---
title: "O framework de “cache” do Django"
version: 5.1
locale: pt-br
source: https://docs.djangoproject.com/pt-br/5.1/topics/cache/
canonical: https://djangodocs.dev/pt-br/5.1/topics/cache/
---
# O framework de “cache” do Django

A fundamental trade-off in dynamic websites is, well, they’re dynamic. Each
time a user requests a page, the web server makes all sorts of calculations –
from database queries to template rendering to business logic – to create the
page that your site’s visitor sees. This is a lot more expensive, from a
processing-overhead perspective, than your standard
read-a-file-off-the-filesystem server arrangement.

For most web applications, this overhead isn’t a big deal. Most web
applications aren’t `washingtonpost.com` or `slashdot.org`; they’re small-
to medium-sized sites with so-so traffic. But for medium- to high-traffic
sites, it’s essential to cut as much overhead as possible.

É aqui que o “cache” entra.

To cache something is to save the result of an expensive calculation so that
you don’t have to perform the calculation next time. Here’s some pseudocode
explaining how this would work for a dynamically generated web page:

```text
given a URL, try finding that page in the cache
if the page is in the cache:
    return the cached page
else:
    generate the page
    save the generated page in the cache (for next time)
    return the generated page
```

Django vem com um sistema de cache robusto que lhe dexa salvar páginas dinâmicas para que não tenham que ser calculadas para cada requisição. Por conveniência, o Django oferece diferentes níveis de granulação do cache: Você pode cachear a saída de uma determinada “view” ,você pode cachear somente os pedaços que estão diciceis de produzir, ou você pode cachear seu site inteiro.

Django also works well with “downstream” caches, such as [Squid](http://www.squid-cache.org/) and browser-based caches. These are the types
of caches that you don’t directly control but to which you can provide hints
(via HTTP headers) about which parts of your site should be cached, and how.

> **See also**
>
> A [A filosofia de construção do frameowrk de cache](/pt-br/5.1/misc/design-philosophies/#cache-design-philosophy) explica um pouco das decisões de desenho do framework.

## Definindo o cache.

O sistema de cache requer um número pequeno de definições. Listando, você deve dizer onde seus dados de cache devem ficar – se na base de dados, no sistema de arquivos ou diretamente em memória. Essa é uma decisão importante que afeta a performance do seu cache; e sim, alguns tipode de cache são mais rápidos que outros.

Suas preferências de “cache” vão na definição [`CACHES`](/pt-br/5.1/ref/settings/#std-setting-CACHES) do seu arquivo de definições. Aqui uma explicação de todos os valores possíveis para o [`CACHES`](/pt-br/5.1/ref/settings/#std-setting-CACHES).

### Memcached

[Memcached](https://memcached.org/) is an entirely memory-based cache server, originally developed
to handle high loads at LiveJournal.com and subsequently open-sourced by
Danga Interactive. It is used by sites such as Facebook and Wikipedia to
reduce database access and dramatically increase site performance.

O memcached é executado como um serviço e aloca um montante de RAM. Tudo o que ele faz é adicionar, recuperar e deletar dados no cache. Todo o dado é armazenado diretamente em memória, então não há custo de acesso ao banco de dados ou ao sistema de arquivos.

After installing Memcached itself, you’ll need to install a Memcached
binding. There are several Python Memcached bindings available; the
two supported by Django are [pylibmc](https://pypi.org/project/pylibmc/) and [pymemcache](https://pypi.org/project/pymemcache/).

Para usar o Memcached com o Django:

- Set [`BACKEND`](/pt-br/5.1/ref/settings/#std-setting-CACHES-BACKEND) to
  `django.core.cache.backends.memcached.PyMemcacheCache` or
  `django.core.cache.backends.memcached.PyLibMCCache` (depending on your
  chosen memcached binding)
- Defina o [`LOCATION`](/pt-br/5.1/ref/settings/#std-setting-CACHES-LOCATION) para os valores de `ip:port`, onde `ip` é o endereço IP do serviço do Memcached e `port` é a porta na quam o Memcached está rodando, ou para um valor de `unix:path`, onde o `path` é o caminho para o arquivo de Socket Unix do Memcached.

In this example, Memcached is running on localhost (127.0.0.1) port 11211, using
the `pymemcache` binding:

```
CACHES = {
    "default": {
        "BACKEND": "django.core.cache.backends.memcached.PyMemcacheCache",
        "LOCATION": "127.0.0.1:11211",
    }
}
```

In this example, Memcached is available through a local Unix socket file
`/tmp/memcached.sock` using the `pymemcache` binding:

```
CACHES = {
    "default": {
        "BACKEND": "django.core.cache.backends.memcached.PyMemcacheCache",
        "LOCATION": "unix:/tmp/memcached.sock",
    }
}
```

One excellent feature of Memcached is its ability to share a cache over
multiple servers. This means you can run Memcached daemons on multiple
machines, and the program will treat the group of machines as a *single*
cache, without the need to duplicate cache values on each machine. To take
advantage of this feature, include all server addresses in
[`LOCATION`](/pt-br/5.1/ref/settings/#std-setting-CACHES-LOCATION), either as a semicolon or comma
delimited string, or as a list.

Neste exemplo, o cache é compartilhado em instâncias de Memcached rodando nos endereços IP  172.19.26.240 e 172.19.26.242, ambos na porta 11211:

```
CACHES = {
    "default": {
        "BACKEND": "django.core.cache.backends.memcached.PyMemcacheCache",
        "LOCATION": [
            "172.19.26.240:11211",
            "172.19.26.242:11211",
        ],
    }
}
```

No exemplo seguinte, o cache está compartilhado nas instâncias de Memcached rodando nos endereços IP 172.19.26.240 (porta 11211), 172.19.26.242 (porta 11212), e 172.19.26.244 (porta 11213):

```
CACHES = {
    "default": {
        "BACKEND": "django.core.cache.backends.memcached.PyMemcacheCache",
        "LOCATION": [
            "172.19.26.240:11211",
            "172.19.26.242:11212",
            "172.19.26.244:11213",
        ],
    }
}
```

By default, the `PyMemcacheCache` backend sets the following options (you can
override them in your [`OPTIONS`](/pt-br/5.1/ref/settings/#std-setting-CACHES-OPTIONS)):

```
"OPTIONS": {
    "allow_unicode_keys": True,
    "default_noreply": False,
    "serde": pymemcache.serde.pickle_serde,
}
```

Um último ponto sobre o Memcached é que o cache baseado em memória tem desvantagem: como o dado cacheado é armazenado em memória, os dados serão perdidos se seu servidor cair. Claramente, a memória não é feita para armazenar dados de maneira permanente, então não conte com cache baseado em memória como seu único armazenamento de dados. Sem dúvida, *nenhum* dos “backends” de cache do Django devem ser usados para armazenamento permanente – eles são todos feitos para solução de cache e não armazenamento – mas colocamos isso aqui porque o cache baseado em memória é temporário.

