class Cache(object): """ This class is used to control the cache objects. If TESTING is True it will use NullCache. """ def __init__(self, app=None, with_jinja2_ext=True): self.with_jinja2_ext = with_jinja2_ext self.cache = None if app is not None: self.init_app(app) else: self.app = None self._memoized = [] def init_app(self, app): "This is used to initialize cache with your app object" app.config.setdefault('CACHE_DEFAULT_TIMEOUT', 300) app.config.setdefault('CACHE_THRESHOLD', 500) app.config.setdefault('CACHE_KEY_PREFIX', None) app.config.setdefault('CACHE_MEMCACHED_SERVERS', None) app.config.setdefault('CACHE_DIR', None) app.config.setdefault('CACHE_OPTIONS', None) app.config.setdefault('CACHE_ARGS', []) app.config.setdefault('CACHE_TYPE', 'null') if self.with_jinja2_ext: setattr(app.jinja_env, JINJA_CACHE_ATTR_NAME, self) app.jinja_env.add_extension(CacheExtension) self.app = app self._set_cache() def _set_cache(self): if self.app.config['TESTING']: self.cache = NullCache() else: import_me = self.app.config['CACHE_TYPE'] if '.' not in import_me: import_me = 'flaskext.cache.backends.' + \ import_me cache_obj = import_string(import_me) cache_args = self.app.config['CACHE_ARGS'][:] cache_options = dict(default_timeout= \ self.app.config['CACHE_DEFAULT_TIMEOUT']) if self.app.config['CACHE_OPTIONS']: cache_options.update(self.app.config['CACHE_OPTIONS']) self.cache = cache_obj(self.app, cache_args, cache_options) if not isinstance(self.cache, BaseCache): raise TypeError("Cache object must subclass " "werkzeug.contrib.cache.BaseCache") def get(self, *args, **kwargs): "Proxy function for internal cache object." return self.cache.get(*args, **kwargs) def set(self, *args, **kwargs): "Proxy function for internal cache object." self.cache.set(*args, **kwargs) def add(self, *args, **kwargs): "Proxy function for internal cache object." self.cache.add(*args, **kwargs) def delete(self, *args, **kwargs): "Proxy function for internal cache object." self.cache.delete(*args, **kwargs) def delete_many(self, *args, **kwargs): "Proxy function for internal cache object." self.cache.delete_many(*args, **kwargs) def cached(self, timeout=None, key_prefix='view/%s', unless=None): """ Decorator. Use this to cache a function. By default the cache key is `view/request.path`. You are able to use this decorator with any function by changing the `key_prefix`. If the token `%s` is located within the `key_prefix` then it will replace that with `request.path` Example:: # An example view function @cache.cached(timeout=50) def big_foo(): return big_bar_calc() # An example misc function to cache. @cache.cached(key_prefix='MyCachedList') def get_list(): return [random.randrange(0, 1) for i in range(50000)] my_list = get_list() .. note:: You MUST have a request context to actually called any functions that are cached. .. versionadded:: 0.4 The returned decorated function now has three function attributes assigned to it. These attributes are readable/writable. **uncached** The original undecorated function **cache_timeout** The cache timeout value for this function. For a custom value to take affect, this must be set before the function is called. **make_cache_key** A function used in generating the cache_key used. :param timeout: Default None. If set to an integer, will cache for that amount of time. Unit of time is in seconds. :param key_prefix: Default 'view/%(request.path)s'. Beginning key to . use for the cache key. .. versionadded:: 0.3.4 Can optionally be a callable which takes no arguments but returns a string that will be used as the cache_key. :param unless: Default None. Cache will *always* execute the caching facilities unless this callable is true. This will bypass the caching entirely. """ def decorator(f): @wraps(f) def decorated_function(*args, **kwargs): #: Bypass the cache entirely. if callable(unless) and unless() is True: return f(*args, **kwargs) cache_key = decorated_function.make_cache_key(*args, **kwargs) rv = self.cache.get(cache_key) if rv is None: rv = f(*args, **kwargs) self.cache.set(cache_key, rv, timeout=decorated_function.cache_timeout) return rv def