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Edit File: test_utils.py
import warnings import sys import os import itertools import pytest import weakref import numpy as np from numpy.testing import ( assert_equal, assert_array_equal, assert_almost_equal, assert_array_almost_equal, assert_array_less, build_err_msg, raises, assert_raises, assert_warns, assert_no_warnings, assert_allclose, assert_approx_equal, assert_array_almost_equal_nulp, assert_array_max_ulp, clear_and_catch_warnings, suppress_warnings, assert_string_equal, assert_, tempdir, temppath, assert_no_gc_cycles, HAS_REFCOUNT ) from numpy.core.overrides import ARRAY_FUNCTION_ENABLED class _GenericTest: def _test_equal(self, a, b): self._assert_func(a, b) def _test_not_equal(self, a, b): with assert_raises(AssertionError): self._assert_func(a, b) def test_array_rank1_eq(self): """Test two equal array of rank 1 are found equal.""" a = np.array([1, 2]) b = np.array([1, 2]) self._test_equal(a, b) def test_array_rank1_noteq(self): """Test two different array of rank 1 are found not equal.""" a = np.array([1, 2]) b = np.array([2, 2]) self._test_not_equal(a, b) def test_array_rank2_eq(self): """Test two equal array of rank 2 are found equal.""" a = np.array([[1, 2], [3, 4]]) b = np.array([[1, 2], [3, 4]]) self._test_equal(a, b) def test_array_diffshape(self): """Test two arrays with different shapes are found not equal.""" a = np.array([1, 2]) b = np.array([[1, 2], [1, 2]]) self._test_not_equal(a, b) def test_objarray(self): """Test object arrays.""" a = np.array([1, 1], dtype=object) self._test_equal(a, 1) def test_array_likes(self): self._test_equal([1, 2, 3], (1, 2, 3)) class TestArrayEqual(_GenericTest): def setup_method(self): self._assert_func = assert_array_equal def test_generic_rank1(self): """Test rank 1 array for all dtypes.""" def foo(t): a = np.empty(2, t) a.fill(1) b = a.copy() c = a.copy() c.fill(0) self._test_equal(a, b) self._test_not_equal(c, b) # Test numeric types and object for t in '?bhilqpBHILQPfdgFDG': foo(t) # Test strings for t in ['S1', 'U1']: foo(t) def test_0_ndim_array(self): x = np.array(473963742225900817127911193656584771) y = np.array(18535119325151578301457182298393896) assert_raises(AssertionError, self._assert_func, x, y) y = x self._assert_func(x, y) x = np.array(43) y = np.array(10) assert_raises(AssertionError, self._assert_func, x, y) y = x self._assert_func(x, y) def test_generic_rank3(self): """Test rank 3 array for all dtypes.""" def foo(t): a = np.empty((4, 2, 3), t) a.fill(1) b = a.copy() c = a.copy() c.fill(0) self._test_equal(a, b) self._test_not_equal(c, b) # Test numeric types and object for t in '?bhilqpBHILQPfdgFDG': foo(t) # Test strings for t in ['S1', 'U1']: foo(t) def test_nan_array(self): """Test arrays with nan values in them.""" a = np.array([1, 2, np.nan]) b = np.array([1, 2, np.nan]) self._test_equal(a, b) c = np.array([1, 2, 3]) self._test_not_equal(c, b) def test_string_arrays(self): """Test two arrays with different shapes are found not equal.""" a = np.array(['floupi', 'floupa']) b = np.array(['floupi', 'floupa']) self._test_equal(a, b) c = np.array(['floupipi', 'floupa']) self._test_not_equal(c, b) def test_recarrays(self): """Test record arrays.""" a = np.empty(2, [('floupi', float), ('floupa', float)]) a['floupi'] = [1, 2] a['floupa'] = [1, 2] b = a.copy() self._test_equal(a, b) c = np.empty(2, [('floupipi', float), ('floupi', float), ('floupa', float)]) c['floupipi'] = a['floupi'].copy() c['floupa'] = a['floupa'].copy() with pytest.raises(TypeError): self._test_not_equal(c, b) def test_masked_nan_inf(self): # Regression test for gh-11121 a = np.ma.MaskedArray([3., 4., 6.5], mask=[False, True, False]) b = np.array([3., np.nan, 6.5]) self._test_equal(a, b) self._test_equal(b, a) a = np.ma.MaskedArray([3., 4., 6.5], mask=[True, False, False]) b = np.array([np.inf, 4., 6.5]) self._test_equal(a, b) self._test_equal(b, a) def test_subclass_that_overrides_eq(self): # While we cannot guarantee testing functions will always work for # subclasses, the tests should ideally rely only on subclasses having # comparison operators, not on them being able to store booleans # (which, e.g., astropy Quantity cannot usefully do). See gh-8452. class MyArray(np.ndarray): def __eq__(self, other): return bool(np.equal(self, other).all()) def __ne__(self, other): return not self == other a = np.array([1., 2.]).view(MyArray) b = np.array([2., 3.]).view(MyArray) assert_(type(a == a), bool) assert_(a == a) assert_(a != b) self._test_equal(a, a) self._test_not_equal(a, b) self._test_not_equal(b, a) @pytest.mark.skipif( not ARRAY_FUNCTION_ENABLED, reason='requires __array_function__') def test_subclass_that_does_not_implement_npall(self): class MyArray(np.ndarray): def __array_function__(self, *args, **kwargs): return NotImplemented a = np.array([1., 2.]).view(MyArray) b = np.array([2., 3.]).view(MyArray) with assert_raises(TypeError): np.all(a) self._test_equal(a, a) self._test_not_equal(a, b) self._test_not_equal(b, a) def test_suppress_overflow_warnings(self): # Based on issue #18992 with pytest.raises(AssertionError): with np.errstate(all="raise"): np.testing.assert_array_equal( np.array([1, 2, 3], np.float32), np.array([1, 1e-40, 3], np.float32)) def test_array_vs_scalar_is_equal(self): """Test comparing an array with a scalar when all values are equal.""" a = np.array([1., 1., 1.]) b = 1. self._test_equal(a, b) def test_array_vs_scalar_not_equal(self): """Test comparing an array with a scalar when not all values equal.""" a = np.array([1., 2., 3.]) b = 1. self._test_not_equal(a, b) def test_array_vs_scalar_strict(self): """Test comparing