Project Structure

Using dvc init in your workspace will initialize a DVC project, including the internal .dvc/ directory. From there on, you will create and manage different DVC metafiles (below), and populate the cache with data artifacts as you work on your ML experiments.

• dvc.yaml 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.