numpy - PyPI Package Compare versions

+29

doc/changelog/2.4.4-changelog.rst


		Contributors
		============

		A total of 8 people contributed to this release. People with a "+" by their
		names contributed a patch for the first time.

		* Charles Harris
		* Daniel Haag +
		* Denis Prokopenko +
		* Harshith J +
		* Koki Watanabe
		* Marten van Kerkwijk
		* Matti Picus
		* Nathan Goldbaum

		Pull requests merged
		====================

		A total of 7 pull requests were merged for this release.

		* `#30978 <https://github.com/numpy/numpy/pull/30978>`__: MAINT: Prepare 2.4.x for further development
		* `#31049 <https://github.com/numpy/numpy/pull/31049>`__: BUG: Add test to reproduce problem described in #30816 (#30818)
		* `#31052 <https://github.com/numpy/numpy/pull/31052>`__: BUG: fix FNV-1a 64-bit selection by using NPY_SIZEOF_UINTP (#31035)
		* `#31053 <https://github.com/numpy/numpy/pull/31053>`__: BUG: avoid warning on ufunc with where=True and no output
		* `#31058 <https://github.com/numpy/numpy/pull/31058>`__: DOC: document caveats of ndarray.resize on 3.14 and newer
		* `#31079 <https://github.com/numpy/numpy/pull/31079>`__: TST: fix POWER VSX feature mapping (#30801)
		* `#31084 <https://github.com/numpy/numpy/pull/31084>`__: MAINT: numpy.i: Replace deprecated ``sprintf`` with ``snprintf``...

+41

doc/source/release/2.4.4-notes.rst

		.. currentmodule:: numpy

		=========================
		NumPy 2.4.4 Release Notes
		=========================

		The NumPy 2.4.3 is a patch release that fixes bugs discovered after the 2.4.2
		release. It should finally close issue #30816, the OpenBLAS threading problem
		on ARM.

		This release supports Python versions 3.11-3.14


		Contributors
		============

		A total of 8 people contributed to this release. People with a "+" by their
		names contributed a patch for the first time.

		* Charles Harris
		* Daniel Haag +
		* Denis Prokopenko +
		* Harshith J +
		* Koki Watanabe
		* Marten van Kerkwijk
		* Matti Picus
		* Nathan Goldbaum


		Pull requests merged
		====================

		A total of 7 pull requests were merged for this release.

		* `#30978 <https://github.com/numpy/numpy/pull/30978>`__: MAINT: Prepare 2.4.x for further development
		* `#31049 <https://github.com/numpy/numpy/pull/31049>`__: BUG: Add test to reproduce problem described in #30816 (#30818)
		* `#31052 <https://github.com/numpy/numpy/pull/31052>`__: BUG: fix FNV-1a 64-bit selection by using NPY_SIZEOF_UINTP (#31035)
		* `#31053 <https://github.com/numpy/numpy/pull/31053>`__: BUG: avoid warning on ufunc with where=True and no output
		* `#31058 <https://github.com/numpy/numpy/pull/31058>`__: DOC: document caveats of ndarray.resize on 3.14 and newer
		* `#31079 <https://github.com/numpy/numpy/pull/31079>`__: TST: fix POWER VSX feature mapping (#30801)
		* `#31084 <https://github.com/numpy/numpy/pull/31084>`__: MAINT: numpy.i: Replace deprecated ``sprintf`` with ``snprintf``...

