- Update to 2.4.2
* Many annotation improvements.
* New casting kwarg 'same_value' for casting by value.
* New PyUFunc_AddLoopsFromSpec function that can be used to add
user sort loops using the ArrayMethod API.
* New __numpy_dtype__ protocol.
* Setting the strides attribute is deprecated.
* Positional out argument to np.maximum, np.minimum is deprecated.
* align= must be passed as boolean to np.dtype().
* Assertion and warning control utilities are deprecated.
* np.fix is pending deprecation.
* in-place modification of ndarray.shape is pending deprecation.
* Deprecation of numpy.lib.user_array.container.
* Removed deprecated MachAr runtime discovery mechanism.
* Raise TypeError on attempt to convert array with ndim > 0 to
scalar.
* Removed numpy.linalg.linalg and numpy.fft.helper.
* Removed interpolation parameter from quantile and percentile
functions.
* Removed numpy.in1d and numpy.ndindex.ndincr().
* Removed fix_imports parameter from numpy.save.
* Removal of four undocumented ndarray.ctypes methods.
* Removed newshape parameter from numpy.reshape.
* numpy.array2string and numpy.sum deprecations finalized.
* Removed some other deprecated functions and arguments.
* NumPy's C extension modules have begun to use multi-phase
initialisation, as defined by PEP 489.
* numpy.round now always returns a copy.
* Type-checkers will no longer accept calls to numpy.arange with
start as a keyword argument.
OBS-URL: https://build.opensuse.org/package/show/devel:languages:python:numeric/python-numpy?expand=0&rev=192
This commit is contained in:
Git OBS Bridge
283
python-numpy.spec
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python-numpy.spec
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#
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# spec file for package python-numpy
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#
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# Copyright (c) 2026 SUSE LLC and contributors
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#
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# All modifications and additions to the file contributed by third parties
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# remain the property of their copyright owners, unless otherwise agreed
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# upon. The license for this file, and modifications and additions to the
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# file, is the same license as for the pristine package itself (unless the
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# license for the pristine package is not an Open Source License, in which
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# case the license is the MIT License). An "Open Source License" is a
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# license that conforms to the Open Source Definition (Version 1.9)
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# published by the Open Source Initiative.
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# Please submit bugfixes or comments via https://bugs.opensuse.org/
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#
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%define plainpython python
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#
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%if 0%{?suse_version} > 1500
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%bcond_without libalternatives
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%bcond_without cblas
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%else
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%bcond_with libalternatives
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%bcond_with cblas
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%endif
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#
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%{?sle15_python_module_pythons}
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Name: python-numpy
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Version: 2.4.2
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Release: 0
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Summary: NumPy array processing for numbers, strings, records and objects
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License: BSD-3-Clause
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URL: http://www.numpy.org/
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Source: https://files.pythonhosted.org/packages/source/n/numpy/numpy-%{version}.tar.gz
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Source99: python-numpy-rpmlintrc
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# PATCH-FIX-OPENSUSE numpy-buildfix.patch -- openSUSE-specific build fixes
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Patch0: numpy-buildfix.patch
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BuildRequires: %{python_module Cython >= 3.0.6}
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BuildRequires: %{python_module base >= 3.11}
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BuildRequires: %{python_module devel}
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BuildRequires: %{python_module meson-python >= 0.18.0}
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BuildRequires: %{python_module pip}
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BuildRequires: %{python_module pyproject-metadata >= 0.7.1}
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BuildRequires: cmake
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%if 0%{?suse_version} < 1600
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BuildRequires: gcc12
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BuildRequires: gcc12-c++
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%else
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BuildRequires: gcc
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BuildRequires: gcc-c++
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%endif
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BuildRequires: ninja >= 1.8.2
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BuildRequires: patchelf
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BuildRequires: python-rpm-macros >= 20210929
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BuildConflicts: gcc11 < 11.2
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%if 0%{?suse_version}
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BuildRequires: fdupes
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%endif
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# SECTION test requirements
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BuildRequires: %{python_module pytest >= 7.4.0}
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BuildRequires: %{python_module hypothesis >= 6.75.0}
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BuildRequires: %{python_module pytest-xdist}
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BuildRequires: %{python_module testsuite}
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BuildRequires: %{python_module typing-extensions >= 4.2.0}
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# /SECTION
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# Last version which packaged %%{_bindir}/f2py without update-alternatives
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Conflicts: %{plainpython}-numpy <= 1.12.0
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%if 0%{?suse_version}
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BuildRequires: gcc-fortran
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%else
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BuildRequires: gcc-gfortran
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%endif
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BuildRequires: blas-devel
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BuildRequires: lapack-devel