an array with a scalar with strict option.""" a = np.array([1., 1., 1.]) b = 1. with pytest.raises(AssertionError): assert_array_equal(a, b, strict=True) def test_array_vs_array_strict(self): """Test comparing two arrays with strict option.""" a = np.array([1., 1., 1.]) b = np.array([1., 1., 1.]) assert_array_equal(a, b, strict=True) def test_array_vs_float_array_strict(self): """Test comparing two arrays with strict option.""" a = np.array([1, 1, 1]) b = np.array([1., 1., 1.]) with pytest.raises(AssertionError): assert_array_equal(a, b, strict=True) class TestBuildErrorMessage: def test_build_err_msg_defaults(self): x = np.array([1.00001, 2.00002, 3.00003]) y = np.array([1.00002, 2.00003, 3.00004]) err_msg = 'There is a mismatch' a = build_err_msg([x, y], err_msg) b = ('\nItems are not equal: There is a mismatch\n ACTUAL: array([' '1.00001, 2.00002, 3.00003])\n DESIRED: array([1.00002, ' '2.00003, 3.00004])') assert_equal(a, b) def test_build_err_msg_no_verbose(self): x = np.array([1.00001, 2.00002, 3.00003]) y = np.array([1.00002, 2.00003, 3.00004]) err_msg = 'There is a mismatch' a = build_err_msg([x, y], err_msg, verbose=False) b = '\nItems are not equal: There is a mismatch' assert_equal(a, b) def test_build_err_msg_custom_names(self): x = np.array([1.00001, 2.00002, 3.00003]) y = np.array([1.00002, 2.00003, 3.00004]) err_msg = 'There is a mismatch' a = build_err_msg([x, y], err_msg, names=('FOO', 'BAR')) b = ('\nItems are not equal: There is a mismatch\n FOO: array([' '1.00001, 2.00002, 3.00003])\n BAR: array([1.00002, 2.00003, ' '3.00004])') assert_equal(a, b) def test_build_err_msg_custom_precision(self): x = np.array([1.000000001, 2.00002, 3.00003]) y = np.array([1.000000002, 2.00003, 3.00004]) err_msg = 'There is a mismatch' a = build_err_msg([x, y], err_msg, precision=10) b = ('\nItems are not equal: There is a mismatch\n ACTUAL: array([' '1.000000001, 2.00002 , 3.00003 ])\n DESIRED: array([' '1.000000002, 2.00003 , 3.00004 ])') assert_equal(a, b) class TestEqual(TestArrayEqual): def setup_method(self): self._assert_func = assert_equal def test_nan_items(self): self._assert_func(np.nan, np.nan) self._assert_func([np.nan], [np.nan]) self._test_not_equal(np.nan, [np.nan]) self._test_not_equal(np.nan, 1) def test_inf_items(self): self._assert_func(np.inf, np.inf) self._assert_func([np.inf], [np.inf]) self._test_not_equal(np.inf, [np.inf]) def test_datetime(self): self._test_equal( np.datetime64("2017-01-01", "s"), np.datetime64("2017-01-01", "s") ) self._test_equal( np.datetime64("2017-01-01", "s"), np.datetime64("2017-01-01", "m") ) # gh-10081 self._test_not_equal( np.datetime64("2017-01-01", "s"), np.datetime64("2017-01-02", "s") ) self._test_not_equal( np.datetime64("2017-01-01", "s"), np.datetime64("2017-01-02", "m") ) def test_nat_items(self): # not a datetime nadt_no_unit = np.datetime64("NaT") nadt_s = np.datetime64("NaT", "s") nadt_d = np.datetime64("NaT", "ns") # not a timedelta natd_no_unit = np.timedelta64("NaT") natd_s = np.timedelta64("NaT", "s") natd_d = np.timedelta64("NaT", "ns") dts = [nadt_no_unit, nadt_s, nadt_d] tds = [natd_no_unit, natd_s, natd_d] for a, b in itertools.product(dts, dts): self._assert_func(a, b) self._assert_func([a], [b]) self._test_not_equal([a], b) for a, b in itertools.product(tds, tds): self._assert_func(a, b) self._assert_func([a], [b]) self._test_not_equal([a], b) for a, b in itertools.product(tds, dts): self._test_not_equal(a, b) self._test_not_equal(a, [b]) self._test_not_equal([a], [b]) self._test_not_equal([a], np.datetime64("2017-01-01", "s")) self._test_not_equal([b], np.datetime64("2017-01-01", "s")) self._test_not_equal([a], np.timedelta64(123, "s")) self._test_not_equal([b], np.timedelta64(123, "s")) def test_non_numeric(self): self._assert_func('ab', 'ab') self._test_not_equal('ab', 'abb') def test_complex_item(self): self._assert_func(complex(1, 2), complex(1, 2)) self._assert_func(complex(1, np.nan), complex(1, np.nan)) self._test_not_equal(complex(1, np.nan), complex(1, 2)) self._test_not_equal(complex(np.nan, 1), complex(1, np.nan)) self._test_not_equal(complex(np.nan, np.inf), complex(np.nan, 2)) def test_negative_zero(self): self._test_not_equal(np.PZERO, np.NZERO) def test_complex(self): x = np.array([complex(1, 2), complex(1, np.nan)]) y = np.array([complex(1, 2), complex(1, 2)]) self._assert_func(x, x) self._test_not_equal(x, y) def test_object(self): #gh-12942 import datetime a = np.array([datetime.datetime(2000, 1, 1), datetime.datetime(2000, 1, 2)]) self._test_not_equal(a, a[::-1]) class TestArrayAlmostEqual(_GenericTest): def setup_method(self): self._assert_func = assert_array_almost_equal def test_closeness(self): # Note that in the course of time we ended up with # `abs(x - y) < 1.5 * 10**(-decimal)` # instead of the previously documented # `abs(x - y) < 0.5 * 10**(-decimal)` # so this check serves to preserve the wrongness. # test scalars self._assert_func(1.499999, 0.0, decimal=0) assert_raises(AssertionError, lambda: self._assert_func(1.5, 0.0, decimal=0)) # test arrays self._assert_func([1.499999], [0.0], decimal=0) assert_raises(AssertionError, lambda: self._assert_func([1.5], [0.0], decimal=0)) def test_simple(self): x = np.array([1234.2222]) y = np.array([1234.2223]) self._assert_func(x, y, decimal=3) self._assert_func(x, y, decimal=4) assert_raises(AssertionError, lambda: self._assert_func(x, y, decimal=5)) def test_nan(self): anan = np.array([np.nan]) aone = np.array([1]) ainf = np.array([np.inf]) self._assert_func(anan, anan) assert_raises(AssertionError, lambda: self._assert_func(anan, aone)) assert_raises(AssertionError, lambda: self._assert_func(anan, ainf)) assert_raises(AssertionError, lambda: self._assert_func(ainf, anan)) def test_inf(self): a = np.array([[1., 2.], [3., 4.]]) b = a.copy() a[0, 0] = np.inf assert_raises(AssertionError, lambda: self._assert_func(a, b)) b[0, 0] = -np.inf assert_raises(AssertionError, lambda: self._assert_func(a, b)) def test_subclass(self): a = np.array([[1., 2.], [3., 4.]]) b = np.ma.masked_array([[1., 2.], [0., 4.]], [[False, False], [True, False]]) self._assert_func(a, b) self._assert_func(b, a) self._assert_func(b, b) # Test fully masked as well (see gh-11123). a = np.ma.MaskedArray(3.5, mask=True) b = np.array([3., 4., 6.5]) self._test_equal(a, b) self._test_equal(b, a) a = np.ma.masked b = np.array([3., 4., 6.5]) self._test_equal(a, b) self._test_equal(b, a) a = np.ma.MaskedArray([3., 4., 6.5], mask=[True, True, True]) b = np.array([1., 2., 3.]) self._test_equal(a, b) self._test_equal(b, a) a = np.ma.MaskedArray([3., 4., 6.5], mask=[True, True, True]) b = np.array(1.) self._test_equal(a, b) self._test_equal(b, a) def test_subclass_that_cannot_be_bool(self): # While we cannot guarantee testing functions will always work for # subclasses, the tests should ideally rely only on subclasses having # comparison operators, not on them being able to store booleans # (which, e.g., astropy Quantity cannot usefully do). See gh-8452. class MyArray(np.ndarray): def __eq__(self, other): return super().__eq__(other).view(np.ndarray) def __lt__(self, other): return super().__lt__(other).view(np.ndarray) def all(self, *args, **kwargs): raise NotImplementedError a = np.array([1., 2.]).view(MyArray) self._assert_func(a, a) class TestAlmostEqual(_GenericTest): def setup_method(self): self._assert_func = assert_almost_equal def test_closeness(self): # Note that in the course of time we ended up with # `abs(x - y) < 1.5 * 10**(-decimal)` # instead of the previously documented # `abs(x - y) < 0.5 * 10**(-decimal)` # so this check serves to preserve the wrongness. # test scalars self._assert_func(1.499999, 0.0, decimal=0) assert_raises(AssertionError, lambda: self._assert_func(1.5, 0.0, decimal=0)) # test arrays self._assert_func([1.499999], [0.0], decimal=0) assert_raises(AssertionError, lambda: self._assert_func([1.5], [0.0], decimal=0)) def test_nan_item(self): self._assert_func(np.nan, np.nan) assert_raises(AssertionError, lambda: self._assert_func(np.nan, 1)) assert_raises(AssertionError, lambda: self._assert_func(np.nan, np.inf)) assert_raises(AssertionError, lambda: self._assert_func(np.inf, np.nan)) def test_inf_item(self): self._assert_func(np.inf, np.inf) self._assert_func(-np.inf, -np.inf) assert_raises(AssertionError, lambda: self._assert_func(np.inf, 1)) assert_raises(AssertionError, lambda: self._assert_func(-np.inf, np.inf)) def test_simple_item(self): self._test_not_equal(1, 2) def test_complex_item(self): self._assert_func(complex(1, 2), complex(1, 2)) self._assert_func(complex(1, np.nan), complex(1, np.nan)) self._assert_func(complex(np.inf, np.nan), complex(np.inf, np.nan)) self._test_not_equal(complex(1, np.nan), complex(1, 2)) self._test_not_equal(complex(np.nan, 1), complex(1, np.nan)) self._test_not_equal(complex(np.nan, np.inf), complex(np.nan, 2)) def test_complex(self): x = np.array([complex(1, 2), complex(1, np.nan)]) z = np.array([complex(1, 2), complex(np.nan, 1)]) y = np.array([complex(1, 2), complex(1, 2)]) self._assert_func(x, x) self._test_not_equal(x, y) self._test_not_equal(x, z) def test_error_message(self): """Check the message is formatted correctly for the decimal value. Also check the message when input includes inf or nan (gh12200)""" x = np.array([1.00000000001, 2.00000000002, 3.00003]) y = np.array([1.00000000002, 2.00000000003, 3.00004]) # Test with a different amount of decimal digits with pytest.raises(AssertionError) as exc_info: self._assert_func(x, y, decimal=12) msgs = str(exc_info.value).split('\n') assert_equal(msgs[3], 'Mismatched elements: 3 / 3 (100%)') assert_equal(msgs[4], 'Max absolute difference: 1.e-05') assert_equal(msgs[5], 'Max relative difference: 3.33328889e-06') assert_equal( msgs[6], ' x: array([1.00000000001, 2.00000000002, 3.00003 ])') assert_equal( msgs[7], ' y: array([1.00000000002, 2.00000000003, 3.00004 ])') # With the default value of decimal digits, only the 3rd element # differs. Note that we only check for the formatting of the arrays # themselves. with pytest.raises(AssertionError) as exc_info: self._assert_func(x, y) msgs = str(exc_info.value).split('\n') assert_equal(msgs[3], 'Mismatched elements: 1 / 3 (33.3%)') assert_equal(msgs[4], 'Max absolute difference: 1.e-05') assert_equal(msgs[5], 'Max relative difference: 3.33328889e-06') assert_equal(msgs[6], ' x: array([1. , 2. , 3.00003])') assert_equal(msgs[7], ' y: array([1. , 2. , 3.00004])') # Check the error message when input includes inf x = np.array([np.inf, 0]) y = np.array([np.inf, 1]) with pytest.raises(AssertionError) as exc_info: self._assert_func(x, y) msgs = str(exc_info.value).split('\n') assert_equal(msgs[3], 'Mismatched elements: 1 / 2 (50%)') assert_equal(msgs[4], 'Max absolute difference: 1.') assert_equal(msgs[5], 'Max relative difference: 1.') assert_equal(msgs[6], ' x: array([inf, 0.])') assert_equal(msgs[7], ' y: array([inf, 1.])') # Check the error message when dividing by zero x = np.array([1, 2]) y = np.array([0, 0]) with pytest.raises(AssertionError) as exc_info: self._assert_func(x, y) msgs = str(exc_info.value).split('\n') assert_equal(msgs[3], 'Mismatched elements: 2 / 2 (100%)') assert_equal(msgs[4], 'Max absolute difference: 2') assert_equal(msgs[5], 'Max relative difference: inf') def test_error_message_2(self): """Check