Hatch

Hatch is a free, MIT-licensed Python project manager for setting up projects and managing development environments across Linux, macOS, and Windows. It can create projects from templates or initialize existing ones, including migrating setuptools configuration from setup.py. Its environment tools support custom scripts and UV, with manual Python installations or automatic installation as part of an environment. Hatch supports reproducible builds, test execution, and static analysis backed by Ruff. For releases, it can upload packages to PyPI or other package indices. Its pluggy-based extension system documents plugin types for environments, builders, publishers, and other project tasks. The tool also lists lockfile support, dependency groups, private registry support, and package publishing. Visual Studio Code can discover Hatch environments through the vscode-python extension, and its installation guide documents an official GitHub Actions install action. Installation choices include standalone installers or binaries, pip, pipx, Homebrew, Conda, and other methods. For unexpected behavior, the documentation directs users to a self-report command that prepares an issue on GitHub.

Hatch covers project setup, environments, quality checks, and publishing in a free, extensible Python tool. Its documented installation methods span major desktop platforms, with plugin and editor integrations available for added workflows.

Hatch may suit Python developers who want project setup and environment management alongside testing, analysis, and package publishing. Its cross-platform installation options accommodate Linux, macOS, and Windows.

Hatch is an open-source Python project manager for developers who want one tool to shape project workflows from setup through release. It suits individuals and teams working across Linux, macOS, and Windows who value configurable environments and repeatable builds. Its strongest case is broad project coverage without a license fee; its command-line, project-focused approach is not a substitute for a hosted development workspace.

Overview

Hatch can start a project from a template, initialize an existing one, and migrate setuptools configuration from setup.py. It also brings environment management, quality checks, builds, and package publishing into the same workflow. Lockfiles, dependency groups, and private-registry support make it relevant beyond project scaffolding, especially for developers coordinating dependencies and releases.

The breadth favors users who want a configurable Python project tool rather than a narrow installer. Hatch’s pluggy-based extension system can add or adapt project tasks, but that flexibility means choosing which workflows and plugins to maintain.

Key features

Environments and builds

Hatch manages environments, supports custom scripts and UV, and can use a manually installed Python or install Python as part of an environment. Reproducible builds help keep build outputs consistent, an important advantage for projects developed across machines. The available choices suit users who need control over their setup; teams seeking a managed workspace should look elsewhere.

Checks and publishing

The test command uses pytest with selected plugins and coverage.py by default. Static analysis is backed by Ruff, with defaults Hatch describes as current and sensible. Hatch can also upload packages to PyPI or other package indices, connecting routine checks to release work without requiring a separate publishing tool.

Extension and editor workflows

Plugins can cover 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 supports automation workflows. These integrations extend Hatch’s reach, though editor support depends on the extension rather than making Hatch a graphical application.

Pricing

Hatch: free. Hatch is MIT-licensed open-source software, with no paid plan or trial required. The free plan includes environment management, package publishing, private registry support, dependency groups, and lockfile support; it is the straightforward choice for both individual developers and teams that want these project-management capabilities without a subscription.

Platforms

Hatch supports Linux, macOS, and Windows. Installation options include platform installers or standalone binaries, as well as pip, pipx, Homebrew, and Conda. That range gives developers multiple ways to fit installation into their existing setup.

Who it's for

Hatch is a strong fit for Python developers who want to standardize project setup, environments, tests, builds, and publishing while retaining room to customize through plugins. It is less suited to readers looking primarily for a hosted notebook or graphical workspace, or for a narrowly scoped package-installation tool.

Pros and cons

Pros

• One project tool covers templates, existing-project initialization, environments, checks, builds, and publishing, reducing workflow fragmentation.
• Reproducible builds, lockfiles, dependency groups, and private-registry support address consistency and dependency needs across projects.
• The MIT-licensed free plan includes the core environment and publishing capabilities, with cross-platform installation options.
• Pluggy-based plugins and integrations with Visual Studio Code and GitHub Actions allow workflows to extend beyond Hatch’s defaults.

Cons

• Hatch is a Python project manager, not a hosted development environment; users wanting a workspace in the browser need a different product.
• Its extensibility and multiple environment and installation options require users to decide which setup fits their work.
• Editor environment discovery is through the vscode-python extension, so Hatch does not itself provide an integrated graphical editor.

Alternatives

• ActiveState Platform is worth considering if a freemium option with a free trial and public-project-only free organization better fits your needs.
• Anaconda Notebooks is a web-based alternative for readers who want notebooks and cloud storage, with a free plan capped at 5 GB.
• pip is a free alternative to consider when a basic Python package installer is a closer fit than Hatch’s broader project workflow.
• pip-tools suits readers seeking free command-line tools installed per virtual environment, with Python 3.9 or later.
• Pixi is another free, cross-platform option; its open-source package-hosting plan includes a global CDN, 100 GB of public packages, and unlimited channel users.
• Twine is a free alternative for readers focused on Python package publishing and using Python 3.10 or later.
• uv is another free, cross-platform open-source Python package tool.
• conda-lock is a free, MIT-licensed option for readers looking specifically for environment lockfile tooling.

Verdict

Choose Hatch if you want a free, extensible Python project manager that handles setup, environments, checks, builds, and publishing across major desktop platforms. Its combination of project-wide capabilities and plugin support is the main reason to pick it. Look elsewhere if your priority is a hosted workspace or a focused package tool rather than a configurable project workflow.