""" flask_caching ~~~~~~~~~~~~~ Adds cache support to your application. :copyright: (c) 2010 by Thadeus Burgess. :license: BSD, see LICENSE for more details. """ import base64 import functools import hashlib import inspect import logging import uuid import warnings from collections import OrderedDict from typing import Any from typing import Callable from typing import Dict from typing import List from typing import Optional from typing import Tuple from typing import Union from flask import current_app from flask import Flask from flask import request from flask import Response from flask import url_for from werkzeug.utils import import_string from flask_caching.backends.base import BaseCache from flask_caching.backends.simplecache import SimpleCache from flask_caching.utils import function_namespace from flask_caching.utils import get_arg_default from flask_caching.utils import get_arg_names from flask_caching.utils import get_id from flask_caching.utils import make_template_fragment_key # noqa: F401 from flask_caching.utils import wants_args __version__ = "2.3.0" logger = logging.getLogger(__name__) SUPPORTED_HASH_FUNCTIONS = [ hashlib.sha1, hashlib.sha224, hashlib.sha256, hashlib.sha384, hashlib.sha512, hashlib.md5, ] class CachedResponse(Response): """ views wraped by @cached can return this (which inherits from flask.Response) to override the cache TTL dynamically """ timeout = None def __init__(self, response, timeout): self.__dict__ = response.__dict__ self.timeout = timeout class Cache: """This class is used to control the cache objects.""" def __init__( self, app: Optional[Flask] = None, with_jinja2_ext: bool = True, config=None, ) -> None: if not (config is None or isinstance(config, dict)): raise ValueError("`config` must be an instance of dict or None") self.with_jinja2_ext = with_jinja2_ext self.config = config self.source_check = None if app is not None: self.init_app(app, config) def init_app(self, app: Flask, config=None) -> None: """This is used to initialize cache with your app object""" if not (config is None or isinstance(config, dict)): raise ValueError("`config` must be an instance of dict or None") #: Ref PR #44. #: Do not set self.app in the case a single instance of the Cache #: object is being used for multiple app instances. #: Example use case would be Cache shipped as part of a blueprint #: or utility library. base_config = app.config.copy() if self.config: base_config.update(self.config) if config: base_config.update(config) config = base_config config.setdefault("CACHE_DEFAULT_TIMEOUT", 300) config.setdefault("CACHE_IGNORE_ERRORS", False) config.setdefault("CACHE_THRESHOLD", 500) config.setdefault("CACHE_KEY_PREFIX", "flask_cache_") config.setdefault("CACHE_MEMCACHED_SERVERS", None) config.setdefault("CACHE_DIR", None) config.setdefault("CACHE_OPTIONS", None) config.setdefault("CACHE_ARGS", []) config.setdefault("CACHE_TYPE", "null") config.setdefault("CACHE_NO_NULL_WARNING", False) config.setdefault("CACHE_SOURCE_CHECK", False) if config["CACHE_TYPE"] == "null" and not config["CACHE_NO_NULL_WARNING"]: warnings.warn( "Flask-Caching: CACHE_TYPE is set to null, " "caching is effectively disabled.", stacklevel=2, ) if ( config["CACHE_TYPE"] in ["filesystem", "FileSystemCache"] and config["CACHE_DIR"] is None ): warnings.warn( f"Flask-Caching: CACHE_TYPE is set to {config['CACHE_TYPE']} but no " "CACHE_DIR is set.", stacklevel=2, ) self.source_check = config["CACHE_SOURCE_CHECK"] if self.with_jinja2_ext: from .jinja2ext import CacheExtension, JINJA_CACHE_ATTR_NAME setattr(app.jinja_env, JINJA_CACHE_ATTR_NAME, self) app.jinja_env.add_extension(CacheExtension) self._set_cache(app, config) def _set_cache(self, app: Flask, config) -> None: import_me = config["CACHE_TYPE"] if "." not in import_me: plain_name_used = True import_me = "flask_caching.backends." + import_me else: plain_name_used = False cache_factory = import_string(import_me) cache_args = config["CACHE_ARGS"][:] cache_options = {"default_timeout": config["CACHE_DEFAULT_TIMEOUT"]} if isinstance(cache_factory, type) and issubclass(cache_factory, BaseCache): cache_factory = cache_factory.factory elif plain_name_used: warnings.warn( "Using the initialization functions in flask_caching.backend " "is deprecated. Use the a full path to backend classes " "directly.", category=DeprecationWarning, stacklevel=2, ) if