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502 lines
16 KiB
502 lines
16 KiB
import sys
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import sysconfig
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import subprocess
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import pkgutil
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import types
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import importlib
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import warnings
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import numpy as np
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import numpy
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import pytest
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try:
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import ctypes
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except ImportError:
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ctypes = None
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def check_dir(module, module_name=None):
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"""Returns a mapping of all objects with the wrong __module__ attribute."""
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if module_name is None:
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module_name = module.__name__
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results = {}
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for name in dir(module):
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item = getattr(module, name)
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if (hasattr(item, '__module__') and hasattr(item, '__name__')
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and item.__module__ != module_name):
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results[name] = item.__module__ + '.' + item.__name__
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return results
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def test_numpy_namespace():
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# None of these objects are publicly documented to be part of the main
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# NumPy namespace (some are useful though, others need to be cleaned up)
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undocumented = {
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'Tester': 'numpy.testing._private.nosetester.NoseTester',
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'_add_newdoc_ufunc': 'numpy.core._multiarray_umath._add_newdoc_ufunc',
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'add_docstring': 'numpy.core._multiarray_umath.add_docstring',
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'add_newdoc': 'numpy.core.function_base.add_newdoc',
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'add_newdoc_ufunc': 'numpy.core._multiarray_umath._add_newdoc_ufunc',
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'byte_bounds': 'numpy.lib.utils.byte_bounds',
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'compare_chararrays': 'numpy.core._multiarray_umath.compare_chararrays',
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'deprecate': 'numpy.lib.utils.deprecate',
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'deprecate_with_doc': 'numpy.lib.utils.deprecate_with_doc',
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'disp': 'numpy.lib.function_base.disp',
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'fastCopyAndTranspose': 'numpy.core._multiarray_umath._fastCopyAndTranspose',
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'get_array_wrap': 'numpy.lib.shape_base.get_array_wrap',
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'get_include': 'numpy.lib.utils.get_include',
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'recfromcsv': 'numpy.lib.npyio.recfromcsv',
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'recfromtxt': 'numpy.lib.npyio.recfromtxt',
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'safe_eval': 'numpy.lib.utils.safe_eval',
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'set_string_function': 'numpy.core.arrayprint.set_string_function',
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'show_config': 'numpy.__config__.show',
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'who': 'numpy.lib.utils.who',
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}
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# We override dir to not show these members
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allowlist = undocumented
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bad_results = check_dir(np)
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# pytest gives better error messages with the builtin assert than with
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# assert_equal
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assert bad_results == allowlist
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@pytest.mark.parametrize('name', ['testing', 'Tester'])
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def test_import_lazy_import(name):
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"""Make sure we can actually use the modules we lazy load.
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While not exported as part of the public API, it was accessible. With the
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use of __getattr__ and __dir__, this isn't always true It can happen that
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an infinite recursion may happen.
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This is the only way I found that would force the failure to appear on the
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badly implemented code.
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We also test for the presence of the lazily imported modules in dir
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"""
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exe = (sys.executable, '-c', "import numpy; numpy." + name)
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result = subprocess.check_output(exe)
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assert not result
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# Make sure they are still in the __dir__
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assert name in dir(np)
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def test_dir_testing():
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"""Assert that output of dir has only one "testing/tester"
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attribute without duplicate"""
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assert len(dir(np)) == len(set(dir(np)))
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def test_numpy_linalg():
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bad_results = check_dir(np.linalg)
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assert bad_results == {}
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def test_numpy_fft():
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bad_results = check_dir(np.fft)
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assert bad_results == {}
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@pytest.mark.skipif(ctypes is None,
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reason="ctypes not available in this python")
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def test_NPY_NO_EXPORT():
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cdll = ctypes.CDLL(np.core._multiarray_tests.__file__)
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# Make sure an arbitrary NPY_NO_EXPORT function is actually hidden
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f = getattr(cdll, 'test_not_exported', None)
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assert f is None, ("'test_not_exported' is mistakenly exported, "
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"NPY_NO_EXPORT does not work")
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# Historically NumPy has not used leading underscores for private submodules
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# much. This has resulted in lots of things that look like public modules
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# (i.e. things that can be imported as `import numpy.somesubmodule.somefile`),
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# but were never intended to be public. The PUBLIC_MODULES list contains
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# modules that are either public because they were meant to be, or because they
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# contain public functions/objects that aren't present in any other namespace
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# for whatever reason and therefore should be treated as public.
