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📄 test__all__.py import collections import numpy as np def test_no_duplicates_in_np__all__(): # Regression test for gh-10198. dups = {k: v for k, v in collections.Counter(np.__all__).items() if v > 1} assert len(dups) == 0	221 B	2026-01-20 12:58
📄 test_ctypeslib.py import sys import pytest import weakref from pathlib import Path import numpy as np from numpy.ctypeslib import ndpointer, load_library, as_array from numpy.distutils.misc_util import get_shared_lib_extension from numpy.testing import assert_, assert_array_equal, assert_raises, assert_equal try: import ctypes except ImportError: ctypes = None else: cdll = None test_cdll = None if hasattr(sys, 'gettotalrefcount'): try: cdll = load_library('_multiarray_umath_d', np.core._multiarray_umath.__file__) except OSError: pass try: test_cdll = load_library('_multiarray_tests', np.core._multiarray_tests.__file__) except OSError: pass if cdll is None: cdll = load_library('_multiarray_umath', np.core._multiarray_umath.__file__) if test_cdll is None: test_cdll = load_library('_multiarray_tests', np.core._multiarray_tests.__file__) c_forward_pointer = test_cdll.forward_pointer @pytest.mark.skipif(ctypes is None, reason="ctypes not available in this python") @pytest.mark.skipif(sys.platform == 'cygwin', reason="Known to fail on cygwin") class TestLoadLibrary: def test_basic(self): loader_path = np.core._multiarray_umath.__file__ out1 = load_library('_multiarray_umath', loader_path) out2 = load_library(Path('_multiarray_umath'), loader_path) out3 = load_library('_multiarray_umath', Path(loader_path)) out4 = load_library(b'_multiarray_umath', loader_path) assert isinstance(out1, ctypes.CDLL) assert out1 is out2 is out3 is out4 def test_basic2(self): # Regression for #801: load_library with a full library name # (including extension) does not work. try: try: so = get_shared_lib_extension(is_python_ext=True) # Should succeed load_library('_multiarray_umath%s' % so, np.core._multiarray_umath.__file__) except ImportError: print("No distutils available, skipping test.") except ImportError as e: msg = ("ctypes is not available on this python: skipping the test" " (import error was: %s)" % str(e)) print(msg) class TestNdpointer: def test_dtype(self): dt = np.intc p = ndpointer(dtype=dt) assert_(p.from_param(np.array([1], dt))) dt = '<i4' p = ndpointer(dtype=dt) assert_(p.from_param(np.array([1], dt))) dt = np.dtype('>i4') p = ndpointer(dtype=dt) p.from_param(np.array([1], dt)) assert_raises(TypeError, p.from_param, np.array([1], dt.newbyteorder('swap'))) dtnames = ['x', 'y'] dtformats = [np.intc, np.float64] dtdescr = {'names': dtnames, 'formats': dtformats} dt = np.dtype(dtdescr) p = ndpointer(dtype=dt) assert_(p.from_param(np.zeros((10,), dt))) samedt = np.dtype(dtdescr) p = ndpointer(dtype=samedt) assert_(p.from_param(np.zeros((10,), dt))) dt2 = np.dtype(dtdescr, align=True) if dt.itemsize != dt2.itemsize: assert_raises(TypeError, p.from_param, np.zeros((10,), dt2)) else: assert_(p.from_param(np.zeros((10,), dt2))) def test_ndim(self): p = ndpointer(ndim=0) assert_(p.from_param(np.array(1))) assert_raises(TypeError, p.from_param, np.array([1])) p = ndpointer(ndim=1) assert_raises(TypeError, p.from_param, np.array(1)) assert_(p.from_param(np.array([1]))) p = ndpointer(ndim=2) assert_(p.from_param(np.array([[1]]))) def test_shape(self): p = ndpointer(shape=(1, 2)) assert_(p.from_param(np.array([[1, 2]]))) assert_raises(TypeError, p.from_param, np.array([[1], [2]])) p = ndpointer(shape=()) assert_(p.from_param(np.array(1))) def test_flags(self): x = np.array([[1, 2], [3, 4]], order='F') p = ndpointer(flags='FORTRAN') assert_(p.from_param(x)) p = ndpointer(flags='CONTIGUOUS') assert_raises(TypeError, p.from_param, x) p = ndpointer(flags=x.flags.num) assert_(p.from_param(x)) assert_raises(TypeError, p.from_param, np.array([[1, 2], [3, 4]])) def test_cache(self): assert_(ndpointer(dtype=np.float64) is ndpointer(dtype=np.float64)) # shapes are normalized assert_(ndpointer(shape=2) is ndpointer(shape=(2,))) # 1.12 <= v < 1.16 had a bug that made these fail assert_(ndpointer(shape=2) is not ndpointer(ndim=2)) assert_(ndpointer(ndim=2) is not ndpointer(shape=2)) @pytest.mark.skipif(ctypes is None, reason="ctypes not available on this python installation") class TestNdpointerCFunc: def test_arguments(self): """ Test that