mkdocs-terok¶
Shared ProperDocs documentation generators for terok projects.
Overview¶
mkdocs-terok ships a terok ProperDocs plugin that drives all built-in
generators automatically — no shim scripts required. For advanced or
consumer-specific use cases the generator modules remain public and can be
called directly via mkdocs-gen-files.
Quick start — plugin¶
# properdocs.yml
plugins:
- search
- terok:
ci_map: true
code_metrics: true
test_map: true
ref_pages: true
All generators default to false (opt-in). CSS and JS assets are injected
automatically unless inject_css / inject_js are set to false.
For a complete, real-world example see this repository's own
properdocs.yml
— it drives the very documentation site you are reading.
Quick start — generator API¶
Each module produces Markdown strings or structured results that consumers wrap
in thin mkdocs-gen-files callbacks:
from mkdocs_terok.ci_map import generate_ci_map
markdown = generate_ci_map()
The generators have no runtime dependency on the doc engine — they handle content generation only.
Modules¶
| Module | Purpose |
|---|---|
mkdocs_terok |
Package root — exports brand_css_path() and mermaid_zoom_js_path() |
mkdocs_terok.plugin |
ProperDocs BasePlugin wrapping all generators |
mkdocs_terok.ref_pages |
Generate API reference pages from source tree |
mkdocs_terok.ci_map |
Parse and visualize GitHub Actions workflows |
mkdocs_terok.code_metrics |
Code quality analysis — optionally parses output from scc, complexipy, tach, vulture, and docstr-coverage (sections degrade gracefully when tools are absent) |
mkdocs_terok.test_map |
Generate test suite maps with marker extraction |
mkdocs_terok.config_reference |
Render Pydantic models as config documentation |
Dogfooding¶
This documentation site uses mkdocs-terok on itself. Every generator in the
library is exercised against this very repository via the terok plugin — see
properdocs.yml
on master for the full live configuration.
Config Reference Demo¶
The Config Reference Demo uses a Pydantic model for a
space weather monitoring station to exercise all three renderers
(render_model_tables, render_yaml_example, render_json_schema) — it
remains as a mkdocs-gen-files script since it requires a consumer-specific
Pydantic model.