### Redis

[Redis](https://redis.io/) is an in-memory database that can be used for caching. To begin you’ll
need a Redis server running either locally or on a remote machine.

After setting up the Redis server, you’ll need to install Python bindings for
Redis. [redis-py](https://pypi.org/project/redis/) is the binding supported natively by Django.
Installing the [hiredis-py](https://pypi.org/project/hiredis/) package is also recommended.

To use Redis as your cache backend with Django:

- Set [`BACKEND`](/pt-br/5.1/ref/settings/#std-setting-CACHES-BACKEND) to
  `django.core.cache.backends.redis.RedisCache`.
- Set [`LOCATION`](/pt-br/5.1/ref/settings/#std-setting-CACHES-LOCATION) to the URL pointing to your Redis
  instance, using the appropriate scheme. See the `redis-py` docs for
  [details on the available schemes](https://redis-py.readthedocs.io/en/stable/connections.html#redis.connection.ConnectionPool.from_url).

For example, if Redis is running on localhost (127.0.0.1) port 6379:

```
CACHES = {
    "default": {
        "BACKEND": "django.core.cache.backends.redis.RedisCache",
        "LOCATION": "redis://127.0.0.1:6379",
    }
}
```

Often Redis servers are protected with authentication. In order to supply a
username and password, add them in the `LOCATION` along with the URL:

```
CACHES = {
    "default": {
        "BACKEND": "django.core.cache.backends.redis.RedisCache",
        "LOCATION": "redis://username:password@127.0.0.1:6379",
    }
}
```

If you have multiple Redis servers set up in the replication mode, you can
specify the servers either as a semicolon or comma delimited string, or as a
list. While using multiple servers, write operations are performed on the first
server (leader). Read operations are performed on the other servers (replicas)
chosen at random:

```
CACHES = {
    "default": {
        "BACKEND": "django.core.cache.backends.redis.RedisCache",
        "LOCATION": [
            "redis://127.0.0.1:6379",  # leader
            "redis://127.0.0.1:6378",  # read-replica 1
            "redis://127.0.0.1:6377",  # read-replica 2
        ],
    }
}
```

### Cache no Banco de Dados

O Django pode armazenar seus dados de cache em um banco de dados. Isso funciona melhor se você tem um servidor de banco de dados rápido e bem indexado.

Para usar uma tabela de banco de dados como seu “backend” de cache:

- Defina o [`BACKEND`](/pt-br/5.1/ref/settings/#std-setting-CACHES-BACKEND) como `django.core.cache.backends.db.DatabaseCache`
- Defina o [`LOCATION`](/pt-br/5.1/ref/settings/#std-setting-CACHES-LOCATION) indicando o `tablename`, o nome da tabela do banco de dados. Este nome pode ser o que você quiser, com tanto que seja um nome de tabela válido e que não esteja sendo usado em seu banco de dados.

Neste exemplo, o nome da tabela de cache é `my_cache_table`:

```
CACHES = {
    "default": {
        "BACKEND": "django.core.cache.backends.db.DatabaseCache",
        "LOCATION": "my_cache_table",
    }
}
```

Unlike other cache backends, the database cache does not support automatic
culling of expired entries at the database level. Instead, expired cache
entries are culled each time `add()`, `set()`, or `touch()` is called.

#### Criando a tabela de cache

Before using the database cache, you must create the cache table with this
command:

```shell
python manage.py createcachetable
```

Isso cria uma tabela no seu banco de dados que tem o formato correto que o sistema de cache do Django para cache em banco de dados precisa. O nome da tabela é pego da definição de [`LOCATION`](/pt-br/5.1/ref/settings/#std-setting-CACHES-LOCATION).

Se estiver usando caches em múltiplos banco de dados, o [`createcachetable`](/pt-br/5.1/ref/django-admin/#django-admin-createcachetable) cria uma tabela para cada cache.

Se estiver usando múltiplas bases de dados, o [`createcachetable`](/pt-br/5.1/ref/django-admin/#django-admin-createcachetable) verifica o método `allow_migrate()` dos seus roteadores de banco de dados (veja abaixo).

Assim como o  [`migrate`](/pt-br/5.1/ref/django-admin/#django-admin-migrate), [`createcachetable`](/pt-br/5.1/ref/django-admin/#django-admin-createcachetable) não irá tocar nenhuma tabela já existente. Somente criará as tabelas faltantes.

Para ver o SQL que deve se executado, ao invés de executá-lo, use a opção [`createcachetable --dry-run`](/pt-br/5.1/ref/django-admin/#cmdoption-createcachetable-dry-run).

#### Múltiplos bancos de dados

Se você está usando “cache” no banco de dados com múltiplos bancos de dados, você também precisará definir instruções de roteamento para sua tabela de “cache” no banco de dados. Para propósitos de roteamento, a tabela de “cache” no banco de dados aparece como um modelo chamado `CacheEntry`, em uma aplicação chamada `django_cache`. Este modelo não aparecerá no cache dos modelos, mas o detalhes do modelo podem ser usado para propósitos de roteamento.

Por exemplo, o roteador a seguir, direciona todas as operações de leitura de cache para `cache_replica`, e todas as operações de escrita para `cache_primary`.  A tabela de cache somente será sincronizada dentro de `cache_primary`:

```
class CacheRouter:
    """A router to control all database cache operations"""

    def db_for_read(self, model, **hints):
        "All cache read operations go to the replica"
        if model._meta.app_label == "django_cache":
            return "cache_replica"
        return None

    def db_for_write(self, model, **hints):
        "All cache write operations go to primary"
        if model._meta.app_label == "django_cache":
            return "cache_primary"
        return None

    def allow_migrate(self, db, app_label, model_name=None, **hints):
        "Only install the cache model on primary"
        if app_label == "django_cache":
            return db == "cache_primary"
        return None
```

Se você não especificar direções de rotas para o modelo de cache do banco de dados, o “backend” de cache usará o banco de dados padrão.

And if you don’t use the database cache backend, you don’t need to worry about
providing routing instructions for the database cache model.

### Cache no sistema de arquivos

O backend baseado em arquivo serializa e armazena cada valor do cache como um arquivo separado. Para usar este backend defina [`BACKEND`](/pt-br/5.1/ref/settings/#std-setting-CACHES-BACKEND) como `"django.core.cache.backends.filebased.FileBasedCache"` e `` LOCATION <CACHES-LOCATION>`para o diretório adequado. Por exemplo, para armazenar dados de cache em ` ``/var/tmp/django\_cache\`\`, use esta definição:

```
CACHES = {
    "default": {
        "BACKEND": "django.core.cache.backends.filebased.FileBasedCache",
        "LOCATION": "/var/tmp/django_cache",
    }
}
```

Se estiver no windows, coloque a letra do disco no começo do caminha, assim:

```
CACHES = {
    "default": {
        "BACKEND": "django.core.cache.backends.filebased.FileBasedCache",
        "LOCATION": "c:/foo/bar",
    }
}
```

O caminho do diretório deve ser absotluto – quer dizer, ele deve começar na raiz do seu sistema de arquivos. Não importa se você coloca uma barra no final da definição.