+1

-0

doc/source/release.rst

		@@ -8,2 +8,3 @@ *************

		2.4.4 <release/2.4.4-notes>
		2.4.3 <release/2.4.3-notes>
		@@ -10,0 +11,0 @@ 2.4.2 <release/2.4.2-notes>

+4

-3

numpy/_core/src/multiarray/fnv.c

		@@ -75,3 +75,4 @@ /*
		* Compute a size_t FNV-1a hash of the given data
		* This will use 32-bit or 64-bit hash depending on the size of size_t
		* This will use 32-bit or 64-bit hash depending on the size of npy_uintp.
		* npy_uintp has the same size as size_t.
		*/
		@@ -81,7 +82,7 @@ size_t
		{
		#if NPY_SIZEOF_SIZE_T == 8
		#if NPY_SIZEOF_UINTP == 8
		return (size_t)npy_fnv1a_64(buf, len, FNV1A_64_INIT);
		#else /* NPY_SIZEOF_SIZE_T == 4 */
		#else /* NPY_SIZEOF_UINTP == 4 */
		return (size_t)npy_fnv1a_32(buf, len, FNV1A_32_INIT);
		#endif
		}

+29

-10

numpy/_core/src/multiarray/shape.c

		@@ -80,8 +80,10 @@ #define NPY_NO_DEPRECATED_API NPY_API_VERSION

		static const char *msg =
		"cannot resize an array that references or is referenced\n"
		"by another object in this way.\n"
		"Use the np.resize function to get a new resized copy or\n "
		"set refcheck=False to disable this check";
		if (PyArray_BASE(self) != NULL
		\|\| (((PyArrayObject_fields *)self)->weakreflist != NULL)) {
		PyErr_SetString(PyExc_ValueError,
		"cannot resize an array that "
		"references or is referenced\n"
		"by another array in this way. Use the np.resize function.");
		PyErr_SetString(PyExc_ValueError, msg);
		return -1;
		@@ -97,12 +99,23 @@ }
		#if PY_VERSION_HEX >= 0x030E00B0
		// Python 3.14 changed reference counting semantics for function-
		// local variables. There is no way to tell if the calling function
		// has been optimized (because it might be implemented in C or Cython)
		//
		// Instead, warn if the refcount is exactly 2 that this might be a
		// false positive
		if (!PyUnstable_Object_IsUniquelyReferenced((PyObject *)self)) {
		if (Py_REFCNT(self) == 2) {
		PyErr_SetString(
		PyExc_ValueError,
		"cannot resize an array that may be referenced "
		"by another object.\n"
		"It is possible that this is a false positive.\n"
		"If you are sure that the array is uniquely referenced, "
		"set refcheck=False.");
		return -1;
		}
		#else
		if (Py_REFCNT(self) > 2) {
		#endif
		PyErr_SetString(
		PyExc_ValueError,
		"cannot resize an array that "
		"references or is referenced\n"
		"by another array in this way.\n"
		"Use the np.resize function or refcheck=False");
		PyErr_SetString(PyExc_ValueError, msg);
		return -1;
		@@ -187,2 +200,8 @@ }
		* weak-references and no base object.
		*
		* On Python 3.13 and older, the check allows objects with exactly one
		* reference to be reallocated in-place. On Python 3.14 and newer, the array
		* must be uniquely referenced. In some cases this can lead to spurious
		* ValueErrors.
		*
		*/
		@@ -189,0 +208,0 @@ NPY_NO_EXPORT PyObject *

+7

-0

numpy/_core/tests/examples/cython/checks.pyx

		@@ -7,2 +7,3 @@ #cython: language_level=3
		"""
		import numpy as np
		cimport numpy as cnp
		@@ -376,1 +377,7 @@ cnp.import_array()
		return cnp.NPY_UINTP > 0


		def resize_refcheck_test():
		# see gh-30991
		a = np.array([[0, 1], [2, 3]], order='C')
		a.resize((2, 1))

+33

-1

numpy/_core/tests/test_cpu_features.py

		@@ -381,8 +381,40 @@ import os
		features = ["VSX", "VSX2", "VSX3", "VSX4"]
		features_map = {"VSX2": "ARCH_2_07", "VSX3": "ARCH_3_00", "VSX4": "ARCH_3_1"}
		features_map = {
		"VSX": "ARCH_2_06",
		"VSX2": "ARCH_2_07",
		"VSX3": "ARCH_3_00",
		"VSX4": "ARCH_3_1B"
		}

		def load_flags(self):
		self.load_flags_auxv()
		platform = self._get_platform()

