Installation on Windows

To use DVC as a Python library, you can install it with conda or with pip.

See Running DVC on Windows for important tips to improve your experience on Windows.

Install with choco

The easiest way to install from command line for most cases is to install Chocolatey on your machine, and use the choco command:

$ choco install dvc

Install with winget

$ winget install --id Iterative.DVC

Install with conda

Requires Miniconda or Anaconda Distribution.

You can use conda from Anaconda Prompt, a POSIX-like command line terminal in Windows.

$ conda install -c conda-forge mamba # installs much faster than conda
$ mamba install -c conda-forge dvc

Depending on the type of the remote storage you plan to use, you might need to install optional dependencies: dvc-s3, dvc-azure, dvc-gdrive, dvc-gs, dvc-oss, dvc-ssh.

Example: with support for Amazon S3 storage

$ conda install -c conda-forge mamba # installs much faster than conda
$ mamba install -c conda-forge dvc-s3

In this case it installs the boto3 library along with DVC.

Install with pip

We strongly recommend creating a virtual environment or using pipx to encapsulate your local environment.

Note that Python 3.8+ is needed to get the latest version of DVC.

$ pip install dvc

Depending on the type of the remote storage you plan to use, you might need to install optional dependencies: [s3], [azure], [gdrive], [gs], [oss], [ssh]. Use [all] to include them all.

Example: with support for Amazon S3 storage

$ pip install "dvc[s3]"

In this case it installs the boto3 library along with DVC.

Windows installer

A quick way is to use the self-contained, executable installer (binary), which is available from the big "Download" button on the home page.

You'll need to download and run the installer again each time you want to update DVC. You may use Windows Uninstaller to remove the program.

Note that this method by default enables symlink permissions for all users, so they can use them to optimize DVC operations.