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GitHub (/ ˈ ɡ ɪ t h ʌ b /) is a proprietary developer platform that allows developers to create, store, manage, and share their code. It uses Git to provide distributed version control and GitHub itself provides access control, bug tracking, software feature requests, task management, continuous integration, and wikis for every project. [8]
Git would come to power GitHub. [7] 2006: 11 October: Competition: First public Git free hosting platform repo.or.cz is fully launched. [8] This came several weeks after an initial launch focusing only on public mirroring and gitweb services. [9] 2007: 19 October: Company: Development of the GitHub platform begins. [10] 2008: 29 February ...
git clone [URL], which clones, or duplicates, a git repository from an external URL. git add [file], which adds a file to git's working directory (files about to be committed). git commit -m [commit message], which commits the files from the current working directory (so they are now part of the repository's history).
[1] [2] [3] Git, the world's most popular version control system, [4] is a distributed version control system. In 2010, software development author Joel Spolsky described distributed version control systems as "possibly the biggest advance in software development technology in the [past] ten years".
Bitbucket Server (formerly known as Stash [18]) is a combination Git server and web interface product written in Java and built with Apache Maven. [19] It allows users to do basic Git operations (such as reviewing or merging code, similar to GitHub) while controlling read and write access to the code.
Monotone (mtn), Mercurial (hg) and git call it "clone"; Bazaar calls it "branch". [citation needed] In some distributed revision control systems, such as Darcs, there is no distinction made between repositories and branches; in these systems, fetching a copy of a repository is equivalent to branching.
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DVC is a free and open-source, platform-agnostic version system for data, machine learning models, and experiments. [1] It is designed to make ML models shareable, experiments reproducible, [2] and to track versions of models, data, and pipelines. [3] [4] [5] DVC works on top of Git repositories [6] and cloud storage. [7]