arguments are coerced from arrays """ c_forward_pointer.restype = ctypes.c_void_p c_forward_pointer.argtypes = (ndpointer(ndim=2),) c_forward_pointer(np.zeros((2, 3))) # too many dimensions assert_raises( ctypes.ArgumentError, c_forward_pointer, np.zeros((2, 3, 4))) @pytest.mark.parametrize( 'dt', [ float, np.dtype(dict( formats=['<i4', '<i4'], names=['a', 'b'], offsets=[0, 2], itemsize=6 )) ], ids=[ 'float', 'overlapping-fields' ] ) def test_return(self, dt): """ Test that return values are coerced to arrays """ arr = np.zeros((2, 3), dt) ptr_type = ndpointer(shape=arr.shape, dtype=arr.dtype) c_forward_pointer.restype = ptr_type c_forward_pointer.argtypes = (ptr_type,) # check that the arrays are equivalent views on the same data arr2 = c_forward_pointer(arr) assert_equal(arr2.dtype, arr.dtype) assert_equal(arr2.shape, arr.shape) assert_equal( arr2.__array_interface__['data'], arr.__array_interface__['data'] ) def test_vague_return_value(self): """ Test that vague ndpointer return values do not promote to arrays """ arr = np.zeros((2, 3)) ptr_type = ndpointer(dtype=arr.dtype) c_forward_pointer.restype = ptr_type c_forward_pointer.argtypes = (ptr_type,) ret = c_forward_pointer(arr) assert_(isinstance(ret, ptr_type)) @pytest.mark.skipif(ctypes is None, reason="ctypes not available on this python installation") class TestAsArray: def test_array(self): from ctypes import c_int pair_t = c_int * 2 a = as_array(pair_t(1, 2)) assert_equal(a.shape, (2,)) assert_array_equal(a, np.array([1, 2])) a = as_array((pair_t * 3)(pair_t(1, 2), pair_t(3, 4), pair_t(5, 6))) assert_equal(a.shape, (3, 2)) assert_array_equal(a, np.array([[1, 2], [3, 4], [5, 6]])) def test_pointer(self): from ctypes import c_int, cast, POINTER p = cast((c_int * 10)(range(10)), POINTER(c_int)) a = as_array(p, shape=(10,)) assert_equal(a.shape, (10,)) assert_array_equal(a, np.arange(10)) a = as_array(p, shape=(2, 5)) assert_equal(a.shape, (2, 5)) assert_array_equal(a, np.arange(10).reshape((2, 5))) # shape argument is required assert_raises(TypeError, as_array, p) def test_struct_array_pointer(self): from ctypes import c_int16, Structure, pointer class Struct(Structure): _fields_ = [('a', c_int16)] Struct3 = 3 Struct c_array = (2 * Struct3)( Struct3(Struct(a=1), Struct(a=2), Struct(a=3)), Struct3(Struct(a=4), Struct(a=5), Struct(a=6)) ) expected = np.array([ [(1,), (2,), (3,)], [(4,), (5,), (6,)], ], dtype=[('a', np.int16)]) def check(x): assert_equal(x.dtype, expected.dtype) assert_equal(x, expected) # all of these should be equivalent check(as_array(c_array)) check(as_array(pointer(c_array), shape=())) check(as_array(pointer(c_array[0]), shape=(2,))) check(as_array(pointer(c_array[0][0]), shape=(2, 3))) def test_reference_cycles(self): # related to gh-6511 import ctypes # create array to work with # don't use int/long to avoid running into bpo-10746 N = 100 a = np.arange(N, dtype=np.short) # get pointer to array pnt = np.ctypeslib.as_ctypes(a) with np.testing.assert_no_gc_cycles(): # decay the array above to a pointer to its first element newpnt = ctypes.cast(pnt, ctypes.POINTER(ctypes.c_short)) # and construct an array using this data b = np.ctypeslib.as_array(newpnt, (N,)) # now delete both, which should cleanup both objects del newpnt, b def test_segmentation_fault(self): arr = np.zeros((224, 224, 3)) c_arr = np.ctypeslib.as_ctypes(arr) arr_ref = weakref.ref(arr) del arr # check the reference wasn't cleaned up assert_(arr_ref() is not None) # check we avoid the segfault c_arr[0][0][0] @pytest.mark.skipif(ctypes is None, reason="ctypes not available on this python installation") class TestAsCtypesType: """ Test conversion from dtypes to ctypes types """ def test_scalar(self): dt = np.dtype('<u2') ct = np.ctypeslib.as_ctypes_type(dt) assert_equal(ct, ctypes.c_uint16.__ctype_le__) dt = np.dtype('>u2') ct = np.ctypeslib.as_ctypes_type(dt) assert_equal(ct, ctypes.c_uint16.