config["CACHE_OPTIONS"]: cache_options.update(config["CACHE_OPTIONS"]) if not hasattr(app, "extensions"): app.extensions = {} app.extensions.setdefault("cache", {}) app.extensions["cache"][self] = cache_factory( app, config, cache_args, cache_options ) self.app = app def _call_fn(self, fn, *args, **kwargs): ensure_sync = getattr(self.app, "ensure_sync", None) if ensure_sync is not None: return ensure_sync(fn)(*args, **kwargs) return fn(*args, **kwargs) @property def cache(self) -> SimpleCache: app = current_app or self.app return app.extensions["cache"][self] def get(self, *args, **kwargs) -> Any: """Proxy function for internal cache object.""" return self.cache.get(*args, **kwargs) def has(self, *args, **kwargs) -> bool: """Proxy function for internal cache object.""" return self.cache.has(*args, **kwargs) def set(self, *args, **kwargs) -> Optional[bool]: """Proxy function for internal cache object.""" return self.cache.set(*args, **kwargs) def add(self, *args, **kwargs) -> bool: """Proxy function for internal cache object.""" return self.cache.add(*args, **kwargs) def delete(self, *args, **kwargs) -> bool: """Proxy function for internal cache object.""" return self.cache.delete(*args, **kwargs) def delete_many(self, *args, **kwargs) -> List[str]: """Proxy function for internal cache object.""" return self.cache.delete_many(*args, **kwargs) def clear(self) -> bool: """Proxy function for internal cache object.""" return self.cache.clear() def get_many(self, *args, **kwargs): """Proxy function for internal cache object.""" return self.cache.get_many(*args, **kwargs) def set_many(self, *args, **kwargs) -> List[Any]: """Proxy function for internal cache object.""" return self.cache.set_many(*args, **kwargs) def get_dict(self, *args, **kwargs) -> Dict[str, Any]: """Proxy function for internal cache object.""" return self.cache.get_dict(*args, **kwargs) def unlink(self, *args, **kwargs) -> List[str]: """Proxy function for internal cache object only support Redis """ unlink = getattr(self.cache, "unlink", None) if unlink is not None and callable(unlink): return unlink(*args, **kwargs) return self.delete_many(*args, **kwargs) def cached( self, timeout: Optional[int] = None, key_prefix: str = "view/%s", unless: Optional[Callable] = None, forced_update: Optional[Callable] = None, response_filter: Optional[Callable] = None, query_string: bool = False, hash_method: Callable = hashlib.md5, cache_none: bool = False, make_cache_key: Optional[Callable] = None, source_check: Optional[bool] = None, response_hit_indication: Optional[bool] = False, ) -> Callable: """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. 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 key_prefix: Default 'view/%(request.path)s'. Beginning key to . use for the cache key. `request.path` will be the actual request path, or in cases where the `make_cache_key`-function is called from other views it will be the expected URL for the view as generated by Flask's `url_for()`. .. 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. :param forced_update: Default None. If this callable is true, cache value will be updated regardless cache is expired or not. Useful for background renewal of cached functions. :param response_filter: Default None. If not None, the callable is invoked after the cached function evaluation, and is given one argument, the response content. If the callable returns False, the content will not be cached. Useful to prevent caching of code 500 responses. :param query_string: Default False. When True, the cache key used will be the result of hashing the ordered query string parameters. This avoids creating different caches for the same query just because the parameters were passed in a different order. See _make_cache_key_query_string() for more details. :param hash_method: Default hashlib.md5. The hash method used to generate the keys for cached results. :param cache_none: Default False. If set to True, add a key exists check when cache.get returns None. This will likely lead to wrongly returned None values in concurrent situations and is not recommended to use. :param make_cache_key: Default None. If set to a callable object, it will be called to generate the cache key :param source_check: Default None. If None will use the value set by CACHE_SOURCE_CHECK. If