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Pipe based dataframe manipulation library that can also transform data on SQL databases

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pydiverse.transform

tests

Pipe based dataframe manipulation library that can also transform data on SQL databases

Installation

To install the package locally in development mode, you will need to install pixi. For those who haven't used pixi before, it is a poetry style dependency management tool based on conda/micromamba/conda-forge package ecosystem. The conda-forge repository has well maintained packages for Linux, macOS, and Windows supporting both ARM and X86 architectures. Especially, installing psycopg2 in a portable way got much easier with pixi. In addition, pixi is really strong in creating lock files for reproducible environments (including system libraries) with many essential features missing in alternative tools like poetry (see pixi.toml).

To start developing, you can run the following commands:

git clone https://github.com/pydiverse/pydiverse.transform.git
cd pydiverse.transform

# Create the environment, activate it and install the pre-commit hooks
pixi install
pixi run postinstall
pixi run pre-commit install

Testing

After installation, you should be able to run:

pixi run pytest

Testing more database backends

To facilitate easy testing, we provide a Docker Compose file to start all required servers. Just run docker compose up in the root directory of the project to start everything, and then run pytest in a new tab.

Afterwards you can run:

pixi run pytest --postgres --mssql

Testing db2 functionality

For running @pytest.mark.ibm_db2 tests, you need to spin up a docker container without docker compose since it needs the --priviledged option which docker compose does not offer.

docker run -h db2server --name db2server --restart=always --detach --privileged=true -p 50000:50000 --env-file docker_db2.env_list -v /Docker:/database ibmcom/db2

Then check docker logs db2server | grep -i completed until you see (*) Setup has completed..

Afterwards you can run:

pixi run -e py312ibm pytest --ibm_db2

Packaging and publishing to pypi and conda-forge using github actions

  • bump version number in pyproject.toml
  • set correct release date in changelog.md
  • push increased version number to main branch
  • tag commit with git tag <version>, e.g. git tag 0.7.0
  • git push --tags

The package should appear on https://pypi.org/project/pydiverse-transform/ in a timely manner. It is normal that it takes a few hours until the new package version is available on https://conda-forge.org/packages/.

Packaging and publishing to Pypi manually

Packages are first released on test.pypi.org:

Finally, they are published via:

  • git tag <version>
  • git push --tags
  • Attention: Please, only continue here, if automatic publishing fails for some reason!
  • pixi run -e release hatch build
  • pixi run -e release twine upload --repository pypi dist/*

Publishing package on conda-forge manually

Conda-forge packages are updated via:

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Pipe based dataframe manipulation library that can also transform data on SQL databases

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