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%if %{with cblas}
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# openblas has significantly better performance for some operations
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BuildRequires: cblas-devel
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Recommends: libopenblas_pthreads0
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%endif
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%if %{with libalternatives}
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BuildRequires: alts
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Requires: alts
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%else
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Requires(post): update-alternatives
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Requires(postun): update-alternatives
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%endif
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%python_subpackages
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%description
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NumPy is a general-purpose array-processing package designed to
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efficiently manipulate large multi-dimensional arrays of arbitrary
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records without sacrificing too much speed for small multi-dimensional
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arrays. NumPy is built on the Numeric code base and adds features
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introduced by numarray as well as an extended C-API and the ability to
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create arrays of arbitrary type which also makes NumPy suitable for
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interfacing with general-purpose data-base applications.
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There are also basic facilities for discrete fourier transform,
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basic linear algebra and random number generation.
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%package devel
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Summary: Development files for numpy applications
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Requires: %{name} = %{version}
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Requires: blas-devel
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Requires: python-devel
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Requires: %plainpython(abi) = %{python_version}
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%if %{with cblas}
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Requires: cblas-devel
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%endif
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Requires: lapack-devel
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%description devel
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This package contains files for developing applications using numpy.
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%prep
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%autosetup -p1 -n numpy-%{version}
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# Fix non-executable scripts
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sed -i '1{/^#!/d}'\
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numpy/distutils/{conv_template,cpuinfo,from_template,system_info}.py \
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numpy/f2py/{__init__,cfuncs,diagnose,crackfortran,f2py2e,rules}.py \
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numpy/random/_examples/cython/extending{,_distributions}.pyx \
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numpy/testing/print_coercion_tables.py
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chmod -x \
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numpy/f2py/{crackfortran,f2py2e,rules}.py \
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numpy/testing/print_coercion_tables.py
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# force cythonization
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rm -f PKG-INFO
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%build
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export PYTHONDONTWRITEBYTECODE=1
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%define _lto_cflags %{nil}
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export CFLAGS="%{optflags} -fno-strict-aliasing"
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%if 0%{?suse_version} < 1600
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export CC=gcc-12
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export CXX=g++-12
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%endif
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%pyproject_wheel
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%install
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%pyproject_install
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%python_clone -a %{buildroot}%{_bindir}/f2py
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%python_clone -a %{buildroot}%{_bindir}/numpy-config
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%if 0%{?suse_version}
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%fdupes %{buildroot}%{_prefix}
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%endif
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%check
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# https://numpy.org/doc/stable/dev/development_environment.html#running-tests
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mkdir -p testing
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cp pytest.ini testing/
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pushd testing
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%python_flavored_alternatives
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%if %{with libalternatives}
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%{python_expand #
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for b in f2py numpy-config; do
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ln -s %{buildroot}%{_bindir}/$b-%{$python_bin_suffix} build/flavorbin/$b
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done
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}
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# flaky tests
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test_failok+=" or test_structured_object_indexing"
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test_failok+=" or test_structured_object_item_setting"
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# flaky due to memory consumption
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test_failok+=" or test_big_arrays"
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# gh#numpy/numpy#22825
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test_failok+=" or TestPrintOptions"
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# gh#numpy/numpy#22835
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test_failok+=" or test_keepdims_out"
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# boo#1148173 gh#numpy/numpy#14438
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%ifarch ppc64 ppc64le
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test_failok+=" or test_generalized_sq"
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# situation with IBM and double numbers is ... complicated
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# gh#numpy/numpy#21094
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test_failok+=" or test_ppc64_ibm_double_double128"
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%endif
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# these tests fail on big endian gh#numpy/numpy#11831