__ctype_be__) dt = np.dtype('u2') ct = np.ctypeslib.as_ctypes_type(dt) assert_equal(ct, ctypes.c_uint16) def test_subarray(self): dt = np.dtype((np.int32, (2, 3))) ct = np.ctypeslib.as_ctypes_type(dt) assert_equal(ct, 2 * (3 * ctypes.c_int32)) def test_structure(self): dt = np.dtype([ ('a', np.uint16), ('b', np.uint32), ]) ct = np.ctypeslib.as_ctypes_type(dt) assert_(issubclass(ct, ctypes.Structure)) assert_equal(ctypes.sizeof(ct), dt.itemsize) assert_equal(ct._fields_, [ ('a', ctypes.c_uint16), ('b', ctypes.c_uint32), ]) def test_structure_aligned(self): dt = np.dtype([ ('a', np.uint16), ('b', np.uint32), ], align=True) ct = np.ctypeslib.as_ctypes_type(dt) assert_(issubclass(ct, ctypes.Structure)) assert_equal(ctypes.sizeof(ct), dt.itemsize) assert_equal(ct._fields_, [ ('a', ctypes.c_uint16), ('', ctypes.c_char * 2), # padding ('b', ctypes.c_uint32), ]) def test_union(self): dt = np.dtype(dict( names=['a', 'b'], offsets=[0, 0], formats=[np.uint16, np.uint32] )) ct = np.ctypeslib.as_ctypes_type(dt) assert_(issubclass(ct, ctypes.Union)) assert_equal(ctypes.sizeof(ct), dt.itemsize) assert_equal(ct._fields_, [ ('a', ctypes.c_uint16), ('b', ctypes.c_uint32), ]) def test_padded_union(self): dt = np.dtype(dict( names=['a', 'b'], offsets=[0, 0], formats=[np.uint16, np.uint32], itemsize=5, )) ct = np.ctypeslib.as_ctypes_type(dt) assert_(issubclass(ct, ctypes.Union)) assert_equal(ctypes.sizeof(ct), dt.itemsize) assert_equal(ct._fields_, [ ('a', ctypes.c_uint16), ('b', ctypes.c_uint32), ('', ctypes.c_char * 5), # padding ]) def test_overlapping(self): dt = np.dtype(dict( names=['a', 'b'], offsets=[0, 2], formats=[np.uint32, np.uint32] )) assert_raises(NotImplementedError, np.ctypeslib.as_ctypes_type, dt)	12 KB	2026-01-20 12:58
📄 test_lazyloading.py import sys import importlib from importlib.util import LazyLoader, find_spec, module_from_spec import pytest # Warning raised by _reload_guard() in numpy/__init__.py @pytest.mark.filterwarnings("ignore:The NumPy module was reloaded") def test_lazy_load(): # gh-22045. lazyload doesn't import submodule names into the namespace # muck with sys.modules to test the importing system old_numpy = sys.modules.pop("numpy") numpy_modules = {} for mod_name, mod in list(sys.modules.items()): if mod_name[:6] == "numpy.": numpy_modules[mod_name] = mod sys.modules.pop(mod_name) try: # create lazy load of numpy as np spec = find_spec("numpy") module = module_from_spec(spec) sys.modules["numpy"] = module loader = LazyLoader(spec.loader) loader.exec_module(module) np = module # test a subpackage import from numpy.lib import recfunctions # test triggering the import of the package np.ndarray finally: if old_numpy: sys.modules["numpy"] = old_numpy sys.modules.update(numpy_modules)	1.13 KB	2026-01-20 12:58
📄 test_matlib.py import numpy as np import numpy.matlib from numpy.testing import assert_array_equal, assert_ def test_empty(): x = numpy.matlib.empty((2,)) assert_(isinstance(x, np.matrix)) assert_(x.shape, (1, 2)) def test_ones(): assert_array_equal(numpy.matlib.ones((2, 3)), np.matrix([[ 1., 1., 1.], [ 1., 1., 1.]])) assert_array_equal(numpy.matlib.ones(2), np.matrix([[ 1., 1.]])) def test_zeros(): assert_array_equal(numpy.matlib.zeros((2, 3)), np.matrix([[ 0., 0., 0.], [ 0., 0., 0.]])) assert_array_equal(numpy.matlib.zeros(2), np.matrix([[ 0., 0.]])) def test_identity(): x = numpy.matlib.identity(2, dtype=int) assert_array_equal(x, np.matrix([[1, 0], [0, 1]])) def test_eye(): xc = numpy.matlib.eye(3, k=1, dtype=int) assert_array_equal(xc, np.matrix([[ 0, 1, 0], [ 0, 0, 1], [ 0, 0, 0]])) assert xc.flags.c_contiguous assert not xc.flags.f_contiguous xf = numpy.matlib.eye(3, 4, dtype=int, order='F') assert_array_equal(xf, np.matrix([[ 1, 0, 0, 0], [ 0, 1, 0, 0], [ 0, 0, 1, 0]])) assert not xf.flags.c_contiguous assert xf.flags.f_contiguous def test_rand(): x = numpy.matlib.rand(3) # check matrix type, array would have shape (3,) assert_(x.ndim == 2) def test_randn(): x = np.matlib.randn(3) # check matrix type, array would have shape (3,) assert_(x.ndim == 2) def test_repmat(): a1 = np.arange(4) x = numpy.matlib.repmat(a1, 2, 2) y = np.array([[0, 1, 2, 3, 0, 1, 2, 3], [0, 1, 2, 3, 0, 1, 2, 3]]) assert_array_equal(x, y)	1.81 KB	2026-01-20 12:58
📄 test_numpy_config.py """ Check the numpy config is valid. """ import numpy as np import pytest from unittest.mock import Mock, patch pytestmark = pytest.mark.skipif( not hasattr(np.__config__, "_built_with_meson"), reason="Requires Meson builds", ) class TestNumPyConfigs: REQUIRED_CONFIG_KEYS = [ "Compilers", "Machine Information", "Python Information", ] @patch("numpy.__config__._check_pyyaml") def test_pyyaml_not_found(self, mock_yaml_importer): mock_yaml_importer.side_effect = ModuleNotFoundError() with pytest.warns(UserWarning): np.show_config() def test_dict_mode(self): config = np.show_config(mode="dicts") assert isinstance(config, dict) assert all([key in config for key in self.REQUIRED_CONFIG_KEYS]), ( "Required key missing," " see index of `False` with `REQUIRED_CONFIG_KEYS`" ) def test_invalid_mode(self): with pytest.raises(AttributeError): np.show_config(mode="foo") def test_warn_to_add_tests(self): assert len(np.__config__.DisplayModes) == 2, ( "New mode detected," " please add UT if applicable and increment this count" )	1.21 KB	2026-01-20 12:58
