summaryrefslogtreecommitdiffstats
path: root/meta-python/recipes-devtools/python/python3-pandas
Commit message (Collapse)AuthorAgeFilesLines
* python3-pandas: compile against target version of numpyGyorgy Sarvari2025-03-101-0/+66
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | python3-numpy headers are required by pandas to compile successfully. By default, this recipe used python3-numpy-native for compilation, which usually works. However in case the bitness of the build-host differs from the target, then problems arise. For example when compiling for 32-bit ARM on a x86-64 machine, the following error appears when trying to import the module: ValueError: Buffer dtype mismatch, expected 'const int64_t' but got 'long long' When running a diff on all numpy headers across native and target, only one header differs, _numpyconfig.h, in a significant way. This header defines the sizes of different datatypes used by numpy, and these sizes strongly depend on the arch bitness. This change switches from python3-numpy-native dependency to python3-numpy to ensure that the correct headers are used. Beside this also patch the meson script, so it accepts an option (numpy_inc_dir) to specify the location of these headers, since it is not able to query them from the class-target module The PYTHONPATH variable is extended with the target's RECIPE_SYSROOT, because numpy is specified as a dependency in meson, and it needs to find the module to continue successfully. Signed-off-by: Gyorgy Sarvari <skandigraun@gmail.com> Signed-off-by: Khem Raj <raj.khem@gmail.com>
* python3-pandas: Downgrade version check for numpy to 1.xKhem Raj2024-08-241-0/+27
| | | | | | Helps it build with PEP-517 backend Signed-off-by: Khem Raj <raj.khem@gmail.com>
* python3-pandas: upgrade 2.0.3 -> 2.2.2Trevor Gamblin2024-08-231-0/+37
pandas 2.2.2 is the first version compatible with numpy 2.0.x. The package now uses meson as the build backend, so change the recipe to inherit that. Its pyproject.toml pins required versions for Cython and meson, but newer upstream pandas releases are using different versions and compatibility strings, so just add an OE-specific patch to relax the requirements a bit for us. Changelog: https://pandas.pydata.org/pandas-docs/version/2.2.2/whatsnew/v2.2.2.html Signed-off-by: Trevor Gamblin <tgamblin@baylibre.com> Signed-off-by: Khem Raj <raj.khem@gmail.com>