the message is formatted correctly when either x or y is a scalar.""" x = 2 y = np.ones(20) with pytest.raises(AssertionError) as exc_info: self._assert_func(x, y) msgs = str(exc_info.value).split('\n') assert_equal(msgs[3], 'Mismatched elements: 20 / 20 (100%)') assert_equal(msgs[4], 'Max absolute difference: 1.') assert_equal(msgs[5], 'Max relative difference: 1.') y = 2 x = np.ones(20) with pytest.raises(AssertionError) as exc_info: self._assert_func(x, y) msgs = str(exc_info.value).split('\n') assert_equal(msgs[3], 'Mismatched elements: 20 / 20 (100%)') assert_equal(msgs[4], 'Max absolute difference: 1.') assert_equal(msgs[5], 'Max relative difference: 0.5') def test_subclass_that_cannot_be_bool(self): # While we cannot guarantee testing functions will always work for # subclasses, the tests should ideally rely only on subclasses having # comparison operators, not on them being able to store booleans # (which, e.g., astropy Quantity cannot usefully do). See gh-8452. class MyArray(np.ndarray): def __eq__(self, other): return super().__eq__(other).view(np.ndarray) def __lt__(self, other): return super().__lt__(other).view(np.ndarray) def all(self, *args, **kwargs): raise NotImplementedError a = np.array([1., 2.]).view(MyArray) self._assert_func(a, a) class TestApproxEqual: def setup_method(self): self._assert_func = assert_approx_equal def test_simple_0d_arrays(self): x = np.array(1234.22) y = np.array(1234.23) self._assert_func(x, y, significant=5) self._assert_func(x, y, significant=6) assert_raises(AssertionError, lambda: self._assert_func(x, y, significant=7)) def test_simple_items(self): x = 1234.22 y = 1234.23 self._assert_func(x, y, significant=4) self._assert_func(x, y, significant=5) self._assert_func(x, y, significant=6) assert_raises(AssertionError, lambda: self._assert_func(x, y, significant=7)) def test_nan_array(self): anan = np.array(np.nan) aone = np.array(1) ainf = np.array(np.inf) self._assert_func(anan, anan) assert_raises(AssertionError, lambda: self._assert_func(anan, aone)) assert_raises(AssertionError, lambda: self._assert_func(anan, ainf)) assert_raises(AssertionError, lambda: self._assert_func(ainf, anan)) def test_nan_items(self): anan = np.array(np.nan) aone = np.array(1) ainf = np.array(np.inf) self._assert_func(anan, anan) assert_raises(AssertionError, lambda: self._assert_func(anan, aone)) assert_raises(AssertionError, lambda: self._assert_func(anan, ainf)) assert_raises(AssertionError, lambda: self._assert_func(ainf, anan)) class TestArrayAssertLess: def setup_method(self): self._assert_func = assert_array_less def test_simple_arrays(self): x = np.array([1.1, 2.2]) y = np.array([1.2, 2.3]) self._assert_func(x, y) assert_raises(AssertionError, lambda: self._assert_func(y, x)) y = np.array([1.0, 2.3]) assert_raises(AssertionError, lambda: self._assert_func(x, y)) assert_raises(AssertionError, lambda: self._assert_func(y, x)) def test_rank2(self): x = np.array([[1.1, 2.2], [3.3, 4.4]]) y = np.array([[1.2, 2.3], [3.4, 4.5]]) self._assert_func(x, y) assert_raises(AssertionError, lambda: self._assert_func(y, x)) y = np.array([[1.0, 2.3], [3.4, 4.5]]) assert_raises(AssertionError, lambda: self._assert_func(x, y)) assert_raises(AssertionError, lambda: self._assert_func(y, x)) def test_rank3(self): x = np.ones(shape=(2, 2, 2)) y = np.ones(shape=(2, 2, 2))+1 self._assert_func(x, y) assert_raises(AssertionError, lambda: self._assert_func(y, x)) y[0, 0, 0] = 0 assert_raises(AssertionError, lambda: self._assert_func(x, y)) assert_raises(AssertionError, lambda: self._assert_func(y, x)) def test_simple_items(self): x = 1.1 y = 2.2 self._assert_func(x, y) assert_raises(AssertionError, lambda: self._assert_func(y, x)) y = np.array([2.2, 3.3]) self._assert_func(x, y) assert_raises(AssertionError, lambda: self._assert_func(y, x)) y = np.array([1.0, 3.3]) assert_raises(AssertionError, lambda: self._assert_func(x, y)) def test_nan_noncompare(self): anan = np.array(np.nan) aone = np.array(1) ainf = np.array(np.inf) self._assert_func(anan, anan) assert_raises(AssertionError, lambda: self._assert_func(aone, anan)) assert_raises(AssertionError, lambda: self._assert_func(anan, aone)) assert_raises(AssertionError, lambda: self._assert_func(anan, ainf)) assert_raises(AssertionError, lambda: self._assert_func(ainf, anan)) def test_nan_noncompare_array(self): x = np.array([1.1, 2.2, 3.3]) anan = np.array(np.nan) assert_raises(AssertionError, lambda: self._assert_func(x, anan)) assert_raises(AssertionError, lambda: self._assert_func(anan, x)) x = np.array([1.1, 2.2, np.nan]) assert_raises(AssertionError, lambda: self._assert_func(x, anan)) assert_raises(AssertionError, lambda: self._assert_func(anan, x)) y = np.array([1.0, 2.0, np.nan]) self._assert_func(y, x) assert_raises(AssertionError, lambda: self._assert_func(x, y)) def test_inf_compare(self): aone = np.array(1) ainf = np.array(np.inf) self._assert_func(aone, ainf) self._assert_func(-ainf, aone) self._assert_func(-ainf, ainf) assert_raises(AssertionError, lambda: self._assert_func(ainf, aone)) assert_raises(AssertionError, lambda: self._assert_func(aone, -ainf)) assert_raises(AssertionError, lambda: self._assert_func(ainf, ainf)) assert_raises(AssertionError, lambda: self._assert_func(ainf, -ainf)) assert_raises(AssertionError, lambda: self._assert_func(-ainf, -ainf)) def test_inf_compare_array(self): x = np.array([1.1, 2.2, np.inf]) ainf = np.array(np.inf) assert_raises(AssertionError, lambda: self._assert_func(x, ainf)) assert_raises(AssertionError, lambda: self._assert_func(ainf, x)) assert_raises(AssertionError, lambda: self._assert_func(x, -ainf)) assert_raises(AssertionError, lambda: self._assert_func(-x, -ainf)) assert_raises(AssertionError, lambda: self._assert_func(-ainf, -x)) self._assert_func(-ainf, x) @pytest.mark.skip(reason="The raises decorator depends on Nose") class TestRaises: def setup_method(self): class MyException(Exception): pass self.e = MyException def raises_exception(self, e): raise e def does_not_raise_exception(self): pass def test_correct_catch(self): raises(self.e)(self.raises_exception)(self.e) # raises? def test_wrong_exception(self): try: raises(self.e)(self.raises_exception)(RuntimeError) # raises? except RuntimeError: return else: raise AssertionError("should have caught RuntimeError") def test_catch_no_raise(self): try: raises(self.e)(self.does_not_raise_exception)() # raises? except AssertionError: return else: raise AssertionError("should have raised an AssertionError") class TestWarns: def test_warn(self): def f(): warnings.warn("yo") return 3 before_filters = sys.modules['warnings'].filters[:] assert_equal(assert_warns(UserWarning, f), 3) after_filters = sys.modules['warnings'].filters assert_raises(AssertionError, assert_no_warnings, f) assert_equal(assert_no_warnings(lambda x: x, 1), 1) # Check that the warnings state is unchanged assert_equal(before_filters, after_filters, "assert_warns does not preserver warnings state") def test_context_manager(self): before_filters = sys.modules['warnings'].filters[:] with assert_warns(UserWarning): warnings.warn("yo") after_filters = sys.modules['warnings'].filters def no_warnings(): with assert_no_warnings(): warnings.warn("yo") assert_raises(AssertionError, no_warnings) assert_equal(before_filters, after_filters, "assert_warns does not preserver warnings state") def test_warn_wrong_warning(self): def f(): warnings.warn("yo", DeprecationWarning) failed = False with warnings.catch_warnings(): warnings.simplefilter("error", DeprecationWarning) try: # Should raise a DeprecationWarning assert_warns(UserWarning, f) failed = True except DeprecationWarning: pass if failed: raise AssertionError("wrong warning caught by assert_warn") class TestAssertAllclose: def test_simple(self): x = 1e-3 y = 1e-9 assert_allclose(x, y, atol=1) assert_raises(AssertionError, assert_allclose, x, y) a = np.array([x, y, x, y]) b = np.array([x, y, x, x]) assert_allclose(a, b, atol=1) assert_raises(AssertionError, assert_allclose, a, b) b[-1] = y * (1 + 1e-8) assert_allclose(a, b) assert_raises(AssertionError, assert_allclose, a, b, rtol=1e-9) assert_allclose(6, 10, rtol=0.5) assert_raises(AssertionError, assert_allclose, 10, 6, rtol=0.5) def test_min_int(self): a = np.array([np.iinfo(np.int_).min], dtype=np.int_) # Should not raise: assert_allclose(a, a) def test_report_fail_percentage(self): a = np.array([1, 1, 1, 1]) b = np.array([1, 1, 1, 2]) with pytest.raises(AssertionError) as exc_info: assert_allclose(a, b) msg = str(exc_info.value) assert_('Mismatched elements: 1 / 4 (25%)\n' 'Max absolute difference: 1\n' 'Max relative difference: 0.5' in msg) def test_equal_nan(self): a = np.array([np.nan]) b = np.array([np.nan]) # Should not raise: assert_allclose(a, b, equal_nan=True) def test_not_equal_nan(self): a = np.array([np.nan]) b = np.array([np.nan]) assert_raises(AssertionError, assert_allclose, a, b, equal_nan=False) def test_equal_nan_default(self): # Make sure equal_nan default behavior remains unchanged. (All # of these functions use assert_array_compare under the hood.) # None of these should raise. a = np.array([np.nan]) b = np.array([np.nan]) assert_array_equal(a, b) assert_array_almost_equal(a, b) assert_array_less(a, b) assert_allclose(a, b) def test_report_max_relative_error(self): a = np.array([0, 1]) b = np.array([0, 2]) with pytest.raises(AssertionError) as exc_info: assert_allclose(a, b) msg = str(exc_info.value) assert_('Max relative difference: 0.5' in msg) def test_timedelta(self): # see gh-18286 a = np.array([[1, 2, 3, "NaT"]], dtype="m8[ns]") assert_allclose(a, a) def test_error_message_unsigned(self): """Check the the message is formatted correctly when overflow can occur (gh21768)""" # Ensure to test for potential overflow in the case of: # x - y # and # y - x x = np.asarray([0, 1, 8], dtype='uint8') y = np.asarray([4, 4, 4], dtype='uint8') with pytest.raises(AssertionError) as exc_info: assert_allclose(x, y, atol=3) msgs = str(exc_info.value).split('\n') assert_equal(msgs[4], 'Max absolute difference: 4') class TestArrayAlmostEqualNulp: def test_float64_pass(self): # The number of units of least precision # In this case, use a few places above the lowest level (ie nulp=1) nulp = 5 x = np.linspace(-20, 20, 50, dtype=np.float64) x = 10**x x = np.r_[-x, x] # Addition eps = np.finfo(x.dtype).eps y = x + x*eps*nulp/2. assert_array_almost_equal_nulp(x, y, nulp) # Subtraction epsneg = np.finfo(x.dtype).epsneg y = x - x*epsneg*nulp/2. assert_array_almost_equal_nulp(x, y, nulp) def test_float64_fail(self): nulp = 5 x = np.linspace(-20, 20, 50, dtype=np.float64) x = 10**x x = np.r_[-x, x] eps = np.finfo(x.dtype).eps y = x + x*eps*nulp*2. assert_raises(AssertionError, assert_array_almost_equal_nulp, x, y, nulp) epsneg = np.finfo(x.dtype).epsneg y = x - x*epsneg*nulp*2. assert_raises(AssertionError, assert_array_almost_equal_nulp, x, y, nulp) def test_float64_ignore_nan(self): # Ignore ULP differences between various NAN's # Note that MIPS may reverse quiet and signaling nans # so we use the builtin version as a base. offset = np.uint64(0xffffffff) nan1_i64 = np.array(np.nan, dtype=np.float64).view(np.uint64) nan2_i64 = nan1_i64 ^ offset # nan payload on MIPS is all ones. nan1_f64 = nan1_i64.view(np.float64) nan2_f64 = nan2_i64.view(np.float64) assert_array_max_ulp(nan1_f64, nan2_f64, 