make_cache_key(*args, **kwargs): if '%s' in key_prefix: cache_key = key_prefix % request.path elif callable(key_prefix): cache_key = key_prefix() else: cache_key = key_prefix cache_key = cache_key.encode('utf-8') return cache_key decorated_function.uncached = f decorated_function.cache_timeout = timeout decorated_function.make_cache_key = make_cache_key return decorated_function return decorator def _memvname(self, funcname): return funcname + '_memver' def memoize_make_version_hash(self): return uuid.uuid4().bytes.encode('base64')[:6] def memoize_make_cache_key(self, fname, make_name=None): """ Function used to create the cache_key for memoized functions. """ def make_cache_key(f, *args, **kwargs): version_key = self._memvname(fname) version_data = self.cache.get(version_key) if version_data is None: version_data = self.memoize_make_version_hash() self.cache.set(version_key, version_data) cache_key = hashlib.md5() #: this should have to be after version_data, so that it #: does not break the delete_memoized functionality. if callable(make_name): altfname = make_name(fname) else: altfname = fname if callable(f): args, kwargs = self.memoize_kwargs_to_args(f, *args, **kwargs) try: updated = "{0}{1}{2}".format(altfname, args, kwargs) except AttributeError: updated = "%s%s%s" % (altfname, args, kwargs) cache_key.update(updated) cache_key = cache_key.digest().encode('base64')[:16] cache_key += version_data return cache_key return make_cache_key def memoize_kwargs_to_args(self, f, *args, **kwargs): #: Inspect the arguments to the function #: This allows the memoization to be the same #: whether the function was called with #: 1, b=2 is equivilant to a=1, b=2, etc. new_args = [] arg_num = 0 m_args = inspect.getargspec(f)[0] for i in range(len(m_args)): if m_args[i] in kwargs: new_args.append(kwargs[m_args[i]]) elif arg_num < len(args): new_args.append(args[arg_num]) arg_num += 1 return tuple(new_args), {} def memoize(self, timeout=None, make_name=None, unless=None): """ Use this to cache the result of a function, taking its arguments into account in the cache key. Information on `Memoization <http://en.wikipedia.org/wiki/Memoization>`_. Example:: @cache.memoize(timeout=50) def big_foo(a, b): return a + b + random.randrange(0, 1000) .. code-block:: pycon >>> big_foo(5, 2) 753 >>> big_foo(5, 3) 234 >>> big_foo(5, 2) 753 .. versionadded:: 0.4 The returned decorated function now has three function attributes assigned to it. **uncached** The original undecorated function. readable only **cache_timeout** The cache timeout value for this function. For a custom value to take affect, this must be set before the function is called. readable and writable **make_cache_key** A function used in generating the cache_key used. readable and writable :param timeout: Default None. If set to an integer, will cache for that amount of time. Unit of time is in seconds. :param make_name: Default None. If set this is a function that accepts a single argument, the function name, and returns a new string to be used as the function name. If not set then the function name is used. :param unless: Default None. Cache will *always* execute the caching facilities unelss this callable is true. This will bypass the caching entirely. .. versionadded:: 0.5 params ``make_name``, ``unless`` """ def memoize(f): @wraps(f) def decorated_function(*args, **kwargs): #: bypass cache if callable(unless) and unless() is True: return f(*args, **kwargs) cache_key = decorated_function.make_cache_key( f, *args, **kwargs) rv = self.cache.get(cache_key) if rv is None: rv = f(*args, **kwargs) self.cache.set(cache_key, rv, timeout=decorated_function.cache_timeout) return rv decorated_function.uncached = f decorated_function.cache_timeout = timeout decorated_function.make_cache_key = self.memoize_make_cache_key( f.