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Before executing any commands I think it’s better to first talk about the concept of VCS and Git. This might all seem a little daunting, but this is where a Version Control System (VCS) comes ...
Git does periodic repacking automatically, but manual repacking is also possible with the git gc command. [46] For data integrity, both the packfile and its index have an SHA-1 checksum [47] inside, and the file name of the packfile also contains an SHA-1 checksum. To check the integrity of a repository, run the git fsck command. [48] [49]
Tig is an ncurses-based text-mode interface for Git. [1] [2] It functions mainly as a Git repository browser, but it can also assist in staging changes for committing at the chunk level and can act as a pager for output from various Git commands.
Wiki-to-Git or Wiki2Git is a tool that helps to download MediaWiki page history and push it to a Git repository. Wiki2Git can be used to export things like a Wikipedia gadget (or a user script) to some Git server (e.g. GitHub or GitLab or Gitea). The history of the Git repository will preserve authors and original messages (original description ...
TortoiseGit is a Git revision control client, implemented as a Windows shell extension and based on TortoiseSVN. It is free software released under the GNU General Public License. In Windows Explorer, besides showing context menu items for Git commands, TortoiseGit provides icon overlays that indicate the status of Git working trees and files.
Cogito (originally git-pasky) is a revision control system layered on top of Git. It is historically the first Git frontend, which appeared in April 2005, just days after Git itself. While Git was initially meant just as the low-level interface, Cogito started with the stated goal of becoming a user-friendly front-end.
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. [6]
ML experiments: To solve the problem of Git overhead, when hundreds of experiments need to be run in a single day and each experiment run requires additional Git commands, DVC 2.0 introduced the lightweight experiments feature. It allows its users to auto-track ML experiments and capture code changes.