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#
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# The PRIVATE_BUT_PRESENT_MODULES list contains modules that look public (lack
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# of underscores) but should not be used. For many of those modules the
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# current status is fine. For others it may make sense to work on making them
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# private, to clean up our public API and avoid confusion.
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PUBLIC_MODULES = ['numpy.' + s for s in [
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"array_api",
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"array_api.linalg",
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"ctypeslib",
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"distutils",
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"distutils.cpuinfo",
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"distutils.exec_command",
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"distutils.misc_util",
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"distutils.log",
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"distutils.system_info",
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"doc",
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"doc.constants",
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"doc.ufuncs",
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"f2py",
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"fft",
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"lib",
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"lib.format", # was this meant to be public?
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"lib.mixins",
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"lib.recfunctions",
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"lib.scimath",
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"lib.stride_tricks",
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"linalg",
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"ma",
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"ma.extras",
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"ma.mrecords",
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"matlib",
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"polynomial",
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"polynomial.chebyshev",
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"polynomial.hermite",
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"polynomial.hermite_e",
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"polynomial.laguerre",
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"polynomial.legendre",
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"polynomial.polynomial",
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"random",
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"testing",
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"typing",
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"typing.mypy_plugin",
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"version",
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]]
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PUBLIC_ALIASED_MODULES = [
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"numpy.char",
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"numpy.emath",
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"numpy.rec",
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]
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PRIVATE_BUT_PRESENT_MODULES = ['numpy.' + s for s in [
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"compat",
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"compat.py3k",
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"conftest",
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"core",
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"core.arrayprint",
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"core.defchararray",
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"core.einsumfunc",
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"core.fromnumeric",
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"core.function_base",
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"core.getlimits",
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"core.memmap",
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"core.multiarray",
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"core.numeric",
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"core.numerictypes",
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"core.overrides",
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"core.records",
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"core.shape_base",
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"core.umath",
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"core.umath_tests",
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"distutils.armccompiler",
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"distutils.ccompiler",
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'distutils.ccompiler_opt',
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"distutils.command",
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"distutils.command.autodist",
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"distutils.command.bdist_rpm",
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"distutils.command.build",
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"distutils.command.build_clib",
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"distutils.command.build_ext",
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"distutils.command.build_py",
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"distutils.command.build_scripts",
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"distutils.command.build_src",
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"distutils.command.config",
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"distutils.command.config_compiler",
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"distutils.command.develop",
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"distutils.command.egg_info",
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"distutils.command.install",
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"distutils.command.install_clib",
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"distutils.command.install_data",
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"distutils.command.install_headers",
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"distutils.command.sdist",
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"distutils.conv_template",
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"distutils.core",
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"distutils.extension",
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"distutils.fcompiler",
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"distutils.fcompiler.absoft",
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"distutils.fcompiler.arm",
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"distutils.fcompiler.compaq",
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"distutils.fcompiler.environment",
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"distutils.fcompiler.g95",
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"distutils.fcompiler.gnu",
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"distutils.fcompiler.hpux",
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"distutils.fcompiler.ibm",
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"distutils.fcompiler.intel",
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"distutils.fcompiler.lahey",
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"distutils.fcompiler.mips",
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"distutils.fcompiler.nag",
