Flask-Caching is an extension to Flask that adds caching support for various backends to any Flask application. Besides providing support for all werkzeug’s original caching backends through a uniformed API, it is also possible to develop your own caching backend by subclassing flask_caching.backends.base.BaseCache class.

Version support

Since 1.8, Flask-Caching supports only Python 3.5+.


Install the extension with one of the following commands:

$ easy_install Flask-Caching

or alternatively if you have pip installed:

$ pip install Flask-Caching

Set Up

Cache is managed through a Cache instance:

from flask import Flask
from flask_caching import Cache

config = {
    "DEBUG": True,          # some Flask specific configs
    "CACHE_TYPE": "simple", # Flask-Caching related configs
app = Flask(__name__)
# tell Flask to use the above defined config
cache = Cache(app)

You may also set up your Cache instance later at configuration time using init_app method:

cache = Cache(config={'CACHE_TYPE': 'simple'})

app = Flask(__name__)

You may also provide an alternate configuration dictionary, useful if there will be multiple Cache instances each with a different backend:

#: Method A: During instantiation of class
cache = Cache(config={'CACHE_TYPE': 'simple'})
#: Method B: During init_app call
cache.init_app(app, config={'CACHE_TYPE': 'simple'})

New in version 0.7.

Caching View Functions

To cache view functions you will use the cached() decorator. This decorator will use request.path by default for the cache_key:

def index():
    return render_template('index.html')

The cached decorator has another optional argument called unless. This argument accepts a callable that returns True or False. If unless returns True then it will bypass the caching mechanism entirely.


When using cached on a view, take care to put it between Flask’s @route decorator and your function definition. Example:

def index():
    return 'Cached for 50s'

If you reverse both decorator, what will be cached is the result of @route decorator, and not the result of your view function.

Caching Other Functions

Using the same @cached decorator you are able to cache the result of other non-view related functions. The only stipulation is that you replace the key_prefix, otherwise it will use the request.path cache_key. Keys control what should be fetched from the cache. If, for example, a key does not exist in the cache, a new key-value entry will be created in the cache. Otherwise the the value (i.e. the cached result) of the key will be returned:

@cache.cached(timeout=50, key_prefix='all_comments')
def get_all_comments():
    comments = do_serious_dbio()
    return [x.author for x in comments]

cached_comments = get_all_comments()


See memoize()

In memoization, the functions arguments are also included into the cache_key.


With functions that do not receive arguments, cached() and memoize() are effectively the same.

Memoize is also designed for methods, since it will take into account the identity. of the ‘self’ or ‘cls’ argument as part of the cache key.

The theory behind memoization is that if you have a function you need to call several times in one request, it would only be calculated the first time that function is called with those arguments. For example, an sqlalchemy object that determines if a user has a role. You might need to call this function many times during a single request. To keep from hitting the database every time this information is needed you might do something like the following:

class Person(db.Model):
    def has_membership(self, role_id):
        return Group.query.filter_by(user=self, role_id=role_id).count() >= 1


Using mutable objects (classes, etc) as part of the cache key can become tricky. It is suggested to not pass in an object instance into a memoized function. However, the memoize does perform a repr() on the passed in arguments so that if the object has a __repr__ function that returns a uniquely identifying string for that object, that will be used as part of the cache key.

For example, an sqlalchemy person object that returns the database id as part of the unique identifier:

class Person(db.Model):
    def __repr__(self):
        return "%s(%s)" % (self.__class__.__name__, self.id)

Deleting memoize cache

New in version 0.2.

You might need to delete the cache on a per-function basis. Using the above example, lets say you change the user’s permissions and assign them to a role, but now you need to re-calculate if they have certain memberships or not. You can do this with the delete_memoized() function:



If only the function name is given as parameter, all the memoized versions of it will be invalidated. However, you can delete specific cache by providing the same parameter values as when caching. In following example only the user-role cache is deleted:

user_has_membership('demo', 'admin')
user_has_membership('demo', 'user')

cache.delete_memoized(user_has_membership, 'demo', 'user')


If a classmethod is memoized, you must provide the class as the first *args argument.

class Foobar(object):
    def big_foo(cls, a, b):
        return a + b + random.randrange(0, 100000)

cache.delete_memoized(Foobar.big_foo, Foobar, 5, 2)

Caching Jinja2 Snippets


{% cache [timeout [,[key1, [key2, ...]]]] %}
{% endcache %}

By default, the value of “path to template file” + “block start line” is used as the cache key. Also, the key name can be set manually. Keys are concatenated together into a single string, that can be used to avoid the same block evaluating in different templates.

