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7 changes: 7 additions & 0 deletions ci/scripts/python_build.sh
Original file line number Diff line number Diff line change
Expand Up @@ -78,6 +78,13 @@ export PYARROW_PARALLEL=${n_jobs}
export CMAKE_PREFIX_PATH
export LD_LIBRARY_PATH=${ARROW_HOME}/lib:${LD_LIBRARY_PATH}

# https://github.com/apache/arrow/issues/46516
# If we are building docs we force Cython>3.1.1 to avoid numpydoc
# failures due to Cython docstring being wrongly generated.
if [ "${BUILD_DOCS_PYTHON}" == "ON" ]; then
${PYTHON:-python} -m pip install --upgrade Cython>3.1.1

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Will that work properly if Cython was installed using conda?
Also, is this necessary at all?

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Will that work properly if Cython was installed using conda?

It does fix the existing failures which install Cython through conda, so the answer seems to be yes (without this it still fails) because the cached docker image installed Cython 3.1.1

Also, is this necessary at all?

I don't think we should merge that specific change, I was validating the existing failing CI jobs.
I think the bests course of action would be to force rebuild the underlying docker image so it is not caches and it installs Cython 3.1.2. I am asking on Zulip if someone has access to docker.io/apache/arrow-dev as rebuilding the image would fix the issue

fi

# https://github.com/apache/arrow/issues/41429
# TODO: We want to out-of-source build. This is a workaround. We copy
# all needed files to the build directory from the source directory
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2 changes: 1 addition & 1 deletion python/pyarrow/types.pxi
Original file line number Diff line number Diff line change
Expand Up @@ -4464,7 +4464,7 @@ def float16():
to a python list, the types of its elements will be ``np.float16``

>>> [type(val) for val in a.to_pylist()]
[<class 'numpy.float16'>, <class 'numpy.float16'>]
[<class 'float'>, <class 'float'>]
"""
return primitive_type(_Type_HALF_FLOAT)

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