Make sure the directory pointed-to by this setting either exists and is
readable and writable, or that it can be created by the system user under which
your web server runs. Continuing the above example, if your server runs as the
user `apache`, make sure the directory `/var/tmp/django_cache` exists and
is readable and writable by the user `apache`, or that it can be created by
the user `apache`.

> **Warning**
>
> When the cache [`LOCATION`](/pt-br/5.1/ref/settings/#std-setting-CACHES-LOCATION) is contained within
> [`MEDIA_ROOT`](/pt-br/5.1/ref/settings/#std-setting-MEDIA_ROOT), [`STATIC_ROOT`](/pt-br/5.1/ref/settings/#std-setting-STATIC_ROOT), or
> [`STATICFILES_FINDERS`](/pt-br/5.1/ref/settings/#std-setting-STATICFILES_FINDERS), sensitive data may be exposed.
>
> An attacker who gains access to the cache file can not only falsify HTML
> content, which your site will trust, but also remotely execute arbitrary
> code, as the data is serialized using [`pickle`](https://docs.python.org/3/library/pickle.html#module-pickle).

> **Warning**
>
> Filesystem caching may become slow when storing a large number of files. If
> you run into this problem, consider using a different caching mechanism.
> You can also subclass
> [FileBasedCache](https://github.com/django/django/blob/stable/5.1.x/django/core/cache/backends/filebased.py) and
> improve the culling strategy.

### Cache em memória local

Este é o cache padrão se não houver outro especificado no arquivo de configurações. Se você quer a vantagem de velocidade do cache em memória mas não tem a capacidade de rodar o Memcached, considere o backend para cache em memória local. Este cache é um cache por processo (veja abaixo) e seguro entre “threads”. Para usá-lo, defina [`BACKEND`](/pt-br/5.1/ref/settings/#std-setting-CACHES-BACKEND) com `"django.core.cache.backends.locmem.LocMemCache"`. Por exemplo:

```
CACHES = {
    "default": {
        "BACKEND": "django.core.cache.backends.locmem.LocMemCache",
        "LOCATION": "unique-snowflake",
    }
}
```

O [`LOCATION`](/pt-br/5.1/ref/settings/#std-setting-CACHES-LOCATION) do cache é usado para identificar armazenamentos individuais em memória is. Se você tem somente um cache `locmem`, você pode omitir o [`LOCATION`](/pt-br/5.1/ref/settings/#std-setting-CACHES-LOCATION); no entanto, se você tiver mais de um cache em memória, você precisa definir um nome para pelo menos um deles de modo a mantê-los separados.

The cache uses a least-recently-used (LRU) culling strategy.

Note that each process will have its own private cache instance, which means no
cross-process caching is possible. This also means the local memory cache isn’t
particularly memory-efficient, so it’s probably not a good choice for
production environments. It’s nice for development.

### Cache fictício (para desenvolvimento)

Finalmente, o Django traz um cache “fictício” que não realiza o cache realmente – somente implementa a interface de cache sem fazer mais nada.

É útil se você tem um ambiente de produção que faz usa pesado de cache em vários lugares menos em um ambiente de desenvolvimento ou teste onde você não quer o cache e não quer alterar seu código para tal. Para ativar o cache fictício, defina a [`BACKEND`](/pt-br/5.1/ref/settings/#std-setting-CACHES-BACKEND)  como abaixo:

```
CACHES = {
    "default": {
        "BACKEND": "django.core.cache.backends.dummy.DummyCache",
    }
}
```

### Usando um esquema de cache personalizado

Embora o Django já tenha suporte para vários mecanismos de “cache”, as vezes você quer usar um mecanismo personalizado. Para usar um mecanismo de “cache” externo, use o caminho de importação do Python como no [`BACKEND`](/pt-br/5.1/ref/settings/#std-setting-CACHES-BACKEND) da definição do [`CACHES`](/pt-br/5.1/ref/settings/#std-setting-CACHES), como a seguir:

```
CACHES = {
    "default": {
        "BACKEND": "path.to.backend",
    }
}
```

If you’re building your own backend, you can use the standard cache backends
as reference implementations. You’ll find the code in the
[django/core/cache/backends/](https://github.com/django/django/blob/stable/5.1.x/django/core/cache/backends/) directory of the Django source.

Note: Without a really compelling reason, such as a host that doesn’t support
them, you should stick to the cache backends included with Django. They’ve
been well-tested and are well-documented.

### Argumentos do cache

Each cache backend can be given additional arguments to control caching
behavior. These arguments are provided as additional keys in the
[`CACHES`](/pt-br/5.1/ref/settings/#std-setting-CACHES) setting. Valid arguments are as follows:

- [`TIMEOUT`](/pt-br/5.1/ref/settings/#std-setting-CACHES-TIMEOUT): The default timeout, in
  seconds, to use for the cache. This argument defaults to `300` seconds (5 minutes).
  You can set `TIMEOUT` to `None` so that, by default, cache keys never
  expire. A value of `0` causes keys to immediately expire (effectively
  “don’t cache”).
- [`OPTIONS`](/pt-br/5.1/ref/settings/#std-setting-CACHES-OPTIONS): Any options that should be
  passed to the cache backend. The list of valid options will vary
  with each backend, and cache backends backed by a third-party library
  will pass their options directly to the underlying cache library.

  Cache backends that implement their own culling strategy (i.e.,
  the `locmem`, `filesystem` and `database` backends) will
  honor the following options:

  - `MAX_ENTRIES`: The maximum number of entries allowed in
    the cache before old values are deleted. This argument
    defaults to `300`.
  - `CULL_FREQUENCY`: The fraction of entries that are culled
    when `MAX_ENTRIES` is reached. The actual ratio is
    `1 / CULL_FREQUENCY`, so set `CULL_FREQUENCY` to `2` to
    cull half the entries when `MAX_ENTRIES` is reached. This argument
    should be an integer and defaults to `3`.

    A value of `0` for `CULL_FREQUENCY` means that the
    entire cache will be dumped when `MAX_ENTRIES` is reached.
    On some backends (`database` in particular) this makes culling *much*
    faster at the expense of more cache misses.

  The Memcached and Redis backends pass the contents of [`OPTIONS`](/pt-br/5.1/ref/settings/#std-setting-CACHES-OPTIONS) as keyword arguments to the client constructors, allowing
  for more advanced control of client behavior. For example usage, see below.
- [`KEY_PREFIX`](/pt-br/5.1/ref/settings/#std-setting-CACHES-KEY_PREFIX): A string that will be
  automatically included (prepended by default) to all cache keys
  used by the Django server.

  See the [cache documentation](#cache-key-prefixing) for
  more information.
- [`VERSION`](/pt-br/5.1/ref/settings/#std-setting-CACHES-VERSION): The default version number
  for cache keys generated by the Django server.

  See the [cache documentation](#cache-versioning) for more
  information.
- [`KEY_FUNCTION`](/pt-br/5.1/ref/settings/#std-setting-CACHES-KEY_FUNCTION)
  A string containing a dotted path to a function that defines how
  to compose a prefix, version and key into a final cache key.