__name__, make_name) return decorated_function return memoize def delete_memoized(self, fname, *args, **kwargs): """ Deletes the specified functions caches, based by given parameters. If parameters are given, only the functions that were memoized with them will be erased. Otherwise all the versions of the caches will be deleted. Example:: @cache.memoize(50) def random_func(): return random.randrange(1, 50) @cache.memoize() def param_func(a, b): return a+b+random.randrange(1, 50) .. code-block:: pycon >>> random_func() 43 >>> random_func() 43 >>> cache.delete_memoized('random_func') >>> random_func() 16 >>> param_func(1, 2) 32 >>> param_func(1, 2) 32 >>> param_func(2, 2) 47 >>> cache.delete_memoized('param_func', 1, 2) >>> param_func(1, 2) 13 >>> param_func(2, 2) 47 :param fname: Name of the memoized function, or a reference to the function. :param \*args: A list of positional parameters used with memoized function. :param \**kwargs: A dict of named parameters used with memoized function. .. note:: Flask-Cache uses inspect to order kwargs into positional args when the function is memoized. If you pass a function reference into ``fname`` instead of the function name, Flask-Cache will be able to place the args/kwargs in the proper order, and delete the positional cache. However, if ``delete_memozied`` is just called with the name of the function, be sure to pass in potential arguments in the same order as defined in your function as args only, otherwise Flask-Cache will not be able to compute the same cache key. .. note:: Flask-Cache maintains an internal random version hash for the function. Using delete_memoized will only swap out the version hash, causing the memoize function to recompute results and put them into another key. This leaves any computed caches for this memoized function within the caching backend. It is recommended to use a very high timeout with memoize if using this function, so that when the version has is swapped, the old cached results would eventually be reclaimed by the caching backend. """ if callable(fname): assert hasattr(fname, 'uncached') f = fname.uncached _fname = f.__name__ else: f = None _fname = fname if not args and not kwargs: version_key = self._memvname(fname) version_data = self.memoize_make_version_hash() self.cache.set(version_key, version_data) else: cache_key = self.memoize_make_cache_key(_fname)(f, *args, **kwargs) self.cache.delete(cache_key)
class Cache(object): """ This class is used to control the cache objects. If TESTING is True it will use NullCache. """ def __init__(self, app=None, with_jinja2_ext=True): self.with_jinja2_ext = with_jinja2_ext self.cache = None if app is not None: self.init_app(app) else: self.app = None self._memoized = [] def init_app(self, app): "This is used to initialize cache with your app object" app.config.setdefault('CACHE_DEFAULT_TIMEOUT', 300) app.config.setdefault('CACHE_THRESHOLD', 500) app.config.setdefault('CACHE_KEY_PREFIX', None) app.config.setdefault('CACHE_MEMCACHED_SERVERS', None) app.config.setdefault('CACHE_DIR', None) app.config.setdefault('CACHE_OPTIONS', None) app.config.setdefault('CACHE_ARGS', []) app.config.setdefault('CACHE_TYPE', 'null') if self.with_jinja2_ext: setattr(app.jinja_env, JINJA_CACHE_ATTR_NAME, self) app.jinja_env.add_extension(CacheExtension) self.app = app self._set_cache() def _set_cache(self): if self.app.config['TESTING']: self.cache = NullCache() else: import_me = self.app.config['CACHE_TYPE'] if '.' not in import_me: import_me = 'flaskext.cache.backends.' + \ import_me cache_obj = import_string(import_me) cache_args = self.app.config['CACHE_ARGS'][:] cache_options = dict(default_timeout= \ self.app.config['CACHE_DEFAULT_TIMEOUT']) if self.app.config['CACHE_OPTIONS']: cache_options.update(self.app.config['CACHE_OPTIONS']) self.cache = cache_obj(self.app, cache_args, cache_options) if not isinstance(self.cache, BaseCache): raise TypeError("Cache object must subclass " "werkzeug.contrib.cache.BaseCache") def get(self, *args, **kwargs): "Proxy function for internal cache object." return self.cache.get(*args, **kwargs) def set(self, *args, **kwargs): "Proxy function for internal cache object." self.cache.set(*args, **kwargs) def add(self, *args, **kwargs): "Proxy function for internal cache object." self.cache.add(*args, **kwargs) def delete(self, *args, **kwargs): "Proxy function for internal cache object." self.cache.delete(*args, **kwargs) def delete_many(self, *args, **kwargs): "Proxy