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Old engine for Continuous Time Bayesian Networks. Superseded by reCTBN. 🐍 https://github.com/madlabunimib/PyCTBN
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PyCTBN/venv/lib/python3.9/site-packages/numpy/tests/test_public_api.py

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import sys
import subprocess
import pkgutil
import types
import importlib
import warnings
import numpy as np
import numpy
import pytest
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 = {
'Tester': 'numpy.testing._private.nosetester.NoseTester',
'_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.<lambda>',
'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',
'mafromtxt': 'numpy.lib.npyio.mafromtxt',
'ndfromtxt': 'numpy.lib.npyio.ndfromtxt',
'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',
'who': 'numpy.lib.utils.who',
}
# These built-in types are re-exported by numpy.
builtins = {
'bool': 'builtins.bool',
'complex': 'builtins.complex',
'float': 'builtins.float',
'int': 'builtins.int',
'long': 'builtins.int',
'object': 'builtins.object',
'str': 'builtins.str',
'unicode': 'builtins.str',
}
whitelist = dict(undocumented, **builtins)
bad_results = check_dir(np)
# pytest gives better error messages with the builtin assert than with
# assert_equal
assert bad_results == whitelist
@pytest.mark.parametrize('name', ['testing', 'Tester'])
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 [
"ctypeslib",
"distutils",
"distutils.cpuinfo",
"distutils.exec_command",
"distutils.misc_util",
"distutils.log",
"distutils.system_info",
"doc",
"doc.basics",
"doc.broadcasting",
"doc.byteswapping",
"doc.constants",
"doc.creation",
"doc.dispatch",
"doc.glossary",
"doc.indexing",
"doc.internals",
"doc.misc",
"doc.structured_arrays",
"doc.subclassing",
"doc.ufuncs",
"dual",
"f2py",
"fft",
"lib",
"lib.format", # was this meant to be public?
"lib.mixins",
"lib.recfunctions",
"lib.scimath",
"linalg",
"ma",
"ma.extras",
"ma.mrecords",
"matlib",
"polynomial",
"polynomial.chebyshev",
"polynomial.hermite",
"polynomial.hermite_e",
"polynomial.laguerre",
"polynomial.legendre",
"polynomial.polynomial",
"polynomial.polyutils",
"random",
"testing",
"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.machar",
"core.memmap",
"core.multiarray",
"core.numeric",
"core.numerictypes",
"core.overrides",
"core.records",
"core.shape_base",
"core.umath",
"core.umath_tests",
"distutils.ccompiler",
"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.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.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.f2py_testing",
"f2py.f90mod_rules",
"f2py.func2subr",
"f2py.rules",
"f2py.use_rules",
"fft.helper",
"lib.arraypad",
"lib.arraysetops",
"lib.arrayterator",
"lib.financial",
"lib.function_base",
"lib.histograms",
"lib.index_tricks",
"lib.nanfunctions",
"lib.npyio",
"lib.polynomial",
"lib.shape_base",
"lib.stride_tricks",
"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.bench",
"ma.core",
"ma.testutils",
"ma.timer_comparison",
"matrixlib",
"matrixlib.defmatrix",
"random.mtrand",
"random.bit_generator",
"testing.print_coercion_tables",
"testing.utils",
]]
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.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("Found unexpected modules: {}".format(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.system_info.copy',
'numpy.distutils.system_info.distutils',
'numpy.distutils.system_info.log',
'numpy.distutils.system_info.os',
'numpy.distutils.system_info.platform',
'numpy.distutils.system_info.re',
'numpy.distutils.system_info.shutil',
'numpy.distutils.system_info.subprocess',
'numpy.distutils.system_info.sys',
'numpy.distutils.system_info.tempfile',
'numpy.distutils.system_info.textwrap',
'numpy.distutils.system_info.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.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))