  See the [cache documentation](#cache-key-transformation)
  for more information.

In this example, a filesystem backend is being configured with a timeout
of 60 seconds, and a maximum capacity of 1000 items:

```
CACHES = {
    "default": {
        "BACKEND": "django.core.cache.backends.filebased.FileBasedCache",
        "LOCATION": "/var/tmp/django_cache",
        "TIMEOUT": 60,
        "OPTIONS": {"MAX_ENTRIES": 1000},
    }
}
```

Here’s an example configuration for a `pylibmc` based backend that enables
the binary protocol, SASL authentication, and the `ketama` behavior mode:

```
CACHES = {
    "default": {
        "BACKEND": "django.core.cache.backends.memcached.PyLibMCCache",
        "LOCATION": "127.0.0.1:11211",
        "OPTIONS": {
            "binary": True,
            "username": "user",
            "password": "pass",
            "behaviors": {
                "ketama": True,
            },
        },
    }
}
```

Here’s an example configuration for a `pymemcache` based backend that enables
client pooling (which may improve performance by keeping clients connected),
treats memcache/network errors as cache misses, and sets the `TCP_NODELAY`
flag on the connection’s socket:

```
CACHES = {
    "default": {
        "BACKEND": "django.core.cache.backends.memcached.PyMemcacheCache",
        "LOCATION": "127.0.0.1:11211",
        "OPTIONS": {
            "no_delay": True,
            "ignore_exc": True,
            "max_pool_size": 4,
            "use_pooling": True,
        },
    }
}
```

Here’s an example configuration for a `redis` based backend that selects
database `10` (by default Redis ships with 16 logical databases), and sets a
custom [connection pool class](https://github.com/redis/redis-py#connection-pools) (`redis.ConnectionPool` is used by default):

```
CACHES = {
    "default": {
        "BACKEND": "django.core.cache.backends.redis.RedisCache",
        "LOCATION": "redis://127.0.0.1:6379",
        "OPTIONS": {
            "db": "10",
            "pool_class": "redis.BlockingConnectionPool",
        },
    }
}
```

## The per-site cache

Once the cache is set up, the simplest way to use caching is to cache your
entire site. You’ll need to add
`'django.middleware.cache.UpdateCacheMiddleware'` and
`'django.middleware.cache.FetchFromCacheMiddleware'` to your
[`MIDDLEWARE`](/pt-br/5.1/ref/settings/#std-setting-MIDDLEWARE) setting, as in this example:

```
MIDDLEWARE = [
    "django.middleware.cache.UpdateCacheMiddleware",
    "django.middleware.common.CommonMiddleware",
    "django.middleware.cache.FetchFromCacheMiddleware",
]
```

> **Note**
>
> No, that’s not a typo: the “update” middleware must be first in the list,
> and the “fetch” middleware must be last. The details are a bit obscure, but
> see [Order of MIDDLEWARE](#order-of-middleware) below if you’d like the full story.

Então, adicione as seguintes definições obrigatórias ao seu arquivo de definições Django:

- [`CACHE_MIDDLEWARE_ALIAS`](/pt-br/5.1/ref/settings/#std-setting-CACHE_MIDDLEWARE_ALIAS) – O apelido do cache para ser usado para armazenamento.
- [`CACHE_MIDDLEWARE_SECONDS`](/pt-br/5.1/ref/settings/#std-setting-CACHE_MIDDLEWARE_SECONDS) – The integer number of seconds each
  page should be cached.
- [`CACHE_MIDDLEWARE_KEY_PREFIX`](/pt-br/5.1/ref/settings/#std-setting-CACHE_MIDDLEWARE_KEY_PREFIX) – If the cache is shared across
  multiple sites using the same Django installation, set this to the name of
  the site, or some other string that is unique to this Django instance, to
  prevent key collisions. Use an empty string if you don’t care.

`FetchFromCacheMiddleware` caches GET and HEAD responses with status 200,
where the request and response headers allow. Responses to requests for the same
URL with different query parameters are considered to be unique pages and are
cached separately. This middleware expects that a HEAD request is answered with
the same response headers as the corresponding GET request; in which case it can
return a cached GET response for HEAD request.

Additionally, `UpdateCacheMiddleware` automatically sets a few headers in
each [`HttpResponse`](/pt-br/5.1/ref/request-response/#django.http.HttpResponse) which affect [downstream caches](#downstream-caches):

- Sets the `Expires` header to the current date/time plus the defined
  [`CACHE_MIDDLEWARE_SECONDS`](/pt-br/5.1/ref/settings/#std-setting-CACHE_MIDDLEWARE_SECONDS).
- Sets the `Cache-Control` header to give a max age for the page –
  again, from the [`CACHE_MIDDLEWARE_SECONDS`](/pt-br/5.1/ref/settings/#std-setting-CACHE_MIDDLEWARE_SECONDS) setting.

See [Middleware](/pt-br/5.1/topics/http/middleware/) for more on middleware.

If a view sets its own cache expiry time (i.e. it has a `max-age` section in
its `Cache-Control` header) then the page will be cached until the expiry
time, rather than [`CACHE_MIDDLEWARE_SECONDS`](/pt-br/5.1/ref/settings/#std-setting-CACHE_MIDDLEWARE_SECONDS). Using the decorators in
`django.views.decorators.cache` you can easily set a view’s expiry time
(using the [`cache_control()`](/pt-br/5.1/topics/http/decorators/#django.views.decorators.cache.cache_control) decorator) or
disable caching for a view (using the
[`never_cache()`](/pt-br/5.1/topics/http/decorators/#django.views.decorators.cache.never_cache) decorator). See the
[using other headers](#controlling-cache-using-other-headers) section for more on these decorators.

If [`USE_I18N`](/pt-br/5.1/ref/settings/#std-setting-USE_I18N) is set to `True` then the generated cache key will
include the name of the active [language](/pt-br/5.1/topics/i18n/#term-language-code) – see also
[How Django discovers language preference](/pt-br/5.1/topics/i18n/translation/#how-django-discovers-language-preference)). This allows you to easily
cache multilingual sites without having to create the cache key yourself.

Cache keys also include the [current time zone](/pt-br/5.1/topics/i18n/timezones/#default-current-time-zone) when [`USE_TZ`](/pt-br/5.1/ref/settings/#std-setting-USE_TZ) is set to `True`.

## The per-view cache

#### `django.views.decorators.cache.cache_page(timeout, * (Separador de parâmetros somente-nomeados (PEP 3102)), cache=None, key_prefix=None)`

A more granular way to use the caching framework is by caching the output of
individual views. `django.views.decorators.cache` defines a `cache_page`
decorator that will automatically cache the view’s response for you:

```
from django.views.decorators.cache import cache_page

@cache_page(60 * 15)
def my_view(request): ...
```

`cache_page` takes a single argument: the cache timeout, in seconds. In the
above example, the result of the `my_view()` view will be cached for 15
minutes. (Note that we’ve written it as `60 * 15` for the purpose of
readability. `60 * 15` will be evaluated to `900` – that is, 15 minutes
multiplied by 60 seconds per minute.)

