تحديد مسار باستخدام مراحل DVC

DVC describes your whole pipeline in one file called dvc.yaml. It lists each stage, the command it runs, and what it depends on. 📄

You rarely hand-write the file. The dvc stage add command builds a stage entry for you from flags you pass on the command line.

The -d flag declares a dependency: a file or script the stage reads. DVC watches these to know when the stage needs to re-run.

The -o flag declares an output the stage produces. DVC tracks these files so later stages can depend on them in turn.

You connect stages by making one stage's output the next stage's dependency. That shared file is the link that forms the pipeline graph.

Each stage in dvc.yaml has a cmd plus its deps and outs. This is the readable record of how your model was built.

The dvc repro command executes the pipeline in dependency order, running each stage only if its inputs changed.

From the deps and outs, DVC infers the full DAG automatically. You never specify run order by hand; the graph decides it.

Run dvc dag to print the pipeline as a graph in your terminal. It is a quick way to confirm stages are wired the way you expect.

After a run, DVC writes dvc.lock with the exact hashes of every input and output. Commit it so teammates reproduce the same result.

dvc.yaml and dvc.lock are plain text, so they live in Git alongside your code. Your whole pipeline becomes versioned and reviewable.

Test your grasp of DVC stage flags.

You wired stages with deps and outs in dvc.yaml, then ran the graph with dvc repro. DVC tracks order and results for you. 🔗