📄 test_numpy_version.py """ Check the numpy version is valid. Note that a development version is marked by the presence of 'dev0' or '+' in the version string, all else is treated as a release. The version string itself is set from the output of ``git describe`` which relies on tags. Examples -------- Valid Development: 1.22.0.dev0 1.22.0.dev0+5-g7999db4df2 1.22.0+5-g7999db4df2 Valid Release: 1.21.0.rc1, 1.21.0.b1, 1.21.0 Invalid: 1.22.0.dev, 1.22.0.dev0-5-g7999db4dfB, 1.21.0.d1, 1.21.a Note that a release is determined by the version string, which in turn is controlled by the result of the ``git describe`` command. """ import re import numpy as np from numpy.testing import assert_ def test_valid_numpy_version(): # Verify that the numpy version is a valid one (no .post suffix or other # nonsense). See gh-6431 for an issue caused by an invalid version. version_pattern = r"^[0-9]+\.[0-9]+\.[0-9]+(a[0-9]\|b[0-9]\|rc[0-9]\|)" dev_suffix = r"(\.dev0\|)(\+[0-9]*\.g[0-9a-f]+\|)" if np.version.release: res = re.match(version_pattern + '$', np.__version__) else: res = re.match(version_pattern + dev_suffix + '$', np.__version__) assert_(res is not None, np.__version__) def test_short_version(): # Check numpy.short_version actually exists if np.version.release: assert_(np.__version__ == np.version.short_version, "short_version mismatch in release version") else: assert_(np.__version__.split("+")[0] == np.version.short_version, "short_version mismatch in development version")	1.54 KB	2026-01-20 12:58
📄 test_public_api.py import sys import sysconfig import subprocess import pkgutil import types import importlib import warnings import numpy as np import numpy import pytest from numpy.testing import IS_WASM try: import ctypes except ImportError: ctypes = None def check_dir(module, module_name=None): """Returns a mapping of all objects with the wrong __module__ attribute.""" if module_name is None: module_name = module.__name__ results = {} for name in dir(module): item = getattr(module, name) if (hasattr(item, '__module__') and hasattr(item, '__name__') and item.__module__ != module_name): results[name] = item.__module__ + '.' + item.__name__ return results def test_numpy_namespace(): # None of these objects are publicly documented to be part of the main # NumPy namespace (some are useful though, others need to be cleaned up) undocumented = { '_add_newdoc_ufunc': 'numpy.core._multiarray_umath._add_newdoc_ufunc', 'add_docstring': 'numpy.core._multiarray_umath.add_docstring', 'add_newdoc': 'numpy.core.function_base.add_newdoc', 'add_newdoc_ufunc': 'numpy.core._multiarray_umath._add_newdoc_ufunc', 'byte_bounds': 'numpy.lib.utils.byte_bounds', 'compare_chararrays': 'numpy.core._multiarray_umath.compare_chararrays', 'deprecate': 'numpy.lib.utils.deprecate', 'deprecate_with_doc': 'numpy.lib.utils.deprecate_with_doc', 'disp': 'numpy.lib.function_base.disp', 'fastCopyAndTranspose': 'numpy.core._multiarray_umath.fastCopyAndTranspose', 'get_array_wrap': 'numpy.lib.shape_base.get_array_wrap', 'get_include': 'numpy.lib.utils.get_include', 'recfromcsv': 'numpy.lib.npyio.recfromcsv', 'recfromtxt': 'numpy.lib.npyio.recfromtxt', 'safe_eval': 'numpy.lib.utils.safe_eval', 'set_string_function': 'numpy.core.arrayprint.set_string_function', 'show_config': 'numpy.