True, include the function's source code in the hash to avoid using cached values when the source code has changed and the input values remain the same. This ensures that the cache_key will be formed with the function's source code hash in addition to other parameters that may be included in the formation of the key. :param response_hit_indication: Default False. If True, it will add to response header field 'hit_cache' if used cache. """ def decorator(f): @functools.wraps(f) def decorated_function(*args, **kwargs): #: Bypass the cache entirely. if self._bypass_cache(unless, f, *args, **kwargs): return self._call_fn(f, *args, **kwargs) nonlocal source_check if source_check is None: source_check = self.source_check try: if make_cache_key is not None and callable(make_cache_key): cache_key = make_cache_key(*args, **kwargs) else: cache_key = decorated_function.make_cache_key( *args, use_request=True, **kwargs ) if ( callable(forced_update) and ( forced_update(*args, **kwargs) if wants_args(forced_update) else forced_update() ) is True ): rv = None found = False else: rv = self.cache.get(cache_key) found = True # If the value returned by cache.get() is None, it # might be because the key is not found in the cache # or because the cached value is actually None if rv is None: # If we're sure we don't need to cache None values # (cache_none=False), don't bother checking for # key existence, as it can lead to false positives # if a concurrent call already cached the # key between steps. This would cause us to # return None when we shouldn't if not cache_none: found = False else: found = self.cache.has(cache_key) except Exception: if self.app.debug: raise logger.exception("Exception possibly due to cache backend.") return self._call_fn(f, *args, **kwargs) if found and self.app.debug: logger.info(f"Cache used for key: {cache_key}") if response_hit_indication: def apply_caching(response): if found: response.headers["hit_cache"] = found return response self.app.after_request_funcs[None].append(apply_caching) if not found: rv = self._call_fn(f, *args, **kwargs) if inspect.isgenerator(rv): rv = [val for val in rv] if response_filter is None or response_filter(rv): cache_timeout = decorated_function.cache_timeout if isinstance(rv, CachedResponse): cache_timeout = rv.timeout or cache_timeout try: self.cache.set( cache_key, rv, timeout=cache_timeout, ) except Exception: if self.app.debug: raise logger.exception("Exception possibly due to cache backend.") return rv def default_make_cache_key(*args, **kwargs): # Convert non-keyword arguments (which is the way # `make_cache_key` expects them) to keyword arguments # (the way `url_for` expects them) argspec_args = inspect.getfullargspec(f).args for arg_name, arg in zip(argspec_args, args): kwargs[arg_name] = arg use_request = kwargs.pop("use_request", False) return _make_cache_key(args, kwargs, use_request=use_request) def _make_cache_key_query_string(): """Create consistent keys for query string arguments. Produces the same cache key regardless of argument order, e.g., both `?limit=10&offset=20` and `?offset=20&limit=10` will always produce the same exact cache key. If func is provided and is callable it will be used to hash the function's source code and include it in the cache key. This will only be done is source_check is True. """ # Create a tuple of (key, value) pairs, where the key is the # argument name and the value is its respective value. Order # this tuple by key. Doing this ensures the cache key created # is always the same for query string args whose keys/values # are the same, regardless of the order in which they are # provided. args_as_sorted_tuple = tuple( sorted(pair for pair in request.args.items(multi=True)) ) # ... now hash the sorted (key, value) tuple so it can be # used as a key for cache. Turn them into bytes so that the # hash function will accept them args_as_bytes = str(args_as_sorted_tuple).encode() cache_hash = hash_method(args_as_bytes) # Use the source code if source_check is True and update the # cache_hash before generating the hashing and using it in # cache_key if source_check and callable(f): func_source_code = inspect.getsource(f) cache_hash.update(func_source_code.encode("utf-8")) cache_hash = str(cache_hash.hexdigest()) cache_key = request.path + cache_hash return cache_key def _make_cache_key(args, kwargs, use_request) -> str: if query_string: return _make_cache_key_query_string() else: if callable(key_prefix): cache_key = key_prefix() elif "%s" in key_prefix: if use_request: cache_key = key_prefix % request.path else: cache_key = key_prefix % url_for(f.