diff --git a/_pytest/python.py b/_pytest/python.py index ea2cfd3c6..1a313a59e 100644 --- a/_pytest/python.py +++ b/_pytest/python.py @@ -6,7 +6,6 @@ import inspect import sys import os import collections -import math from itertools import count import py @@ -1091,587 +1090,6 @@ def _showfixtures_main(config, session): red=True) -# builtin pytest.raises helper - -def raises(expected_exception, *args, **kwargs): - """ - Assert that a code block/function call raises ``expected_exception`` - and raise a failure exception otherwise. - - This helper produces a ``ExceptionInfo()`` object (see below). - - If using Python 2.5 or above, you may use this function as a - context manager:: - - >>> with raises(ZeroDivisionError): - ... 1/0 - - .. versionchanged:: 2.10 - - In the context manager form you may use the keyword argument - ``message`` to specify a custom failure message:: - - >>> with raises(ZeroDivisionError, message="Expecting ZeroDivisionError"): - ... pass - Traceback (most recent call last): - ... - Failed: Expecting ZeroDivisionError - - .. note:: - - When using ``pytest.raises`` as a context manager, it's worthwhile to - note that normal context manager rules apply and that the exception - raised *must* be the final line in the scope of the context manager. - Lines of code after that, within the scope of the context manager will - not be executed. For example:: - - >>> value = 15 - >>> with raises(ValueError) as exc_info: - ... if value > 10: - ... raise ValueError("value must be <= 10") - ... assert exc_info.type == ValueError # this will not execute - - Instead, the following approach must be taken (note the difference in - scope):: - - >>> with raises(ValueError) as exc_info: - ... if value > 10: - ... raise ValueError("value must be <= 10") - ... - >>> assert exc_info.type == ValueError - - Or you can use the keyword argument ``match`` to assert that the - exception matches a text or regex:: - - >>> with raises(ValueError, match='must be 0 or None'): - ... raise ValueError("value must be 0 or None") - - >>> with raises(ValueError, match=r'must be \d+$'): - ... raise ValueError("value must be 42") - - Or you can specify a callable by passing a to-be-called lambda:: - - >>> raises(ZeroDivisionError, lambda: 1/0) - - - or you can specify an arbitrary callable with arguments:: - - >>> def f(x): return 1/x - ... - >>> raises(ZeroDivisionError, f, 0) - - >>> raises(ZeroDivisionError, f, x=0) - - - A third possibility is to use a string to be executed:: - - >>> raises(ZeroDivisionError, "f(0)") - - - .. autoclass:: _pytest._code.ExceptionInfo - :members: - - .. note:: - Similar to caught exception objects in Python, explicitly clearing - local references to returned ``ExceptionInfo`` objects can - help the Python interpreter speed up its garbage collection. - - Clearing those references breaks a reference cycle - (``ExceptionInfo`` --> caught exception --> frame stack raising - the exception --> current frame stack --> local variables --> - ``ExceptionInfo``) which makes Python keep all objects referenced - from that cycle (including all local variables in the current - frame) alive until the next cyclic garbage collection run. See the - official Python ``try`` statement documentation for more detailed - information. - - """ - __tracebackhide__ = True - msg = ("exceptions must be old-style classes or" - " derived from BaseException, not %s") - if isinstance(expected_exception, tuple): - for exc in expected_exception: - if not isclass(exc): - raise TypeError(msg % type(exc)) - elif not isclass(expected_exception): - raise TypeError(msg % type(expected_exception)) - - message = "DID NOT RAISE {0}".format(expected_exception) - match_expr = None - - if not args: - if "message" in kwargs: - message = kwargs.pop("message") - if "match" in kwargs: - match_expr = kwargs.pop("match") - message += " matching '{0}'".format(match_expr) - return RaisesContext(expected_exception, message, match_expr) - elif isinstance(args[0], str): - code, = args - assert isinstance(code, str) - frame = sys._getframe(1) - loc = frame.f_locals.copy() - loc.update(kwargs) - #print "raises frame scope: %r" % frame.f_locals - try: - code = _pytest._code.Source(code).compile() - py.builtin.exec_(code, frame.f_globals, loc) - # XXX didn'T mean f_globals == f_locals something special? - # this is destroyed here ... - except expected_exception: - return _pytest._code.ExceptionInfo() - else: - func = args[0] - try: - func(*args[1:], **kwargs) - except expected_exception: - return _pytest._code.ExceptionInfo() - fail(message) - -raises.Exception = fail.Exception - -class RaisesContext(object): - def __init__(self, expected_exception, message, match_expr): - self.expected_exception = expected_exception - self.message = message - self.match_expr = match_expr - self.excinfo = None - - def __enter__(self): - self.excinfo = object.