NumPy: array processing for numbers, strings, records and objects
NumPy is a general-purpose array-processing package designed to
efficiently manipulate large multi-dimensional arrays of arbitrary
records without sacrificing too much speed for small multi-dimensional
arrays. NumPy is built on the Numeric code base and adds features
introduced by numarray as well as an extended C-API and the ability to
create arrays of arbitrary type which also makes NumPy suitable for
interfacing with general-purpose data-base applications.
There are also basic facilities for discrete fourier transform,
basic linear algebra and random number generation.
- Developed at devel:languages:python:numeric
- Sources inherited from project openSUSE:Factory
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Source Files
| Filename | Size | Changed |
|---|---|---|
| _constraints | 0000000182 182 Bytes | |
| _multibuild | 0000000056 56 Bytes | |
| ignore-pkg_resources-deprecation.patch | 0000000555 555 Bytes | |
| numpy-1.25.2.tar.gz | 0010805282 10.3 MB | |
| numpy-1.9.0-remove-__declspec.patch | 0000001152 1.13 KB | |
| numpy-buildfix.patch | 0000001025 1 KB | |
| python-numpy-rpmlintrc | 0000000478 478 Bytes | |
| python-numpy.changes | 0000145583 142 KB | |
| python-numpy.spec | 0000013693 13.4 KB |
Revision 119 (latest revision is 129)
Ana Guerrero (anag+factory)
accepted
request 1104294
from
Daniel Garcia (dgarcia)
(revision 119)
- Use %pyproject_wheel and %pyproject_install macros
- Disable broken tests in armv7l (bsc#1212710)
- limit to Cython < 3
- update to 1.25.2:
* Upgrade various build dependencies.
* use ``-ftrapping-math`` with Clang on macOS
* properly handle negative indexes in ufunc_at fast path
* PyObject_IsTrue and PyObject_Not error handling in setflags
* histogram small range robust
* Update meson.build files from main branch
* exclude min, max and round from ``np.__all__``
* Dependabot updates
* Fix the signature for np.array_api.take
* update OpenBLAS to an intermeidate commit
* Fix reference count leak in str(scalar).
* fix invalid function pointer conversion error
* Factor out slow ``getenv`` call used for memory policy warning
* correct URL in cirrus.star [skip cirrus]
* Fix C types in scalartypes
* do not modify the input to ufunc_at
* Further fixes to indexing loop and added tests
- Update to 1.25.1:
* NumPy 1.25.1 is a maintenance release that fixes bugs and regressions
discovered after the 1.25.0 release. The Python versions supported by
this release are 3.9-3.11.
* #23968: MAINT: prepare 1.25.x for further development
* #24036: BLD: Port long double identification to C for meson
* #24037: BUG: Fix reduction return NULL to be goto fail
* #24038: BUG: Avoid undefined behavior in array.astype()
* #24039: BUG: Ensure __array_ufunc__ works without any kwargs passed
* #24117: MAINT: Pin urllib3 to avoid anaconda-client bug.
* #24118: TST: Pin pydantic<2 in Pyodide workflow
* #24119: MAINT: Bump pypa/cibuildwheel from 2.13.0 to 2.13.1
* #24120: MAINT: Bump actions/checkout from 3.5.2 to 3.5.3
* #24122: BUG: Multiply or Divides using SIMD without a full vector can...
* #24127: MAINT: testing for IS_MUSL closes #24074
* #24128: BUG: Only replace dtype temporarily if dimensions changed
* #24129: MAINT: Bump actions/setup-node from 3.6.0 to 3.7.0
* #24134: BUG: Fix private procedures in f2py modules
- Skipped 1.25.0:
* The NumPy 1.25.0 release continues the ongoing work to improve the
handling and promotion of dtypes, increase the execution speed, and
clarify the documentation. There has also been work to prepare for the
future NumPy 2.0.0 release, resulting in a large number of new and
expired deprecation. Highlights are:
- Support for MUSL, there are now MUSL wheels.
- Support the Fujitsu C/C++ compiler.
- Object arrays are now supported in einsum
- Support for inplace matrix multiplication (@=).
* Full changelog: https://github.com/numpy/numpy/releases/tag/v1.25.0
The Python versions supported in this release are 3.9-3.11.
- Remove upstream patch:
* remove-deprecated-hypothesis-funcs.patch
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