Set the timeout to None for no timeout, but with custom keys:

{% cache None, "key" %}
{% endcache %}

Set timeout to del to delete cached value:

{% cache 'del', key1 %}
{% endcache %}

If keys are provided, you may easily generate the template fragment key and delete it from outside of the template context:

from flask_caching import make_template_fragment_key
key = make_template_fragment_key("key1", vary_on=["key2", "key3"])

Considering we have render_form_field and render_submit macros:

{% cache 60*5 %}
    {% render_form_field(form.username) %}
    {% render_submit() %}
{% endcache %}

Clearing Cache

See clear().

Here’s an example script to empty your application’s cache:

from flask_caching import Cache

from yourapp import app, your_cache_config

cache = Cache()

def main():
    cache.init_app(app, config=your_cache_config)

    with app.app_context():

if __name__ == '__main__':


Some backend implementations do not support completely clearing the cache. Also, if you’re not using a key prefix, some implementations (e.g. Redis) will flush the whole database. Make sure you’re not storing any other data in your caching database.

Explicitly Caching Data

Data can be cached explicitly by using the proxy methods like Cache.set(), and Cache.get() directly. There are many other proxy methods available via the Cache class.

For example:

def html(foo=None):
    if foo is not None:
        cache.set("foo", foo)
    bar = cache.get("foo")
    return render_template_string(
        "<html><body>foo cache: {{bar}}</body></html>", bar=bar

Configuring Flask-Caching

The following configuration values exist for Flask-Caching:


Specifies which type of caching object to use. This is an import string that will be imported and instantiated. It is assumed that the import object is a function that will return a cache object that adheres to the cache API.

For flask_caching.backends.cache objects, you do not need to specify the entire import string, just one of the following names.

Built-in cache types:

  • null: NullCache (default)
  • simple: SimpleCache
  • filesystem: FileSystemCache
  • redis: RedisCache (redis required)
  • redissentinel: RedisSentinelCache (redis required)
  • rediscluster: RedisClusterCache (redis required)
  • uwsgi: UWSGICache (uwsgi required)
  • memcached: MemcachedCache (pylibmc or memcache required)
  • gaememcached: same as memcached (for backwards compatibility)
  • saslmemcached: SASLMemcachedCache (pylibmc required)
  • spreadsaslmemcached: SpreadSASLMemcachedCache (pylibmc required)
CACHE_NO_NULL_WARNING Silents the warning message when using cache type of ‘null’.
CACHE_ARGS Optional list to unpack and pass during the cache class instantiation.
CACHE_OPTIONS Optional dictionary to pass during the cache class instantiation.
CACHE_DEFAULT_TIMEOUT The default timeout that is used if no timeout is specified. Unit of time is seconds.
CACHE_IGNORE_ERRORS If set to any errors that occurred during the deletion process will be ignored. However, if it is set to False it will stop on the first error. This option is only relevant for the backends filesystem and simple. Defaults to False.
CACHE_THRESHOLD The maximum number of items the cache will store before it starts deleting some. Used only for SimpleCache and FileSystemCache
CACHE_KEY_PREFIX A prefix that is added before all keys. This makes it possible to use the same memcached server for different apps. Used only for RedisCache and MemcachedCache
CACHE_SOURCE_CHECK The default condition applied to function decorators which controls if the source code of the function should be included when forming the hash which is used as the cache key. This ensures that if the source code changes, the cached value will not be returned when the new function is called even if the arguments are the same. Defaults to False.
CACHE_UWSGI_NAME The name of the uwsgi caching instance to connect to, for example: mycache@localhost:3031, defaults to an empty string, which means uWSGI will cache in the local instance. If the cache is in the same instance as the werkzeug app, you only have to provide the name of the cache.
CACHE_MEMCACHED_SERVERS A list or a tuple of server addresses. Used only for MemcachedCache
CACHE_MEMCACHED_USERNAME Username for SASL authentication with memcached. Used only for SASLMemcachedCache
CACHE_MEMCACHED_PASSWORD Password for SASL authentication with memcached. Used only for SASLMemcachedCache
CACHE_REDIS_HOST A Redis server host. Used only for RedisCache.
CACHE_REDIS_PORT A Redis server port. Default is 6379. Used only for RedisCache.
CACHE_REDIS_PASSWORD A Redis password for server. Used only for RedisCache and RedisSentinelCache.
CACHE_REDIS_DB A Redis db (zero-based number index). Default is 0. Used only for RedisCache and RedisSentinelCache.
CACHE_REDIS_SENTINELS A list or a tuple of Redis sentinel addresses. Used only for RedisSentinelCache.
CACHE_REDIS_SENTINEL_MASTER The name of the master server in a sentinel configuration. Used only for RedisSentinelCache.
CACHE_REDIS_CLUSTER A string of comma-separated Redis cluster node addresses. e.g. host1:port1,host2:port2,host3:port3 . Used only for RedisClusterCache.
CACHE_DIR Directory to store cache. Used only for FileSystemCache.
CACHE_REDIS_URL URL to connect to Redis server. Example redis://user:password@localhost:6379/2. Supports protocols redis://, rediss:// (redis over TLS) and unix://. See more info about URL support [here](http://redis-py.readthedocs.io/en/latest/index.html#redis.ConnectionPool.from_url). Used only for RedisCache.