__config__.show', 'show_runtime': 'numpy.lib.utils.show_runtime', 'who': 'numpy.lib.utils.who', } # We override dir to not show these members allowlist = undocumented bad_results = check_dir(np) # pytest gives better error messages with the builtin assert than with # assert_equal assert bad_results == allowlist @pytest.mark.skipif(IS_WASM, reason="can't start subprocess") @pytest.mark.parametrize('name', ['testing']) def test_import_lazy_import(name): """Make sure we can actually use the modules we lazy load. While not exported as part of the public API, it was accessible. With the use of __getattr__ and __dir__, this isn't always true It can happen that an infinite recursion may happen. This is the only way I found that would force the failure to appear on the badly implemented code. We also test for the presence of the lazily imported modules in dir """ exe = (sys.executable, '-c', "import numpy; numpy." + name) result = subprocess.check_output(exe) assert not result # Make sure they are still in the __dir__ assert name in dir(np) def test_dir_testing(): """Assert that output of dir has only one "testing/tester" attribute without duplicate""" assert len(dir(np)) == len(set(dir(np))) def test_numpy_linalg(): bad_results = check_dir(np.linalg) assert bad_results == {} def test_numpy_fft(): bad_results = check_dir(np.fft) assert bad_results == {} @pytest.mark.skipif(ctypes is None, reason="ctypes not available in this python") def test_NPY_NO_EXPORT(): cdll = ctypes.CDLL(np.core._multiarray_tests.__file__) # Make sure an arbitrary NPY_NO_EXPORT function is actually hidden f = getattr(cdll, 'test_not_exported', None) assert f is None, ("'test_not_exported' is mistakenly exported, " "NPY_NO_EXPORT does not work") # Historically NumPy has not used leading underscores for private submodules # much. This has resulted in lots of things that look like public modules # (i.e. things that can be imported as `import numpy.somesubmodule.somefile`), # but were never intended to be public. The PUBLIC_MODULES list contains # modules that are either public because they were meant to be, or because they # contain public functions/objects that aren't present in any other namespace # for whatever reason and therefore should be treated as public. # # The PRIVATE_BUT_PRESENT_MODULES list contains modules that look public (lack # of underscores) but should not be used. For many of those modules the # current status is fine. For others it may make sense to work on making them # private, to clean up our public API and avoid confusion. PUBLIC_MODULES = ['numpy.' + s for s in [ "array_api", "array_api.linalg", "ctypeslib", "distutils", "distutils.cpuinfo", "distutils.exec_command", "distutils.misc_util", "distutils.log", "distutils.system_info", "doc", "doc.constants", "doc.ufuncs", "dtypes", "exceptions", "f2py", "fft", "lib", "lib.format", # was this meant to be public? "lib.mixins", "lib.recfunctions", "lib.scimath", "lib.stride_tricks", "linalg", "ma", "ma.extras", "ma.mrecords", "matlib", "polynomial", "polynomial.chebyshev", "polynomial.hermite", "polynomial.hermite_e", "polynomial.laguerre", "polynomial.legendre", "polynomial.polynomial", "random", "testing", "testing.overrides", "typing", "typing.mypy_plugin", "version", ]] PUBLIC_ALIASED_MODULES = [ "numpy.char", "numpy.emath", "numpy.rec", ] PRIVATE_BUT_PRESENT_MODULES = ['numpy.' + s for s in [ "compat", "compat.py3k", "conftest", "core", "core.arrayprint", "core.defchararray", "core.einsumfunc", "core.fromnumeric", "core.function_base", "core.getlimits", "core.memmap", "core.multiarray", "core.numeric", "core.numerictypes", "core.overrides", "core.records", "core.shape_base", "core.umath", "core.umath_tests", "distutils.armccompiler", "distutils.fujitsuccompiler", "distutils.ccompiler", 'distutils.ccompiler_opt', "distutils.command", "distutils.command.autodist", "distutils.command.bdist_rpm", "distutils.command.build", "distutils.command.build_clib", "distutils.command.build_ext", "distutils.command.build_py", "distutils.command.build_scripts", "distutils.command.build_src", "distutils.command.config", "distutils.command.config_compiler", "distutils.command.develop", "distutils.command.egg_info", "distutils.command.install", "distutils.command.install_clib", "distutils.command.install_data", "distutils.command.install_headers", "distutils.command.sdist", "distutils.conv_template", "distutils.core", "distutils.extension", "distutils.fcompiler", "distutils.fcompiler.absoft", "distutils.fcompiler.arm", "distutils.fcompiler.compaq", "distutils.fcompiler.environment", "distutils.fcompiler.g95", "distutils.fcompiler.gnu", "distutils.fcompiler.hpux", "distutils.fcompiler.ibm", "distutils.fcompiler.intel", "distutils.fcompiler.lahey", "distutils.fcompiler.mips", "distutils.fcompiler.nag", "distutils.fcompiler.none", "distutils.fcompiler.pathf95", "distutils.fcompiler.pg", "distutils.fcompiler.nv", "distutils.fcompiler.sun", "distutils.fcompiler.vast", "distutils.fcompiler.fujitsu", "distutils.from_template