A python package to avoid writing and maintaining duplicated python docstrings.

Overview

PyPI - Python Version PyPI Code Style Codecov branch

docstring-inheritance is a python package to avoid writing and maintaining duplicated python docstrings. The typical usage is to enable the inheritance of the docstrings from a base class such that its derived classes fully or partly inherit the docstrings.

Features

  • Handle numpy and google docstring formats (i.e. sections based docstrings):
  • Handle docstrings for functions, classes, methods, class methods, static methods, properties.
  • Handle docstrings for classes with multiple or multi-level inheritance.
  • Docstring sections are inherited individually, like methods for a classes.
  • For docstring sections documenting signatures, the signature arguments are inherited individually.
  • Minimum performance cost: the inheritance is performed at import time, not for each call.
  • Compatible with rendering the documentation with Sphinx.

Licenses

The source code is distributed under the MIT license. The documentation is distributed under the CC BY-SA 4.0 license. The dependencies, with their licenses, are given in the CREDITS.rst file.

Installation

Install via pip:

pip install docstring-inheritance

Basic Usage

Inheriting docstrings for classes

docstring-inheritance provides metaclasses to enable the docstrings of a class to be inherited from its base classes. This feature is automatically transmitted to its derived classes as well. The docstring inheritance is performed for the docstrings of the:

  • class
  • methods
  • classmethods
  • staticmethods
  • properties

Use the NumpyDocstringInheritanceMeta metaclass to inherit docstrings in numpy format.

Use the GoogleDocstringInheritanceMeta metaclass to inherit docstrings in google format.

from docstring_inheritance import NumpyDocstringInheritorMeta


class Parent(metaclass=NumpyDocstringInheritorMeta):
    def meth(self, x, y=None):
        """Parent summary.

        Parameters
        ----------
        x:
           Description for x.
        y:
           Description for y.

        Notes
        -----
        Parent notes.
        """


class Child(Parent):
    def meth(self, x, z):
        """
        Parameters
        ----------
        z:
           Description for z.

        Returns
        -------
        Something.

        Notes
        -----
        Child notes.
        """


# The inherited docstring is
Child.meth.__doc__ = """Parent summary.

Parameters
----------
x:
   Description for x.
z:
   Description for z.

Returns
-------
Something.

Notes
-----
Child notes.
"""

Inheriting docstrings for functions

docstring-inheritance provides functions to inherit the docstring of a callable from a string. This is typically used to inherit the docstring of a function from another function.

Use the inherit_google_docstring function to inherit docstrings in google format.

Use the inherit_numpy_docstring function to inherit docstrings in numpy format.

from docstring_inheritance import inherit_google_docstring


def parent():
    """Parent summary.

    Args:
        x: Description for x.
        y: Description for y.

    Notes:
        Parent notes.
    """


def child():
    """
    Args:
        z: Description for z.

    Returns:
        Something.

    Notes:
        Child notes.
    """
    

inherit_google_docstring(parent.__doc__, child)


# The inherited docstring is
child.__doc__ = """Parent summary.

Args:
    x: Description for x.
    z: Description for z.

Returns:
    Something.

Notes:
    Child notes.
"""

Docstring inheritance specification

Sections order

The sections of an inherited docstring are sorted according to order defined in the NumPy docstring format specification:

  • Summary
  • Extended summary
  • Parameters for the NumPy format or Args for the Google format
  • Returns
  • Yields
  • Receives
  • Other Parameters
  • Attributes
  • Methods
  • Raises
  • Warns
  • Warnings
  • See Also
  • Notes
  • References
  • Examples
  • sections with other names come next

This ordering is also used for the docstring written with the Google docstring format specification even though it does not define all of these sections.

Sections with items

Those sections are:

  • Other Parameters
  • Methods
  • Attributes

The inheritance is done at the key level, i.e. a section of the inheritor will not fully override the parent one:

  • the keys in the parent section and not in the child section are inherited,
  • the keys in the child section and not in the parent section are kept,
  • for keys that are both in the parent and child section, the child ones are kept.

This allows to only document the new keys in such a section of an inheritor. For instance:

from docstring_inheritance import NumpyDocstringInheritorMeta


class Parent(metaclass=NumpyDocstringInheritorMeta):
    """
    Attributes
    ----------
    x:
       Description for x
    y:
       Description for y
    """


class Child(Parent):
    """
    Attributes
    ----------
    y:
       Overridden description for y
    z:
       Description for z
    """

    
# The inherited docstring is
Child.__doc__ = """
Attributes
----------
x:
   Description for x
y:
   Overridden description for y
z:
   Description for z
"""

Here the keys are the attribute names. The description for the key y has been overridden and the description for the key z has been added. The only remaining description from the parent is for the key x.

Sections documenting signatures

Those sections are:

  • Parameters (numpy format only)
  • Args (google format only)

In addition to the inheritance behavior described above:

  • the arguments not existing in the inheritor signature are removed,
  • the arguments are sorted according the inheritor signature,
  • the arguments with no descriptions are provided with a dummy description.
from docstring_inheritance import GoogleDocstringInheritorMeta


class Parent(metaclass=GoogleDocstringInheritorMeta):
    def meth(self, w, x, y):
        """
        Args:
            w: Description for w
            x: Description for x
            y: Description for y
        """


class Child(Parent):
    def meth(self, w, y, z):
        """
        Args:
            z: Description for z
            y: Overridden description for y
        """


# The inherited docstring is
Child.meth.__doc__ = """
Args:
    w: Description for w
    y: Overridden description for y
    z: Description for z
"""

Here the keys are the arguments names. The description for the key y has been overridden and the description for the key z has been added. The only remaining description from the parent is for the key w.

