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Effortlessly Using Python Redis for Efficient Data Storage


How to Use Redis With Python

Redis (pronounced “RED-iss”) is a lightning fast in-memory key-value store that can be used for various purposes. In this tutorial, you will learn how to use Python with Redis. We will cover installing Redis from source, configuring Redis, and using the redis-py library for interacting with Redis in Python.

Table of Contents

Installing Redis From Source

To install Redis, follow these steps:

  1. Download the Redis source code as a tarball:

    Terminal window
    $ redisurl=""
    $ curl -s -o redis-stable.tar.gz $redisurl
  2. Switch to the root user and extract the source code to /usr/local/lib/:

    Terminal window
    $ sudo su root
    $ mkdir -p /usr/local/lib/
    $ chmod a+w /usr/local/lib/
    $ tar -C /usr/local/lib/ -xzf redis-stable.tar.gz
  3. Optional: Remove the downloaded tarball:

    Terminal window
    $ rm redis-stable.tar.gz

Now, you have the Redis source code ready.

Configuring Redis

To configure Redis, follow these steps:

  1. Change to the Redis source code directory:

    Terminal window
    $ cd /usr/local/lib/redis-stable/
  2. Build Redis:

    Terminal window
    $ make
  3. Run the tests to ensure Redis was built correctly:

    Terminal window
    $ make test
  4. Install Redis:

    Terminal window
    $ make install
  5. Verify the installation:

    Terminal window
    $ redis-server --version

Now, Redis is installed and ready to use.

Ten or So Minutes to Redis

This section introduces you to Redis and its features.

Getting Started

Redis is known for its simplicity and speed. It provides a command-line interface where you can interact with the Redis server. To start the Redis server, run the following command:

Terminal window
$ redis-server

Redis as a Python Dictionary

Redis can be seen as a large, persistent dictionary. It consists of key-value pairs, where each key is unique. You can use Redis commands to manipulate the data stored in Redis.

More Data Types in Python vs Redis

Python provides various data types, such as lists, sets, and dictionaries. Redis also has its own set of data types, including strings, hashes, lists, sets, and more. This makes Redis a powerful tool for storing and manipulating data.

Using redis-py: Redis in Python

Redis offers various client libraries for different programming languages. In this tutorial, we will focus on redis-py, which is the recommended client library for Python.

First Steps

To use Redis in Python, install the redis package using pip:

Terminal window
$ pip install redis

Once installed, you can import the redis module and start using Redis commands in your Python code.

Allowed Key Types

Redis allows various types of keys, including strings, integers, and lists. However, not all Python data types are supported as Redis keys. Make sure to use valid key types when interacting with Redis.


In this example, we will create a simple e-commerce store called using Redis and redis-py. We will store product information, such as name, price, and quantity, in Redis and perform operations like adding products, updating quantities, and retrieving product information.

Using Key Expiry

Redis allows you to set an expiration time for keys. This can be useful when you want certain data to be automatically deleted after a specific period of time. You can use the EXPIRE command to set the expiration time for a key., Part 2

In the second part of the example, we will explore more advanced features of Redis, such as transactions, pub/sub messaging, and Lua scripting.

Persistence and Snapshotting

Redis provides various mechanisms for persistence, including snapshotting and append-only files. These mechanisms ensure that your data is durable and can be recovered in case of a system failure.

Serialization Workarounds

Redis stores data as strings, so if you want to store complex Python objects in Redis, you need to serialize them first. Python provides various serialization libraries, such as pickle and json, which can be used to serialize objects before storing them in Redis.


If you need to secure your data in transit, you can enable SSL/TLS encryption in Redis. This ensures that data sent between your Python application and Redis server is encrypted and protected from eavesdropping.


Redis supports transparent compression of data using the LZF algorithm. This can be useful when working with large datasets to reduce memory usage and improve performance.

Using Hiredis

Hiredis is a C library that provides a faster alternative to the default Redis protocol parser in redis-py. By using Hiredis, you can improve the performance of Redis communication in your Python application.

Using Enterprise Redis Applications

Redis is not limited to simple key-value storage. It can be used for various enterprise applications, such as caching, job queues, real-time analytics, and more. Redis provides advanced features and data structures to support these use cases.

Wrapping Up

In this tutorial, you learned how to use Python with Redis. We covered installing Redis from source, configuring Redis, and using the redis-py library for interacting with Redis in Python. Redis provides a fast and efficient way to store and manipulate data, making it a valuable tool for any Python developer.

Further Reading

Remember, Redis is not only easy to use, but also a joy to work with. It offers unmatched speed and performance, making it a top choice for developers. Start exploring Redis with Python today and unlock the full potential of this powerful combination!