", "distutils.intelccompiler", "distutils.lib2def", "distutils.line_endings", "distutils.mingw32ccompiler", "distutils.msvccompiler", "distutils.npy_pkg_config", "distutils.numpy_distribution", "distutils.pathccompiler", "distutils.unixccompiler", "f2py.auxfuncs", "f2py.capi_maps", "f2py.cb_rules", "f2py.cfuncs", "f2py.common_rules", "f2py.crackfortran", "f2py.diagnose", "f2py.f2py2e", "f2py.f90mod_rules", "f2py.func2subr", "f2py.rules", "f2py.symbolic", "f2py.use_rules", "fft.helper", "lib.arraypad", "lib.arraysetops", "lib.arrayterator", "lib.function_base", "lib.histograms", "lib.index_tricks", "lib.nanfunctions", "lib.npyio", "lib.polynomial", "lib.shape_base", "lib.twodim_base", "lib.type_check", "lib.ufunclike", "lib.user_array", # note: not in np.lib, but probably should just be deleted "lib.utils", "linalg.lapack_lite", "linalg.linalg", "ma.core", "ma.testutils", "ma.timer_comparison", "matrixlib", "matrixlib.defmatrix", "polynomial.polyutils", "random.mtrand", "random.bit_generator", "testing.print_coercion_tables", ]] def is_unexpected(name): """Check if this needs to be considered.""" if '._' in name or '.tests' in name or '.setup' in name: return False if name in PUBLIC_MODULES: return False if name in PUBLIC_ALIASED_MODULES: return False if name in PRIVATE_BUT_PRESENT_MODULES: return False return True # These are present in a directory with an __init__.py but cannot be imported # code_generators/ isn't installed, but present for an inplace build SKIP_LIST = [ "numpy.core.code_generators", "numpy.core.code_generators.genapi", "numpy.core.code_generators.generate_umath", "numpy.core.code_generators.ufunc_docstrings", "numpy.core.code_generators.generate_numpy_api", "numpy.core.code_generators.generate_ufunc_api", "numpy.core.code_generators.numpy_api", "numpy.core.code_generators.generate_umath_doc", "numpy.core.code_generators.verify_c_api_version", "numpy.core.cversions", "numpy.core.generate_numpy_api", "numpy.distutils.msvc9compiler", ] def test_all_modules_are_expected(): """ Test that we don't add anything that looks like a new public module by accident. Check is based on filenames. """ modnames = [] for _, modname, ispkg in pkgutil.walk_packages(path=np.__path__, prefix=np.__name__ + '.', onerror=None): if is_unexpected(modname) and modname not in SKIP_LIST: # We have a name that is new. If that's on purpose, add it to # PUBLIC_MODULES. We don't expect to have to add anything to # PRIVATE_BUT_PRESENT_MODULES. Use an underscore in the name! modnames.append(modname) if modnames: raise AssertionError(f'Found unexpected modules: {modnames}') # Stuff that clearly shouldn't be in the API and is detected by the next test # below SKIP_LIST_2 = [ 'numpy.math', 'numpy.distutils.log.sys', 'numpy.distutils.log.logging', 'numpy.distutils.log.warnings', 'numpy.doc.constants.re', 'numpy.doc.constants.textwrap', 'numpy.lib.emath', 'numpy.lib.math', 'numpy.matlib.char', 'numpy.matlib.rec', 'numpy.matlib.emath', 'numpy.matlib.exceptions', 'numpy.matlib.math', 'numpy.matlib.linalg', 'numpy.matlib.fft', 'numpy.matlib.random', 'numpy.matlib.ctypeslib', 'numpy.matlib.ma', ] def test_all_modules_are_expected_2(): """ Method checking all objects. The pkgutil-based method in `test_all_modules_are_expected` does not catch imports into a namespace, only filenames. So this test is more thorough, and checks this like: import .lib.scimath as emath To check if something in a module is (effectively) public, one can check if there's anything in that namespace that's a public function/object but is not exposed in a higher-level namespace. For example for a `numpy.lib` submodule:: mod = np.lib.mixins for obj in mod.__all__: if obj in np.__all__: continue elif obj in np.lib.__all__: continue else: print(obj) """ def find_unexpected_members(mod_name): members = [] module = importlib.import_module(mod_name) if hasattr(module, '__all__'): objnames = module.