function for internal cache object." self.cache.delete_many(*args, **kwargs) def cached(self, timeout=None, key_prefix='view/%s', unless=None): """ Decorator. Use this to cache a function. By default the cache key is `view/request.path`. You are able to use this decorator with any function by changing the `key_prefix`. If the token `%s` is located within the `key_prefix` then it will replace that with `request.path` Example:: # An example view function @cache.cached(timeout=50) def big_foo(): return big_bar_calc() # An example misc function to cache. @cache.cached(key_prefix='MyCachedList') def get_list(): return [random.randrange(0, 1) for i in range(50000)] my_list = get_list() .. note:: You MUST have a request context to actually called any functions that are cached. .. versionadded:: 0.4 The returned decorated function now has three function attributes assigned to it. These attributes are readable/writable. **uncached** The original undecorated function **cache_timeout** The cache timeout value for this function. For a custom value to take affect, this must be set before the function is called. **make_cache_key** A function used in generating the cache_key used. :param timeout: Default None. If set to an integer, will cache for that amount of time. Unit of time is in seconds. :param key_prefix: Default 'view/%(request.path)s'. Beginning key to . use for the cache key. .. versionadded:: 0.3.4 Can optionally be a callable which takes no arguments but returns a string that will be used as the cache_key. :param unless: Default None. Cache will *always* execute the caching facilities unless this callable is true. This will bypass the caching entirely. """ def decorator(f): @wraps(f) def decorated_function(*args, **kwargs): #: Bypass the cache entirely. if callable(unless) and unless() is True: return f(*args, **kwargs) cache_key = decorated_function.make_cache_key(*args, **kwargs) rv = self.cache.get(cache_key) if rv is None: rv = f(*args, **kwargs) self.cache.set(cache_key, rv, timeout=decorated_function.cache_timeout) return rv def make_cache_key(*args, **kwargs): if callable(key_prefix): cache_key = key_prefix() elif '%s' in key_prefix: cache_key = key_prefix % request.path else: cache_key = key_prefix cache_key = cache_key.encode('utf-8') return cache_key decorated_function.uncached = f decorated_function.cache_timeout = timeout decorated_function.make_cache_key = make_cache_key return decorated_function return decorator def _memvname(self, funcname): return funcname + '_memver' def memoize_make_version_hash(self): return uuid.uuid4().bytes.encode('base64')[:6] def memoize_make_cache_key(self, fname, make_name=None): """ Function used to create the cache_key for memoized functions. """ def make_cache_key(f, *args, **kwargs): version_key = self._memvname(fname) version_data = self.cache.get(version_key) if version_data is None: version_data = self.memoize_make_version_hash() self.cache.set(version_key, version_data) cache_key = hashlib.md5() #: this should have to be after version_data, so that it #: does not break the delete_memoized functionality. if callable(make_name): altfname = make_name(fname) else: altfname = fname if callable(f): args, kwargs = self.memoize_kwargs_to_args(f, *args, **kwargs) try: updated = "{0}{1}{2}".format(altfname, args, kwargs) except AttributeError: updated = "%s%s%s" % (altfname, args, kwargs) cache_key.update(updated) cache_key = cache_key.digest().encode('base64')[:16] cache_key += version_data return cache_key return make_cache_key def memoize_kwargs_to_args(self, f, *args, **kwargs): #: Inspect the arguments to the function #: This allows the memoization to be the same #: whether the function was called with #: 1, b=2 is equivilant to a=1, b=2, etc. new_args = [] arg_num = 0 m_args = inspect.getargspec(f)[0] for i in range(len(m_args)): if m_args[i] in kwargs: new_args.append(kwargs[m_args[i]]) elif arg_num < len(args): new_args.append(args[arg_num]) arg_num += 1 return tuple(new_args), {} def memoize(self, timeout=None, make_name=None, unless=None): """ Use this to cache the result of a function, taking its