248 lines
8.2 KiB
Python
248 lines
8.2 KiB
Python
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"""
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Pytest configuration and fixtures for the Numpy test suite.
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"""
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import os
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import sys
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import tempfile
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from contextlib import contextmanager
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import warnings
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import hypothesis
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import pytest
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import numpy
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from numpy._core._multiarray_tests import get_fpu_mode
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from numpy.testing._private.utils import NOGIL_BUILD
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try:
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from scipy_doctest.conftest import dt_config
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HAVE_SCPDT = True
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except ModuleNotFoundError:
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HAVE_SCPDT = False
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_old_fpu_mode = None
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_collect_results = {}
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# Use a known and persistent tmpdir for hypothesis' caches, which
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# can be automatically cleared by the OS or user.
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hypothesis.configuration.set_hypothesis_home_dir(
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os.path.join(tempfile.gettempdir(), ".hypothesis")
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)
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# We register two custom profiles for Numpy - for details see
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# https://hypothesis.readthedocs.io/en/latest/settings.html
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# The first is designed for our own CI runs; the latter also
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# forces determinism and is designed for use via np.test()
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hypothesis.settings.register_profile(
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name="numpy-profile", deadline=None, print_blob=True,
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)
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hypothesis.settings.register_profile(
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name="np.test() profile",
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deadline=None, print_blob=True, database=None, derandomize=True,
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suppress_health_check=list(hypothesis.HealthCheck),
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)
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# Note that the default profile is chosen based on the presence
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# of pytest.ini, but can be overridden by passing the
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# --hypothesis-profile=NAME argument to pytest.
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_pytest_ini = os.path.join(os.path.dirname(__file__), "..", "pytest.ini")
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hypothesis.settings.load_profile(
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"numpy-profile" if os.path.isfile(_pytest_ini) else "np.test() profile"
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)
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# The experimentalAPI is used in _umath_tests
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os.environ["NUMPY_EXPERIMENTAL_DTYPE_API"] = "1"
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def pytest_configure(config):
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config.addinivalue_line("markers",
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"valgrind_error: Tests that are known to error under valgrind.")
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config.addinivalue_line("markers",
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"leaks_references: Tests that are known to leak references.")
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config.addinivalue_line("markers",
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"slow: Tests that are very slow.")
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config.addinivalue_line("markers",
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"slow_pypy: Tests that are very slow on pypy.")
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def pytest_addoption(parser):
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parser.addoption("--available-memory", action="store", default=None,
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help=("Set amount of memory available for running the "
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"test suite. This can result to tests requiring "
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"especially large amounts of memory to be skipped. "
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"Equivalent to setting environment variable "
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"NPY_AVAILABLE_MEM. Default: determined"
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"automatically."))
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gil_enabled_at_start = True
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if NOGIL_BUILD:
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gil_enabled_at_start = sys._is_gil_enabled()
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def pytest_sessionstart(session):
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available_mem = session.config.getoption('available_memory')
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if available_mem is not None:
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os.environ['NPY_AVAILABLE_MEM'] = available_mem
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def pytest_terminal_summary(terminalreporter, exitstatus, config):
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if NOGIL_BUILD and not gil_enabled_at_start and sys._is_gil_enabled():
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tr = terminalreporter
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tr.ensure_newline()
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tr.section("GIL re-enabled", sep="=", red=True, bold=True)
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tr.line("The GIL was re-enabled at runtime during the tests.")
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tr.line("This can happen with no test failures if the RuntimeWarning")
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tr.line("raised by Python when this happens is filtered by a test.")
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tr.line("")
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tr.line("Please ensure all new C modules declare support for running")
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tr.line("without the GIL. Any new tests that intentionally imports ")
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tr.line("code that re-enables the GIL should do so in a subprocess.")
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pytest.exit("GIL re-enabled during tests", returncode=1)
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#FIXME when yield tests are gone.
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@pytest.hookimpl()
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def pytest_itemcollected(item):
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"""
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Check FPU precision mode was not changed during test collection.
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The clumsy way we do it here is mainly necessary because numpy
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still uses yield tests, which can execute code at test collection
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time.
