache_loader(key) can load a cache from another cache system or data source when there is a cache miss. The cache_writer(key, value) can take the results and write to another cache system or data source. The cache_loader(key) and cache_writer(key, value) needs you to implement and configure to the cache instance.
LRU (Least-Recently-Used) strategy for recycling old cache items when the capacity of the cache is full. FIFO (First-In-First-Out) and LFU (Least-Frequently-Used) can also be used instead.
Supports dynamic replacement eviction by using replace_evict_func(func) and a cleanup function using replace_cleanup_func(func).
Creates a daemon when a cache instance is initialized and will regularly clean up invalid cache items by invoking cleanup(). The cache instance will invoke cleanup() after using get()/put()/pop().
Each cache instance has a thread pool for improving throughput, which can be disabled by passing enable_thread_pool=False to the Cache() function which can also invoke dynamic control or by disabling the thread pool at runtime
statistic_record() outputs the recorded statistics of each cache item including: hit counts, hit rate, miss counts, expiration time, remaining survival time, birthday, and key and value

Installation

Install using pip

pip install python-common-cache

Usage

There are two ways to use the cache

The first is to use it like a dictionary:

cache = Cache(expire=10)
cache['key'] = 'data'
def foo():
    # cache hit and return data from the cache
    if cache['key'] is not None:
        return cache['key']
    # cache miss and return data from a data source or service
    ....

The second way is to use a decorator which is more convenient:

>>> import time
>>> cache = Cache()
>>> @cache.access_cache(key='a')
... def a():
...     return 'a from data source'
>>> a()
'a from data source'
>>> cache.get('a')
'a from data source'
>>> cache.put(key='b', value='b from cache')
>>> @cache.access_cache(key='b')
... def b():
...     return 'b from data source'
>>> b()
'b from cache'
>>> c_key = 'c'
>>> @cache.access_cache(key_location_on_param=0)
... def c(key):
...     return 'c from data source'
>>> c(c_key)
'c from data source'
>>> cache.get(c_key)
'c from data source'
>>> @cache.access_cache(key='d', auto_update=False)
... def d():
...     return 'd from data source'
>>> d()
'd from data source'
>>> cache.get('d') == None
True
>>> @cache.access_cache(key='e', cache_loader=lambda k: '%s from cache loader' % k)
... def e():
...     return 'e from data source'
>>> e()
'e from cache loader'
>>> out_dict = {}
>>> def writer(k, v):
...     out_dict[k] = v
>>> @cache.access_cache(key='f', cache_writer=writer)
... def f():
...     return 'f from data source'
>>> f()
'f from data source'
>>> time.sleep(1) # wait to execute complete because it in the other thread
>>> out_dict
{'f': 'f from data source'}
>>> cache.with_cache_loader(lambda k: '%s from cache loader(global)' % k)
True
>>> @cache.access_cache(key='g')
... def g():
...     return 'g from data source'
>>> g()
'g from cache loader(global)'

For more usage examples please read the source code of the Cache class where there are many examples for reference.

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