chore: increase PySpark min version to 3.5.0
#1744
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EdAbati
changed the title
3.5.0
EdAbati
commented
Jan 7, 2025
| @@ -99,7 +99,7 @@ jobs: | |||
| cache-suffix: ${{ matrix.python-version }} | |||
| cache-dependency-glob: "pyproject.toml" | |||
| - name: install-not-so-old-versions | |||
| run: uv pip install tox virtualenv setuptools pandas==2.0.3 polars==0.20.8 numpy==1.24.4 pyarrow==15.0.0 "pyarrow-stubs<17" pyspark==3.4.0 scipy==1.8.0 scikit-learn==1.3.0 dask[dataframe]==2024.10 tzdata --system | |||
| run: uv pip install tox virtualenv setuptools pandas==2.0.3 polars==0.20.8 numpy==1.24.4 pyarrow==15.0.0 "pyarrow-stubs<17" pyspark==3.5.0 scipy==1.8.0 scikit-learn==1.3.0 dask[dataframe]==2024.10 tzdata --system | |||
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As a bonus we can also test pyspark 3.5.0 with numpy <2.0 without adding a new step (useful for std and var)
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MarcoGorelli
approved these changes
Jan 7, 2025
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thanks @EdAbati !
separately, we should also add this minimum to MINIMUM_VERSIONS in narwhals/utils.py
FBruzzesi
reviewed
Jan 7, 2025
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Quite satisfying diff! Thanks @EdAbati !
Could you also address the MIN_VERSIONS dictionary in narwhals/utils.py?
Edit: just read @MarcoGorelli comment 😂
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What type of PR is this? (check all applicable)
Related issues
all,anyandnull_countSpark Expressions #1724 (comment)Checklist
If you have comments or can explain your changes, please do so below
Pros: make it easier to implement expressions that comes out-of-the-box with Pyspark 3.5
Cons: may hurt adoption since we only support the latest pyspark version (but pyspark 3.5.0 is already 1+ year old)
I think it is fine to focus on API coverage first and worry about supporting older versions later