Python unittest.case() Examples

def addExpectedFailure(self, test, err):
        method = getattr(test, test._testMethodName)
        try:
            reason = method.__et_xfail_reason__
            not_impl = getattr(method, '__et_xfail_not_implemented__', False)
        except AttributeError:
            # Maybe the whole test case class is decorated?
            reason = getattr(test, '__et_xfail_reason__', None)
            not_impl = getattr(test, '__et_xfail_not_implemented__', False)

        marker = Markers.not_implemented if not_impl else Markers.xfailed
        if not_impl:
            self.notImplemented.append(
                (test, self._exc_info_to_string(err, test)))
        else:
            super().addExpectedFailure(test, err)

        self.report_progress(test, marker, reason) 

def assert_raises(*args, **kwargs):
    """
    assert_raises(exception_class, callable, *args, **kwargs)
    assert_raises(exception_class)

    Fail unless an exception of class exception_class is thrown
    by callable when invoked with arguments args and keyword
    arguments kwargs. If a different type of exception is
    thrown, it will not be caught, and the test case will be
    deemed to have suffered an error, exactly as for an
    unexpected exception.

    Alternatively, `assert_raises` can be used as a context manager:

    >>> from numpy.testing import assert_raises
    >>> with assert_raises(ZeroDivisionError):
    ...     1 / 0

    is equivalent to

    >>> def div(x, y):
    ...     return x / y
    >>> assert_raises(ZeroDivisionError, div, 1, 0)

    """
    __tracebackhide__ = True  # Hide traceback for py.test
    return _d.assertRaises(*args,**kwargs) 

def _feedErrorsToResult(self, result, errors):
        # copy from python3.5.3 unittest.case
        for test, exc_info in errors:
            if exc_info is not None:
                if issubclass(exc_info[0], self.failureException):
                    result.addFailure(test, exc_info)
                else:
                    result.addError(test, exc_info) 

def _addExpectedFailure(self, result, exc_info):
        # copy from python3.5.3 unittest.case
        try:
            addExpectedFailure = result.addExpectedFailure
        except AttributeError:
            warnings.warn("TestResult has no addExpectedFailure method, reporting as passes",
                          RuntimeWarning)
            result.addSuccess(self)
        else:
            addExpectedFailure(self, exc_info) 

def _addUnexpectedSuccess(self, result):
        # copy from python3.5.3 unittest.case
        try:
            addUnexpectedSuccess = result.addUnexpectedSuccess
        except AttributeError:
            warnings.warn("TestResult has no addUnexpectedSuccess method, reporting as failure",
                          RuntimeWarning)
            # We need to pass an actual exception and traceback to addFailure,
            # otherwise the legacy result can choke.
            try:
                raise _UnexpectedSuccess
            except _UnexpectedSuccess:
                result.addFailure(self, sys.exc_info())
        else:
            addUnexpectedSuccess(self) 

def record_exceptions(self, errors):
        assertionRecorder = self.get_result_emitter('assertionRecorder')
        for case, exc_info in errors:
            if not exc_info or exc_info in self._exceptions:
                continue
            self._exceptions.add(exc_info)
            if type(exc_info) is tuple:
                exc_type, e, tb = exc_info
                assertionRecorder.traceback(exc_type, e, tb) 

def assert_raises(*args, **kwargs):
    """
    assert_raises(exception_class, callable, *args, **kwargs)
    assert_raises(exception_class)

    Fail unless an exception of class exception_class is thrown
    by callable when invoked with arguments args and keyword
    arguments kwargs. If a different type of exception is
    thrown, it will not be caught, and the test case will be
    deemed to have suffered an error, exactly as for an
    unexpected exception.