0) def test_float32_pass(self): nulp = 5 x = np.linspace(-20, 20, 50, dtype=np.float32) x = 10**x x = np.r_[-x, x] eps = np.finfo(x.dtype).eps y = x + x*eps*nulp/2. assert_array_almost_equal_nulp(x, y, nulp) epsneg = np.finfo(x.dtype).epsneg y = x - x*epsneg*nulp/2. assert_array_almost_equal_nulp(x, y, nulp) def test_float32_fail(self): nulp = 5 x = np.linspace(-20, 20, 50, dtype=np.float32) x = 10**x x = np.r_[-x, x] eps = np.finfo(x.dtype).eps y = x + x*eps*nulp*2. assert_raises(AssertionError, assert_array_almost_equal_nulp, x, y, nulp) epsneg = np.finfo(x.dtype).epsneg y = x - x*epsneg*nulp*2. assert_raises(AssertionError, assert_array_almost_equal_nulp, x, y, nulp) def test_float32_ignore_nan(self): # Ignore ULP differences between various NAN's # Note that MIPS may reverse quiet and signaling nans # so we use the builtin version as a base. offset = np.uint32(0xffff) nan1_i32 = np.array(np.nan, dtype=np.float32).view(np.uint32) nan2_i32 = nan1_i32 ^ offset # nan payload on MIPS is all ones. nan1_f32 = nan1_i32.view(np.float32) nan2_f32 = nan2_i32.view(np.float32) assert_array_max_ulp(nan1_f32, nan2_f32, 0) def test_float16_pass(self): nulp = 5 x = np.linspace(-4, 4, 10, dtype=np.float16) x = 10**x x = np.r_[-x, x] eps = np.finfo(x.dtype).eps y = x + x*eps*nulp/2. assert_array_almost_equal_nulp(x, y, nulp) epsneg = np.finfo(x.dtype).epsneg y = x - x*epsneg*nulp/2. assert_array_almost_equal_nulp(x, y, nulp) def test_float16_fail(self): nulp = 5 x = np.linspace(-4, 4, 10, dtype=np.float16) x = 10**x x = np.r_[-x, x] eps = np.finfo(x.dtype).eps y = x + x*eps*nulp*2. assert_raises(AssertionError, assert_array_almost_equal_nulp, x, y, nulp) epsneg = np.finfo(x.dtype).epsneg y = x - x*epsneg*nulp*2. assert_raises(AssertionError, assert_array_almost_equal_nulp, x, y, nulp) def test_float16_ignore_nan(self): # Ignore ULP differences between various NAN's # Note that MIPS may reverse quiet and signaling nans # so we use the builtin version as a base. offset = np.uint16(0xff) nan1_i16 = np.array(np.nan, dtype=np.float16).view(np.uint16) nan2_i16 = nan1_i16 ^ offset # nan payload on MIPS is all ones. nan1_f16 = nan1_i16.view(np.float16) nan2_f16 = nan2_i16.view(np.float16) assert_array_max_ulp(nan1_f16, nan2_f16, 0) def test_complex128_pass(self): nulp = 5 x = np.linspace(-20, 20, 50, dtype=np.float64) x = 10**x x = np.r_[-x, x] xi = x + x*1j eps = np.finfo(x.dtype).eps y = x + x*eps*nulp/2. assert_array_almost_equal_nulp(xi, x + y*1j, nulp) assert_array_almost_equal_nulp(xi, y + x*1j, nulp) # The test condition needs to be at least a factor of sqrt(2) smaller # because the real and imaginary parts both change y = x + x*eps*nulp/4. assert_array_almost_equal_nulp(xi, y + y*1j, nulp) epsneg = np.finfo(x.dtype).epsneg y = x - x*epsneg*nulp/2. assert_array_almost_equal_nulp(xi, x + y*1j, nulp) assert_array_almost_equal_nulp(xi, y + x*1j, nulp) y = x - x*epsneg*nulp/4. assert_array_almost_equal_nulp(xi, y + y*1j, nulp) def test_complex128_fail(self): nulp = 5 x = np.linspace(-20, 20, 50, dtype=np.float64) x = 10**x x = np.r_[-x, x] xi = x + x*1j eps = np.finfo(x.dtype).eps y = x + x*eps*nulp*2. assert_raises(AssertionError, assert_array_almost_equal_nulp, xi, x + y*1j, nulp) assert_raises(AssertionError, assert_array_almost_equal_nulp, xi, y + x*1j, nulp) # The test condition needs to be at least a factor of sqrt(2) smaller # because the real and imaginary parts both change y = x + x*eps*nulp assert_raises(AssertionError, assert_array_almost_equal_nulp, xi, y + y*1j, nulp) epsneg = np.finfo(x.dtype).epsneg y = x - x*epsneg*nulp*2. assert_raises(AssertionError, assert_array_almost_equal_nulp, xi, x + y*1j, nulp) assert_raises(AssertionError, assert_array_almost_equal_nulp, xi, y + x*1j, nulp) y = x - x*epsneg*nulp assert_raises(AssertionError, assert_array_almost_equal_nulp, xi, y + y*1j, nulp) def test_complex64_pass(self): nulp = 5 x = np.linspace(-20, 20, 50, dtype=np.float32) x = 10**x x = np.r_[-x, x] xi = x + x*1j eps = np.finfo(x.dtype).eps y = x + x*eps*nulp/2. assert_array_almost_equal_nulp(xi, x + y*1j, nulp) assert_array_almost_equal_nulp(xi, y + x*1j, nulp) y = x + x*eps*nulp/4. assert_array_almost_equal_nulp(xi, y + y*1j, nulp) epsneg = np.finfo(x.dtype).epsneg y = x - x*epsneg*nulp/2. assert_array_almost_equal_nulp(xi, x + y*1j, nulp) assert_array_almost_equal_nulp(xi, y + x*1j, nulp) y = x - x*epsneg*nulp/4. assert_array_almost_equal_nulp(xi, y + y*1j, nulp) def test_complex64_fail(self): nulp = 5 x = np.linspace(-20, 20, 50, dtype=np.float32) x = 10**x x = np.r_[-x, x] xi = x + x*1j eps = np.finfo(x.dtype).eps y = x + x*eps*nulp*2. assert_raises(AssertionError, assert_array_almost_equal_nulp, xi, x + y*1j, nulp) assert_raises(AssertionError, assert_array_almost_equal_nulp, xi, y + x*1j, nulp) y = x + x*eps*nulp assert_raises(AssertionError, assert_array_almost_equal_nulp, xi, y + y*1j, nulp) epsneg = np.finfo(x.dtype).epsneg y = x - x*epsneg*nulp*2. assert_raises(AssertionError, assert_array_almost_equal_nulp, xi, x + y*1j, nulp) assert_raises(AssertionError, assert_array_almost_equal_nulp, xi, y + x*1j, nulp) y = x - x*epsneg*nulp assert_raises(AssertionError, assert_array_almost_equal_nulp, xi, y + y*1j, nulp) class TestULP: def test_equal(self): x = np.random.randn(10) assert_array_max_ulp(x, x, maxulp=0) def test_single(self): # Generate 1 + small deviation, check that adding eps gives a few UNL x = np.ones(10).astype(np.float32) x += 0.01 * np.random.randn(10).astype(np.float32) eps = np.finfo(np.float32).eps assert_array_max_ulp(x, x+eps, maxulp=20) def test_double(self): # Generate 1 + small deviation, check