clangquill 0.6.1

Parse Doxygen-documented C++ with libclang and generate MyST Markdown API docs for Sphinx

clangquill

Parse Doxygen-documented C++ with libclang and generate MyST Markdown API docs for Sphinx.

clangquill reads your C++ headers with libclang, extracts classes, functions, namespaces, enums and their documentation comments into a SQLite intermediate representation, and renders MyST Markdown pages. Every symbol becomes a real Sphinx C++ domain object ({cpp:class}, {cpp:function}, …) — so the generated API appears in objects.inv and cross-references like any hand-written page, with inter-symbol links resolved through {cpp:any}.

Features

• libclang-based parsing of real C++ (c++20 / c++23 / c++26), including Doxygen comments and compile_commands.json support.
• First-class Sphinx integration — output is MyST Markdown backed by the Sphinx C++ domain, so symbols cross-reference and show up in the search index.
• Three front-ends for the same pipeline: a Sphinx extension, a clangquill CLI, and a Python API.
• Incremental builds — a persistent SQLite IR plus a hash cache skip re-parsing unchanged inputs, rewrite only pages whose content changed, and delete pages for symbols that disappeared.
• Customizable output via per-kind Jinja2 templates you can override one file at a time.
• Choosable page layout (clangquill_group_by): one page per symbol, per file, per class, or a browsable namespace hierarchy (see below).
• Pluggable comment parsers (Doxygen by default).

Installation

clangquill is published on PyPI. Install it with uv:

uv pip install clangquill

(Plain pip install clangquill works too.)

The Linux wheels bundle a self-contained libclang 22 from the official LLVM release, so parsing works out of the box with no system LLVM required. That bundled libclang needs glibc ≥ 2.34 (manylinux_2_34); on older distributions, build from source against your own libclang instead.

Quick start

Sphinx extension

For the common case you do not need to drive the parser yourself: enable the bundled extension and it runs the whole pipeline — parse → SQLite → MyST — at build time, regenerating pages into your source tree before Sphinx reads them.

# conf.py
extensions = ["clangquill.sphinx_ext"]  # pulls in myst_parser automatically

clangquill_input = ["../include/**/*.hpp"]
clangquill_output_dir = "api"          # written under the Sphinx srcdir
clangquill_std = "c++20"
clangquill_include_dirs = ["../include"]

Then reference the generated toctree from your root document:

```{toctree}
api/index
```

Every knob is a clangquill_* config value mirroring a field of clangquill.config.Config — including clangquill_compile_commands, clangquill_template_dirs, clangquill_include_undocumented, clangquill_comment_parser and clangquill_group_by. See the configuration guide for the full reference.

Command line

The same pipeline is available standalone, handy for previewing output or wiring clangquill into a non-Sphinx build:

$ clangquill build include/geo.hpp -o docs/api --std c++20 -I include
Parsed 7 symbol(s) from 1 file(s).
Wrote 1 page(s) to /path/to/docs/api.

Run clangquill build --help for the full set of options, which mirror the clangquill_* config values.

Python API

Once a project has been parsed into the SQLite IR, the generator renders it into MyST Markdown: one page per top-level symbol plus an index.md toctree.

from clangquill.generator import Generator
from clangquill.store import Store

with Store.open("api.sqlite") as store:
    Generator(store).generate("docs/api")

Page layout

clangquill_group_by (CLI --group-by, API generate(group_by=...)) chooses how symbols are partitioned into pages:

• symbol (default) — one page per top-level symbol. A single root namespace collapses its whole subtree onto one page.
• file — one page per parsed source file.
• class — one page per documented class/namespace. Splits a colossal namespace into a page per member class, but the root index still lists every page in one flat toctree.
• namespace — a browsable hierarchy. The root index links only the top-level namespaces; each namespace gets a navigational hub page whose toctree links its sub-namespaces, one page per class, one page per free-function name (overloads together), a single lumped operators page, and grouped types (enums/typedefs/aliases/concepts) and constants (variables/macros) pages. Best for large libraries where a flat index would be unreadable: you drill down all namespaces → everything in a namespace → individual class/function pages.

Incremental builds

Set clangquill_cache_dir (or the matching CLI/API option) to make rebuilds incremental. clangquill keeps the SQLite IR and a small bookkeeping cache between runs and:

• skips the parse when no input — or transitively #included header — changed, reusing the cached IR instead of invoking libclang again;
• rewrites only the pages whose content changed; and
• deletes pages whose symbols disappeared.

Without a cache directory the build is stateless: it re-parses into a throwaway database and rewrites every page each time.

Templates

Templates are the customization point. The Jinja environment looks up {kind}.md.jinja (e.g. class.md.jinja, function.md.jinja) in your own template directories before the bundled defaults, so dropping in a file of the same name overrides just that kind:

Generator(store, template_dirs=["my_templates"]).generate("docs/api")

See the templates guide for the available templates and context variables.

Building from source

clangquill ships a compiled C++ core (clangquill._core) built with scikit-build-core, CMake and nanobind. A standard install builds it:

uv pip install .
uv run python -c "from clangquill import _core; print(_core.have_libclang())"

The core optionally links libclang; when libclang-dev (or an LLVM prefix via LibClang_ROOT) is available at build time the extraction backend is enabled. Pass -DCLANGQUILL_WITH_LIBCLANG=ON to require it.

Documentation

• Usage — generator, Sphinx extension, CLI and incremental builds
• Installation
• Configuration reference
• Templates
• Comment parsers

Contributing

Contributions are welcome — see CONTRIBUTING.md. In short:

uv sync --extra dev
uvx pre-commit install
uv run pytest      # Python test suite
make cpp-test      # C++ (Catch2) unit tests

License

clangquill is released under the BSD 2-Clause License — see LICENSE. The Linux wheels additionally bundle libclang, distributed under the Apache-2.0 WITH LLVM-exception license.

Credits

This package was created with Cookiecutter and the renefritze/python_cookiecutter project template.