10 Best Python Packaging Libraries 2024

Here are some of the famous Python Packaging Libraries. Some use cases of Python Packaging Libraries include Automating Dependency Installation, Package Distribution, Version Management, and Documentation.

Python Packaging libraries are libraries that provide a set of tools and resources to help developers package, distribute, and install Python applications. These libraries provide tools for creating installers, setting up virtual environments, uploading packages to PyPI, and more.

Let us have a look at some of the famous Python Packaging Libraries.

pyenv

• Allows you to install different versions of Python packages.
• Automatically install any version of Python that you specify.
• Allows you to easily switch between different Python versions and virtual environments.

poetry

• Provides an expressive command line interface which allows users to quickly interact with their projects.
• Virtual environment can be used to install and manage the dependencies of your project.
• Supports version resolution which allows you to specify a range of versions of a package that is compatible with your project.

pipenv

• Ability to automatically generate a Pipfile, which is a file containing all the dependencies required for your project.
• Provides a CLI interface, which makes it easier to install and manage packages.
• Provides security features, such as checking for vulnerable packages, that other Python packaging libraries lack.

conda

• Makes it easy to create and manage multiple isolated environments.
• Automatically determines and resolves the dependencies between packages, so users don’t need to worry about compatibility errors.
• Allows users to store different versions of packages so they can be easily reverted if needed.

tox

• Allows for configuration-based testing, meaning you can easily define the tests to run and configure the environment for each test.
• Can be easily integrated with continuous integration tools such as Jenkins, Travis, and CircleCI.
• Automates the testing process, allowing you to easily run tests on different versions of Python, as well as different environments.

flake8

• Integrates with many popular text editors, making it simple to use.
• Highly configurable and can be used to enforce custom code style guidelines.
• Can be used to check compliance with PEP8, the official Python style guide.

setuptools

• Automatically identifies and installs any dependencies that a package may have.
• Supports versioning packages, making it easy to keep track of different versions of your packages.
• Includes support for building and distributing packages on Windows, making it easy to create packages that can be used on Windows systems.

pybuilder

• Supports a wide range of build tasks, from creating packages to creating virtual environments to running unit tests.
• Supports automated testing and continuous integration, allowing developers to quickly and easily test their projects.
• Dsigned to be fast and efficient, allowing developers to focus on writing code and not worrying about the build process.

flit

• Package metadata and configuration is stored in the same directory as the code.
• Simplicity and minimalism make it unique from other Python Packaging libraries.
• Allows developers to quickly set up and share their projects without having to create additional files or directories.

twine

• Built-in verification system that ensures packages are uploaded with the correct metadata and signatures.
• Supports both HTTP and HTTPS protocols, making it a secure way to upload packages to PyPI.
• Can be used to upload packages to custom PyPI indexes, allowing users to keep their packages private and secure.