		if platform:
		power_match = re.search(r'power(\d+)', platform, re.IGNORECASE)
		if power_match:
		power_gen = int(power_match.group(1))
		if power_gen >= 7:
		self.features_flags.add("ARCH_2_06")
		if power_gen >= 8:
		self.features_flags.add("ARCH_2_07")
		if power_gen >= 9:
		self.features_flags.add("ARCH_3_00")
		if power_gen >= 10:
		self.features_flags.add("ARCH_3_1B")

		def _get_platform(self):
		"""Get the AT_PLATFORM value from AUXV"""
		try:
		auxv = subprocess.check_output(['/bin/true'], env={"LD_SHOW_AUXV": "1"})
		for line in auxv.split(b'\n'):
		if line.startswith(b'AT_PLATFORM'):
		parts = line.split(b':', 1)
		if len(parts) == 2:
		return parts[1].strip().decode().lower()
		except Exception:
		pass
		return None


		is_zarch = re.match(r"^(s390x)", machine, re.IGNORECASE)
		@@ -389,0 +421,0 @@ @pytest.mark.skipif(not is_linux or not is_zarch,

+15

-0

numpy/_core/tests/test_cython.py

		@@ -353,1 +353,16 @@ import os
		assert checks.check_npy_uintp_type_enum()


		@pytest.mark.skipif(
		sys.version_info < (3, 14),
		reason="Tests behavior that happens on Python 3.14 and newer"
		)
		@pytest.mark.skipif(
		sysconfig.get_platform() == 'win-arm64',
		reason='no checks module on win-arm64'
		)
		def test_resize_refcheck(install_temp):
		import checks
		msg = "It is possible that this is a false positive."
		with pytest.raises(ValueError, match=msg):
		checks.resize_refcheck_test()

+8

-0

numpy/linalg/tests/test_regression.py

		@@ -10,2 +10,3 @@ """ Test functions for linalg module
		assert_,
		assert_almost_equal,
		assert_array_almost_equal,
		@@ -184,1 +185,8 @@ assert_array_equal,
		"probably due to OpenBLAS threading issues")

		def test_norm_linux_arm(self):
		# gh-30816
		a = np.arange(20000) / 50000
		b = a + 1j * np.roll(np.flip(a), 12345)
		norm = np.linalg.norm(b)
		assert_almost_equal(norm, 46.18628948075393)

+2

-2

numpy/version.py

		@@ -5,8 +5,8 @@
		"""
		version = "2.4.3"
		version = "2.4.4"
		__version__ = version
		full_version = version

		git_revision = "8bcb2e72e67c343e55165e6064fe6a9dc011e954"
		git_revision = "be93fe2960dbf49b4647f5783c66d967fb2c65b5"
		release = 'dev' not in version and '+' not in version
		short_version = version.split("+")[0]

+1

-1

PKG-INFO

		Metadata-Version: 2.4
		Name: numpy
		Version: 2.4.3
		Version: 2.4.4
		Summary: Fundamental package for array computing in Python
		@@ -5,0 +5,0 @@ Author: Travis E. Oliphant et al.

+1

-1

pyproject.toml

		@@ -10,3 +10,3 @@ [build-system]
		name = "numpy"
		version = "2.4.3"
		version = "2.4.4"
		description = "Fundamental package for array computing in Python"
		@@ -13,0 +13,0 @@ authors = [{name = "Travis E. Oliphant et al."}]

+2

-2

requirements/ci_requirements.txt

		spin
		# Keep this in sync with ci32_requirements.txt
		scipy-openblas32==0.3.31.126.1
		scipy-openblas64==0.3.31.126.1
		scipy-openblas32==0.3.31.188.0
		scipy-openblas64==0.3.31.188.0

+1

-1

requirements/ci32_requirements.txt

		spin
		# Keep this in sync with ci_requirements.txt
		scipy-openblas32==0.3.31.126.1
		scipy-openblas32==0.3.31.188.0

doc/source/reference/c-api/array.rst