that adding eps gives a few UNL x = np.ones(10).astype(np.float64) x += 0.01 * np.random.randn(10).astype(np.float64) eps = np.finfo(np.float64).eps assert_array_max_ulp(x, x+eps, maxulp=200) def test_inf(self): for dt in [np.float32, np.float64]: inf = np.array([np.inf]).astype(dt) big = np.array([np.finfo(dt).max]) assert_array_max_ulp(inf, big, maxulp=200) def test_nan(self): # Test that nan is 'far' from small, tiny, inf, max and min for dt in [np.float32, np.float64]: if dt == np.float32: maxulp = 1e6 else: maxulp = 1e12 inf = np.array([np.inf]).astype(dt) nan = np.array([np.nan]).astype(dt) big = np.array([np.finfo(dt).max]) tiny = np.array([np.finfo(dt).tiny]) zero = np.array([np.PZERO]).astype(dt) nzero = np.array([np.NZERO]).astype(dt) assert_raises(AssertionError, lambda: assert_array_max_ulp(nan, inf, maxulp=maxulp)) assert_raises(AssertionError, lambda: assert_array_max_ulp(nan, big, maxulp=maxulp)) assert_raises(AssertionError, lambda: assert_array_max_ulp(nan, tiny, maxulp=maxulp)) assert_raises(AssertionError, lambda: assert_array_max_ulp(nan, zero, maxulp=maxulp)) assert_raises(AssertionError, lambda: assert_array_max_ulp(nan, nzero, maxulp=maxulp)) class TestStringEqual: def test_simple(self): assert_string_equal("hello", "hello") assert_string_equal("hello\nmultiline", "hello\nmultiline") with pytest.raises(AssertionError) as exc_info: assert_string_equal("foo\nbar", "hello\nbar") msg = str(exc_info.value) assert_equal(msg, "Differences in strings:\n- foo\n+ hello") assert_raises(AssertionError, lambda: assert_string_equal("foo", "hello")) def test_regex(self): assert_string_equal("a+*b", "a+*b") assert_raises(AssertionError, lambda: assert_string_equal("aaa", "a+b")) def assert_warn_len_equal(mod, n_in_context): try: mod_warns = mod.__warningregistry__ except AttributeError: # the lack of a __warningregistry__ # attribute means that no warning has # occurred; this can be triggered in # a parallel test scenario, while in # a serial test scenario an initial # warning (and therefore the attribute) # are always created first mod_warns = {} num_warns = len(mod_warns) if 'version' in mod_warns: # Python 3 adds a 'version' entry to the registry, # do not count it. num_warns -= 1 assert_equal(num_warns, n_in_context) def test_warn_len_equal_call_scenarios(): # assert_warn_len_equal is called under # varying circumstances depending on serial # vs. parallel test scenarios; this test # simply aims to probe both code paths and # check that no assertion is uncaught # parallel scenario -- no warning issued yet class mod: pass mod_inst = mod() assert_warn_len_equal(mod=mod_inst, n_in_context=0) # serial test scenario -- the __warningregistry__ # attribute should be present class mod: def __init__(self): self.__warningregistry__ = {'warning1':1, 'warning2':2} mod_inst = mod() assert_warn_len_equal(mod=mod_inst, n_in_context=2) def _get_fresh_mod(): # Get this module, with warning registry empty my_mod = sys.modules[__name__] try: my_mod.__warningregistry__.clear() except AttributeError: # will not have a __warningregistry__ unless warning has been # raised in the module at some point pass return my_mod def test_clear_and_catch_warnings(): # Initial state of module, no warnings my_mod = _get_fresh_mod() assert_equal(getattr(my_mod, '__warningregistry__', {}), {}) with clear_and_catch_warnings(modules=[my_mod]): warnings.simplefilter('ignore') warnings.warn('Some warning') assert_equal(my_mod.__warningregistry__, {}) # Without specified modules, don't clear warnings during context. # catch_warnings doesn't make an entry for 'ignore'. with clear_and_catch_warnings(): warnings.simplefilter('ignore') warnings.warn('Some warning') assert_warn_len_equal(my_mod, 0) # Manually adding two warnings to the registry: my_mod.__warningregistry__ = {'warning1': 1, 'warning2': 2} # Confirm that specifying module keeps old warning, does not add new with clear_and_catch_warnings(modules=[my_mod]): warnings.simplefilter('ignore') warnings.warn('Another warning') assert_warn_len_equal(my_mod, 2) # Another warning, no module spec it clears up registry with clear_and_catch_warnings(): warnings.simplefilter('ignore') warnings.warn('Another warning') assert_warn_len_equal(my_mod, 0) def test_suppress_warnings_module(): # Initial state of module, no warnings my_mod = _get_fresh_mod() assert_equal(getattr(my_mod, '__warningregistry__', {}), {}) def warn_other_module(): # Apply along axis is implemented in python; stacklevel=2 means # we end up inside its module, not ours. def warn(arr): warnings.warn("Some warning 2", stacklevel=2) return arr np.apply_along_axis(warn, 0, [0]) # Test module based warning suppression: assert_warn_len_equal(my_mod, 0) with suppress_warnings() as sup: sup.record(UserWarning) # suppress warning from other module (may have .pyc ending), # if apply_along_axis is moved, had to be changed. sup.filter(module=np.lib.shape_base) warnings.warn("Some warning") warn_other_module() # Check that the suppression did test the file correctly (this module # got filtered) assert_equal(len(sup.log), 1) assert_equal(sup.log[0].message.args[0], "Some warning") assert_warn_len_equal(my_mod, 0) sup = suppress_warnings() # Will have to be changed if apply_along_axis is moved: sup.filter(module=my_mod) with sup: warnings.warn('Some warning') assert_warn_len_equal(my_mod, 0) # And test repeat works: sup.filter(module=my_mod) with sup: warnings.warn('Some warning') assert_warn_len_equal(my_mod, 0) # Without specified modules with suppress_warnings(): warnings.simplefilter('ignore') warnings.warn('Some warning') assert_warn_len_equal(my_mod, 0) def