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CppUnit is a unit testing framework module for the C++ programming language. It allows unit-testing of C sources as well as C++ with minimal source modification. It was started around 2000 by Michael Feathers as a C++ port of JUnit for Windows and ported to Unix by Jerome Lacoste. [2] The library is released under the GNU Lesser General Public ...
Open source framework for writing Unit, Integration and functional tests. It includes pre-configured logging framework and extent reports, utilities to write flow for manual/semi-automated testing. It supports BDD testing using cucumber scripts. Arquillian: Yes [294] Open source framework for writing Integration and functional tests.
Python 3.0, released in 2008, was a major revision not completely backward-compatible with earlier versions. Python 2.7.18, released in 2020, was the last release of Python 2. [37] Python consistently ranks as one of the most popular programming languages, and has gained widespread use in the machine learning community. [38] [39] [40] [41]
Project Jupyter's name is a reference to the three core programming languages supported by Jupyter, which are Julia, Python and R. Its name and logo are an homage to Galileo's discovery of the moons of Jupiter, as documented in notebooks attributed to Galileo. Jupyter is financially sponsored by NumFOCUS. [1]
In 2009, a Google sponsored branch named Unladen Swallow was created to incorporate a just-in-time compiler into CPython. [7] [8] Development ended in 2011 without it being merged into the main implementation, [9] though some of its code, such as improvements to the cPickle module, made it in. [10] [7]
SDKs may include sample software and/or technical notes along with documentation, and tutorials to help clarify points made by the primary reference material. [4] [5] SDKs often include licenses that make them unsuitable for building software intended to be developed under an incompatible license.
For Dummies is an extensive series of instructional reference books which are intended to present non-intimidating guides for readers new to the various topics covered. The series has been a worldwide success with editions in numerous languages.
scikit-learn (formerly scikits.learn and also known as sklearn) is a free and open-source machine learning library for the Python programming language. [3] It features various classification, regression and clustering algorithms including support-vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific ...