Astral vs Hatch

Astral makes open-source tools for Python development, including Ruff, a linter, and uv, a package and project manager. Both are written in Rust. uv brings together project management, a universal lockfile, script execution, Python version management, tool installation, workspaces and a pip-compatible interface. Astral describes that interface as providing a 10–100x speedup over pip. uv supports macOS, Linux and Windows. Its documented integrations include Docker, Jupyter, marimo, GitHub Actions, GitLab CI/CD, pre-commit, PyTorch, FastAPI, Bazel, artifact registries, Renovate, Dependabot, AWS Lambda and Coiled. Astral says its tools are permissively licensed and free forever. It describes security controls for workflows and releases, including read-only default workflow permissions, full-length commit-SHA pinning, Trusted Publishing, Sigstore attestations and immutable GitHub releases. Documentation directs users to its Discord community for support. The separate pyx package registry offers optimized installs and other package-management features, but is no longer accepting new signups. Astral has announced an agreement to join OpenAI as part of the Codex team.

Hatch is a free, MIT-licensed Python project manager for creating projects and managing development environments on Linux, macOS, and Windows. It can start projects from templates or initialize existing ones, including migrating setuptools configuration from setup.py. Environment management supports custom scripts and UV, with manual Python installations or automatic installation as part of an environment. Hatch also supports reproducible builds, test execution, and static analysis backed by Ruff. For publishing, it can upload packages to PyPI and other package indices; lockfiles, dependency groups, and private registries are listed capabilities. Its plugin system uses pluggy, with documented extension types for environments, builders, publishers, and other project tasks. Visual Studio Code can discover Hatch environments through the vscode-python extension, and an official GitHub Actions install action is documented. Installation options include standalone installers or binaries, pip, pipx, Homebrew, Conda, and other methods. The documentation provides a self-report command that prepares a GitHub issue for unexpected behavior.