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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.
Python is a high-level, general-purpose programming language. Its design philosophy emphasizes code readability with the use of significant indentation. [33] Python is dynamically type-checked and garbage-collected. It supports multiple programming paradigms, including structured (particularly procedural), object-oriented and functional ...
You are free: to share – to copy, distribute and transmit the work; to remix – to adapt the work; Under the following conditions: attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made.
Anaconda is an open source [9] [10] data science and artificial intelligence distribution platform for Python and R programming languages.Developed by Anaconda, Inc., [11] an American company [1] founded in 2012, [11] the platform is used to develop and manage data science and AI projects. [9]
The default can be overridden (e.g. in source code comment) to Python 3 (or 2) syntax. Since Python 3 syntax has changed in recent versions, Cython may not be up to date with the latest additions. Cython has "native support for most of the C++ language" and "compiles almost all existing Python code". [7] Cython 3.0.0 was released on 17 July ...
IPython continued to exist as a Python shell and kernel for Jupyter, but the notebook interface and other language-agnostic parts of IPython were moved under the Jupyter name. [11] [12] Jupyter is language agnostic and its name is a reference to core programming languages supported by Jupyter, which are Julia, Python, and R. [13]
VPython is Open Source, and a part of the Python Library, combining the Python programming language with a 3D graphics module called Visual.. This library application allows users to create 3D objects, such as spheres and cones, and then display these objects in an app window.
SimpleITK: A Simplified Path to Insight - an online tutorial using Jupyter notebooks in Python. Organization on GitHub; Short examples illustrating how to use some of the library components are available on read the docs. Class and procedure documentation is available via Doxygen.