For all the devs out there willing to contribute to DVC, here is a quick guide to contributing to iterative/dvc repo
๐ Open a new issue
๐ป Set up a dev environment
๐ด Fork iterative/dvc
๐งช Add tests and run them locally
โฌ๏ธ Submit a pull request @iterativeai
๐งต [1/7]
๐ Open a new issue
Open a new issue in the issue tracker, whether it be a bug report or a feature request. ๐๐ฝ github.com/iterative/dvc/โฆ
๐งต[2/7]
๐ด Fork iterative/dvc
Fork iterative/dvc and then clone it into your local computer to start contributing.
๐งต[3/7]
๐ป Set up a dev environment
Make sure that you have Python 3.8 or higher installed. Install DVC in editable mode with โpip install -e ".[all,tests]" '.
All this is preferably in a virtual environment.
๐งต [4/7]
๐งช Add tests and run them locally
We have unit tests in "tests/unit/" and functional tests in "tests/func/". Consider writing the former to ensure complicated functions and classes behave as expected.
The simplest way to run tests is using the command "python-m tests".
๐งต [5/7]
Well done ๐. Weโre just about thereโฆ
โฌ๏ธ Submit a pull request
And finally, submit a pull request, referencing any issues it addresses and get it reviewed and merged. ๐
๐งต[6/7]
โค๏ธThanks for reading
We all could make #DVC more helpful for everyone together ๐ค
Go ahead, fork DVC and try resolving an issue ๐๐ฝ github.com/iterative/dvc
๐งต [7/7]
โข โข โข
Missing some Tweet in this thread? You can try to
force a refresh
๐ฆ Here are some of the cool commands you can try out right now in the DVC command line interface!
๐ป dvc dag
๐ง dvc freeze
๐ฆ dvc move
๐ dvc metrics show
๐งน dvc gc
๐งต [1/7]
๐ป dvc dag
๐๐๐ ๐๐๐ is very helpful in quickly checking out the stages of a pipeline up to the target stage in a simple visual representation. If the target is omitted, it will show the full project DAG.
๐งต [2/7]
๐ง dvc freeze
๐๐๐ ๐๐๐๐๐ฃ๐ helps us to freeze stages until ๐๐๐ ๐๐๐๐๐๐๐ฃ๐ is used on them. Frozen stages are never executed by ๐๐๐ ๐๐๐๐๐.
๐ฆ Did you hear? By popular demand, CML.dev now supports @Bitbucket Pipelines, rounding out our coverage of the leading version control platforms! ๐
๐งต 1/6
You can get started with CML in @Bitbucket by forking this repo and cloning it to your local workstation.
Quickly run new experiments and compare their resulting metrics in the experiments table. Use the command palette or buttons to run new experiments, or add them to the queue for later.