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Pip's command-line interface allows the install of Python software packages by issuing a command: pip install some-package-name. Users can also remove the package by issuing a command: pip uninstall some-package-name. pip has a feature to manage full lists of packages and corresponding version numbers, possible through a "requirements" file. [14]
Visual Studio Code was first announced on April 29, 2015, by Microsoft at the 2015 Build conference. A preview build was released shortly thereafter. [13]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.
PyPI as an index allows users to search for packages by keywords or by filters against their metadata, such as free software license or compatibility with POSIX. [9] A single entry on PyPI is able to store, aside from just a package and its metadata, previous releases of the package, precompiled wheels (e.g. containing DLLs on Windows), as well ...
vcpkg provides access to C and C++ libraries to its supported platforms. The command-line utility is currently available on Windows, macOS and Linux. [2]vcpkg was first announced at CppCon 2016.
Installation (or setup) of a computer program (including device drivers and plugins), is the act of making the program ready for execution.Installation refers to the particular configuration of software or hardware with a view to making it usable with the computer.
Python is a multi-paradigm programming language. Object-oriented programming and structured programming are fully supported, and many of their features support functional programming and aspect-oriented programming (including metaprogramming [71] and metaobjects). [72]
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]
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.