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"""
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global _old_fpu_mode
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mode = get_fpu_mode()
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if _old_fpu_mode is None:
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_old_fpu_mode = mode
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elif mode != _old_fpu_mode:
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_collect_results[item] = (_old_fpu_mode, mode)
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_old_fpu_mode = mode
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@pytest.fixture(scope="function", autouse=True)
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def check_fpu_mode(request):
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"""
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Check FPU precision mode was not changed during the test.
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"""
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old_mode = get_fpu_mode()
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yield
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new_mode = get_fpu_mode()
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if old_mode != new_mode:
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raise AssertionError("FPU precision mode changed from {0:#x} to {1:#x}"
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" during the test".format(old_mode, new_mode))
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collect_result = _collect_results.get(request.node)
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if collect_result is not None:
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old_mode, new_mode = collect_result
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raise AssertionError("FPU precision mode changed from {0:#x} to {1:#x}"
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" when collecting the test".format(old_mode,
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new_mode))
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@pytest.fixture(autouse=True)
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def add_np(doctest_namespace):
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doctest_namespace['np'] = numpy
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@pytest.fixture(autouse=True)
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def env_setup(monkeypatch):
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monkeypatch.setenv('PYTHONHASHSEED', '0')
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@pytest.fixture(params=[True, False])
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def weak_promotion(request):
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"""
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Fixture to ensure "legacy" promotion state or change it to use the new
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weak promotion (plus warning). `old_promotion` should be used as a
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parameter in the function.
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"""
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state = numpy._get_promotion_state()
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if request.param:
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numpy._set_promotion_state("weak_and_warn")
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else:
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numpy._set_promotion_state("legacy")
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yield request.param
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numpy._set_promotion_state(state)
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if HAVE_SCPDT:
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@contextmanager
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def warnings_errors_and_rng(test=None):
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"""Filter out the wall of DeprecationWarnings.
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"""
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msgs = ["The numpy.linalg.linalg",
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"The numpy.fft.helper",
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"dep_util",
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"pkg_resources",
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"numpy.core.umath",
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"msvccompiler",
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"Deprecated call",
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"numpy.core",
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"`np.compat`",
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"Importing from numpy.matlib",
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"This function is deprecated.", # random_integers
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"Data type alias 'a'", # numpy.rec.fromfile
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"Arrays of 2-dimensional vectors", # matlib.cross
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"`in1d` is deprecated", ]
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msg = "|".join(msgs)
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msgs_r = [
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"invalid value encountered",
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"divide by zero encountered"
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]
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msg_r = "|".join(msgs_r)
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with warnings.catch_warnings():
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warnings.filterwarnings(
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'ignore', category=DeprecationWarning, message=msg
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)
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warnings.filterwarnings(
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'ignore', category=RuntimeWarning, message=msg_r
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)
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yield
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# find and check doctests under this context manager
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dt_config.user_context_mgr = warnings_errors_and_rng
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# numpy specific tweaks from refguide-check
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dt_config.rndm_markers.add('#uninitialized')
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dt_config.rndm_markers.add('# uninitialized')
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import doctest
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dt_config.optionflags = doctest.NORMALIZE_WHITESPACE | doctest.ELLIPSIS
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# recognize the StringDType repr
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dt_config.check_namespace['StringDType'] = numpy.dtypes.StringDType
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# temporary skips
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dt_config.skiplist = set([
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'numpy.savez', # unclosed file
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'numpy.matlib.savez',
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'numpy.__array_namespace_info__',
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'numpy.matlib.__array_namespace_info__',
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])
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# xfail problematic tutorials
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dt_config.pytest_extra_xfail = {
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'how-to-verify-bug.rst': '',
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'c-info.ufunc-tutorial.rst': '',
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'basics.interoperability.rst': 'needs pandas',
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'basics.dispatch.rst': 'errors out in /testing/overrides.py',
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'basics.subclassing.rst': '.. testcode:: admonitions not understood',
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'misc.rst': 'manipulates warnings',
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}
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# ignores are for things fail doctest collection (optionals etc)
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dt_config.pytest_extra_ignore = [
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'numpy/distutils',
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'numpy/_core/cversions.py',
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'numpy/_pyinstaller',
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'numpy/random/_examples',
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'numpy/compat',
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'numpy/f2py/_backends/_distutils.py',
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]
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