__new__(_pytest._code.ExceptionInfo) - return self.excinfo - - def __exit__(self, *tp): - __tracebackhide__ = True - if tp[0] is None: - fail(self.message) - if sys.version_info < (2, 7): - # py26: on __exit__() exc_value often does not contain the - # exception value. - # http://bugs.python.org/issue7853 - if not isinstance(tp[1], BaseException): - exc_type, value, traceback = tp - tp = exc_type, exc_type(value), traceback - self.excinfo.__init__(tp) - suppress_exception = issubclass(self.excinfo.type, self.expected_exception) - if sys.version_info[0] == 2 and suppress_exception: - sys.exc_clear() - if self.match_expr: - self.excinfo.match(self.match_expr) - return suppress_exception - - - -# builtin pytest.approx helper - -class ApproxBase(object): - """ - Provide shared utilities for making approximate comparisons between numbers - or sequences of numbers. - """ - - def __init__(self, expected, rel=None, abs=None): - self.expected = expected - self.abs = abs - self.rel = rel - - def __repr__(self): - return ', '.join( - repr(self._approx_scalar(x)) - for x in self._yield_expected()) - - def __eq__(self, actual): - return all( - a == self._approx_scalar(x) - for a, x in self._yield_comparisons(actual)) - - __hash__ = None - - def __ne__(self, actual): - return not (actual == self) - - def _approx_scalar(self, x): - return ApproxScalar(x, rel=self.rel, abs=self.abs) - - def _yield_expected(self, actual): - """ - Yield all the expected values associated with this object. This is - used to implement the `__repr__` method. - """ - raise NotImplementedError - - def _yield_comparisons(self, actual): - """ - Yield all the pairs of numbers to be compared. This is used to - implement the `__eq__` method. - """ - raise NotImplementedError - - - -try: - import numpy as np - - class ApproxNumpy(ApproxBase, np.ndarray): - """ - Perform approximate comparisons for numpy arrays. - - This class must inherit from numpy.ndarray in order to allow the approx - to be on either side of the `==` operator. The reason for this has to - do with how python decides whether to call `a.__eq__()` or `b.__eq__()` - when it encounters `a == b`. - - If `a` and `b` are not related by inheritance, `a` gets priority. So - as long as `a.__eq__` is defined, it will be called. Because most - implementations of `a.__eq__` end up calling `b.__eq__`, this detail - usually doesn't matter. However, `numpy.ndarray.__eq__` raises an - error complaining that "the truth value of an array with more than - one element is ambiguous. Use a.any() or a.all()" when compared with a - custom class, so `b.__eq__` never gets called. - - The trick is that the priority rules change if `a` and `b` are related - by inheritance. Specifically, `b.__eq__` gets priority if `b` is a - subclass of `a`. So we can guarantee that `ApproxNumpy.__eq__` gets - called by inheriting from `numpy.ndarray`. - """ - - def __new__(cls, expected, rel=None, abs=None): - """ - Numpy uses __new__ (rather than __init__) to initialize objects. - - The `expected` argument must be a numpy array. This should be - ensured by the approx() delegator function. - """ - assert isinstance(expected, np.ndarray) - obj = super(ApproxNumpy, cls).__new__(cls, expected.shape) - obj.__init__(expected, rel, abs) - return obj - - def __repr__(self): - # It might be nice to rewrite this function to account for the - # shape of the array... - return '[' + ApproxBase.__repr__(self) + ']' - - def __eq__(self, actual): - try: - actual = np.array(actual) - except: - raise ValueError("cannot cast '{0}' to numpy.ndarray".format(actual)) - - if actual.shape != self.expected.shape: - return False - - return ApproxBase.__eq__(self, actual) - - def _yield_expected(self): - for x in self.expected: - yield x - - def _yield_comparisons(self, actual): - # We can be sure that `actual` is a numpy array, because it's - # casted in `__eq__` before being passed to `ApproxBase.