Redis is an in-memory data store with on-disk persistence.

Use Cases#

Redis offers a high-performance cache that scales exceptionally well, making it an ideal choice for larger applications, especially those that make a large volume of concurrent requests.

Usage Example#

Initialize your session with a RedisCache instance:

>>> from requests_cache import CachedSession, RedisCache
>>> session = CachedSession(backend=RedisCache())

Or by alias:

>>> session = CachedSession(backend='redis')

Connection Options#

This backend accepts any keyword arguments for redis.client.Redis:

>>> backend = RedisCache(host='', port=6379)
>>> session = CachedSession('http_cache', backend=backend)

Or you can pass an existing Redis object:

>>> from redis import Redis

>>> connection = Redis(host='', port=6379)
>>> backend = RedisCache(connection=connection))
>>> session = CachedSession('http_cache', backend=backend)


Redis operates on data in memory, and by default also persists data to snapshots on disk. This is optimized for performance, with a minor risk of data loss, and is usually the best configuration for a cache. If you need different behavior, the frequency and type of persistence can be customized or disabled entirely. See Redis Persistence for details.


Redis natively supports TTL on a per-key basis, and can automatically remove expired responses from the cache. This will be set by by default, according to normal expiration settings. See Redis: EXPIRE docs for more details on internal TTL behavior.

If you intend to reuse expired responses, e.g. with Conditional Requests or stale_if_error, you can use the ttl_offset argument to add additional time before deletion (default: 1 hour). In other words, this makes backend expiration longer than cache expiration:

>>> backend = RedisCache(ttl_offset=3600)

Alternatively, you can disable TTL completely with the ttl argument:

>>> backend = RedisCache(ttl=False)


If you can’t easily set up your own Redis server, another option is redislite. It contains its own lightweight, embedded Redis database, and can be used as a drop-in replacement for redis-py. Usage example:

>>> from redislite import Redis
>>> from requests_cache import CachedSession, RedisCache

>>> backend = RedisCache(connection=Redis())
>>> session = CachedSession(backend=backend)