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pytkdocs¤

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Load Python objects documentation.

Requirements¤

pytkdocs requires Python 3.6 or above.

To install Python 3.6, I recommend using pyenv.
# install pyenv
git clone https://github.com/pyenv/pyenv ~/.pyenv

# setup pyenv (you should also put these three lines in .bashrc or similar)
export PATH="${HOME}/.pyenv/bin:${PATH}"
export PYENV_ROOT="${HOME}/.pyenv"
eval "$(pyenv init -)"

# install Python 3.6
pyenv install 3.6.12

# make it available globally
pyenv global system 3.6.12

Installation¤

With pip:

python3.6 -m pip install pytkdocs

With pipx:

python3.6 -m pip install --user pipx

pipx install --python python3.6 pytkdocs

With conda:

conda install -c conda-forge pytkdocs

Usage¤

pytkdocs accepts JSON on standard input and writes JSON on standard output.

Input format:

{
  "objects": [
    {
      "path": "pytkdocs",
      "new_path_syntax": false,
      "members": true,
      "inherited_members": false,
      "filters": [
        "!^_[^_]"
      ],
      "docstring_style": "google",
      "docstring_options": {
        "replace_admonitions": true
      }
    }
  ]
}

Output format:

{
  "loading_errors": [
    "string (message)"
  ],
  "parsing_errors": {
    "string (object)": [
      "string (message)"
    ]
  },
  "objects": [
    {
      "name": "pytkdocs",
      "path": "pytkdocs",
      "category": "module",
      "file_path": "/media/data/dev/pawamoy/pytkdocs/src/pytkdocs/__init__.py",
      "relative_file_path": "pytkdocs/__init__.py",
      "properties": [
        "special"
      ],
      "parent_path": "pytkdocs",
      "has_contents": true,
      "docstring": "pytkdocs package.\n\nLoad Python objects documentation.",
      "docstring_sections": [
        {
          "type": "markdown",
          "value": "pytkdocs package.\n\nLoad Python objects documentation."
        }
      ],
      "source": {
        "code": "\"\"\"\npytkdocs package.\n\nLoad Python objects documentation.\n\"\"\"\n\nfrom typing import List\n\n__all__: List[str] = []\n",
        "line_start": 1
      },
      "children": {
        "pytkdocs.__all__": {
          "name": "__all__",
          "path": "pytkdocs.__all__",
          "category": "attribute",
          "file_path": "/media/data/dev/pawamoy/pytkdocs/src/pytkdocs/__init__.py",
          "relative_file_path": "pytkdocs/__init__.py",
          "properties": [
            "special"
          ],
          "parent_path": "pytkdocs",
          "has_contents": false,
          "docstring": null,
          "docstring_sections": [],
          "source": {},
          "children": {},
          "attributes": [],
          "methods": [],
          "functions": [],
          "modules": [],
          "classes": []
        }
      },
      "attributes": [
        "pytkdocs.__all__"
      ],
      "methods": [],
      "functions": [],
      "modules": [
        "pytkdocs.__main__",
        "pytkdocs.cli",
        "pytkdocs.loader",
        "pytkdocs.objects",
        "pytkdocs.parsers",
        "pytkdocs.properties",
        "pytkdocs.serializer"
      ],
      "classes": []
    }
  ]
}

Command-line¤

Running pytkdocs without argument will read the whole standard input, and output the result once.

Running pytkdocs --line-by-line will enter an infinite loop, where at each iteration one line is read on the standard input, and the result is written back on one line. This allows other programs to use pytkdocs in a subprocess, feeding it single lines of JSON, and reading back single lines of JSON as well. This mode was actually implemented specifically for mkdocstrings.

Configuration¤

The configuration options available are:

  • new_path_syntax: when set to true, this option forces the use of the new object path syntax, which uses a colon (:) to delimit modules from other objects.

  • filters: filters are regular expressions that allow to select or un-select objects based on their name. They are applied recursively (on every child of every object). If the expression starts with an exclamation mark, it will filter out objects matching it (the exclamation mark is removed before evaluation). If not, objects matching it are selected. Every regular expression is performed against every name. It allows fine-grained filtering. Example:

    • !^_: filter out every object whose name starts with _ (private/protected)
    • ^__: but still select those who start with two _ (class-private)
    • !^__.*__$: except those who also end with two _ (specials)
  • members: this option allows to explicitly select the members of the top-object. If True, select every members that passes filters. If False, select nothing. If it's a list of names, select only those members, and apply filters on their children only.

  • inherited_members: true or false (default). When enabled, inherited members will be selected as well.

  • docstring_style: the docstring style to use when parsing the docstring. google, restructured-text1 and numpy2.

  • docstring_options: options to pass to the docstring parser.

    • google accepts a replace_admonitions boolean option (default: true). When enabled, this option will replace titles of an indented block by their Markdown admonition equivalent: AdmonitionType: Title will become !!! admonitiontype "Title".
    • restructured-text does not accept any options.
    • numpy does not accept any options.

1: reStructured Text parsing is in active development and is not feature complete yet. 2: The following sections are currently not supported : Notes, See Also, Warns and References.

Details on new_path_syntax¤

Example:

New syntax package.module:Class.attribute
Old syntax package.module.Class.attribute
  • If there is a colon is an object's path, pytkdocs splits the path accordingly, regardless of the value of new_path_syntax.
  • If there isn't a colon, and new_path_syntax is false, pytkdocs uses the old importing behavior.
  • If there isn't a colon, and new_path_syntax is true, pytkdocs uses the new importing behavior and therefore considers that the path points to a module.
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