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%ifarch s390x ppc ppc64
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test_failok+=" or TestFReturnCharacter"
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%endif
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# missing instruction set
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%ifarch s390x
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test_failok+=" or test_truncate_f32"
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%endif
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%ifarch %{ix86}
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# (arm 32-bit seems okay here)
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# gh#numpy/numpy#18387
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test_failok+=" or test_pareto"
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# gh#numpy/numpy#18388
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test_failok+=" or test_float_remainder_overflow"
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%endif
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%ifarch %{ix86} %{arm32}
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# too much memory for 32bit
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test_failok+=" or test_identityless_reduction_huge_array"
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test_failok+=" or test_huge_vectordot"
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# invalid int type for 32bit
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test_failok+=" or (test_kind and test_quad_precision)"
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test_failok+=" or (test_kind and test_int)"
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test_failok+=" or (test_kind and test_real)"
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test_failok+=" or (test_multinomial_pvals_float32)"
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%endif
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%ifarch %{arm}
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# https://github.com/numpy/numpy/issues/24001
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test_failok+=" or (test_cpu_features and test_features)"
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test_failok+=" or (test_umath and test_unary_spurious_fpexception)"
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%endif
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%ifarch riscv64
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# These tests fail due to non-portable assumptions about the signbit of NaN
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# gh#numpy/numpy#8213
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test_failok+=" or (test_umath and test_fpclass)"
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test_failok+=" or (test_numeric and TestBoolCmp and test_float)"
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test_failok+=" or (test_umath and test_fp_noncontiguous)"
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%endif
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# The meson command is always on the primary python and wants to import numpy from there
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test_failok+=" or test_limited_api"
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# gh#numpy/numpy#27531
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test_failok+=" or test_api_importable"
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echo "
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import sys
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import numpy
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r = numpy.test(label='full', verbose=2,
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extra_argv=['-v', '-n', 'auto', '-k'] + sys.argv[1:])
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sys.exit(0 if r else 1)
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" > runobstest.py
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%{python_expand # for all python3 flavors
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export PYTHONPATH=%{buildroot}%{$python_sitearch}
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export PYTHONDONTWRITEBYTECODE=1
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[ -n "$test_failok" ] && $python runobstest.py "${test_failok:4}" ||:
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# test_new_policy: duplicates test runs and output and does not follow our deselection
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$python runobstest.py "not (test_new_policy ${test_failok} or slow)"
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}
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popd
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%endif
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%pre
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# If libalternatives is used: Removing old update-alternatives entries.
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%python_libalternatives_reset_alternative f2py
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%post
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%python_install_alternative f2py numpy-config
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%postun
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%python_uninstall_alternative f2py
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%files %{python_files}
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%doc README.md THANKS.txt
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%license LICENSE.txt
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%python_alternative %{_bindir}/f2py
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%python_alternative %{_bindir}/numpy-config
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%{python_sitearch}/numpy/
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%{python_sitearch}/numpy-%{version}.dist-info
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%exclude %{python_sitearch}/numpy/_core/include
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%exclude %{python_sitearch}/numpy/_core/lib/libnpymath.a
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%exclude %{python_sitearch}/numpy/_core/lib/pkgconfig/numpy.pc
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%exclude %{python_sitearch}/numpy/distutils/mingw/*.c
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%exclude %{python_sitearch}/numpy/distutils/checks/*.c
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%exclude %{python_sitearch}/numpy/f2py/src/
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%exclude %{python_sitearch}/numpy/random/lib/libnpyrandom.a
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%files %{python_files devel}
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%license LICENSE.txt
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%{python_sitearch}/numpy/_core/include/
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%if 0%{python_version_nodots} < 312
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%{python_sitearch}/numpy/distutils/mingw/*.c
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%{python_sitearch}/numpy/distutils/checks/*.c
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%endif
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%{python_sitearch}/numpy/f2py/src/
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%{python_sitearch}/numpy/_core/lib/libnpymath.a
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%{python_sitearch}/numpy/_core/lib/pkgconfig/numpy.pc
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%{python_sitearch}/numpy/random/lib/libnpyrandom.a
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%changelog
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