Simple objects/methods results cacher with optional persistent cacheing. Supports Memory Files or Redis as storage
Project description
Simple cacher for your objects. Store copy of objects in memory (or pickle in file) and returns copy of that objects. Function arguments it is a cache key.
>>> from object_cacher import ObjectCacher >>> @ObjectCacher(timeout=5) ... def test(*args): ... print ('Real call') ... return args ... >>> test(1,2,3) Real call (1, 2, 3)>>> test(1,2,3) (1, 2, 3)>>> test(1,2,3,4) Real call (1, 2, 3, 4)>>> test(1,2,3,4) ... (1, 2, 3, 4)
Makes cache for results of hard functions or methods. For example you have remote RESTful api with a lot of dictionaries. You may cache it:
>>> from urllib import urlopen >>> from object_cacher import ObjectCacher >>> @ObjectCacher(timeout=60) ... def get_api(): ... print "This real call" ... return urlopen('https://api.github.com/').read() ... >>> get_api() This real call '{"current_user_url":"https://api.github.com/user", ...' >>> get_api() '{"current_user_url":"https://api.github.com/user", ...'
As result you made http request only once.
For methods you may use it like this:
>>> from urllib import urlopen >>> from object_cacher import ObjectCacher >>> class API(object): ... @ObjectCacher(timeout=60, ignore_self=True) ... def get_methods(self): ... print "Real call" ... return urlopen('https://api.github.com/').read() ... >>> a = API() >>> a.get_methods() Real call '{"current_user_url":"https://api.github.com/user", ...' >>> b = API() >>> b.get_methods() '{"current_user_url":"https://api.github.com/user", ...'
If ignore_self parameter is set, cache will be shared by all instances. Otherwise cache for instances will be split.
Also you may use persistent cache. The “ObjectPersistentCacher” class-decorator makes file-based pickle-serialized cache storage. When you want to keep cache after rerun you must determine cache id:
>>> from urllib import urlopen >>> from object_cacher import ObjectCacher >>> class API(object): ... @ObjectPersistentCacher(timeout=60, ignore_self=True, oid='com.github.api.listofmethods') ... def get_methods(self): ... print "Real call" ... return urlopen('https://api.github.com/').read() ... >>> a = API() >>> a.get_methods() Real call '{"current_user_url":"https://api.github.com/user", ...' >>> b = API() >>> b.get_methods() '{"current_user_url":"https://api.github.com/user", ...'
That is keep cache after rerun.
You may change cache dir for ObjectPersistentCacher via changing ‘CACHE_DIR’ class-property.
>>> ObjectPersistentCacher.CACHE_DIR = '/var/tmp/my_cache'
Installation
You may install from pypi
pip install object_cacher
or manual
python setup.py install
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