The best Buildout alternatives
The rest of Best Python Package Managers, in this site's order: each with what it costs, where it runs and its record score.
It suits organizations that need to manage runtime projects and permissions across teams.
Pixi suits developers working in robotics, data science, machine learning, and other software workflows that benefit from reproducible environments.
Hatch may suit Python developers who want project setup and environment management alongside testing, analysis, and package publishing.
Mamba suits developers and data practitioners managing conda environments across supported platforms.
pip suits Python users who need to install packages from public indexes, repositories, or local sources.
It is for developers and system administrators who want to compile pinned pip requirements and synchronize virtual environments.
Spack suits scientific computing teams and users who need to manage configurable software builds across systems or architectures.
Twine suits developers who need to upload built Python distributions to public or private package repositories.
uv suits Python developers who want dependency and environment management alongside Python version and command-line tool management.
It suits Python developers looking for an open-source linter and package and project management tools across macOS, Linux, or Windows.
conda-lock suits people managing conda environments who need reproducible installations across multiple target platforms.
Miniconda suits command-line users who know which packages they need and want to build isolated project environments.
virtualenv suits Python developers who need separate environments for projects, interpreters, and dependencies.
It suits Python developers and teams managing repeatable test sessions across interpreters and dependency sets.
It suits Python maintainers packaging libraries or applications for distribution and installation.