$ wget <desired redis version>
$ tar xzf <file>
$ cd <created folder>
$ make

$ redis-server

$ redis-cli

Redis is not a database. If you need an analogy, think of it as a dict that runs on another computer.

Where in regular python dict you take things out and then modify them, in Redis you modify things inside and then you take them out. This helps if more than two Python applications talk to the same Redis.

In web development, you can use Redis as cache (key=url or post_id, value=html), as rate limiting backend (expiring entries, key=ip, value=count). In any Python project, you can use Redis as queue backend (Celery can use Redis), or to synchronize your non-essential state between Python instances.

• Full list of commands in: http://redis.io/commands

• ping, if everything is good, the server will respond pong.
• select, to select one of the 16 databases that Redis manage.

$ pip install redis

import redis
r = redis.StrictRedis(host='192.168.0.100', db=0, socket_timeout=2)
r.set('foo', 'bar')
print r.get('foo')

• You can connect to several isolated interfaces changing db argument.
• Redis instances are thread safe.
• You can't create nested structures in Redis, meaning you can't (for example) store a native redis list inside a native redis hash-map. If you need nested structures, you might want to just store a JSON instead. Another option is to store an “id”/key to a different redis object as the value of the map key, but that requires multiple calls to the server to get the full object.
• flushdb() will flush the database you are connected to (cleaning all the keys), while flushall() will clear all the keys in every database.
• Connecting/disconnecting for each operation is too expensive, so it is much better to maintain the connection opened. With redis-py it can be done by declaring a pool of connections (ConnectionPool class). redis-py uses a connection pool to manage connections to a Redis server. By default, each Redis instance you create will in turn create its own connection pool. You can choose a concrete connection pool in the next way:

pool = redis.ConnectionPool(host='localhost', port=6379, db=0)
r = redis.Redis(connection_pool=pool)

• You can obtain the keys calling the keys() function of an StricRedis object. It also accept a pattern…

r = redis.StrictRedis(host=YOUR_HOST, port=YOUR_PORT, db=YOUR_DB)
r.keys()
keys(pattern='*')

• A Redis object has the info() to obtain information about Redis server like