__eq__`, - # which is the only method that calls this one. - for i in np.ndindex(self.expected.shape): - yield actual[i], self.expected[i] - - -except ImportError: - np = None - -class ApproxMapping(ApproxBase): - """ - Perform approximate comparisons for mappings where the values are numbers - (the keys can be anything). - """ - - def __repr__(self): - item = lambda k, v: "'{0}': {1}".format(k, self._approx_scalar(v)) - return '{' + ', '.join(item(k,v) for k,v in self.expected.items()) + '}' - - def __eq__(self, actual): - if actual.keys() != self.expected.keys(): - return False - - return ApproxBase.__eq__(self, actual) - - def _yield_comparisons(self, actual): - for k in self.expected.keys(): - yield actual[k], self.expected[k] - - -class ApproxSequence(ApproxBase): - """ - Perform approximate comparisons for sequences of numbers. - """ - - def __repr__(self): - open, close = '()' if isinstance(self.expected, tuple) else '[]' - return open + ApproxBase.__repr__(self) + close - - def __eq__(self, actual): - if len(actual) != len(self.expected): - return False - return ApproxBase.__eq__(self, actual) - - def _yield_expected(self): - return iter(self.expected) - - def _yield_comparisons(self, actual): - return zip(actual, self.expected) - - -class ApproxScalar(ApproxBase): - """ - Perform approximate comparisons for single numbers only. - """ - - def __repr__(self): - """ - Return a string communicating both the expected value and the tolerance - for the comparison being made, e.g. '1.0 +- 1e-6'. Use the unicode - plus/minus symbol if this is python3 (it's too hard to get right for - python2). - """ - if isinstance(self.expected, complex): - return str(self.expected) - - # Infinities aren't compared using tolerances, so don't show a - # tolerance. - if math.isinf(self.expected): - return str(self.expected) - - # If a sensible tolerance can't be calculated, self.tolerance will - # raise a ValueError. In this case, display '???'. - try: - vetted_tolerance = '{:.1e}'.format(self.tolerance) - except ValueError: - vetted_tolerance = '???' - - if sys.version_info[0] == 2: - return '{0} +- {1}'.format(self.expected, vetted_tolerance) - else: - return u'{0} \u00b1 {1}'.format(self.expected, vetted_tolerance) - - def __eq__(self, actual): - """ - Return true if the given value is equal to the expected value within - the pre-specified tolerance. - """ - from numbers import Number - - # Give a good error message we get values to compare that aren't - # numbers, rather than choking on them later on. - if not isinstance(actual, Number): - raise ValueError("approx can only compare numbers, not '{0}'".format(actual)) - if not isinstance(self.expected, Number): - raise ValueError("approx can only compare numbers, not '{0}'".format(self.expected)) - - # Short-circuit exact equality. - if actual == self.expected: - return True - - # Infinity shouldn't be approximately equal to anything but itself, but - # if there's a relative tolerance, it will be infinite and infinity - # will seem approximately equal to everything. The equal-to-itself - # case would have been short circuited above, so here we can just - # return false if the expected value is infinite. The abs() call is - # for compatibility with complex numbers. - if math.isinf(abs(self.expected)): - return False - - # Return true if the two numbers are within the tolerance. - return abs(self.expected - actual) <= self.tolerance - - __hash__ = None - - @property - def tolerance(self): - """ - Return the tolerance for the comparison. This could be either an - absolute tolerance or a relative tolerance, depending on what the user - specified or which would be larger. - """ - set_default = lambda x, default: x if x is not None else default - - # Figure out what the absolute tolerance should be. ``self.abs`` is - # either None or a value specified by the user. - absolute_tolerance = set_default(self.abs, 1e-12) - - if absolute_tolerance < 0: - raise ValueError("absolute tolerance can't be negative: {}".format(absolute_tolerance)) - if math.isnan(absolute_tolerance): - raise ValueError("absolute tolerance can't be NaN.") - - # If the user specified an absolute tolerance but not a relative one, - # just return the absolute tolerance. - if self.rel is None: - if self.abs is not None: - return absolute_tolerance - - # Figure out what the relative tolerance should be. ``self.rel`` is - # either None or a value specified by the user. This is done after - # we've made sure the user didn't ask for an absolute tolerance only, - # because we don't want to raise errors about the relative tolerance if - # we aren't even going to