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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. Jupyter is financially sponsored by NumFOCUS. [1]
Nuitka compiles Python into C. [164] It works with Python 3.4 to 3.12 (and 2.6 and 2.7), for Python's main supported platforms (and Windows 7 or even Windows XP) and for Android. It claims complete support for Python 3.10, some support for 3.11 and 3.12 and experimental support for Python 3.13. It supports macOS including Apple Silicon-based.
In addition to including the features, languages and plugins supported by VS Code, it has unique functionality built by Google. These include a built-in generative artificial intelligence assistant powered by Gemini , Nix integrations, and iOS and Android emulators .
Visual Studio Code was first announced on April 29, 2015 by Microsoft at the 2015 Build conference. A preview build was released shortly thereafter. [14]On November 18, 2015, the project "Visual Studio Code — Open Source" (also known as "Code — OSS"), on which Visual Studio Code is based, was released under the open-source MIT License and made available on GitHub.
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]
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]
Mojo was created for an easy transition from Python. The language has syntax similar to Python's, with inferred static typing, [30] and allows users to import Python modules. [31] It uses LLVM and MLIR as its compilation backend. [12] [32] [33] The language also intends to add a foreign function interface to call C/C++ and Python code.
PyPy (/ ˈ p aɪ p aɪ /) is an implementation of the Python programming language. [2] PyPy often runs faster than the standard implementation CPython because PyPy uses a just-in-time compiler. [3] Most Python code runs well on PyPy except for code that depends on CPython extensions, which either does not work or incurs some overhead when run ...