The cache timeout set by `cache_page` takes precedence over the `max-age`
directive from the `Cache-Control` header.

The per-view cache, like the per-site cache, is keyed off of the URL. If
multiple URLs point at the same view, each URL will be cached separately.
Continuing the `my_view` example, if your URLconf looks like this:

```
urlpatterns = [
    path("foo/<int:code>/", my_view),
]
```

then requests to `/foo/1/` and `/foo/23/` will be cached separately, as
you may expect. But once a particular URL (e.g., `/foo/23/`) has been
requested, subsequent requests to that URL will use the cache.

`cache_page` can also take an optional keyword argument, `cache`,
which directs the decorator to use a specific cache (from your
[`CACHES`](/pt-br/5.1/ref/settings/#std-setting-CACHES) setting) when caching view results. By default, the
`default` cache will be used, but you can specify any cache you
want:

```
@cache_page(60 * 15, cache="special_cache")
def my_view(request): ...
```

You can also override the cache prefix on a per-view basis. `cache_page`
takes an optional keyword argument, `key_prefix`,
which works in the same way as the [`CACHE_MIDDLEWARE_KEY_PREFIX`](/pt-br/5.1/ref/settings/#std-setting-CACHE_MIDDLEWARE_KEY_PREFIX)
setting for the middleware.  It can be used like this:

```
@cache_page(60 * 15, key_prefix="site1")
def my_view(request): ...
```

The `key_prefix` and `cache` arguments may be specified together. The
`key_prefix` argument and the [`KEY_PREFIX`](/pt-br/5.1/ref/settings/#std-setting-CACHES-KEY_PREFIX)
specified under [`CACHES`](/pt-br/5.1/ref/settings/#std-setting-CACHES) will be concatenated.

Additionally, `cache_page` automatically sets `Cache-Control` and
`Expires` headers in the response which affect [downstream caches](#downstream-caches).

### Specifying per-view cache in the URLconf

The examples in the previous section have hard-coded the fact that the view is
cached, because `cache_page` alters the `my_view` function in place. This
approach couples your view to the cache system, which is not ideal for several
reasons. For instance, you might want to reuse the view functions on another,
cache-less site, or you might want to distribute the views to people who might
want to use them without being cached. The solution to these problems is to
specify the per-view cache in the URLconf rather than next to the view functions
themselves.

You can do so by wrapping the view function with `cache_page` when you refer
to it in the URLconf. Here’s the old URLconf from earlier:

```
urlpatterns = [
    path("foo/<int:code>/", my_view),
]
```

Aqui é a mesma coisa, com `my_view` empacotado em `cache_page`:

```
from django.views.decorators.cache import cache_page

urlpatterns = [
    path("foo/<int:code>/", cache_page(60 * 15)(my_view)),
]
```

## Template fragment caching

If you’re after even more control, you can also cache template fragments using
the `cache` template tag. To give your template access to this tag, put
`{% load cache %}` near the top of your template.

The `{% cache %}` template tag caches the contents of the block for a given
amount of time. It takes at least two arguments: the cache timeout, in seconds,
and the name to give the cache fragment. The fragment is cached forever if
timeout is `None`. The name will be taken as is, do not use a variable. For
example:

```html+django
{% load cache %}
{% cache 500 sidebar %}
    .. sidebar ..
{% endcache %}
```

Sometimes you might want to cache multiple copies of a fragment depending on
some dynamic data that appears inside the fragment. For example, you might want a
separate cached copy of the sidebar used in the previous example for every user
of your site. Do this by passing one or more additional arguments, which may be
variables with or without filters, to the `{% cache %}` template tag to
uniquely identify the cache fragment:

```html+django
{% load cache %}
{% cache 500 sidebar request.user.username %}
    .. sidebar for logged in user ..
{% endcache %}
```

If [`USE_I18N`](/pt-br/5.1/ref/settings/#std-setting-USE_I18N) is set to `True` the per-site middleware cache will
[respect the active language](#i18n-cache-key). For the `cache` template
tag you could use one of the
[translation-specific variables](/pt-br/5.1/topics/i18n/translation/#template-translation-vars) available in
templates to achieve the same result:

```html+django
{% load i18n %}
{% load cache %}

{% get_current_language as LANGUAGE_CODE %}

{% cache 600 welcome LANGUAGE_CODE %}
    {% translate "Welcome to example.com" %}
{% endcache %}
```

The cache timeout can be a template variable, as long as the template variable
resolves to an integer value. For example, if the template variable
`my_timeout` is set to the value `600`, then the following two examples are
equivalent:

```html+django
{% cache 600 sidebar %} ... {% endcache %}
{% cache my_timeout sidebar %} ... {% endcache %}
```

This feature is useful in avoiding repetition in templates. You can set the
timeout in a variable, in one place, and reuse that value.

By default, the cache tag will try to use the cache called “template\_fragments”.
If no such cache exists, it will fall back to using the default cache. You may
select an alternate cache backend to use with the `using` keyword argument,
which must be the last argument to the tag.

```html+django
{% cache 300 local-thing ...  using="localcache" %}
```

It is considered an error to specify a cache name that is not configured.

#### `django.core.cache.utils.make_template_fragment_key(fragment_name, vary_on=None)`

If you want to obtain the cache key used for a cached fragment, you can use
`make_template_fragment_key`. `fragment_name` is the same as second argument
to the `cache` template tag; `vary_on` is a list of all additional arguments
passed to the tag. This function can be useful for invalidating or overwriting
a cached item, for example:

```pycon
>>> from django.core.cache import cache
>>> from django.core.cache.utils import make_template_fragment_key
# cache key for {% cache 500 sidebar username %}
>>> key = make_template_fragment_key("sidebar", [username])
>>> cache.delete(key)  # invalidates cached template fragment
True
```

## The low-level cache API

Sometimes, caching an entire rendered page doesn’t gain you very much and is,
in fact, inconvenient overkill.

Perhaps, for instance, your site includes a view whose results depend on
several expensive queries, the results of which change at different intervals.
In this case, it would not be ideal to use the full-page caching that the
per-site or per-view cache strategies offer, because you wouldn’t want to
cache the entire result (since some of the data changes often), but you’d still
want to cache the results that rarely change.

For cases like this, Django exposes a low-level cache API. You can use this API
to store objects in the cache with any level of granularity you like.  You can
cache any Python object that can be pickled safely: strings, dictionaries,
lists of model objects, and so forth. (Most common Python objects can be
pickled; refer to the Python documentation for more information about
pickling.)

### Accessing the cache

#### `django.core.cache.caches`

You can access the caches configured in the [`CACHES`](/pt-br/5.1/ref/settings/#std-setting-CACHES) setting
through a dict-like object: `django.core.cache.caches`. Repeated
requests for the same alias in the same thread will return the same
object.

```pycon
>>> from django.core.cache import caches
>>> cache1 = caches["myalias"]
>>> cache2 = caches["myalias"]
>>> cache1 is cache2
True
```

If the named key does not exist, `InvalidCacheBackendError` will be
raised.

