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Persistent caching decorator

Project description

functioncache

functioncache is a decorator which saves the return value of functions even
after the interpreter dies. For example this is useful on functions that download
and parse webpages. All you need to do is specify how long
the return values should be cached (use seconds, like time.sleep).

USAGE:

from functioncache import functioncache

@functioncache(24 * 60 * 60)
def time_consuming_function(args):
# etc

@functioncache(functioncache.YEAR)
def another_function(args):
# etc

USAGE FOR *INSTANCE AGNOSTIC* CLASS METHODS:

Normally, you wouldn't want to cache class method results, because
they may be affected by changes to the state of the object (self).

*If you know what you're doing* and are sure that a class method
would not be affected by the object's state (for example - object
is a proxy to a remote service), you'll need to make sure the first
argument (self) doesn't get cached.

In that case, you should use the ignore_instance=True keyword:

class db:
@functioncache(functioncache.HOUR,ignore_instance=True)
def query(...):
...

NOTE: All arguments of the decorated function and the return value need to be
picklable for this to work.

NOTE: The cache isn't automatically cleaned, it is only overwritten. If your
function can receive many different arguments that rarely repeat, your
cache may forever grow. One day I might add a feature that once in every
100 calls scans the db for outdated stuff and erases.

Tested on python 2.7 and 3.1
(ignore_instance tested on python 2.7 and it rocks)

License: BSD, do what you wish with this. Could be awesome to hear if you found
it useful and/or you have suggestions. ubershmekel at gmail


A trick to invalidate a single value:

@functioncache.functioncache
def somefunc(x, y, z):
return x * y * z

del somefunc._db[functioncache._args_key(somefunc, (1,2,3), {})]
# or just iterate of somefunc._db (it's a shelve, like a dict) to find the right key.

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