arguments into account in the cache key. Information on `Memoization <http://en.wikipedia.org/wiki/Memoization>`_. Example:: @cache.memoize(timeout=50) def big_foo(a, b): return a + b + random.randrange(0, 1000) .. code-block:: pycon >>> big_foo(5, 2) 753 >>> big_foo(5, 3) 234 >>> big_foo(5, 2) 753 .. versionadded:: 0.4 The returned decorated function now has three function attributes assigned to it. **uncached** The original undecorated function. readable only **cache_timeout** The cache timeout value for this function. For a custom value to take affect, this must be set before the function is called. readable and writable **make_cache_key** A function used in generating the cache_key used. readable and writable :param timeout: Default None. If set to an integer, will cache for that amount of time. Unit of time is in seconds. :param make_name: Default None. If set this is a function that accepts a single argument, the function name, and returns a new string to be used as the function name. If not set then the function name is used. :param unless: Default None. Cache will *always* execute the caching facilities unelss this callable is true. This will bypass the caching entirely. .. versionadded:: 0.5 params ``make_name``, ``unless`` """ def memoize(f): @wraps(f) def decorated_function(*args, **kwargs): #: bypass cache if callable(unless) and unless() is True: return f(*args, **kwargs) cache_key = decorated_function.make_cache_key(f, *args, **kwargs) rv = self.cache.get(cache_key) if rv is None: rv = f(*args, **kwargs) self.cache.set(cache_key, rv, timeout=decorated_function.cache_timeout) return rv decorated_function.uncached = f decorated_function.cache_timeout = timeout decorated_function.make_cache_key = self.memoize_make_cache_key(f.__name__, make_name) return decorated_function return memoize def delete_memoized(self, fname, *args, **kwargs): """ Deletes the specified functions caches, based by given parameters. If parameters are given, only the functions that were memoized with them will be erased. Otherwise all the versions of the caches will be deleted. Example:: @cache.memoize(50) def random_func(): return random.randrange(1, 50) @cache.memoize() def param_func(a, b): return a+b+random.randrange(1, 50) .. code-block:: pycon >>> random_func() 43 >>> random_func() 43 >>> cache.delete_memoized('random_func') >>> random_func() 16 >>> param_func(1, 2) 32 >>> param_func(1, 2) 32 >>> param_func(2, 2) 47 >>> cache.delete_memoized('param_func', 1, 2) >>> param_func(1, 2) 13 >>> param_func(2, 2) 47 :param fname: Name of the memoized function, or a reference to the function. :param \*args: A list of positional parameters used with memoized function. :param \**kwargs: A dict of named parameters used with memoized function. .. note:: Flask-Cache uses inspect to order kwargs into positional args when the function is memoized. If you pass a function reference into ``fname`` instead of the function name, Flask-Cache will be able to place the args/kwargs in the proper order, and delete the positional cache. However, if ``delete_memozied`` is just called with the name of the function, be sure to pass in potential arguments in the same order as defined in your function as args only, otherwise Flask-Cache will not be able to compute the same cache key. .. note:: Flask-Cache maintains an internal random version hash for the function. Using delete_memoized will only swap out the version hash, causing the memoize function to recompute results and put them into another key. This leaves any computed caches for this memoized function within the caching backend. It is recommended to use a very high timeout with memoize if using this function, so that when the version has is swapped, the old cached results would eventually be reclaimed by the caching backend. """ if callable(fname): assert hasattr(fname, 'uncached') f = fname.uncached _fname = f.__name__ else: f = None _fname = fname if not args and not kwargs: version_key = self._memvname(fname) version_data = self.memoize_make_version_hash() self.cache.set(version_key, version_data) else: cache_key = self.memoize_make_cache_key(_fname)(f, *args, **kwargs) self.cache.delete(cache_key)