To provide thread-safety, a different instance of the cache backend will
be returned for each thread.

#### `django.core.cache.cache`

As a shortcut, the default cache is available as
`django.core.cache.cache`:

```pycon
>>> from django.core.cache import cache
```

This object is equivalent to `caches['default']`.

### Basic usage

The basic interface is:

#### `cache.set(key, value, timeout=DEFAULT_TIMEOUT, version=None)`

```pycon
>>> cache.set("my_key", "hello, world!", 30)
```

#### `cache.get(key, default=None, version=None)`

```pycon
>>> cache.get("my_key")
'hello, world!'
```

`key` should be a `str`, and `value` can be any picklable Python object.

The `timeout` argument is optional and defaults to the `timeout` argument
of the appropriate backend in the [`CACHES`](/pt-br/5.1/ref/settings/#std-setting-CACHES) setting (explained above).
It’s the number of seconds the value should be stored in the cache. Passing in
`None` for `timeout` will cache the value forever. A `timeout` of `0`
won’t cache the value.

If the object doesn’t exist in the cache, `cache.get()` returns `None`:

```pycon
>>> # Wait 30 seconds for 'my_key' to expire...
>>> cache.get("my_key")
None
```

If you need to determine whether the object exists in the cache and you have
stored a literal value `None`, use a sentinel object as the default:

```pycon
>>> sentinel = object()
>>> cache.get("my_key", sentinel) is sentinel
False
>>> # Wait 30 seconds for 'my_key' to expire...
>>> cache.get("my_key", sentinel) is sentinel
True
```

`cache.get()` can take a `default` argument. This specifies which value to
return if the object doesn’t exist in the cache:

```pycon
>>> cache.get("my_key", "has expired")
'has expired'
```

#### `cache.add(key, value, timeout=DEFAULT_TIMEOUT, version=None)`

To add a key only if it doesn’t already exist, use the `add()` method.
It takes the same parameters as `set()`, but it will not attempt to
update the cache if the key specified is already present:

```pycon
>>> cache.set("add_key", "Initial value")
>>> cache.add("add_key", "New value")
>>> cache.get("add_key")
'Initial value'
```

If you need to know whether `add()` stored a value in the cache, you can
check the return value. It will return `True` if the value was stored,
`False` otherwise.

#### `cache.get_or_set(key, default, timeout=DEFAULT_TIMEOUT, version=None)`

If you want to get a key’s value or set a value if the key isn’t in the cache,
there is the `get_or_set()` method. It takes the same parameters as `get()`
but the default is set as the new cache value for that key, rather than
returned:

```pycon
>>> cache.get("my_new_key")  # returns None
>>> cache.get_or_set("my_new_key", "my new value", 100)
'my new value'
```

You can also pass any callable as a *default* value:

```pycon
>>> import datetime
>>> cache.get_or_set("some-timestamp-key", datetime.datetime.now)
datetime.datetime(2014, 12, 11, 0, 15, 49, 457920)
```

#### `cache.get_many(keys, version=None)`

There’s also a `get_many()` interface that only hits the cache once.
`get_many()` returns a dictionary with all the keys you asked for that
actually exist in the cache (and haven’t expired):

```pycon
>>> cache.set("a", 1)
>>> cache.set("b", 2)
>>> cache.set("c", 3)
>>> cache.get_many(["a", "b", "c"])
{'a': 1, 'b': 2, 'c': 3}
```

#### `cache.set_many(dict, timeout)`

To set multiple values more efficiently, use `set_many()` to pass a dictionary
of key-value pairs:

```pycon
>>> cache.set_many({"a": 1, "b": 2, "c": 3})
>>> cache.get_many(["a", "b", "c"])
{'a': 1, 'b': 2, 'c': 3}
```

Like `cache.set()`, `set_many()` takes an optional `timeout` parameter.

On supported backends (memcached), `set_many()` returns a list of keys that
failed to be inserted.

#### `cache.delete(key, version=None)`

You can delete keys explicitly with `delete()` to clear the cache for a
particular object:

```pycon
>>> cache.delete("a")
True
```

`delete()` returns `True` if the key was successfully deleted, `False`
otherwise.

#### `cache.delete_many(keys, version=None)`

If you want to clear a bunch of keys at once, `delete_many()` can take a list
of keys to be cleared:

```pycon
>>> cache.delete_many(["a", "b", "c"])
```

#### `cache.clear()`

Finally, if you want to delete all the keys in the cache, use
`cache.clear()`.  Be careful with this; `clear()` will remove *everything*
from the cache, not just the keys set by your application:

```pycon
>>> cache.clear()
```

#### `cache.touch(key, timeout=DEFAULT_TIMEOUT, version=None)`

`cache.touch()` sets a new expiration for a key. For example, to update a key
to expire 10 seconds from now:

```pycon
>>> cache.touch("a", 10)
True
```

Like other methods, the `timeout` argument is optional and defaults to the
`TIMEOUT` option of the appropriate backend in the [`CACHES`](/pt-br/5.1/ref/settings/#std-setting-CACHES) setting.

`touch()` returns `True` if the key was successfully touched, `False`
otherwise.

#### `cache.incr(key, delta=1, version=None)`

#### `cache.decr(key, delta=1, version=None)`

You can also increment or decrement a key that already exists using the
`incr()` or `decr()` methods, respectively. By default, the existing cache
value will be incremented or decremented by 1. Other increment/decrement values
can be specified by providing an argument to the increment/decrement call. A
ValueError will be raised if you attempt to increment or decrement a
nonexistent cache key:

```pycon
>>> cache.set("num", 1)
>>> cache.incr("num")
2
>>> cache.incr("num", 10)
12
>>> cache.decr("num")
11
>>> cache.decr("num", 5)
6
```

> **Note**
>
> `incr()`/`decr()` methods are not guaranteed to be atomic. On those
> backends that support atomic increment/decrement (most notably, the
> memcached backend), increment and decrement operations will be atomic.
> However, if the backend doesn’t natively provide an increment/decrement
> operation, it will be implemented using a two-step retrieve/update.

#### `cache.close()`

You can close the connection to your cache with `close()` if implemented by
the cache backend.

```pycon
>>> cache.close()
```

> **Note**
>
> For caches that don’t implement `close` methods it is a no-op.

> **Note**
>
> The async variants of base methods are prefixed with `a`, e.g.
> `cache.aadd()` or `cache.adelete_many()`. See [Asynchronous support](#id16)
> for more details.

### Cache key prefixing

If you are sharing a cache instance between servers, or between your
production and development environments, it’s possible for data cached
by one server to be used by another server. If the format of cached
data is different between servers, this can lead to some very hard to
diagnose problems.