test_suppress_warnings_type(): # Initial state of module, no warnings my_mod = _get_fresh_mod() assert_equal(getattr(my_mod, '__warningregistry__', {}), {}) # Test module based warning suppression: with suppress_warnings() as sup: sup.filter(UserWarning) warnings.warn('Some warning') assert_warn_len_equal(my_mod, 0) sup = suppress_warnings() sup.filter(UserWarning) with sup: warnings.warn('Some warning') assert_warn_len_equal(my_mod, 0) # And test repeat works: sup.filter(module=my_mod) with sup: warnings.warn('Some warning') assert_warn_len_equal(my_mod, 0) # Without specified modules with suppress_warnings(): warnings.simplefilter('ignore') warnings.warn('Some warning') assert_warn_len_equal(my_mod, 0) def test_suppress_warnings_decorate_no_record(): sup = suppress_warnings() sup.filter(UserWarning) @sup def warn(category): warnings.warn('Some warning', category) with warnings.catch_warnings(record=True) as w: warnings.simplefilter("always") warn(UserWarning) # should be supppressed warn(RuntimeWarning) assert_equal(len(w), 1) def test_suppress_warnings_record(): sup = suppress_warnings() log1 = sup.record() with sup: log2 = sup.record(message='Some other warning 2') sup.filter(message='Some warning') warnings.warn('Some warning') warnings.warn('Some other warning') warnings.warn('Some other warning 2') assert_equal(len(sup.log), 2) assert_equal(len(log1), 1) assert_equal(len(log2),1) assert_equal(log2[0].message.args[0], 'Some other warning 2') # Do it again, with the same context to see if some warnings survived: with sup: log2 = sup.record(message='Some other warning 2') sup.filter(message='Some warning') warnings.warn('Some warning') warnings.warn('Some other warning') warnings.warn('Some other warning 2') assert_equal(len(sup.log), 2) assert_equal(len(log1), 1) assert_equal(len(log2), 1) assert_equal(log2[0].message.args[0], 'Some other warning 2') # Test nested: with suppress_warnings() as sup: sup.record() with suppress_warnings() as sup2: sup2.record(message='Some warning') warnings.warn('Some warning') warnings.warn('Some other warning') assert_equal(len(sup2.log), 1) assert_equal(len(sup.log), 1) def test_suppress_warnings_forwarding(): def warn_other_module(): # Apply along axis is implemented in python; stacklevel=2 means # we end up inside its module, not ours. def warn(arr): warnings.warn("Some warning", stacklevel=2) return arr np.apply_along_axis(warn, 0, [0]) with suppress_warnings() as sup: sup.record() with suppress_warnings("always"): for i in range(2): warnings.warn("Some warning") assert_equal(len(sup.log), 2) with suppress_warnings() as sup: sup.record() with suppress_warnings("location"): for i in range(2): warnings.warn("Some warning") warnings.warn("Some warning") assert_equal(len(sup.log), 2) with suppress_warnings() as sup: sup.record() with suppress_warnings("module"): for i in range(2): warnings.warn("Some warning") warnings.warn("Some warning") warn_other_module() assert_equal(len(sup.log), 2) with suppress_warnings() as sup: sup.record() with suppress_warnings("once"): for i in range(2): warnings.warn("Some warning") warnings.warn("Some other warning") warn_other_module() assert_equal(len(sup.log), 2) def test_tempdir(): with tempdir() as tdir: fpath = os.path.join(tdir, 'tmp') with open(fpath, 'w'): pass assert_(not os.path.isdir(tdir)) raised = False try: with tempdir() as tdir: raise ValueError() except ValueError: raised = True assert_(raised) assert_(not os.path.isdir(tdir)) def test_temppath(): with temppath() as fpath: with open(fpath, 'w'): pass assert_(not os.path.isfile(fpath)) raised = False try: with temppath() as fpath: raise ValueError() except ValueError: raised = True assert_(raised) assert_(not os.path.isfile(fpath)) class my_cacw(clear_and_catch_warnings): class_modules = (sys.modules[__name__],) def test_clear_and_catch_warnings_inherit(): # Test can subclass and add default modules my_mod = _get_fresh_mod() with my_cacw(): warnings.simplefilter('ignore') warnings.warn('Some warning') assert_equal(my_mod.__warningregistry__, {}) @pytest.mark.skipif(not HAS_REFCOUNT, reason="Python lacks refcounts") class TestAssertNoGcCycles: """ Test assert_no_gc_cycles """ def test_passes(self): def no_cycle(): b = [] b.append([]) return b with assert_no_gc_cycles(): no_cycle() assert_no_gc_cycles(no_cycle) def test_asserts(self): def make_cycle(): a = [] a.append(a) a.append(a) return a with assert_raises(AssertionError): with assert_no_gc_cycles(): make_cycle() with assert_raises(AssertionError): assert_no_gc_cycles(make_cycle) @pytest.mark.slow def test_fails(self): """ Test that in cases where the garbage cannot be collected, we raise an error, instead of hanging forever trying to clear it. """ class ReferenceCycleInDel: """ An object that not only contains a reference cycle, but creates new cycles whenever it's garbage-collected and its __del__ runs """ make_cycle = True def __init__(self): self.cycle = self def __del__(self): # break the current cycle so that `self` can be freed self.cycle = None if ReferenceCycleInDel.make_cycle: # but create a new one so that the garbage collector has more # work to do. ReferenceCycleInDel() try: w = weakref.ref(ReferenceCycleInDel()) try: with assert_raises(RuntimeError): # this will be unable to get a baseline empty garbage assert_no_gc_cycles(lambda: None) except AssertionError: # the above test is only necessary if the GC actually tried to free # our object anyway, which python 2.7 does not. if w() is not None: pytest.skip("GC does not call __del__ on cyclic objects") raise finally: # make sure that we stop creating reference cycles ReferenceCycleInDel.make_cycle = False