Project Structure

Using dvc init in your workspace will start a DVC project, including the internal .dvc/ directory. From there on, you will create and manage different DVC files and populate the cache as you use DVC and work on your data science experiments.

• dvc.yaml pipelines files define stages that form the pipeline(s) of a project. All stage-based features such as dvc params, dvc metrics, and dvc plots are specified here.
• .dvc files ("dot DVC files") are placeholders to track data files and directories.
• .dvcignore files (optional) contain a list of paths for DVC to ignore, which can dramatically increase its operational performance.
• Internal files and directories in .dvc/ contains the local configuration file(s), default local cache location, and other utilities that DVC needs to operate.

These metafiles should be versioned with Git (in Git-enabled repositories).