To prevent this, Django provides the ability to prefix all cache keys
used by a server. When a particular cache key is saved or retrieved,
Django will automatically prefix the cache key with the value of the
[`KEY_PREFIX`](/pt-br/5.1/ref/settings/#std-setting-CACHES-KEY_PREFIX) cache setting.

By ensuring each Django instance has a different
[`KEY_PREFIX`](/pt-br/5.1/ref/settings/#std-setting-CACHES-KEY_PREFIX), you can ensure that there will be no
collisions in cache values.

### Cache versioning

When you change running code that uses cached values, you may need to
purge any existing cached values. The easiest way to do this is to
flush the entire cache, but this can lead to the loss of cache values
that are still valid and useful.

Django provides a better way to target individual cache values.
Django’s cache framework has a system-wide version identifier,
specified using the [`VERSION`](/pt-br/5.1/ref/settings/#std-setting-CACHES-VERSION) cache setting.
The value of this setting is automatically combined with the cache
prefix and the user-provided cache key to obtain the final cache key.

By default, any key request will automatically include the site
default cache key version. However, the primitive cache functions all
include a `version` argument, so you can specify a particular cache
key version to set or get. For example:

```pycon
>>> # Set version 2 of a cache key
>>> cache.set("my_key", "hello world!", version=2)
>>> # Get the default version (assuming version=1)
>>> cache.get("my_key")
None
>>> # Get version 2 of the same key
>>> cache.get("my_key", version=2)
'hello world!'
```

The version of a specific key can be incremented and decremented using
the `incr_version()` and `decr_version()` methods. This
enables specific keys to be bumped to a new version, leaving other
keys unaffected. Continuing our previous example:

```pycon
>>> # Increment the version of 'my_key'
>>> cache.incr_version("my_key")
>>> # The default version still isn't available
>>> cache.get("my_key")
None
# Version 2 isn't available, either
>>> cache.get("my_key", version=2)
None
>>> # But version 3 *is* available
>>> cache.get("my_key", version=3)
'hello world!'
```

### Cache key transformation

As described in the previous two sections, the cache key provided by a
user is not used verbatim – it is combined with the cache prefix and
key version to provide a final cache key. By default, the three parts
are joined using colons to produce a final string:

```
def make_key(key, key_prefix, version):
    return "%s:%s:%s" % (key_prefix, version, key)
```

If you want to combine the parts in different ways, or apply other
processing to the final key (e.g., taking a hash digest of the key
parts), you can provide a custom key function.

The [`KEY_FUNCTION`](/pt-br/5.1/ref/settings/#std-setting-CACHES-KEY_FUNCTION) cache setting
specifies a dotted-path to a function matching the prototype of
`make_key()` above. If provided, this custom key function will
be used instead of the default key combining function.

### Cache key warnings

Memcached, the most commonly-used production cache backend, does not allow
cache keys longer than 250 characters or containing whitespace or control
characters, and using such keys will cause an exception. To encourage
cache-portable code and minimize unpleasant surprises, the other built-in cache
backends issue a warning (`django.core.cache.backends.base.CacheKeyWarning`)
if a key is used that would cause an error on memcached.

If you are using a production backend that can accept a wider range of keys (a
custom backend, or one of the non-memcached built-in backends), and want to use
this wider range without warnings, you can silence `CacheKeyWarning` with
this code in the `management` module of one of your
[`INSTALLED_APPS`](/pt-br/5.1/ref/settings/#std-setting-INSTALLED_APPS):

```
import warnings

from django.core.cache import CacheKeyWarning

warnings.simplefilter("ignore", CacheKeyWarning)
```

If you want to instead provide custom key validation logic for one of the
built-in backends, you can subclass it, override just the `validate_key`
method, and follow the instructions for [using a custom cache backend](#id9). For
instance, to do this for the `locmem` backend, put this code in a module:

```
from django.core.cache.backends.locmem import LocMemCache

class CustomLocMemCache(LocMemCache):
    def validate_key(self, key):
        """Custom validation, raising exceptions or warnings as needed."""
        ...
```

…and use the dotted Python path to this class in the
[`BACKEND`](/pt-br/5.1/ref/settings/#std-setting-CACHES-BACKEND) portion of your [`CACHES`](/pt-br/5.1/ref/settings/#std-setting-CACHES) setting.

## Suporte assíncrono

Django has developing support for asynchronous cache backends, but does not
yet support asynchronous caching. It will be coming in a future release.

`django.core.cache.backends.base.BaseCache` has async variants of [all
base methods](#cache-basic-interface). By convention, the asynchronous versions
of all methods are prefixed with `a`. By default, the arguments for both
variants are the same:

```pycon
>>> await cache.aset("num", 1)
>>> await cache.ahas_key("num")
True
```

## Downstream caches

So far, this document has focused on caching your *own* data. But another type
of caching is relevant to web development, too: caching performed by
“downstream” caches. These are systems that cache pages for users even before
the request reaches your website.

Here are a few examples of downstream caches:

- When using HTTP, your ISP (Internet Service Provider) may cache
  certain pages, so if you requested a page from `http://example.com/`, your
  ISP would send you the page without having to access example.com directly.
  The maintainers of example.com have no knowledge of this caching; the ISP
  sits between example.com and your web browser, handling all of the caching
  transparently. Such caching is not possible under HTTPS as it would
  constitute a man-in-the-middle attack.
- Your Django website may sit behind a *proxy cache*, such as Squid Web
  Proxy Cache (<http://www.squid-cache.org/>), that caches pages for
  performance. In this case, each request first would be handled by the
  proxy, and it would be passed to your application only if needed.
- Your web browser caches pages, too. If a web page sends out the
  appropriate headers, your browser will use the local cached copy for
  subsequent requests to that page, without even contacting the web page
  again to see whether it has changed.

Downstream caching is a nice efficiency boost, but there’s a danger to it:
Many web pages’ contents differ based on authentication and a host of other
variables, and cache systems that blindly save pages based purely on URLs could
expose incorrect or sensitive data to subsequent visitors to those pages.

For example, if you operate a web email system, then the contents of the
“inbox” page depend on which user is logged in. If an ISP blindly cached your
site, then the first user who logged in through that ISP would have their
user-specific inbox page cached for subsequent visitors to the site.  That’s
not cool.

Fortunately, HTTP provides a solution to this problem. A number of HTTP headers
exist to instruct downstream caches to differ their cache contents depending on
designated variables, and to tell caching mechanisms not to cache particular
pages. We’ll look at some of these headers in the sections that follow.

## Using `Vary` headers

The `Vary` header defines which request headers a cache
mechanism should take into account when building its cache key. For example, if
the contents of a web page depend on a user’s language preference, the page is
said to “vary on language.”

By default, Django’s cache system creates its cache keys using the requested
fully-qualified URL – e.g.,
`"https://www.example.com/stories/2005/?order_by=author"`. This means every
request to that URL will use the same cached version, regardless of user-agent
differences such as cookies or language preferences. However, if this page
produces different content based on some difference in request headers – such
as a cookie, or a language, or a user-agent – you’ll need to use the `Vary`
header to tell caching mechanisms that the page output depends on those things.

