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The Python interface to the Redis key-value store.
Installation | Usage | Advanced Topics | Contributing
**Note: ** redis-py 5.0 will be the last version of redis-py to support Python 3.7, as it has reached end of life. redis-py 5.1 will support Python 3.8+.
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Start a redis via docker:
docker run -p 6379:6379 -it redis/redis-stack:latest
To install redis-py, simply:
$ pip install redis
For faster performance, install redis with hiredis support, this provides a compiled response parser, and for most cases requires zero code changes. By default, if hiredis >= 1.0 is available, redis-py will attempt to use it for response parsing.
$ pip install "redis[hiredis]"
Looking for a high-level library to handle object mapping? See redis-om-python!
The most recent version of this library supports redis version 5.0, 6.0, 6.2, 7.0, 7.2 and 7.4.
The table below highlights version compatibility of the most-recent library versions and redis versions.
Library version | Supported redis versions |
---|---|
3.5.3 | <= 6.2 Family of releases |
>= 4.5.0 | Version 5.0 to 7.0 |
>= 5.0.0 | Version 5.0 to current |
>>> import redis
>>> r = redis.Redis(host='localhost', port=6379, db=0)
>>> r.set('foo', 'bar')
True
>>> r.get('foo')
b'bar'
The above code connects to localhost on port 6379, sets a value in Redis, and retrieves it. All responses are returned as bytes in Python, to receive decoded strings, set decode_responses=True. For this, and more connection options, see these examples.
To enable support for RESP3, ensure you have at least version 5.0 of the client, and change your connection object to include protocol=3
>>> import redis
>>> r = redis.Redis(host='localhost', port=6379, db=0, protocol=3)
By default, redis-py uses a connection pool to manage connections. Each instance of a Redis class receives its own connection pool. You can however define your own redis.ConnectionPool.
>>> pool = redis.ConnectionPool(host='localhost', port=6379, db=0)
>>> r = redis.Redis(connection_pool=pool)
Alternatively, you might want to look at Async connections, or Cluster connections, or even Async Cluster connections.
There is built-in support for all of the out-of-the-box Redis commands. They are exposed using the raw Redis command names (HSET
, HGETALL
, etc.) except where a word (i.e. del) is reserved by the language. The complete set of commands can be found here, or the documentation.
The official Redis command documentation does a great job of explaining each command in detail. redis-py attempts to adhere to the official command syntax. There are a few exceptions:
MULTI/EXEC: These are implemented as part of the Pipeline class. The pipeline is wrapped with the MULTI and EXEC statements by default when it is executed, which can be disabled by specifying transaction=False. See more about Pipelines below.
SUBSCRIBE/LISTEN: Similar to pipelines, PubSub is implemented as a separate class as it places the underlying connection in a state where it can't execute non-pubsub commands. Calling the pubsub method from the Redis client will return a PubSub instance where you can subscribe to channels and listen for messages. You can only call PUBLISH from the Redis client (see this comment on issue #151 for details).
For more details, please see the documentation on advanced topics page.
The following is a basic example of a Redis pipeline, a method to optimize round-trip calls, by batching Redis commands, and receiving their results as a list.
>>> pipe = r.pipeline()
>>> pipe.set('foo', 5)
>>> pipe.set('bar', 18.5)
>>> pipe.set('blee', "hello world!")
>>> pipe.execute()
[True, True, True]
The following example shows how to utilize Redis Pub/Sub to subscribe to specific channels.
>>> r = redis.Redis(...)
>>> p = r.pubsub()
>>> p.subscribe('my-first-channel', 'my-second-channel', ...)
>>> p.get_message()
{'pattern': None, 'type': 'subscribe', 'channel': b'my-second-channel', 'data': 1}
redis-py is developed and maintained by Redis Inc. It can be found here, or downloaded from pypi.
Special thanks to:
FAQs
Python client for Redis database and key-value store
We found that redis demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 2 open source maintainers collaborating on the project.
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