__name__, **kwargs) else: cache_key = key_prefix if source_check and callable(f): func_source_code = inspect.getsource(f) func_source_hash = hash_method(func_source_code.encode("utf-8")) func_source_hash = str(func_source_hash.hexdigest()) cache_key += func_source_hash return cache_key decorated_function.uncached = f decorated_function.cache_timeout = timeout decorated_function.make_cache_key = default_make_cache_key return decorated_function return decorator def _memvname(self, funcname: str) -> str: return funcname + "_memver" def _memoize_make_version_hash(self) -> str: return base64.b64encode(uuid.uuid4().bytes)[:6].decode("utf-8") def _memoize_version( self, f: Callable, args: Optional[Any] = None, kwargs=None, reset: bool = False, delete: bool = False, timeout: Optional[int] = None, forced_update: Optional[Union[bool, Callable]] = False, args_to_ignore: Optional[Any] = None, ) -> Union[Tuple[str, str], Tuple[str, None]]: """Updates the hash version associated with a memoized function or method. """ fname, instance_fname = function_namespace(f, args=args) version_key = self._memvname(fname) fetch_keys = [version_key] args_to_ignore = args_to_ignore or [] if "self" in args_to_ignore: instance_fname = None if instance_fname: instance_version_key = self._memvname(instance_fname) fetch_keys.append(instance_version_key) # Only delete the per-instance version key or per-function version # key but not both. if delete: self.cache.delete_many(fetch_keys[-1]) return fname, None version_data_list = list(self.cache.get_many(*fetch_keys)) dirty = False if ( callable(forced_update) and ( forced_update(*(args or ()), **(kwargs or {})) if wants_args(forced_update) else forced_update() ) is True ): # Mark key as dirty to update its TTL dirty = True if version_data_list[0] is None: version_data_list[0] = self._memoize_make_version_hash() dirty = True if instance_fname and version_data_list[1] is None: version_data_list[1] = self._memoize_make_version_hash() dirty = True # Only reset the per-instance version or the per-function version # but not both. if reset: fetch_keys = fetch_keys[-1:] version_data_list = [self._memoize_make_version_hash()] dirty = True if dirty: self.cache.set_many( dict(zip(fetch_keys, version_data_list)), timeout=timeout ) return fname, "".join(version_data_list) def _memoize_make_cache_key( self, make_name: Optional[Callable] = None, timeout: Optional[Callable] = None, forced_update: bool = False, hash_method: Callable = hashlib.md5, source_check: Optional[bool] = False, args_to_ignore: Optional[Any] = None, ) -> Callable: """Function used to create the cache_key for memoized functions.""" def make_cache_key(f, *args, **kwargs): _timeout = getattr(timeout, "cache_timeout", timeout) fname, version_data = self._memoize_version( f, args=args, kwargs=kwargs, timeout=_timeout, forced_update=forced_update, args_to_ignore=args_to_ignore, ) #: this should have to be after version_data, so that it #: does not break the delete_memoized functionality. altfname = make_name(fname) if callable(make_name) else fname if callable(f): keyargs, keykwargs = self._memoize_kwargs_to_args( f, *args, **kwargs, args_to_ignore=args_to_ignore ) else: keyargs, keykwargs = args, kwargs updated = f"{altfname}{keyargs}{keykwargs}" cache_key = hash_method() cache_key.update(updated.encode("utf-8")) # Use the source code if source_check is True and update the # cache_key with the function's source. if source_check and callable(f): func_source_code = inspect.getsource(f) cache_key.update(func_source_code.encode("utf-8")) cache_key = base64.b64encode(cache_key.digest())[:16] cache_key = cache_key.decode("utf-8") cache_key += version_data return cache_key return make_cache_key def _memoize_kwargs_to_args(self, f: Callable, *args, **kwargs) -> Any: #: Inspect the arguments to the function #: This allows the memoization to be the same #: whether the function was called with #: 1, b=2 is equivalent to a=1, b=2, etc. new_args = [] arg_num = 0 args_to_ignore = kwargs.pop("args_to_ignore", None) or [] # If the function uses VAR_KEYWORD type of parameters, # we