install
Install Git hooks into the DVC repository to automate certain common actions.
Synopsis
usage: dvc install [-h] [-q | -v] [--use-pre-commit-tool]
Description
DVC provides an intelligent data repository on top of a regular Git repo to
store code and configuration files. With dvc install
, the two are more tightly
integrated in order to cause certain convenient actions to happen automatically.
Note that this command requires the DVC project to be a Git
repository. But the hooks won't activate if the current branch (commit, tag,
etc.) doesn't have DVC initialized (no .dvc/
directory present).
Namely:
Checkout: For any commit hash, branch or tag, git checkout
restores the
DVC project files corresponding to that
version. Some of these files, in turn refer to data stored in
cache, but not necessarily current in the workspace.
Normally, it's necessary to use dvc checkout
to also update the workspace
accordingly.
This hook automates dvc checkout
after git checkout
.
Commit/Reproduce: Before committing DVC changes with Git, it may be
necessary using dvc commit
to store new data files not yet in cache. Or the
changes might require reproducing the corresponding
pipeline (with dvc repro
) to regenerate the
project's results (which implicitly commits them to DVC as well).
This hook automates dvc status
before git commit
when needed, to remind the
user to employ either dvc commit
or dvc repro
.
Push: While publishing changes to the Git remote with git push
, its easy
to forget that the dvc push
command is necessary to upload new or updated data
files and directories tracked by DVC to remote storage.
This hook automates dvc push
before git push
.
Installed Git hooks
- A
post-checkout
hook executesdvc checkout
aftergit checkout
to automatically update the workspace with the correct data file versions. - A
pre-commit
hook executesdvc status
beforegit commit
to inform the user about the differences between cache and workspace. - A
pre-push
hook executesdvc push
beforegit push
to upload files and directories tracked by DVC to thedvc remote default
.
If a hook already exists, DVC will raise an exception. In that case, try to manually edit the existing file or remove it and retry install.
For more information about git hooks, refer to the git-scm documentation.
Disable Git hooks
When you use dvc install
, it creates three files under the .git/hooks
directory:
.git/hooks
├── post-checkout
├── pre-commit
└── pre-push
To disable them, you need to remove or edit those files (i.e.
rm .git/hooks/post-checkout
, vim .git/hooks/pre-commit
).
Using the Pre-commit tool
DVC provides support to manage Git hooks with
pre-commit. To adjust .pre-commit-config.yaml
, you
can either use dvc install --use-pre-commit-tool
or add these entries by hand:
repos:
- hooks:
- id: dvc-pre-commit
language_version: python3
stages:
- pre-commit
- id: dvc-pre-push
# use s3/gs/etc instead of all to only install specific cloud support
additional_dependencies: ['.[all]']
language_version: python3
stages:
- pre-push
- always_run: true
id: dvc-post-checkout
language_version: python3
stages:
- post-checkout
repo: https://github.com/iterative/dvc
rev: 3.56.0
# rev should be set to a specific revision (e.g. 3.56.0) since pre-commit
# does not allow using mutable references.
# If using `main`, see pre-commit guide:
# https://pre-commit.com/#using-the-latest-version-for-a-repository
Note that by default, the pre-commit tool only installs pre-commit
hooks. To
enable the pre-push
and post-checkout
hooks, you must explicitly configure
the tool this way:
$ pre-commit install --hook-type pre-push --hook-type post-checkout --hook-type pre-commit
Options
-
--use-pre-commit-tool
- configures DVC pre-commit, pre-push, post-checkout Git hooks in the pre-commit config file (.pre-commit-config.yaml
). -
-h
,--help
- prints the usage/help message, and exit. -
-q
,--quiet
- do not write anything to standard output. Exit with 0 if no problems arise, otherwise 1. -
-v
,--verbose
- displays detailed tracing information.
Examples
Let's employ a simple workspace with some data, code, ML models,
pipeline stages, such as the DVC project created in our
Get Started section. Then we can see what happens with
dvc install
in different situations.
