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Python Any 2013 1.0.1 (2021) Unlicense (PD) perldoc: Larry Wall: Text Perl Any 1994 5.16.3 Artistic, GPL phpDocumentor: Joshua Eichorn Text PHP Any 2000 3.0.0 LGPL for 1.x, MIT for 2+ pydoc: Ka-Ping Yee [1] Text Python Any 2000 in Python core Python: RDoc: Dave Thomas Text C, C++, Ruby Any 2001/12/14 in Ruby core Ruby: ROBODoc: Frans Slothouber ...
Umple code embedding one or more of Java, Python, C++, PHP or Ruby Pure Umple code describing associations, patterns, state machines, etc. Java, Python, C++, PHP, Ruby, ECcore, Umlet, Yuml, Textuml, JSON, Papyrus XMI, USE, NuXMV, Alloy Velocity apache: Java Passive [2] Tier Templates Java driver code Any text Yii2 Gii: PHP Active Tier
It was developed for, and is used extensively by, the Python project for documentation. [9] Since its introduction in 2008, Sphinx has been adopted by many other important Python projects, including Bazaar, SQLAlchemy, MayaVi, SageMath, SciPy, Django and Pylons. It is also used for the Blender user manual [10] and Python API documentation. [11]
It works on Linux, Windows, macOS, and is available in Python, [8] R, [9] and models built using CatBoost can be used for predictions in C++, Java, [10] C#, Rust, Core ML, ONNX, and PMML. The source code is licensed under Apache License and available on GitHub. [6] InfoWorld magazine awarded the library "The best machine learning tools" in 2017.
(For example, upon encountering a variable declaration, user-written code could save the name and type of the variable into an external data structure, so that these could be checked against later variable references detected by the parser.)
Parse tree generated with NLTK. 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.
Soon after, the Python and R packages were built, and XGBoost now has package implementations for Java, Scala, Julia, Perl, and other languages. This brought the library to more developers and contributed to its popularity among the Kaggle community, where it has been used for a large number of competitions. [11]
Boost is a set of libraries for the C++ programming language that provides support for tasks and structures such as linear algebra, pseudorandom number generation, multithreading, image processing, regular expressions, and unit testing. It contains 164 individual libraries (as of version 1.76).