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A Jupyter Notebook document is a JSON file, following a versioned schema, usually ending with the ".ipynb" extension. The main parts of the Jupyter Notebooks are: Metadata, Notebook format and list of cells. Metadata is a data Dictionary of definitions to set up and display the notebook. Notebook Format is a version number of the software.
A notebook interface or computational notebook is a virtual notebook environment used for literate programming, a method of writing computer programs. [1] Some notebooks are WYSIWYG environments including executable calculations embedded in formatted documents; others separate calculations and text into separate sections.
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 .
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]
[10] [11] [12] It is available both in browsers via Jupyter notebooks, [12] [13] and locally on Linux and macOS. [ 14 ] [ 15 ] Mojo aims to combine the usability of a high-level programming language , specifically Python , with the performance of a system programming language such as C++ , Rust , and Zig . [ 16 ]
Cython is written in Python and C and works on Windows, macOS, and Linux, producing C source files compatible with CPython 2.6, 2.7, and 3.3 and later versions. The Cython source code that Cython compiles (to C) can use both Python 2 and Python 3 syntax, defaulting to Python 2 syntax in Cython 0.x and Python 3 syntax in Cython 3.x.
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R is a programming language for statistical computing and data visualization.It has been adopted in the fields of data mining, bioinformatics and data analysis. [9]The core R language is augmented by a large number of extension packages, containing reusable code, documentation, and sample data.