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  2. Epydoc - Wikipedia

    en.wikipedia.org/wiki/Epydoc

    Epydoc is a documentation generator that processes its own lightweight markup language Epytext for Python documentation strings. As opposed to freeform Python docstrings, reStructuredText (both also supported) and other markup languages for docstrings, Epytext supports linking between different pieces of documentation.

  3. Comparison of documentation generators - Wikipedia

    en.wikipedia.org/wiki/Comparison_of...

    C/C++, C#, D, IDL, Fortran, Java, PHP, Python Any 1997/10/26 1.9.1 GPL Epydoc: Edward Loper Text Python Any 2002/01/— 3.0 (2008) MIT: fpdoc (Free Pascal Documentation Generator) Sebastian Guenther and Free Pascal Core Text (Object)Pascal/Delphi FPC tier 1 targets 2005 3.2.2 GPL reusable parts are GPL with static linking exception Haddock ...

  4. Doxygen - Wikipedia

    en.wikipedia.org/wiki/Doxygen

    Like other documentation generators such as Javadoc, Doxygen extracts information from both the comment and the symbolic (non-comment) code. A comment is associated with a programming symbol by immediately preceding it in the code. Markup in the comments allows for controlling inclusion and formatting of the resulting documentation.

  5. doctest - Wikipedia

    en.wikipedia.org/wiki/Doctest

    Docstrings can in turn be extracted from program files to generate documentation in other formats such as HTML or PDF. A program file can be made to contain the documentation, tests, as well as the code and the tests easily verified against the code. This allows code, tests, and documentation to evolve together.

  6. Sphinx (documentation generator) - Wikipedia

    en.wikipedia.org/wiki/Sphinx_(documentation...

    It is also used for the Blender user manual [10] and Python API documentation. [11] In 2010, Eric Holscher announced [12] the creation of the Read the Docs project as part of an effort to make maintenance of software documentation easier. Read the Docs automates the process of building and uploading Sphinx documentation after every commit.

  7. Help:Cheatsheet - Wikipedia

    en.wikipedia.org/wiki/Help:Cheatsheet

    Main page; Contents; Current events; Random article; About Wikipedia; Contact us

  8. Natural Language Toolkit - Wikipedia

    en.wikipedia.org/wiki/Natural_Language_Toolkit

    The Natural Language Toolkit, or more commonly NLTK, is a suite of libraries and programs for symbolic and statistical natural language processing (NLP) for English written in the Python programming language. It supports classification, tokenization, stemming, tagging, parsing, and semantic reasoning functionalities. [4]

  9. Cypher (query language) - Wikipedia

    en.wikipedia.org/wiki/Cypher_(query_language)

    Supported data types include scalar value types such as boolean, string, number, integer, and floating-point numbers. It also supports temporal types like datetime, localdatetime, date, time, localtime, and duration. Container data types for maps and lists are available, along with graph types for node, relationship, path, and a void type. [5]