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"distutils.fcompiler.none",
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"distutils.fcompiler.pathf95",
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"distutils.fcompiler.pg",
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"distutils.fcompiler.nv",
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"distutils.fcompiler.sun",
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"distutils.fcompiler.vast",
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"distutils.fcompiler.fujitsu",
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"distutils.from_template",
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"distutils.intelccompiler",
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"distutils.lib2def",
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"distutils.line_endings",
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"distutils.mingw32ccompiler",
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"distutils.msvccompiler",
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"distutils.npy_pkg_config",
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"distutils.numpy_distribution",
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"distutils.pathccompiler",
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"distutils.unixccompiler",
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"dual",
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"f2py.auxfuncs",
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"f2py.capi_maps",
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"f2py.cb_rules",
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"f2py.cfuncs",
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"f2py.common_rules",
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"f2py.crackfortran",
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"f2py.diagnose",
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"f2py.f2py2e",
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"f2py.f90mod_rules",
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"f2py.func2subr",
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"f2py.rules",
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"f2py.symbolic",
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"f2py.use_rules",
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"fft.helper",
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"lib.arraypad",
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"lib.arraysetops",
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"lib.arrayterator",
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"lib.function_base",
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"lib.histograms",
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"lib.index_tricks",
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"lib.nanfunctions",
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"lib.npyio",
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"lib.polynomial",
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"lib.shape_base",
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"lib.twodim_base",
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"lib.type_check",
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"lib.ufunclike",
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"lib.user_array", # note: not in np.lib, but probably should just be deleted
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"lib.utils",
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"linalg.lapack_lite",
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"linalg.linalg",
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"ma.bench",
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"ma.core",
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"ma.testutils",
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"ma.timer_comparison",
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"matrixlib",
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"matrixlib.defmatrix",
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"polynomial.polyutils",
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"random.mtrand",
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"random.bit_generator",
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"testing.print_coercion_tables",
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"testing.utils",
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]]
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def is_unexpected(name):
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"""Check if this needs to be considered."""
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if '._' in name or '.tests' in name or '.setup' in name:
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return False
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if name in PUBLIC_MODULES:
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return False
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if name in PUBLIC_ALIASED_MODULES:
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return False
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if name in PRIVATE_BUT_PRESENT_MODULES:
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return False
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return True
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# These are present in a directory with an __init__.py but cannot be imported
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# code_generators/ isn't installed, but present for an inplace build
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SKIP_LIST = [
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"numpy.core.code_generators",
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"numpy.core.code_generators.genapi",
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"numpy.core.code_generators.generate_umath",
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"numpy.core.code_generators.ufunc_docstrings",
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"numpy.core.code_generators.generate_numpy_api",
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"numpy.core.code_generators.generate_ufunc_api",
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"numpy.core.code_generators.numpy_api",
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"numpy.core.code_generators.generate_umath_doc",
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"numpy.core.cversions",
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"numpy.core.generate_numpy_api",
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"numpy.distutils.msvc9compiler",
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]
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def test_all_modules_are_expected():
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"""
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Test that we don't add anything that looks like a new public module by
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accident. Check is based on filenames.
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"""
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modnames = []
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for _, modname, ispkg in pkgutil.walk_packages(path=np.__path__,
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prefix=np.__name__ + '.',
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onerror=None):
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if is_unexpected(modname) and modname not in SKIP_LIST:
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# We have a name that is new. If that's on purpose, add it to
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# PUBLIC_MODULES. We don't expect to have to add anything to
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# PRIVATE_BUT_PRESENT_MODULES. Use an underscore in the name!