use it. - relative_tolerance = set_default(self.rel, 1e-6) * abs(self.expected) - - if relative_tolerance < 0: - raise ValueError("relative tolerance can't be negative: {}".format(absolute_tolerance)) - if math.isnan(relative_tolerance): - raise ValueError("relative tolerance can't be NaN.") - - # Return the larger of the relative and absolute tolerances. - return max(relative_tolerance, absolute_tolerance) - - - -def approx(expected, rel=None, abs=None): - """ - Assert that two numbers (or two sets of numbers) are equal to each other - within some tolerance. - - Due to the `intricacies of floating-point arithmetic`__, numbers that we - would intuitively expect to be equal are not always so:: - - >>> 0.1 + 0.2 == 0.3 - False - - __ https://docs.python.org/3/tutorial/floatingpoint.html - - This problem is commonly encountered when writing tests, e.g. when making - sure that floating-point values are what you expect them to be. One way to - deal with this problem is to assert that two floating-point numbers are - equal to within some appropriate tolerance:: - - >>> abs((0.1 + 0.2) - 0.3) < 1e-6 - True - - However, comparisons like this are tedious to write and difficult to - understand. Furthermore, absolute comparisons like the one above are - usually discouraged because there's no tolerance that works well for all - situations. ``1e-6`` is good for numbers around ``1``, but too small for - very big numbers and too big for very small ones. It's better to express - the tolerance as a fraction of the expected value, but relative comparisons - like that are even more difficult to write correctly and concisely. - - The ``approx`` class performs floating-point comparisons using a syntax - that's as intuitive as possible:: - - >>> from pytest import approx - >>> 0.1 + 0.2 == approx(0.3) - True - - The same syntax also works on sequences of numbers:: - - >>> (0.1 + 0.2, 0.2 + 0.4) == approx((0.3, 0.6)) - True - >>> {'a': 0.1 + 0.2, 'b': 0.2 + 0.4} == approx({'a': 0.3, 'b': 0.6}) - True - - By default, ``approx`` considers numbers within a relative tolerance of - ``1e-6`` (i.e. one part in a million) of its expected value to be equal. - This treatment would lead to surprising results if the expected value was - ``0.0``, because nothing but ``0.0`` itself is relatively close to ``0.0``. - To handle this case less surprisingly, ``approx`` also considers numbers - within an absolute tolerance of ``1e-12`` of its expected value to be - equal. Infinite numbers are another special case. They are only - considered equal to themselves, regardless of the relative tolerance. Both - the relative and absolute tolerances can be changed by passing arguments to - the ``approx`` constructor:: - - >>> 1.0001 == approx(1) - False - >>> 1.0001 == approx(1, rel=1e-3) - True - >>> 1.0001 == approx(1, abs=1e-3) - True - - If you specify ``abs`` but not ``rel``, the comparison will not consider - the relative tolerance at all. In other words, two numbers that are within - the default relative tolerance of ``1e-6`` will still be considered unequal - if they exceed the specified absolute tolerance. If you specify both - ``abs`` and ``rel``, the numbers will be considered equal if either - tolerance is met:: - - >>> 1 + 1e-8 == approx(1) - True - >>> 1 + 1e-8 == approx(1, abs=1e-12) - False - >>> 1 + 1e-8 == approx(1, rel=1e-6, abs=1e-12) - True - - If you're thinking about using ``approx``, then you might want to know how - it compares to other good ways of comparing floating-point numbers. All of - these algorithms are based on relative and absolute tolerances and should - agree for the most part, but they do have meaningful differences: - - - ``math.isclose(a, b, rel_tol=1e-9, abs_tol=0.0)``: True if the relative - tolerance is met w.r.t. either ``a`` or ``b`` or if the absolute - tolerance is met. Because the relative tolerance is calculated w.r.t. - both ``a`` and ``b``, this test is symmetric (i.e. neither ``a`` nor - ``b`` is a "reference value"). You have to specify an absolute tolerance - if you want to compare to ``0.0`` because there is no tolerance by - default. Only available in python>=3.5. `More information...`__ - - __ https://docs.python.org/3/library/math.html#math.isclose - - - ``numpy.isclose(a, b, rtol=1e-5, atol=1e-8)``: True if the difference - between ``a`` and ``b`` is less that the sum of the relative tolerance - w.r.t. ``b`` and the absolute tolerance. Because the relative tolerance - is only calculated w.r.t. ``b``, this test is asymmetric and you can - think of ``b`` as the reference value. Support for comparing sequences - is provided by ``numpy.allclose``. `More information...