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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]
This page was last edited on 26 November 2021, at 16:57 (UTC).; Text is available under the Creative Commons Attribution-ShareAlike 4.0 License; additional terms may apply.
Google App Engine, a platform for developing and hosting web applications in Google-managed data centers, including Python. Grok, a web framework based on Zope Toolkit technology; Jam.py (web framework), a "full stack" WSGI rapid application development framework; Nevow, a web application framework originally developed by the company Divmod
As the notebook interface increased in popularity over the next two decades, notebooks for various computational back ends ("kernels") have been introduced, including MATLAB, Python, Julia, R, Scala, Elixir, SQL, and others. [16] [17] The variety of notebook interface has since been extended and new forms are still evolving. [18]
Google Cloud Platform is a part [8] of Google Cloud, which includes the Google Cloud Platform public cloud infrastructure, as well as Google Workspace (G Suite), enterprise versions of Android and ChromeOS, and application programming interfaces (APIs) for machine learning and enterprise mapping services.
This is a list of notable library packages implementing a graphical user interface (GUI) platform-independent GUI library (PIGUI). These can be used to develop software that can be ported to multiple computing platforms with no change to its source code.
Cross-platform: Python: Tkinter: PSFL: Yes Yes Yes No Unknown No No Yes No Yes Yes Unknown No No Komodo IDE: ActiveState: 10.2 2017-02-21 Cross-platform: Unknown Mozilla platform Proprietary: Yes Yes Yes Unknown Unknown Unknown Unknown Unknown Unknown Unknown Unknown Unknown Bazaar, CVS, Git, Mercurial, Perforce, SVN: Un ...
In May 2017, Google announced a software stack specifically for mobile development, TensorFlow Lite. [29] In January 2019, the TensorFlow team released a developer preview of the mobile GPU inference engine with OpenGL ES 3.1 Compute Shaders on Android devices and Metal Compute Shaders on iOS devices. [ 30 ]