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modnames.append(modname)
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if modnames:
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raise AssertionError(f'Found unexpected modules: {modnames}')
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# Stuff that clearly shouldn't be in the API and is detected by the next test
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# below
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SKIP_LIST_2 = [
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'numpy.math',
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'numpy.distutils.log.sys',
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'numpy.doc.constants.re',
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'numpy.doc.constants.textwrap',
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'numpy.lib.emath',
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'numpy.lib.math',
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'numpy.matlib.char',
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'numpy.matlib.rec',
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'numpy.matlib.emath',
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'numpy.matlib.math',
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'numpy.matlib.linalg',
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'numpy.matlib.fft',
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'numpy.matlib.random',
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'numpy.matlib.ctypeslib',
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'numpy.matlib.ma',
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]
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def test_all_modules_are_expected_2():
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"""
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Method checking all objects. The pkgutil-based method in
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`test_all_modules_are_expected` does not catch imports into a namespace,
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only filenames. So this test is more thorough, and checks this like:
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import .lib.scimath as emath
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To check if something in a module is (effectively) public, one can check if
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there's anything in that namespace that's a public function/object but is
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not exposed in a higher-level namespace. For example for a `numpy.lib`
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submodule::
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mod = np.lib.mixins
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for obj in mod.__all__:
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if obj in np.__all__:
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continue
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elif obj in np.lib.__all__:
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continue
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else:
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print(obj)
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"""
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def find_unexpected_members(mod_name):
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members = []
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module = importlib.import_module(mod_name)
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if hasattr(module, '__all__'):
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objnames = module.__all__
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else:
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objnames = dir(module)
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for objname in objnames:
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if not objname.startswith('_'):
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fullobjname = mod_name + '.' + objname
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if isinstance(getattr(module, objname), types.ModuleType):
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if is_unexpected(fullobjname):
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if fullobjname not in SKIP_LIST_2:
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members.append(fullobjname)
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return members
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unexpected_members = find_unexpected_members("numpy")
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for modname in PUBLIC_MODULES:
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unexpected_members.extend(find_unexpected_members(modname))
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if unexpected_members:
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raise AssertionError("Found unexpected object(s) that look like "
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"modules: {}".format(unexpected_members))
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def test_api_importable():
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"""
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Check that all submodules listed higher up in this file can be imported
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Note that if a PRIVATE_BUT_PRESENT_MODULES entry goes missing, it may
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simply need to be removed from the list (deprecation may or may not be
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needed - apply common sense).
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"""
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def check_importable(module_name):
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try:
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importlib.import_module(module_name)
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except (ImportError, AttributeError):
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return False
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return True
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module_names = []
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for module_name in PUBLIC_MODULES:
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if not check_importable(module_name):
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module_names.append(module_name)
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if module_names:
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raise AssertionError("Modules in the public API that cannot be "
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"imported: {}".format(module_names))
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for module_name in PUBLIC_ALIASED_MODULES:
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try:
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eval(module_name)
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except AttributeError:
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module_names.append(module_name)
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|
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if module_names:
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raise AssertionError("Modules in the public API that were not "
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"found: {}".format(module_names))
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with warnings.catch_warnings(record=True) as w:
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warnings.filterwarnings('always', category=DeprecationWarning)
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warnings.filterwarnings('always', category=ImportWarning)
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for module_name in PRIVATE_BUT_PRESENT_MODULES:
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if not check_importable(module_name):
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module_names.append(module_name)
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if module_names:
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raise AssertionError("Modules that are not really public but looked "
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"public and can not be imported: "
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"{}".format(module_names))
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@pytest.mark.xfail(
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sysconfig.get_config_var("Py_DEBUG") is not None,
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reason=(
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"NumPy possibly built with `USE_DEBUG=True ./tools/travis-test.sh`, "
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"which does not expose the `array_api` entry point. "
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"See https://github.com/numpy/numpy/pull/19800"
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),
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)
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def test_array_api_entry_point():
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"""
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Entry point for Array API implementation can be found with importlib and
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returns the numpy.array_api namespace.
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"""
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eps = importlib.metadata.entry_points()
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try:
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xp_eps = eps.select(group="array_api")
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except AttributeError:
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# The select interface for entry_points was introduced in py3.10,
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# deprecating its dict interface. We fallback to dict keys for finding
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# Array API entry points so that running this test in <=3.9 will
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# still work - see https://github.com/numpy/numpy/pull/19800.
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xp_eps = eps.get("array_api", [])
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assert len(xp_eps) > 0, "No entry points for 'array_api' found"
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try:
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ep = next(ep for ep in xp_eps if ep.name == "numpy")
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except StopIteration:
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raise AssertionError("'numpy' not in array_api entry points") from None
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xp = ep.load()
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msg = (
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f"numpy entry point value '{ep.value}' "
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"does not point to our Array API implementation"
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)
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assert xp is numpy.array_api, msg
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