Advanced usage

Abstract base class

To create a parent class that both is abstract and has docstring inheritance, an additional metaclass is required:

import abc
from docstring_inheritance import NumpyDocstringInheritorMeta


class Meta(abc.ABCMeta, NumpyDocstringInheritorMeta):
    pass


class Parent(metaclass=Meta):
    pass

Similar projects

custom_inherit: docstring-inherit started as fork of this project, we would like to thank its author.

Yet Another MkDocs Parser

yamp Motivation You want to document your project. You make an effort and write docstrings. You try Sphinx. You think it sucks and it's slow -- I did.

Max Halford 10 May 20, 2022
This is a tool to make easier brawl stars modding using csv manipulation

Brawler Maker : Modding Tool for Brawl Stars This is a tool to make easier brawl stars modding using csv manipulation if you want to support me, just

6 Nov 16, 2022
💯 Coolest snippets

nvim-snippets This was originally included in my personal Neovim setup, but I didn't like having all the snippets there so I decided to have them sepa

Eliaz Bobadilla 6 Aug 31, 2022
Software engineering course project. Secondhand trading system.

PigeonSale Software engineering course project. Secondhand trading system. Documentation API doumenatation: list of APIs Backend documentation: notes

Harry Lee 1 Sep 01, 2022
A simple XLSX/CSV reader - to dictionary converter

sheet2dict A simple XLSX/CSV reader - to dictionary converter Installing To install the package from pip, first run: python3 -m pip install --no-cache

Tomas Pytel 216 Nov 25, 2022
Reproducible Data Science at Scale!

Pachyderm: The Data Foundation for Machine Learning Pachyderm provides the data layer that allows machine learning teams to productionize and scale th

Pachyderm 5.7k Dec 29, 2022
A web app builds using streamlit API with python backend to analyze and pick insides from multiple data formats.

Data-Analysis-Web-App Data Analysis Web App can analysis data in multiple formates(csv, txt, xls, xlsx, ods, odt) and gives shows you the analysis in

Kumar Saksham 19 Dec 09, 2022
Collections of Beautiful Latex Snippets

HandyLatex Collections of Beautiful Latex Snippets Table 👉 Succinct table with bold separation line and gray text %################## Dependencies ##

Xintao 15 Apr 11, 2022
Automated generation of real Swagger/OpenAPI 2.0 schemas from Django REST Framework code.

drf-yasg - Yet another Swagger generator Generate real Swagger/OpenAPI 2.0 specifications from a Django Rest Framework API. Compatible with Django Res

Cristi Vîjdea 3k Dec 31, 2022
Some code that takes a pipe-separated input and converts that into a table!

tablemaker A program that takes an input: a | b | c # With comments as well. e | f | g h | i |jk And converts it to a table: ┌───┬───┬────┐ │ a │ b │

CodingSoda 2 Aug 30, 2022
A Collection of Cheatsheets, Books, Questions, and Portfolio For DS/ML Interview Prep

Here are the sections: Data Science Cheatsheets Data Science EBooks Data Science Question Bank Data Science Case Studies Data Science Portfolio Data J

James Le 2.5k Jan 02, 2023
Sphinx Bootstrap Theme

Sphinx Bootstrap Theme This Sphinx theme integrates the Bootstrap CSS / JavaScript framework with various layout options, hierarchical menu navigation

Ryan Roemer 584 Nov 16, 2022
Poetry plugin to export the dependencies to various formats

Poetry export plugin This package is a plugin that allows the export of locked packages to various formats. Note: For now, only the requirements.txt f

Poetry 90 Jan 05, 2023
Fast, efficient Blowfish cipher implementation in pure Python (3.4+).

blowfish This module implements the Blowfish cipher using only Python (3.4+). Blowfish is a block cipher that can be used for symmetric-key encryption

Jashandeep Sohi 41 Dec 31, 2022
FxBuzzly - Buzzly.art links do not embed in Discord, this fixes them (rudimentarily)

fxBuzzly Buzzly.art links do not embed in Discord, this fixes them (rudimentaril

Dania Rifki 2 Oct 27, 2022
Quick tutorial on orchest.io that shows how to build multiple deep learning models on your data with a single line of code using python

Deep AutoViML Pipeline for orchest.io Quickstart Build Deep Learning models with a single line of code: deep_autoviml Deep AutoViML helps you build te

Ram Seshadri 6 Oct 02, 2022
A Material Design theme for MkDocs

A Material Design theme for MkDocs Create a branded static site from a set of Markdown files to host the documentation of your Open Source or commerci

Martin Donath 12.3k Jan 04, 2023
Hasköy is an open-source variable sans-serif typeface family

Hasköy Hasköy is an open-source variable sans-serif typeface family. Designed with powerful opentype features and each weight includes latin-extended

67 Jan 04, 2023
Toolchain for project structure and documents optimisation

ritocco Toolchain for project structure and documents optimisation

Harvey Wu 1 Jan 12, 2022
freeCodeCamp Scientific Computing with Python Project for Certification.

Polygon_Area_Calculator freeCodeCamp Python Project freeCodeCamp Scientific Computing with Python Project for Certification. In this project you will

Rajdeep Mondal 1 Dec 23, 2021