    Alternatively, `assert_raises` can be used as a context manager:

    >>> from numpy.testing import assert_raises
    >>> with assert_raises(ZeroDivisionError):
    ...     1 / 0

    is equivalent to

    >>> def div(x, y):
    ...     return x / y
    >>> assert_raises(ZeroDivisionError, div, 1, 0)

    """
    __tracebackhide__ = True  # Hide traceback for py.test
    return _d.assertRaises(*args,**kwargs) 

def assert_raises(*args, **kwargs):
    """
    assert_raises(exception_class, callable, *args, **kwargs)
    assert_raises(exception_class)

    Fail unless an exception of class exception_class is thrown
    by callable when invoked with arguments args and keyword
    arguments kwargs. If a different type of exception is
    thrown, it will not be caught, and the test case will be
    deemed to have suffered an error, exactly as for an
    unexpected exception.

    Alternatively, `assert_raises` can be used as a context manager:

    >>> from numpy.testing import assert_raises
    >>> with assert_raises(ZeroDivisionError):
    ...     1 / 0

    is equivalent to

    >>> def div(x, y):
    ...     return x / y
    >>> assert_raises(ZeroDivisionError, div, 1, 0)

    """
    __tracebackhide__ = True  # Hide traceback for py.test
    return _d.assertRaises(*args,**kwargs) 

def assert_raises(*args, **kwargs):
    """
    assert_raises(exception_class, callable, *args, **kwargs)
    assert_raises(exception_class)

    Fail unless an exception of class exception_class is thrown
    by callable when invoked with arguments args and keyword
    arguments kwargs. If a different type of exception is
    thrown, it will not be caught, and the test case will be
    deemed to have suffered an error, exactly as for an
    unexpected exception.

    Alternatively, `assert_raises` can be used as a context manager:

    >>> from numpy.testing import assert_raises
    >>> with assert_raises(ZeroDivisionError):
    ...     1 / 0

    is equivalent to

    >>> def div(x, y):
    ...     return x / y
    >>> assert_raises(ZeroDivisionError, div, 1, 0)

    """
    __tracebackhide__ = True  # Hide traceback for py.test
    return _d.assertRaises(*args,**kwargs) 

def _addSkip(self, result, test_case, reason):
        # copy from python3.5.3 unittest.case
        addSkip = getattr(result, 'addSkip', None)
        if addSkip is not None:
            addSkip(test_case, reason)
        else:
            warnings.warn("TestResult has no addSkip method, skips not reported",
                          RuntimeWarning, 2)
            result.addSuccess(test_case) 

def ignore_loop(func=None):
    """
    Ignore the error case where the loop did not run during the test.
    """
    warnings.warn("ignore_loop() is deprecated in favor of "
                  "fail_on(unused_loop=False)", DeprecationWarning)
    checker = asynctest._fail_on._fail_on({"unused_loop": False})
    return checker if func is None else checker(func) 

def test_reduce_move(self):
        from operator import add
        # reduce tests may have already triggered this warning
        reset_module_registry(unittest.case)
        with warnings.catch_warnings():
            warnings.filterwarnings("error", "reduce")
            self.assertRaises(DeprecationWarning, reduce, add, range(10)) 

def subTest(self, *args, **kwargs):
        try:
            self._subtest = unittest.case._SubTest(self, object(), {})
            yield
        finally:
            self._subtest = None 

def _create(cls, base_path, file_path, content, mode, encoding, errors):
    # type: (Text, Optional[Text], AnyStr, Text, Text, Text) -> Tuple[_TempFile, Text]
    # pylint: enable=line-too-long
    """Module-private: create a tempfile instance."""
    if file_path:
      cleanup_path = os.path.join(base_path, _get_first_part(file_path))
      path = os.path.join(base_path, file_path)
      _makedirs_exist_ok(os.path.dirname(path))
      # The file may already exist, in which case, ensure it's writable so that
      # it can be truncated.
      if os.path.exists(path) and not os.access(path, os.W_OK):
        stat_info = os.stat(path)
        os.chmod(path, stat_info.st_mode | stat.S_IWUSR)
    else:
      _makedirs_exist_ok(base_path)
      fd, path = tempfile.mkstemp(dir=str(base_path))
      os.close(fd)
      cleanup_path = path

    tf = cls(path)