need to pass these further kw_keys_remaining = [key for key in kwargs.keys() if key not in args_to_ignore] arg_names = get_arg_names(f) args_len = len(arg_names) for i in range(args_len): arg_default = get_arg_default(f, i) if arg_names[i] in args_to_ignore: arg = None arg_num += 1 elif i == 0 and arg_names[i] in ("self", "cls"): #: use the id func of the class instance #: this supports instance methods for #: the memoized functions, giving more #: flexibility to developers arg = get_id(args[0]) arg_num += 1 elif arg_names[i] in kwargs: arg = kwargs[arg_names[i]] kw_keys_remaining.pop(kw_keys_remaining.index(arg_names[i])) elif arg_num < len(args): arg = args[arg_num] arg_num += 1 elif arg_default: arg = arg_default arg_num += 1 else: arg = None arg_num += 1 #: Attempt to convert all arguments to a #: hash/id or a representation? #: Not sure if this is necessary, since #: using objects as keys gets tricky quickly. # if hasattr(arg, '__class__'): # try: # arg = hash(arg) # except: # arg = get_id(arg) #: Or what about a special __cacherepr__ function #: on an object, this allows objects to act normal #: upon inspection, yet they can define a representation #: that can be used to make the object unique in the #: cache key. Given that a case comes across that #: an object "must" be used as a cache key # if hasattr(arg, '__cacherepr__'): # arg = arg.__cacherepr__ new_args.append(arg) new_args.extend(args[len(arg_names) :]) return ( tuple(new_args), OrderedDict( sorted((k, v) for k, v in kwargs.items() if k in kw_keys_remaining) ), ) def _bypass_cache( self, unless: Optional[Callable], f: Callable, *args, **kwargs ) -> bool: """Determines whether or not to bypass the cache by calling unless(). Supports both unless() that takes in arguments and unless() that doesn't. """ bypass_cache = False if callable(unless): argspec = inspect.getfullargspec(unless) has_args = len(argspec.args) > 0 or argspec.varargs or argspec.varkw # If unless() takes args, pass them in. if has_args: if unless(f, *args, **kwargs) is True: bypass_cache = True elif unless() is True: bypass_cache = True return bypass_cache def memoize( self, timeout: Optional[int] = None, make_name: Optional[Callable] = None, unless: Optional[Callable] = None, forced_update: Optional[Callable] = None, response_filter: Optional[Callable] = None, hash_method: Callable = hashlib.md5, cache_none: bool = False, source_check: Optional[bool] = None, args_to_ignore: Optional[Any] = None, ) -> Callable: """Use this to cache the result of a function, taking its arguments into account in the cache key. Information on `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 unless this callable is true. This will bypass the caching entirely. :param forced_update: Default None. If this callable is true, cache value will be updated regardless cache is expired or not. Useful for background renewal of cached functions. :param response_filter: Default None. If not None, the callable is invoked after the cached funtion evaluation, and is given one arguement, the response content. If the callable returns False, the content will not be cached. Useful to prevent caching of code 500 responses. :param hash_method: Default hashlib.md5. The hash method used to generate the keys for cached results. :param cache_none: Default False. If set to True, add a key exists check when cache.get returns None. This will likely lead to wrongly returned None values in concurrent situations and is not recommended to use. :param source_check: Default None. If None will use the value set by CACHE_SOURCE_CHECK. If True, include the function's source code in the hash to avoid using cached values when the source code has changed and the input values remain the same. This ensures that the cache_key will be formed with the function's source code hash in addition to other parameters that may be included in the formation of the key. :param args_to_ignore: List of arguments that will be ignored while generating the cache key. Default to None. This means that those arguments may change without affecting the cache value that will be returned. .. versionadded:: 0.5 params ``make_name``, ``unless`` .. versionadded:: 1.10 params ``args_to_ignore`` """ def memoize(f): @functools.wraps(f) def decorated_function(*args, **kwargs): #: bypass cache if self._bypass_cache(unless, f, *args, **kwargs): return