# 使用 Homebrew, chocolatey, Nix, scoop, winget 安装 dvc 查看 dvc 的安装路径、可执行文件、元数据以及面向 AI 代理工作流的安全说明。 ## 安装 ```sh sudo av install brew:dvc ``` 其他安装命令: ### macOS - Homebrew (100%): ```sh brew install dvc ``` 证据: local Homebrew formula metadata ### Linux - Nix (92%): ```sh nix profile install nixpkgs#dvc ``` 证据: nixpkgs package indexes: dvc from https://raw.githubusercontent.com/NixOS/nixpkgs/master/pkgs/top-level/all-packages.nix ### Windows - Chocolatey (92%): ```sh choco install dvc ``` 证据: Chocolatey community package catalog: dvc from http://community.chocolatey.org/api/v2/Packages?$filter=IsLatestVersion&$select=Id&$top=1000&$skiptoken='11','dotnetcore-desktopruntime' - Scoop (92%): ```sh scoop install main/dvc ``` 证据: Scoop official bucket manifest trees: bucket/dvc.json from https://api.github.com/repos/ScoopInstaller/Main/git/trees/master?recursive=1 - winget (92%): ```sh winget install --id Iterative.DVC -e ``` 证据: Windows Package Manager source index: Iterative.DVC from https://cdn.winget.microsoft.com/cache/source.msix ## 软件包事实 - **软件包键:** brew:dvc - **软件包管理器:** Homebrew - **版本:** 3.67.1 - **来源摘要:** Git for data science projects - **主页:** - **最后更新:** 2026-07-25T12:27:58Z - **已生成:** 2026-08-03T19:37:03+00:00 ## 可执行文件 - dvc (别名) ## 安装行为 - Bottle: 不可用 ## 版本和新鲜度 - 页面生成时间: 2026-08-03 - 管理器版本: 3.67.1 ## 项目历史与用法 DVC, Data Version Control, is a Git-adjacent command-line system for versioning datasets, models, pipelines, and machine-learning experiments. Its package history matters because it made the everyday Git workflow feel usable for large data artifacts that do not belong directly inside a Git repository. ### 项目历史 The public GitHub repository was created in March 2017, and the oldest release metadata exposed by GitHub shows a beta release, 0.8.1, in May 2017. The project developed around the idea that code, data, model files, metrics, and pipeline stages should be reproducible from a repository without forcing large binary artifacts into Git itself. DVC 2.0.0 was released on 2021-03-03, reflecting a period when the tool had broadened from data-file tracking into experiment and pipeline workflows. The 3.x release line was active through 2026, with release metadata showing frequent 3.x updates and a 3.67.1 release on 2026-03-31. ### 采用历史 DVC became common in machine-learning engineering because it mapped data-science needs onto a familiar developer mental model: Git commits track code and lightweight metadata, while DVC remotes hold larger artifacts. Package-manager coverage across Homebrew, Chocolatey, Scoop, winget, Nix, and Python packaging reflects that it is used by both local workstation users and CI-oriented teams. Its adoption also followed the rise of reproducible ML pipelines and experiment tracking. Instead of being only a storage helper, DVC became a CLI layer for project structure: `dvc init`, `dvc add`, `dvc push`, `dvc pull`, `dvc repro`, and experiment commands give data-science repos repeatable operational verbs. ### 使用方式 Typical users initialize DVC inside an existing Git project, add datasets or model files to DVC tracking, configure a remote object store, and commit the generated metadata files to Git. Pipelines are then described so stages can be reproduced and cached, while results and metrics can be compared across experiments. DVC is especially useful when teams need a Git-like review and checkout workflow for data without storing gigabytes in Git history. It is also used in CI to fetch exact data/model versions and run reproducible training or evaluation jobs. ### 为什么软件包爱好者会关心 DVC is package-nerd significant because it is one of the clearest examples of a developer-tool CLI crossing into data science without abandoning Unix and Git habits. It treats datasets as content-addressed artifacts, keeps metadata text-friendly, and lets package managers install the same `dvc` command across macOS, Linux, and Windows. It also sits in a crowded but important lineage that includes Git LFS, lakeFS, MLflow, Pachyderm, and experiment trackers. DVC's distinction is that it keeps a repo-centered workflow rather than forcing every team into a hosted platform first. ### 时间线 - 2017-03-04: Public GitHub repository created. - 2017-05-04: Oldest visible GitHub release metadata shows beta release 0.8.1. - 2021-03-03: DVC 2.0.0 released. - 2023-2026: DVC 3.x became the long-running active release line. - 2026-03-31: GitHub release metadata shows DVC 3.67.1. ### Related projects - DVC is related to Git and Git LFS for version-control workflows, object stores such as S3-compatible remotes for artifact storage, and ML platforms such as MLflow and lakeFS that overlap with reproducibility, experiment, or data-versioning concerns. ### 来源 - - - - ## 安全说明 没有找到 dvc 的匹配本地密钥处理 manifest。Nucleus 软件包元数据仍在此发布，以便未来覆盖拥有稳定的软件包 URL。 ## Configuration and credential file locations These source-backed paths show where this package keeps local settings or durable credentials. Automic Vault can use them as review targets for secret scanning, migration, and command approval. ## Configuration files - Linux: ~/.config/dvc/config, /etc/xdg/dvc/config - macOS: ~/Library/Application Support/dvc/config, /Library/Application Support/dvc/config - Unix: .dvc/config.local, .dvc/config - Windows: .dvc\config.local, .dvc\config, %LocalAppData%\iterative\dvc\config, %AllUsersProfile%\Application Data\iterative\dvc\config ## Credential files - Unix: .dvc/config.local ## 其他软件包管理器记录 - Nix - dvc: normalized package name match | nixpkgs package indexes: dvc from https://raw.githubusercontent.com/NixOS/nixpkgs/master/pkgs/top-level/all-packages.nix - Chocolatey - dvc: normalized package name match | Chocolatey community package catalog: dvc from http://community.chocolatey.org/api/v2/Packages?$filter=IsLatestVersion&$select=Id&$top=1000&$skiptoken='11','dotnetcore-desktopruntime' - Scoop - main/dvc: normalized package name match | Scoop official bucket manifest trees: bucket/dvc.json from https://api.github.com/repos/ScoopInstaller/Main/git/trees/master?recursive=1 - winget - Iterative.DVC: normalized package name match | Windows Package Manager source index: Iterative.DVC from https://cdn.winget.microsoft.com/cache/source.msix ## Combined YAML source View the package source record on GitHub. [combined/dvc.yml](https://github.com/mxcl/pkgdb/blob/main/combined/dvc.yml) ## 来源 - pkg.so package database - Geiger risk classifier - curated configuration and credential file locations - curated package history - pkgdb category and tag curation - external package-manager database matches - cross-ecosystem install command graph