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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]
Some package managers, including pip, use PyPI as the default source for packages and their dependencies. [6] [7] As of 6 May 2024, more than 530,000 Python packages are available. PyPI primarily hosts Python packages in the form of source archives, called "sdists", or of "wheels" [8] that may contain binary modules from a compiled language.
The following package management systems distribute the source code of their apps. Either the user must know how to compile the packages, or they come with a script that automates the compilation process. For example, in GoboLinux a recipe file contains information on how to download, unpack, compile and install a package using its Compile tool ...
A package manager or package-management system is a collection of software tools that automates the process of installing, upgrading, configuring, and removing computer programs for a computer in a consistent manner. [1] A package manager deals with packages, distributions of software and data in archive files.
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The Windows Installer CleanUp Utility is a legacy software utility for the Microsoft Windows operating system designed to solve installation problems of apps that use the Windows Installer technology. An app whose Windows Installer entries are damaged cannot be uninstalled or reinstalled via the normal means.
Called meta-build tools, these generate configuration files for other build tools such as those listed above.. CMake – Cross-platform build tool for configuring platform-specific builds; very popoular; integrated with IDEs such as Qt Creator, [1] KDevelop and GNOME Builder [2]
Data cleansing or data cleaning is the process of identifying and correcting (or removing) corrupt, inaccurate, or irrelevant records from a dataset, table, or database.It involves detecting incomplete, incorrect, or inaccurate parts of the data and then replacing, modifying, or deleting the affected data. [1]