self._call_fn(f, *args, **kwargs) nonlocal source_check if source_check is None: source_check = self.source_check try: cache_key = decorated_function.make_cache_key(f, *args, **kwargs) if ( callable(forced_update) and ( forced_update(*args, **kwargs) if wants_args(forced_update) else forced_update() ) is True ): rv = None found = False else: rv = self.cache.get(cache_key) found = True # If the value returned by cache.get() is None, it # might be because the key is not found in the cache # or because the cached value is actually None if rv is None: # If we're sure we don't need to cache None values # (cache_none=False), don't bother checking for # key existence, as it can lead to false positives # if a concurrent call already cached the # key between steps. This would cause us to # return None when we shouldn't if not cache_none: found = False else: found = self.cache.has(cache_key) except Exception: if self.app.debug: raise logger.exception("Exception possibly due to cache backend.") return self._call_fn(f, *args, **kwargs) if not found: rv = self._call_fn(f, *args, **kwargs) if inspect.isgenerator(rv): rv = [val for val in rv] if response_filter is None or response_filter(rv): try: self.cache.set( cache_key, rv, timeout=decorated_function.cache_timeout, ) except Exception: if self.app.debug: raise logger.exception("Exception possibly due to cache backend.") return rv decorated_function.uncached = f decorated_function.cache_timeout = timeout decorated_function.make_cache_key = self._memoize_make_cache_key( make_name=make_name, timeout=decorated_function, forced_update=forced_update, hash_method=hash_method, source_check=source_check, args_to_ignore=args_to_ignore, ) decorated_function.delete_memoized = lambda: self.delete_memoized(f) return decorated_function return memoize def delete_memoized(self, f, *args, **kwargs) -> None: """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 versions of the caches will be forgotten. 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 Delete memoized is also smart about instance methods vs class methods. When passing a instancemethod, it will only clear the cache related to that instance of that object. (object uniqueness can be overridden by defining the __repr__ method, such as user id). When passing a classmethod, it will clear all caches related across all instances of that class. Example:: class Adder(object): @cache.memoize() def add(self, b): return b + random.random() .. code-block:: pycon >>> adder1 = Adder() >>> adder2 = Adder() >>> adder1.add(3) 3.23214234 >>> adder2.add(3) 3.60898509 >>> cache.delete_memoized(adder1.add) >>> adder1.add(3) 3.01348673 >>> adder2.add(3) 3.60898509 >>> cache.delete_memoized(Adder.add) >>> adder1.add(3) 3.53235667 >>> adder2.add(3) 3.72341788 :param fname: 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. .. note:: Flask-Caching uses inspect to order kwargs into positional args when the function is memoized. If you pass a function reference into ``fname``, Flask-Caching will be able to place the args/kwargs in the proper order, and delete the positional cache. However, if ``delete_memoized`` 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-Caching will not be able to compute the same cache key and delete all memoized versions of it. .. note:: Flask-Caching 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 hash is swapped, the old cached results would eventually be reclaimed by the caching backend. """ if not callable(f): raise TypeError( "Deleting messages by relative name is not supported, please " "use a function reference." ) if not (args or kwargs): self._memoize_version(f, reset=True) else: cache_key = f.make_cache_key(f.uncached, *args, **kwargs) self.cache.delete(cache_key) def delete_memoized_verhash(self, f: Callable, *args) -> None: """Delete the version hash associated with the function. .. warning:: Performing this operation could leave keys behind that have been created with this version hash. It is up to the application to make sure that all keys that may have been created with this version hash at least have timeouts so they will not sit orphaned in the cache backend. """ if not callable(f): raise TypeError( "Deleting messages by relative name is not supported, please" "use a function reference." ) self._memoize_version(f, delete=True)