__all__ else: objnames = dir(module) for objname in objnames: if not objname.startswith('_'): fullobjname = mod_name + '.' + objname if isinstance(getattr(module, objname), types.ModuleType): if is_unexpected(fullobjname): if fullobjname not in SKIP_LIST_2: members.append(fullobjname) return members unexpected_members = find_unexpected_members("numpy") for modname in PUBLIC_MODULES: unexpected_members.extend(find_unexpected_members(modname)) if unexpected_members: raise AssertionError("Found unexpected object(s) that look like " "modules: {}".format(unexpected_members)) def test_api_importable(): """ Check that all submodules listed higher up in this file can be imported Note that if a PRIVATE_BUT_PRESENT_MODULES entry goes missing, it may simply need to be removed from the list (deprecation may or may not be needed - apply common sense). """ def check_importable(module_name): try: importlib.import_module(module_name) except (ImportError, AttributeError): return False return True module_names = [] for module_name in PUBLIC_MODULES: if not check_importable(module_name): module_names.append(module_name) if module_names: raise AssertionError("Modules in the public API that cannot be " "imported: {}".format(module_names)) for module_name in PUBLIC_ALIASED_MODULES: try: eval(module_name) except AttributeError: module_names.append(module_name) if module_names: raise AssertionError("Modules in the public API that were not " "found: {}".format(module_names)) with warnings.catch_warnings(record=True) as w: warnings.filterwarnings('always', category=DeprecationWarning) warnings.filterwarnings('always', category=ImportWarning) for module_name in PRIVATE_BUT_PRESENT_MODULES: if not check_importable(module_name): module_names.append(module_name) if module_names: raise AssertionError("Modules that are not really public but looked " "public and can not be imported: " "{}".format(module_names)) @pytest.mark.xfail( hasattr(np.__config__, "_built_with_meson"), reason = "Meson does not yet support entry points via pyproject.toml", ) @pytest.mark.xfail( sysconfig.get_config_var("Py_DEBUG") is not None, reason=( "NumPy possibly built with `USE_DEBUG=True ./tools/travis-test.sh`, " "which does not expose the `array_api` entry point. " "See https://github.com/numpy/numpy/pull/19800" ), ) def test_array_api_entry_point(): """ Entry point for Array API implementation can be found with importlib and returns the numpy.array_api namespace. """ eps = importlib.metadata.entry_points() try: xp_eps = eps.select(group="array_api") except AttributeError: # The select interface for entry_points was introduced in py3.10, # deprecating its dict interface. We fallback to dict keys for finding # Array API entry points so that running this test in <=3.9 will # still work - see https://github.com/numpy/numpy/pull/19800. xp_eps = eps.get("array_api", []) assert len(xp_eps) > 0, "No entry points for 'array_api' found" try: ep = next(ep for ep in xp_eps if ep.name == "numpy") except StopIteration: raise AssertionError("'numpy' not in array_api entry points") from None xp = ep.load() msg = ( f"numpy entry point value '{ep.value}' " "does not point to our Array API implementation" ) assert xp is numpy.array_api, msg @pytest.mark.parametrize("name", [ 'ModuleDeprecationWarning', 'VisibleDeprecationWarning', 'ComplexWarning', 'TooHardError', 'AxisError']) def test_moved_exceptions(name): # These were moved to the exceptions namespace, but currently still # available assert name in np.__all__ assert name not in np.__dir__() # Fetching works, but __module__ is set correctly: assert getattr(np, name).__module__ == "numpy.exceptions" assert name in np.exceptions.__all__ getattr(np.exceptions, name)	16.48 KB	2026-01-20 12:58
📄 test_reloading.py from numpy.testing import ( assert_raises, assert_warns, assert_, assert_equal, IS_WASM, ) from numpy.compat import pickle import pytest import sys import subprocess import textwrap from importlib import reload def test_numpy_reloading(): # gh-7844. Also check that relevant globals retain their identity. import numpy as np import numpy._globals _NoValue = np._NoValue VisibleDeprecationWarning = np.VisibleDeprecationWarning ModuleDeprecationWarning = np.ModuleDeprecationWarning with assert_warns(UserWarning): reload(np) assert_(_NoValue is np._NoValue) assert_(ModuleDeprecationWarning is np.ModuleDeprecationWarning) assert_(VisibleDeprecationWarning is np.VisibleDeprecationWarning) assert_raises(RuntimeError, reload, numpy._globals) with assert_warns(UserWarning): reload(np) assert_(_NoValue is np._NoValue) assert_(ModuleDeprecationWarning is np.ModuleDeprecationWarning) assert_(VisibleDeprecationWarning is np.VisibleDeprecationWarning) def test_novalue(): import numpy as np for proto in range(2, pickle.HIGHEST_PROTOCOL + 1): assert_equal(repr(np._NoValue), '<no