- April 25, 2007
- cache function threading threads thread
- 6 (after 6 ratings)
Please see original snippet for commentary, all I did was add the caching of the arguments.
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import cPickle as pickle import md5 def cache_function(length): """ A variant of the snippet posted by Jeff Wheeler at http://www.djangosnippets.org/snippets/109/ Caches a function, using the function and its arguments as the key, and the return value as the value saved. It passes all arguments on to the function, as it should. The decorator itself takes a length argument, which is the number of seconds the cache will keep the result around. It will put in a MethodNotFinishedError in the cache while the function is processing. This should not matter in most cases, but if the app is using threads, you won't be able to get the previous value, and will need to wait until the function finishes. If this is not desired behavior, you can remove the first two lines after the ``else``. """ def decorator(func): def inner_func(*args, **kwargs): from django.core.cache import cache raw = [func.__name__, func.__module__, args, kwargs] pickled = pickle.dumps(raw, protocol=pickle.HIGHEST_PROTOCOL) key = md5.new(pickled).hexdigest() value = cache.get(key) if cache.has_key(key): return value else: # This will set a temporary value while ``func`` is being # processed. When using threads, this is vital, as otherwise # the function can be called several times before it finishes # and is put into the cache. class MethodNotFinishedError(Exception): pass cache.set(key, MethodNotFinishedError( 'The function %s has not finished processing yet. This \ value will be replaced when it finishes.' % (func.__name__) ), length) result = func(*args, **kwargs) cache.set(key, result, length) return result return inner_func return decorator