memorised A Python module containing handy "python-memcached" decorators and utils
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Python library Python decorators python-memcached decorators

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A Python module containing handy "python-memcached" decorators and utils memorised is a Python library which contains handy python-memcached decorators and utilities. Specifically the memorise decorator allows you to quickly and simply add memcache caching to any function or method.Installation:Install "memorised" using the supplied setup.py:: python setup.pyOr install "memorised" using easy_install:: easy_install memorisedUsage:To cache a simple unbound function, just include the "@memorise()" tag to the function definition (the paranthesis are needed as the decorator needs to be initialised at the time of binding to handle "memorise" specific arguements):: @memorise() def myfunction(): return 'hello world'You can do the same for simple instance and class methos, however for most instance methods, e.g. when caching results for database models, you probably want to include some form of identity to single out a method call on one instance from another instance. You can do this by providing a list of one ore more 'parent keys', these are the names of attributes in the parent instance that you want to be appended to the memcache key:: class MyModel: id = 1 @memorise(parent_keys=) def get_stats(): return blah()You may also wish to keep attributes in line with the value retrieved from memcache, especially if those attributes are 'pickled' or accessed directly by other code. To do this just pass the name of the attribute to update as a string via the "set" arguement:: class MyModel: def __init__(self): self.a = None @memorise(set='a') def get_a(): return self.a"memorise()" supports dependancy injection for the python-memcached Client instance by passing in the "mc" arguement:: mc = memcached.Client(, debug=0) @memorise(mc=mc) def myfunction() return 'hello world'Alternatively you can pass in a list of memcache servers, via the "mc_servers" arguement, to use a new Client instance, but to use same the server pool.For other usage examples see the unittests in "tests.py". Note: if you don't have memcache running at localhost:11211, you will need to either start it or modify the test suite to use a different memcache Client configuration, otherwise all the tests will fail. Requirements: · Python

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