    if content:
      if isinstance(content, six.text_type):
        tf.write_text(content, mode=mode, encoding=encoding, errors=errors)
      else:
        tf.write_bytes(content, mode)

    else:
      tf.write_bytes(b'')

    return tf, cleanup_path 

def getTestCaseNames(self, testCaseClass):  # pylint:disable=invalid-name
    """Validates and returns a (possibly randomized) list of test case names."""
    for name in dir(testCaseClass):
      if _is_suspicious_attribute(testCaseClass, name):
        raise TypeError(TestLoader._ERROR_MSG % name)
    names = super(TestLoader, self).getTestCaseNames(testCaseClass)
    if self._seed is not None:
      logging.info('Randomizing test order with seed: %d', self._seed)
      logging.info('To reproduce this order, re-run with '
                   '--test_randomize_ordering_seed=%d', self._seed)
      self._random.shuffle(names)
    return names 

def test_reduce_move(self):
        from operator import add
        # reduce tests may have already triggered this warning
        reset_module_registry(unittest.case)
        with warnings.catch_warnings():
            warnings.filterwarnings("error", "reduce")
            self.assertRaises(DeprecationWarning, reduce, add, range(10)) 

def assert_raises(*args, **kwargs):
    """
    assert_raises(exception_class, callable, *args, **kwargs)
    assert_raises(exception_class)

    Fail unless an exception of class exception_class is thrown
    by callable when invoked with arguments args and keyword
    arguments kwargs. If a different type of exception is
    thrown, it will not be caught, and the test case will be
    deemed to have suffered an error, exactly as for an
    unexpected exception.

    Alternatively, `assert_raises` can be used as a context manager:

    >>> from numpy.testing import assert_raises
    >>> with assert_raises(ZeroDivisionError):
    ...     1 / 0

    is equivalent to

    >>> def div(x, y):
    ...     return x / y
    >>> assert_raises(ZeroDivisionError, div, 1, 0)

    """
    __tracebackhide__ = True  # Hide traceback for py.test
    return _d.assertRaises(*args,**kwargs) 

def assert_raises(*args, **kwargs):
    """
    assert_raises(exception_class, callable, *args, **kwargs)
    assert_raises(exception_class)

    Fail unless an exception of class exception_class is thrown
    by callable when invoked with arguments args and keyword
    arguments kwargs. If a different type of exception is
    thrown, it will not be caught, and the test case will be
    deemed to have suffered an error, exactly as for an
    unexpected exception.

    Alternatively, `assert_raises` can be used as a context manager:

    >>> from numpy.testing import assert_raises
    >>> with assert_raises(ZeroDivisionError):
    ...     1 / 0

    is equivalent to

    >>> def div(x, y):
    ...     return x / y
    >>> assert_raises(ZeroDivisionError, div, 1, 0)

    """
    __tracebackhide__ = True  # Hide traceback for py.test
    return _d.assertRaises(*args,**kwargs) 

def assert_raises(*args, **kwargs):
    """
    assert_raises(exception_class, callable, *args, **kwargs)
    assert_raises(exception_class)

    Fail unless an exception of class exception_class is thrown
    by callable when invoked with arguments args and keyword
    arguments kwargs. If a different type of exception is
    thrown, it will not be caught, and the test case will be
    deemed to have suffered an error, exactly as for an
    unexpected exception.

    Alternatively, `assert_raises` can be used as a context manager:

    >>> from numpy.testing import assert_raises
    >>> with assert_raises(ZeroDivisionError):
    ...     1 / 0

    is equivalent to

    >>> def div(x, y):
    ...     return x / y
    >>> assert_raises(ZeroDivisionError, div, 1, 0)

    """
    __tracebackhide__ = True  # Hide traceback for py.test
    return _d.assertRaises(*args,**kwargs) 

def assert_raises(*args, **kwargs):
    """
    assert_raises(exception_class, callable, *args, **kwargs)
    assert_raises(exception_class)

    Fail unless an exception of class exception_class is thrown
    by callable when invoked with arguments args and keyword
    arguments kwargs. If a different type of exception is
    thrown, it will not be caught, and the test case will be
    deemed to have suffered an error, exactly as for an
    unexpected exception.