value>') assert_(pickle.loads(pickle.dumps(np._NoValue, protocol=proto)) is np._NoValue) @pytest.mark.skipif(IS_WASM, reason="can't start subprocess") def test_full_reimport(): """At the time of writing this, it is not truly supported, but apparently enough users rely on it, for it to be an annoying change when it started failing previously. """ # Test within a new process, to ensure that we do not mess with the # global state during the test run (could lead to cryptic test failures). # This is generally unsafe, especially, since we also reload the C-modules. code = textwrap.dedent(r""" import sys from pytest import warns import numpy as np for k in list(sys.modules.keys()): if "numpy" in k: del sys.modules[k] with warns(UserWarning): import numpy as np """) p = subprocess.run([sys.executable, '-c', code], capture_output=True) if p.returncode: raise AssertionError( f"Non-zero return code: {p.returncode!r}\n\n{p.stderr.decode()}" )	2.3 KB	2026-01-20 12:58
📄 test_scripts.py """ Test scripts Test that we can run executable scripts that have been installed with numpy. """ import sys import os import pytest from os.path import join as pathjoin, isfile, dirname import subprocess import numpy as np from numpy.testing import assert_equal, IS_WASM is_inplace = isfile(pathjoin(dirname(np.__file__), '..', 'setup.py')) def find_f2py_commands(): if sys.platform == 'win32': exe_dir = dirname(sys.executable) if exe_dir.endswith('Scripts'): # virtualenv return [os.path.join(exe_dir, 'f2py')] else: return [os.path.join(exe_dir, "Scripts", 'f2py')] else: # Three scripts are installed in Unix-like systems: # 'f2py', 'f2py{major}', and 'f2py{major.minor}'. For example, # if installed with python3.9 the scripts would be named # 'f2py', 'f2py3', and 'f2py3.9'. version = sys.version_info major = str(version.major) minor = str(version.minor) return ['f2py', 'f2py' + major, 'f2py' + major + '.' + minor] @pytest.mark.skipif(is_inplace, reason="Cannot test f2py command inplace") @pytest.mark.xfail(reason="Test is unreliable") @pytest.mark.parametrize('f2py_cmd', find_f2py_commands()) def test_f2py(f2py_cmd): # test that we can run f2py script stdout = subprocess.check_output([f2py_cmd, '-v']) assert_equal(stdout.strip(), np.__version__.encode('ascii')) @pytest.mark.skipif(IS_WASM, reason="Cannot start subprocess") def test_pep338(): stdout = subprocess.check_output([sys.executable, '-mnumpy.f2py', '-v']) assert_equal(stdout.strip(), np.__version__.encode('ascii'))	1.61 KB	2026-01-20 12:58
📄 test_warnings.py """ Tests which scan for certain occurrences in the code, they may not find all of these occurrences but should catch almost all. """ import pytest from pathlib import Path import ast import tokenize import numpy class ParseCall(ast.NodeVisitor): def __init__(self): self.ls = [] def visit_Attribute(self, node): ast.NodeVisitor.generic_visit(self, node) self.ls.append(node.attr) def visit_Name(self, node): self.ls.append(node.id) class FindFuncs(ast.NodeVisitor): def __init__(self, filename): super().__init__() self.__filename = filename def visit_Call(self, node): p = ParseCall() p.visit(node.func) ast.NodeVisitor.generic_visit(self, node) if p.ls[-1] == 'simplefilter' or p.ls[-1] == 'filterwarnings': if node.args[0].s == "ignore": raise AssertionError( "warnings should have an appropriate stacklevel; found in " "{} on line {}".format(self.__filename, node.lineno)) if p.ls[-1] == 'warn' and ( len(p.ls) == 1 or p.ls[-2] == 'warnings'): if "testing/tests/test_warnings.py" == self.__filename: # This file return # See if stacklevel exists: if len(node.args) == 3: return args = {kw.arg for kw in node.keywords} if "stacklevel" in args: return raise AssertionError( "warnings should have an appropriate stacklevel; found in " "{} on line {}".format(self.__filename, node.lineno)) @pytest.mark.slow def test_warning_calls(): # combined "ignore" and stacklevel error base = Path(numpy.__file__).parent for path in base.rglob("*.py"): if base / "testing" in path.parents: continue if path == base / "__init__.py": continue if path == base / "random" / "__init__.py": continue # use tokenize to auto-detect encoding on systems where no # default encoding is defined (e.g. LANG='C') with tokenize.open(str(path)) as file: tree = ast.parse(file.read()) FindFuncs(path).visit(tree)	2.23 KB	2026-01-20 12:58

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