> ## Documentation Index > Fetch the complete documentation index at: https://mintlify.com/treeverse/dvc/llms.txt > Use this file to discover all available pages before exploring further. # dvc commit > Record changes to files or directories tracked by DVC ## Synopsis ```bash theme={null} dvc commit [options] [...] ``` ## Description The `dvc commit` command records changes to files or directories tracked by DVC by storing the current versions in the cache. It updates the hash values in `.dvc` files or `dvc.lock` to match the current workspace state. Use `dvc commit` when: * You've modified tracked data files and want to save the new version * You used `dvc add --no-commit` and now want to commit the data to cache * You've updated outputs of a DVC pipeline stage and want to persist them * You need to update `.dvc` file metadata to reflect current file state The commit operation: 1. Computes hashes of the current workspace files 2. Moves/copies the files into the DVC cache 3. Updates `.dvc` or `dvc.lock` files with new hash values 4. Creates links from cache back to workspace Unlike Git's commit, `dvc commit` doesn't create a new version history entry. It updates the current tracking state. Version history is maintained through Git commits of the `.dvc` files. ## Options Limit command scope to specific tracked files/directories, `.dvc` files, or stage names. If not specified, commits all changed tracked data. ```bash theme={null} dvc commit data/raw.csv models/ ``` Commit data even if hash values for dependencies or outputs did not change. Forces a recommit of the data. ```bash theme={null} dvc commit --force train.dvc ``` Use this when you want to ensure data is in cache even if DVC thinks nothing changed. Commit all dependencies of the specified target. Useful for pipeline stages that depend on other stages. ```bash theme={null} dvc commit --with-deps evaluate.dvc ``` Commit cache for subdirectories of the specified directory. ```bash theme={null} dvc commit --recursive data/ ``` Don't recreate links from cache to workspace after committing. By default, after committing files to cache, DVC recreates the workspace files as links to the cache to save space. ## Examples ### Basic commit Commit all modified tracked files: ```bash theme={null} dvc commit ``` ```terminal theme={null} Committing data/train.csv Committing models/model.pkl ``` ### Commit specific files Commit only specific targets: ```bash theme={null} dvc commit data/processed.csv ``` ### Commit after modifying data Typical workflow when updating tracked data: ```bash theme={null} # Modify your data file echo "new data" >> data/dataset.csv # Commit the changes to DVC dvc commit data/dataset.csv.dvc # The .dvc file now has updated hashes git add data/dataset.csv.dvc git commit -m "Update dataset" ``` ### Commit after add --no-commit When you used `--no-commit` during add: ```bash theme={null} # Add file without caching dvc add --no-commit large-file.bin # Later, commit it to cache dvc commit large-file.bin.dvc ``` ### Force commit Force a commit even when DVC thinks nothing changed: ```bash theme={null} dvc commit --force data/dataset.csv.dvc ``` This will recompute hashes and move data to cache even if the file appears unchanged. ### Commit pipeline outputs Commit outputs from a DVC pipeline stage: ```bash theme={null} # After running a pipeline manually or with modified code dvc commit train.dvc ``` ### Recursive commit Commit all `.dvc` files in a directory: ```bash theme={null} dvc commit --recursive experiments/ ``` ## Example workflows ### Workflow 1: Update tracked data ```bash theme={null} # 1. Modify your data python process_data.py # Updates data/processed.csv # 2. Commit changes to DVC dvc commit data/processed.csv.dvc # 3. Commit the updated .dvc file to Git git add data/processed.csv.dvc git commit -m "Update processed data with new logic" # 4. Push both Git and DVC changes git push dvc push ``` ### Workflow 2: Pipeline development ```bash theme={null} # 1. Modify your training script vim train.py # 2. Run the modified pipeline dvc repro # 3. If you modified outputs manually after repro dvc commit train.dvc # 4. Commit to Git git add train.dvc dvc.lock git commit -m "Update training pipeline" ``` ### Workflow 3: Batch operations ```bash theme={null} # Process multiple files python batch_process.py # Modifies multiple tracked files # Commit all changes dvc commit # Review what changed git diff *.dvc # Commit to Git git add *.dvc git commit -m "Batch update all datasets" ``` ## Understanding the difference from Git | Operation | Git Commit | DVC Commit | | ------------------- | ----------------------------------- | ---------------------------------------------------- | | **What it does** | Creates a new commit in Git history | Updates hash in `.dvc` files and moves data to cache | | **Version control** | Yes, creates history entry | No, just updates current state | | **What's tracked** | Text files, code, `.dvc` files | Large data files, models, datasets | | **Where data goes** | Git repository | DVC cache (local or remote) | **Best practice**: After `dvc commit`, always `git commit` the updated `.dvc` files to create a version history entry. ## Handling changes When you commit, DVC may prompt you to confirm changes: ```terminal theme={null} dependencies ['data/raw.csv'] and outputs ['data/processed.csv'] of train.dvc changed. Are you sure you want to commit it? [y/n] ``` To skip the prompt, use `--force`: ```bash theme={null} dvc commit --force ``` ## Performance considerations **Commit specific targets** - Instead of committing everything with `dvc commit`, specify targets to avoid unnecessary hash computations for unchanged files. **Use --no-relink for speed** - If you don't need workspace files updated, use `--no-relink` to skip the relinking step. ## Related commands * `dvc add` - Start tracking new files * `dvc checkout` - Update workspace from cache * `dvc push` - Upload committed data to remote storage * `dvc status` - Check which files have changed