Start by cloning our example repo if you don't already have it:
$ git clone https://github.com/iterative/example-get-started
$ cd example-get-started
Now let's install the requirements. But before we do that, we strongly recommend creating a virtual environment:
$ python3 -m venv .env
$ source .env/bin/activate
$ pip install -r src/requirements.txt
Download the precomputed data using:
$ dvc pull -aT
Example: Checkout both Git and DVC
Switching from one Git commit to another (with git checkout
) may change the
set of DVC files in the workspace. This could mean
that the currently present data no longer matches the project's version (which
can be fixed with dvc checkout
).
Let's first list the available tags in the Get Started repo:
$ git tag
0-git-init
1-dvc-init
2-track-data
3-config-remote
4-import-data
5-source-code
6-prepare-stage
7-ml-pipeline
8-evaluation
9-bigrams-model
10-bigrams-experiment
...
These tags are used to mark points in the development of the project, and to
document specific experiments conducted in it. To take a look at one, we
checkout the 7-ml-pipeline
tag:
$ git checkout 7-ml-pipeline
Note: checking out '7-ml-pipeline'.
You are in 'detached HEAD' state...
$ dvc status
featurize:
changed outs:
modified: data/features
...
$ dvc checkout
$ dvc status
Data and pipelines are up to date.
After running git checkout
we are also shown a message saying You are in
'detached HEAD' state. Returning the workspace to a normal state requires
running git checkout master
.
We also see that the first dvc status
tells us about differences between the
project's cache and the data files currently in the workspace. Git
changed the DVC files in the workspace, which changed references to data files.
dvc status
first informed us that the data files in the workspace no longer
matched the hash values in the corresponding .dvc
and dvc.lock
files.
Running dvc checkout
then brings them up to date, and a second dvc status
tells us that the data files now do match the DVC files.
$ git checkout master
Previous HEAD position was 6666298 Create ML pipeline stages
Switched to branch 'master'
Your branch is up to date with 'origin/master'.
$ dvc checkout
We've seen the default behavior with there being no Git hooks installed. We want
to see how the behavior changes after installing the Git hooks. We must first
reset the workspace to the HEAD
commit before installing the hooks.
$ dvc install
$ cat .git/hooks/pre-commit
#!/bin/sh
exec dvc status
$ cat .git/hooks/post-checkout
#!/bin/sh
exec dvc checkout
The two Git hooks have been installed, and the one of interest for this exercise
is the post-checkout
script that runs after git checkout
.
We can now repeat the command run earlier, to see the difference.
$ git checkout 7-ml-pipeline
HEAD is now at 6666298 Create ML pipeline stages
M model.pkl
M data/features/
$ dvc status
Data and pipelines are up to date.
Look carefully at this output and it is clear that the dvc checkout
command
has indeed been run. As a result the workspace is up to date with the data files
matching what is referenced in the DVC files.
Example: Showing DVC status when committing with Git
To follow this example, start with the same workspace as before, making sure it
is not in a detached HEAD state by running git checkout master
.
If we simply edit one of the code files:
$ vi src/featurization.py
$ git commit -a -m "modified featurization"
featurize:
changed deps:
modified: src/featurization.py
[master 1116ddc] modified featurization
1 file changed, 1 insertion(+), 1 deletion(-)
We see that the output of dvc status
has appeared in the git commit
interaction. This new behavior corresponds to the Git hook installed, and it
informs us that the workspace is out of sync. Therefore, we know that
dvc repro
command is needed:
$ dvc repro
...
To track the changes with git run:
git add dvc.lock
$ git status -s
M dvc.lock
$ git commit -a -m "updated data after modified featurization"
Data and pipelines are up to date.
[master 78d0c44] modified featurization
5 files changed, 12 insertions(+), 12 deletions(-)
After reproducing the pipeline, the data files should be in sync with the code
and configuration, and we want to commit the changes with Git. In doing so,
dvc status
is run automatically again, informing us that the data files have
been updated indeed, with the Data and pipelines are up to date.
message.