    Alternatively, `assert_raises` can be used as a context manager:

    >>> from numpy.testing import assert_raises
    >>> with assert_raises(ZeroDivisionError):
    ...     1 / 0

    is equivalent to

    >>> def div(x, y):
    ...     return x / y
    >>> assert_raises(ZeroDivisionError, div, 1, 0)

    """
    __tracebackhide__ = True  # Hide traceback for py.test
    return _d.assertRaises(*args,**kwargs) 

def assert_raises(*args, **kwargs):
    """
    assert_raises(exception_class, callable, *args, **kwargs)
    assert_raises(exception_class)

    Fail unless an exception of class exception_class is thrown
    by callable when invoked with arguments args and keyword
    arguments kwargs. If a different type of exception is
    thrown, it will not be caught, and the test case will be
    deemed to have suffered an error, exactly as for an
    unexpected exception.

    Alternatively, `assert_raises` can be used as a context manager:

    >>> from numpy.testing import assert_raises
    >>> with assert_raises(ZeroDivisionError):
    ...     1 / 0

    is equivalent to

    >>> def div(x, y):
    ...     return x / y
    >>> assert_raises(ZeroDivisionError, div, 1, 0)

    """
    __tracebackhide__ = True  # Hide traceback for py.test
    return _d.assertRaises(*args,**kwargs) 

def test_reduce_move(self):
        from operator import add
        # reduce tests may have already triggered this warning
        reset_module_registry(unittest.case)
        with warnings.catch_warnings():
            warnings.filterwarnings("error", "reduce")
            self.assertRaises(DeprecationWarning, reduce, add, range(10)) 

def assert_raises(*args, **kwargs):
    """
    assert_raises(exception_class, callable, *args, **kwargs)
    assert_raises(exception_class)

    Fail unless an exception of class exception_class is thrown
    by callable when invoked with arguments args and keyword
    arguments kwargs. If a different type of exception is
    thrown, it will not be caught, and the test case will be
    deemed to have suffered an error, exactly as for an
    unexpected exception.

    Alternatively, `assert_raises` can be used as a context manager:

    >>> from numpy.testing import assert_raises
    >>> with assert_raises(ZeroDivisionError):
    ...     1 / 0

    is equivalent to

    >>> def div(x, y):
    ...     return x / y
    >>> assert_raises(ZeroDivisionError, div, 1, 0)

    """
    __tracebackhide__ = True  # Hide traceback for py.test
    return _d.assertRaises(*args,**kwargs) 

def test_reduce_move(self):
        from operator import add
        # reduce tests may have already triggered this warning
        reset_module_registry(unittest.case)
        with warnings.catch_warnings():
            warnings.filterwarnings("error", "reduce")
            self.assertRaises(DeprecationWarning, reduce, add, range(10)) 

def format_test(self, test):
        if isinstance(test, unittest.case._SubTest):
            if test.params:
                params = ', '.join(
                    f'{k}={v!r}' for k, v in test.params.items())
            else:
                params = '<subtest>'
            return f'{test.test_case} {{{params}}}'
        else:
            if hasattr(test, 'fail_notes') and test.fail_notes:
                fail_notes = ', '.join(
                    f'{k}={v!r}' for k, v in test.fail_notes.items())
                return f'{test} {{{fail_notes}}}'
            else:
                return str(test) 

def teardown_suite() -> None:
    # The TestSuite methods are mutating the *result* object,
    # and the suite itself does not hold any state whatsoever,
    # and, in our case specifically, it doesn't even hold
    # references to tests being run, so we can think of
    # its methods as static.
    suite = StreamingTestSuite()
    suite._tearDownPreviousClass(None, result)
    suite._handleModuleTearDown(result) 

def test_reduce_move(self):
        from operator import add
        # reduce tests may have already triggered this warning
        reset_module_registry(unittest.case)
        with warnings.catch_warnings():
            warnings.filterwarnings("error", "reduce")
            self.assertRaises(DeprecationWarning, reduce, add, range(10)) 