class Cache(object): """ This class is used to control the cache objects. If TESTING is True it will use NullCache. """ def __init__(self, app=None, with_jinja2_ext=True): self.cache = None if app is not None: self.init_app(app) else: self.app = None self._memoized = [] if self.app and with_jinja2_ext: from jinja2ext import CacheExtension env = self.app.jinja_env setattr(env, JINJA_CACHE_ATTR_NAME, self.cache) env.add_extension(CacheExtension) def init_app(self, app): "This is used to initialize cache with your app object" app.config.setdefault('CACHE_DEFAULT_TIMEOUT', 300) app.config.setdefault('CACHE_THRESHOLD', 500) app.config.setdefault('CACHE_KEY_PREFIX', None) app.config.setdefault('CACHE_MEMCACHED_SERVERS', None) app.config.setdefault('CACHE_DIR', None) app.config.setdefault('CACHE_OPTIONS', None) app.config.setdefault('CACHE_ARGS', []) app.config.setdefault('CACHE_TYPE', 'null') self.app = app self._set_cache() def _set_cache(self): if self.app.config['TESTING']: self.cache = NullCache() else: import_me = self.app.config['CACHE_TYPE'] if '.' not in import_me: import_me = 'flaskext.cache.backends.' + \ import_me cache_obj = import_string(import_me) cache_args = self.app.config['CACHE_ARGS'][:] cache_options = dict(default_timeout= \ self.app.config['CACHE_DEFAULT_TIMEOUT']) if self.app.config['CACHE_OPTIONS']: cache_options.update(self.app.config['CACHE_OPTIONS']) self.cache = cache_obj(self.app, cache_args, cache_options) if not isinstance(self.cache, BaseCache): raise TypeError("Cache object must subclass " "werkzeug.contrib.cache.BaseCache") def get(self, *args, **kwargs): "Proxy function for internal cache object." return self.cache.get(*args, **kwargs) def set(self, *args, **kwargs): "Proxy function for internal cache object." self.cache.set(*args, **kwargs) def add(self, *args, **kwargs): "Proxy function for internal cache object." self.cache.add(*args, **kwargs) def delete(self, *args, **kwargs): "Proxy function for internal cache object." self.cache.delete(*args, **kwargs) def delete_many(self, *args, **kwargs): "Proxy function for internal cache object." self.cache.delete_many(*args, **kwargs) def cached(self, timeout=None, key_prefix='view/%s', unless=None): """ Decorator. Use this to cache a function. By default the cache key is `view/request.path`. You are able to use this decorator with any function by changing the `key_prefix`. If the token `%s` is located within the `key_prefix` then it will replace that with `request.path` Example:: # An example view function @cache.cached(timeout=50) def big_foo(): return big_bar_calc() # An example misc function to cache. @cache.cached(key_prefix='MyCachedList') def get_list(): return [random.randrange(0, 1) for i in range(50000)] my_list = get_list() .. note:: You MUST have a request context to actually called any functions that are cached. .. versionadded:: 0.4 The returned decorated function now has three function attributes assigned to it. These attributes are readable/writable. **uncached** The original undecorated function **cache_timeout** The cache timeout value for this function. For a custom value to take affect, this must be set before the function is called. **make_cache_key** A function used in generating the cache_key used. :param timeout: Default None. If set to an integer, will cache for that amount of time. Unit of time is in seconds. :param key_prefix: Default 'view/%(request.path)s'. Beginning key to . use for the cache key. .. versionadded:: 0.3.4 Can optionally be a callable which takes no arguments but returns a string that will be used as the cache_key. :param unless: Default None. Cache will *always* execute the caching facilities unless this callable is true. This will bypass the caching entirely. """ def decorator(f): @wraps(f) def decorated_function(*args, **kwargs): #: Bypass the cache entirely. if callable(unless) and unless() is True: return f(*args, **kwargs) cache_key = decorated_function.make_cache_key(*args, **kwargs) rv = self.cache.get(cache_key) if rv is None: rv = f(*args, **kwargs) self.cache.set(cache_key, rv, timeout=decorated_function.cache_timeout) return rv def make_cache_key(*args, **kwargs): if '%s' in key_prefix: cache_key = key_prefix % request.path elif callable(key_prefix): cache_key = key_prefix() else: cache_key = key_prefix cache_key = cache_key.encode('utf-8') return cache_key decorated_function.uncached = f decorated_function.cache_timeout = timeout decorated_function.make_cache_key = make_cache_key return decorated_function return decorator def get_memoize_names(self): """ Returns all function names used for memoized functions. This *will* include multiple function names when the memoized function has been called with differing arguments. :return: set of function names """ return set([item[0] for item in self._memoized]) def get_memoize_keys(self): """ Returns all cache_keys used for memoized functions. :return: list generator of cache_keys """ return [item[1] for item in self._memoized] def memoize(self, timeout=None): """ Use this to cache the result of a function, taking its arguments into account in the cache key. Information on `Memoization <http://en.wikipedia.org/wiki/Memoization>`_. Example:: @cache.memoize(timeout=50) def big_foo(a, b): return a + b + random.randrange(0, 1000) .. code-block:: pycon >>> big_foo(5, 2) 753 >>> big_foo(5, 3) 234 >>> big_foo(5, 2) 753 .. versionadded:: 0.4 The returned decorated function now has three function attributes assigned to it. These attributes are readable/writable. **uncached** The original undecorated function **cache_timeout** The cache timeout value for this function. For a custom value to take affect, this must be set before the function is called. **make_cache_key** A function used in generating the cache_key used. :param timeout: Default None. If set to an integer, will cache for that amount of time. Unit of time is in seconds. """ def memoize(f): @wraps(f) def decorated_function(*args, **kwargs): cache_key = decorated_function.make_cache_key(*args, **kwargs) rv = self.cache.get(cache_key) if rv is None: rv = f(*args, **kwargs) self.cache.set(cache_key, rv, timeout=decorated_function.cache_timeout) self._memoized.append((f.__name__, cache_key)) return rv def make_cache_key(*args, **kwargs): cache_key = hashlib.md5() try: updated = "{0}{1}{2}".format(f.__name__, args, kwargs) except AttributeError: updated = "%s%s%s" % (f.__name__, args, kwargs) cache_key.update(updated) cache_key = cache_key.digest().encode('base64')[:22] return cache_key decorated_function.uncached = f decorated_function.cache_timeout = timeout decorated_function.make_cache_key = make_cache_key return decorated_function return memoize def delete_memoized(self, fname, *args, **kwargs): """ Deletes the specified functions caches, based by given parameters. If parameters are given, only the functions that were memoized with them will be erased. Otherwise all the versions of the caches will be deleted. Example:: @cache.memoize(50) def random_func(): return random.randrange(1, 50) @cache.memoize() def param_func(a, b): return a+b+random.randrange(1, 50) .. code-block:: pycon >>> random_func() 43 >>> random_func() 43 >>> cache.delete_memoized('random_func') >>> random_func() 16 >>> param_func(1, 2) 32 >>> param_func(1, 2) 32 >>> param_func(2, 2) 47 >>> cache.delete_memoized('param_func', 1, 2) >>> param_func(1, 2) 13 >>> param_func(2, 2) 47 :param fname: Name of the memoized function. :param \*args: A list of positional parameters used with memoized function. :param \**kwargs: A dict of named parameters used with memoized function. """ def deletes(item): # If no parameters given, delete all memoized versions of the function if not args and not kwargs: if item[0] == fname: self.cache.delete(item[1]) return True return False # Construct the cache key as in memoized function cache_key = hashlib.md5() try: updated = "{0}{1}{2}".format(fname, args, kwargs) except AttributeError: updated = "%s%s%s" % (fname, args, kwargs) cache_key.update(updated) cache_key = cache_key.digest().encode('base64')[:22] if item[1] == cache_key: self.cache.delete(item[1]) return True return False self._memoized[:] = [x for x in self._memoized if not deletes(x)]