To do this in Django, use the convenient
[`django.views.decorators.vary.vary_on_headers()`](/pt-br/5.1/topics/http/decorators/#django.views.decorators.vary.vary_on_headers) view decorator, like so:

```
from django.views.decorators.vary import vary_on_headers

@vary_on_headers("User-Agent")
def my_view(request): ...
```

In this case, a caching mechanism (such as Django’s own cache middleware) will
cache a separate version of the page for each unique user-agent.

The advantage to using the `vary_on_headers` decorator rather than manually
setting the `Vary` header (using something like `response.headers['Vary'] =
'user-agent'`) is that the decorator *adds* to the `Vary` header (which may
already exist), rather than setting it from scratch and potentially overriding
anything that was already in there.

You can pass multiple headers to `vary_on_headers()`:

```
@vary_on_headers("User-Agent", "Cookie")
def my_view(request): ...
```

This tells downstream caches to vary on *both*, which means each combination of
user-agent and cookie will get its own cache value. For example, a request with
the user-agent `Mozilla` and the cookie value `foo=bar` will be considered
different from a request with the user-agent `Mozilla` and the cookie value
`foo=ham`.

Because varying on cookie is so common, there’s a
[`django.views.decorators.vary.vary_on_cookie()`](/pt-br/5.1/topics/http/decorators/#django.views.decorators.vary.vary_on_cookie) decorator. These two views
are equivalent:

```
@vary_on_cookie
def my_view(request): ...

@vary_on_headers("Cookie")
def my_view(request): ...
```

The headers you pass to `vary_on_headers` are not case sensitive;
`"User-Agent"` is the same thing as `"user-agent"`.

You can also use a helper function, [`django.utils.cache.patch_vary_headers()`](/pt-br/5.1/ref/utils/#django.utils.cache.patch_vary_headers),
directly. This function sets, or adds to, the `Vary header`. For example:

```
from django.shortcuts import render
from django.utils.cache import patch_vary_headers

def my_view(request):
    ...
    response = render(request, "template_name", context)
    patch_vary_headers(response, ["Cookie"])
    return response
```

`patch_vary_headers` takes an [`HttpResponse`](/pt-br/5.1/ref/request-response/#django.http.HttpResponse) instance as
its first argument and a list/tuple of case-insensitive header names as its
second argument.

For more on Vary headers, see the [**official Vary spec**](https://datatracker.ietf.org/doc/html/rfc9110.html#section-12.5.5).

## Controlling cache: Using other headers

Other problems with caching are the privacy of data and the question of where
data should be stored in a cascade of caches.

A user usually faces two kinds of caches: their own browser cache (a private
cache) and their provider’s cache (a public cache). A public cache is used by
multiple users and controlled by someone else. This poses problems with
sensitive data–you don’t want, say, your bank account number stored in a
public cache. So web applications need a way to tell caches which data is
private and which is public.

The solution is to indicate a page’s cache should be “private.” To do this in
Django, use the [`cache_control()`](/pt-br/5.1/topics/http/decorators/#django.views.decorators.cache.cache_control) view
decorator. Example:

```
from django.views.decorators.cache import cache_control

@cache_control(private=True)
def my_view(request): ...
```

This decorator takes care of sending out the appropriate HTTP header behind the
scenes.

Note that the cache control settings “private” and “public” are mutually
exclusive. The decorator ensures that the “public” directive is removed if
“private” should be set (and vice versa). An example use of the two directives
would be a blog site that offers both private and public entries. Public
entries may be cached on any shared cache. The following code uses
[`patch_cache_control()`](/pt-br/5.1/ref/utils/#django.utils.cache.patch_cache_control), the manual way to modify the
cache control header (it is internally called by the
[`cache_control()`](/pt-br/5.1/topics/http/decorators/#django.views.decorators.cache.cache_control) decorator):

```
from django.views.decorators.cache import patch_cache_control
from django.views.decorators.vary import vary_on_cookie

@vary_on_cookie
def list_blog_entries_view(request):
    if request.user.is_anonymous:
        response = render_only_public_entries()
        patch_cache_control(response, public=True)
    else:
        response = render_private_and_public_entries(request.user)
        patch_cache_control(response, private=True)

    return response
```

You can control downstream caches in other ways as well (see [**RFC 9111**](https://datatracker.ietf.org/doc/html/rfc9111.html) for
details on HTTP caching). For example, even if you don’t use Django’s
server-side cache framework, you can still tell clients to cache a view for a
certain amount of time with the [**max-age**](https://datatracker.ietf.org/doc/html/rfc9111.html#section-5.2.2.1)
directive:

```
from django.views.decorators.cache import cache_control

@cache_control(max_age=3600)
def my_view(request): ...
```

(If you *do* use the caching middleware, it already sets the `max-age` with
the value of the [`CACHE_MIDDLEWARE_SECONDS`](/pt-br/5.1/ref/settings/#std-setting-CACHE_MIDDLEWARE_SECONDS) setting. In that case,
the custom `max_age` from the
[`cache_control()`](/pt-br/5.1/topics/http/decorators/#django.views.decorators.cache.cache_control) decorator will take
precedence, and the header values will be merged correctly.)

Any valid `Cache-Control` response directive is valid in `cache_control()`.
Here are some more examples:

- `no_transform=True`
- `must_revalidate=True`
- `stale_while_revalidate=num_seconds`
- `no_cache=True`

The full list of known directives can be found in the [IANA registry](https://www.iana.org/assignments/http-cache-directives/http-cache-directives.xhtml)
(note that not all of them apply to responses).

If you want to use headers to disable caching altogether,
[`never_cache()`](/pt-br/5.1/topics/http/decorators/#django.views.decorators.cache.never_cache) is a view decorator that
adds headers to ensure the response won’t be cached by browsers or other
caches. Example:

```
from django.views.decorators.cache import never_cache

@never_cache
def myview(request): ...
```

## Order of `MIDDLEWARE`

If you use caching middleware, it’s important to put each half in the right
place within the [`MIDDLEWARE`](/pt-br/5.1/ref/settings/#std-setting-MIDDLEWARE) setting. That’s because the cache
middleware needs to know which headers by which to vary the cache storage.
Middleware always adds something to the `Vary` response header when it can.

`UpdateCacheMiddleware` runs during the response phase, where middleware is
run in reverse order, so an item at the top of the list runs *last* during the
response phase. Thus, you need to make sure that `UpdateCacheMiddleware`
appears *before* any other middleware that might add something to the `Vary`
header. The following middleware modules do so:

- `SessionMiddleware` adiciona `Cookie`
- `GZipMiddleware` adds `Accept-Encoding`
- `LocaleMiddleware` adds `Accept-Language`

`FetchFromCacheMiddleware`, on the other hand, runs during the request phase,
where middleware is applied first-to-last, so an item at the top of the list
runs *first* during the request phase. The `FetchFromCacheMiddleware` also
needs to run after other middleware updates the `Vary` header, so
`FetchFromCacheMiddleware` must be *after* any item that does so.