def test_reduce_move(self):
        from operator import add
        # reduce tests may have already triggered this warning
        reset_module_registry(unittest.case)
        with warnings.catch_warnings():
            warnings.filterwarnings("error", "reduce")
            self.assertRaises(DeprecationWarning, reduce, add, range(10)) 

def assert_allclose(actual, desired, rtol=1e-7, atol=0, equal_nan=True,
                    err_msg='', verbose=True):
    """
    Raises an AssertionError if two objects are not equal up to desired
    tolerance.

    The test is equivalent to ``allclose(actual, desired, rtol, atol)``.
    It compares the difference between `actual` and `desired` to
    ``atol + rtol * abs(desired)``.

    .. versionadded:: 1.5.0

    Parameters
    ----------
    actual : array_like
        Array obtained.
    desired : array_like
        Array desired.
    rtol : float, optional
        Relative tolerance.
    atol : float, optional
        Absolute tolerance.
    equal_nan : bool, optional.
        If True, NaNs will compare equal.
    err_msg : str, optional
        The error message to be printed in case of failure.
    verbose : bool, optional
        If True, the conflicting values are appended to the error message.

    Raises
    ------
    AssertionError
        If actual and desired are not equal up to specified precision.

    See Also
    --------
    assert_array_almost_equal_nulp, assert_array_max_ulp

    Examples
    --------
    >>> x = [1e-5, 1e-3, 1e-1]
    >>> y = np.arccos(np.cos(x))
    >>> assert_allclose(x, y, rtol=1e-5, atol=0)

    """
    __tracebackhide__ = True  # Hide traceback for py.test
    import numpy as np

    def compare(x, y):
        return np.core.numeric.isclose(x, y, rtol=rtol, atol=atol,
                                       equal_nan=equal_nan)

    actual, desired = np.asanyarray(actual), np.asanyarray(desired)
    header = 'Not equal to tolerance rtol=%g, atol=%g' % (rtol, atol)
    assert_array_compare(compare, actual, desired, err_msg=str(err_msg),
                         verbose=verbose, header=header, equal_nan=equal_nan) 

def assert_allclose(actual, desired, rtol=1e-7, atol=0, equal_nan=True,
                    err_msg='', verbose=True):
    """
    Raises an AssertionError if two objects are not equal up to desired
    tolerance.

    The test is equivalent to ``allclose(actual, desired, rtol, atol)``.
    It compares the difference between `actual` and `desired` to
    ``atol + rtol * abs(desired)``.

    .. versionadded:: 1.5.0

    Parameters
    ----------
    actual : array_like
        Array obtained.
    desired : array_like
        Array desired.
    rtol : float, optional
        Relative tolerance.
    atol : float, optional
        Absolute tolerance.
    equal_nan : bool, optional.
        If True, NaNs will compare equal.
    err_msg : str, optional
        The error message to be printed in case of failure.
    verbose : bool, optional
        If True, the conflicting values are appended to the error message.

    Raises
    ------
    AssertionError
        If actual and desired are not equal up to specified precision.

    See Also
    --------
    assert_array_almost_equal_nulp, assert_array_max_ulp

    Examples
    --------
    >>> x = [1e-5, 1e-3, 1e-1]
    >>> y = np.arccos(np.cos(x))
    >>> assert_allclose(x, y, rtol=1e-5, atol=0)

    """
    __tracebackhide__ = True  # Hide traceback for py.test
    import numpy as np

    def compare(x, y):
        return np.core.numeric.isclose(x, y, rtol=rtol, atol=atol,
                                       equal_nan=equal_nan)

    actual, desired = np.asanyarray(actual), np.asanyarray(desired)
    header = 'Not equal to tolerance rtol=%g, atol=%g' % (rtol, atol)
    assert_array_compare(compare, actual, desired, err_msg=str(err_msg),
                         verbose=verbose, header=header, equal_nan=equal_nan)