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We should add a Crossbow build running the PyArrow test suite with a debug-enabled CPython interpreter, to better test the sanity of our low-level C++/Python interface code.
One possibility is to install CPython using conda and the conda-forge/label/python_debug::python package reference.
…reter (#43565)
### Rationale for this change
Debug builds of CPython help catch low-level errors when using the Python C API. This is illustrated in GH-43487: a debug build of CPython detected that we were incref'ing a Python object without holding the GIL (which is a race condition otherwise).
### What changes are included in this PR?
1. Add a Docker build with a conda-installed debug interpreter.
2. Add a Crossbow job to run said Docker build with Python 3.12.
### Are these changes tested?
Yes, by the adding Crossbow job. The job now fails with a crash in `test_udf.py`, because of GH-43487.
### Are there any user-facing changes?
No.
* GitHub Issue: #43559
Authored-by: Antoine Pitrou <antoine@python.org>
Signed-off-by: Antoine Pitrou <antoine@python.org>
Describe the enhancement requested
We should add a Crossbow build running the PyArrow test suite with a debug-enabled CPython interpreter, to better test the sanity of our low-level C++/Python interface code.
One possibility is to install CPython using conda and the
conda-forge/label/python_debug::python
package reference.Related to #43557
Component(s)
Continuous Integration, Python
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