rustdoc vs Sphinx
rustdoc
doc.rust-lang.org
Sphinx
sphinx-doc.orgSide by side
| Figure | rustdoc | Sphinx |
|---|---|---|
| Price from | — | Free |
| Free plan | — | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | — | Yes |
| Windows | Yes | Yes |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| API | — | Yes |
| Self-hosted | — | Yes |
| Plans published | 0 | 1 |
| Spec score · Documentation Generators | 7.4 (#23) | 8.2 (#7) |
| Installation | Rust's installation page recommends rustup and provides installation instructions for Windows, macOS, Linux, and other Unix-like systems. | Sphinx is a Python application installable through PyPI, Conda, Linux package managers, Homebrew or MacPorts, Chocolatey, Docker, or from source. |
| Purpose | rustdoc generates documentation for Rust projects from a crate root or Markdown file, producing HTML, CSS, and JavaScript. | Sphinx generates technical documentation from structured text. |
| Support | The Rust site directs users to the documentation, Rust Forge contributor documentation, and the Users Forum for help. | The project directs users to Stack Overflow, GitHub Discussions, GitHub Issues, or the sphinx-users mailing list for questions and problem reports. |
Plans
In their own words
Sphinx
Sphinx is a free Python application that generates technical documentation from structured text. Authors can use reStructuredText or MyST Markdown; Markdown requires installing MyST-Parser separately. Built-in builders produce HTML, LaTeX for PDF, ePub, manual pages, Texinfo, and plain text. References can link sections, figures, tables, citations, glossaries, and code objects within one project or across projects. The autodoc extension imports documented modules and includes material from their docstrings. Themes and extensions, both built-in and third-party, add options such as diagrams, doctests, and API documentation. Other built-in extensions provide GitHub Pages publishing, Graphviz graphs, and intersphinx links. Sphinx also supports gettext-based translation and full-text search. It can be installed through Python and platform package managers, Docker, or from source, then deployed to services such as Read the Docs, GitHub Pages, GitLab Pages, Netlify, or self-hosted servers. Its code is released under the two-clause BSD license, and the project is community supported.