Install

• Using pip
• Using conda
• Using mamba
• From source

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pip install skrub -U

Deep learning dependencies

Deep-learning based encoders like TextEncoder require installing optional dependencies to use them. The following will install torch, transformers, and sentence-transformers.

$ pip install skrub[transformers] -U

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conda install -c conda-forge skrub

Deep learning dependencies

Deep-learning based encoders like TextEncoder require installing optional dependencies to use them. The following will install torch, transformers, and sentence-transformers.

$ conda install -c conda-forge skrub[transformers]

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mamba install -c conda-forge skrub

Deep learning dependencies

Deep-learning based encoders like TextEncoder require installing optional dependencies to use them. The following will install torch, transformers, and sentence-transformers.

$ mamba install -c conda-forge skrub[transformers]

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Advanced Usage for Contributors

1. Fork the project

To contribute to the project, you first need to fork skrub on GitHub.

That will enable you to push your commits to a branch on your fork.

2. Clone your fork

Clone your forked repo to your local machine:

git clone https://github.com/<YOUR_USERNAME>/skrub
cd skrub

Next, add the upstream remote (i.e. the official skrub repository). This allows you to pull the latest changes from the main repository:

git remote add upstream https://github.com/skrub-data/skrub.git

Verify that both the origin (your fork) and upstream (official repo) are correctly set up:

git remote -v

3. Setup your environment

Now, setup a development environment. For example, you can use conda to create a virtual environment:

conda create -n skrub python=3.10 # or any later python version
conda activate skrub

Install the local package in editable mode with development dependencies:

pip install -e ".[dev, lint, test]"

Enable pre-commit hooks to ensure code style consistency:

pre-commit install

Optionally, configure Git to ignore certain revisions in git blame and IDE integrations. These revisions are listed in .git-blame-ignore-revs:

git config blame.ignoreRevsFile .git-blame-ignore-revs

4. Run the tests

To ensure your environment is correctly set up, run the test suite:

pytest -s skrub/tests

Testing should take about 5 minutes. If no errors or failures are found, your environment is ready for development!

Now that you’re set up, review our implementation guidelines and start coding!

Deep learning dependencies

Deep-learning based encoders like TextEncoder require installing optional dependencies to use them. The following will install torch, transformers, and sentence-transformers.

$ pip install -e ".[transformers]"