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In the new release, all the transforms and library are delivered as a single package with extra for dev, ray, spark, and later on for kfp. In almost all cases, users should install from pypi. Another, although unsupported method, developers can use a git URL to do the same. The following below to install the ray extra for the latest release. pip install 'data-prep-toolkit[ray] @ git+https://github.com/IBM/data-prep-kit.git#subdirectory=data-processing-lib/'
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In the new release, all the transforms and library are delivered as a single package with extra for dev, ray, spark, and later on for kfp. In almost all cases, users should install from pypi. Another, although unsupported method, developers can use a git URL to do the same. The following below to install the ray extra for the latest release.
pip install 'data-prep-toolkit[ray] @ git+https://github.com/IBM/data-prep-kit.git#subdirectory=data-processing-lib/'
or using a requirements.txt file with the following line to do the same:
data-prep-toolkit[ray] @ git+https://github.com/IBM/data-prep-kit.git#subdirectory=data-processing-lib/
This approach does not currently work for the transforms as they currently follow a flat structure.
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