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Kivy is a free and open source Python framework for developing mobile apps and other multitouch application software with a natural user interface (NUI).It is distributed under the terms of the MIT License, and can run on Android, iOS, Linux, macOS, and Windows.
PyCharm is an integrated development environment (IDE) used for programming in Python. It provides code analysis, a graphical debugger, an integrated unit tester, integration with version control systems, and supports web development with Django. PyCharm is developed by the Czech company JetBrains and built on their IntelliJ platform. [4]
It is also used for the Blender user manual [10] and Python API documentation. [11] In 2010, Eric Holscher announced [12] the creation of the Read the Docs project as part of an effort to make maintenance of software documentation easier. Read the Docs automates the process of building and uploading Sphinx documentation after every commit.
Flask is a micro web framework written in Python.It is classified as a microframework because it does not require particular tools or libraries. [2] It has no database abstraction layer, form validation, or any other components where pre-existing third-party libraries provide common functions.
Shiny is a web framework for developing web applications (apps), originally in R and since 2022 in python. It is free and open source. [2] It was announced by Joe Cheng, CTO of Posit, formerly RStudio, in 2012. [3] One of the uses of Shiny has been in fast prototyping. [4] In 2022, a separate implementation Shiny for Python was announced. [5]
It is an open-source cross-platform integrated development environment (IDE) for scientific programming in the Python language.Spyder integrates with a number of prominent packages in the scientific Python stack, including NumPy, SciPy, Matplotlib, pandas, IPython, SymPy and Cython, as well as other open-source software.
Django's primary goal is to ease the creation of complex, database-driven websites. The framework emphasizes reusability and "pluggability" of components, less code, low coupling, rapid development, and the principle of don't repeat yourself. [9] Python is used throughout, even for settings, files, and data models.
PyJL compiles/transpiles a subset of Python to "human-readable, maintainable, and high-performance Julia source code". [88] Despite claiming high performance, no tool can claim to do that for arbitrary Python code; i.e. it's known not possible to compile to a faster language or machine code. Unless semantics of Python are changed, but in many ...