Built-in Cache Backends


Set CACHE_TYPE to null to use this type.

Cache that doesn’t cache



Set CACHE_TYPE to simple to use this type.

Uses a local python dictionary for caching. This is not really thread safe.

Relevant configuration values



Set CACHE_TYPE to filesystem to use this type.

Uses the filesystem to store cached values


There is a single valid entry in CACHE_OPTIONS: mode, which should be a 3 digit linux-style permissions octal mode.


Set CACHE_TYPE to redis to use this type.


Entries in CACHE_OPTIONS are passed to the redis client as **kwargs


Set CACHE_TYPE to redissentinel to use this type.


Entries in CACHE_OPTIONS are passed to the redis client as **kwargs


Set CACHE_TYPE to rediscluster to use this type.


Entries in CACHE_OPTIONS are passed to the redis client as **kwargs


Set CACHE_TYPE to memcached to use this type.

Uses a memcached server as a backend. Supports either pylibmc or memcache or google app engine memcache library.

Relevant configuration values



Flask-Caching does not pass additional configuration options to memcached backends. To add additional configuration to these caches, directly set the configuration options on the object after instantiation:

from flask_caching import Cache
cache = Cache()

# Can't configure the client yet...
cache.init_app(flask_app, {"CACHE_TYPE": "memcached"})

# Break convention and set options on the _client object
# directly. For pylibmc behaviors:
cache.cache._client.behaviors({"tcp_nodelay": True})

Alternatively, see Custom Cache Backends.


Set CACHE_TYPE to saslmemcached to use this type.

Uses a memcached server as a backend. Intended to be used with a SASL enabled connection to the memcached server. pylibmc is required and SASL must be supported by libmemcached.

Relevant configuration values



Since the SASL Memcached cache types do not use werkzeug’s original built-in cache infrastructure, they can be configured with CACHE_OPTIONS.

New in version 0.10.


Set CACHE_TYPE to spreadsaslmemcached to use this type.

Same as SASLMemcachedCache however, it has the ablity to spread value across multiple keys if it is bigger than the memcached treshold which by default is 1M. Uses pickle.

New in version 0.11.

Changed in version 1.1.0: Renamed spreadsaslmemcachedcache to spreadsaslmemcached for the sake of consistency.

Custom Cache Backends

You are able to easily add your own custom cache backends by exposing a function that can instantiate and return a cache object. CACHE_TYPE will be the import string to your custom function. It should expect to receive three arguments.

  • app
  • args
  • kwargs

Your custom cache object must also subclass the flask_caching.backends.cache.BaseCache class. Flask-Caching will make sure that threshold is already included in the kwargs options dictionary since it is common to all BaseCache classes.

An example Redis cache implementation:

#: the_app/custom.py
class RedisCache(BaseCache):
    def __init__(self, servers, default_timeout=500):

def redis(app, config, args, kwargs):
   return RedisCache(*args, **kwargs)

With this example, your CACHE_TYPE might be the_app.custom.redis

An example PylibMC cache implementation to change binary setting and provide username/password if SASL is enabled on the library:

#: the_app/custom.py
def pylibmccache(app, config, args, kwargs):
    return pylibmc.Client(servers=config['CACHE_MEMCACHED_SERVERS'],

With this example, your CACHE_TYPE might be the_app.custom.pylibmccache