`__ - - __ http://docs.scipy.org/doc/numpy-1.10.0/reference/generated/numpy.isclose.html - - - ``unittest.TestCase.assertAlmostEqual(a, b)``: True if ``a`` and ``b`` - are within an absolute tolerance of ``1e-7``. No relative tolerance is - considered and the absolute tolerance cannot be changed, so this function - is not appropriate for very large or very small numbers. Also, it's only - available in subclasses of ``unittest.TestCase`` and it's ugly because it - doesn't follow PEP8. `More information...`__ - - __ https://docs.python.org/3/library/unittest.html#unittest.TestCase.assertAlmostEqual - - - ``a == pytest.approx(b, rel=1e-6, abs=1e-12)``: True if the relative - tolerance is met w.r.t. ``b`` or if the absolute tolerance is met. - Because the relative tolerance is only calculated w.r.t. ``b``, this test - is asymmetric and you can think of ``b`` as the reference value. In the - special case that you explicitly specify an absolute tolerance but not a - relative tolerance, only the absolute tolerance is considered. - """ - - from collections import Mapping, Sequence - try: - String = basestring # python2 - except NameError: - String = str, bytes # python3 - - # Delegate the comparison to a class that knows how to deal with the type - # of the expected value (e.g. int, float, list, dict, numpy.array, etc). - # - # This architecture is really driven by the need to support numpy arrays. - # The only way to override `==` for arrays without requiring that approx be - # the left operand is to inherit the approx object from `numpy.ndarray`. - # But that can't be a general solution, because it requires (1) numpy to be - # installed and (2) the expected value to be a numpy array. So the general - # solution is to delegate each type of expected value to a different class. - # - # This has the advantage that it made it easy to support mapping types - # (i.e. dict). The old code accepted mapping types, but would only compare - # their keys, which is probably not what most people would expect. - - if np and isinstance(expected, np.ndarray): - cls = ApproxNumpy - elif isinstance(expected, Mapping): - cls = ApproxMapping - elif isinstance(expected, Sequence) and not isinstance(expected, String): - cls = ApproxSequence - else: - cls = ApproxScalar - - return cls(expected, rel, abs) - # # the basic pytest Function item diff --git a/_pytest/python_api.py b/_pytest/python_api.py new file mode 100644 index 000000000..029276c95 --- /dev/null +++ b/_pytest/python_api.py @@ -0,0 +1,588 @@ +import math +import sys + +import py + +from _pytest.compat import isclass +from _pytest.runner import fail +import _pytest._code + +# builtin pytest.approx helper + +class ApproxBase(object): + """ + Provide shared utilities for making approximate comparisons between numbers + or sequences of numbers. + """ + + def __init__(self, expected, rel=None, abs=None): + self.expected = expected + self.abs = abs + self.rel = rel + + def __repr__(self): + return ', '.join( + repr(self._approx_scalar(x)) + for x in self._yield_expected()) + + def __eq__(self, actual): + return all( + a == self._approx_scalar(x) + for a, x in self._yield_comparisons(actual)) + + __hash__ = None + + def __ne__(self, actual): + return not (actual == self) + + def _approx_scalar(self, x): + return ApproxScalar(x, rel=self.rel, abs=self.abs) + + def _yield_expected(self, actual): + """ + Yield all the expected values associated with this object. This is + used to implement the `__repr__` method. + """ + raise NotImplementedError + + def _yield_comparisons(self, actual): + """ + Yield all the pairs of numbers to be compared. This is used to + implement the `__eq__` method. + """ + raise NotImplementedError + + + +try: + import numpy as np + + class ApproxNumpy(ApproxBase, np.ndarray): + """ + Perform approximate comparisons for numpy arrays. + + This class must inherit from numpy.ndarray in order to allow the approx + to be on either side of the `==` operator. The reason for this has to + do with how python decides whether to call `a.__eq__()` or `b.__eq__()` + when it encounters `a == b`. + + If `a` and `b` are not related by inheritance, `a` gets priority. So + as long as `a.__eq__` is defined, it will be called. Because most + implementations of `a.__eq__` end up calling `b.__eq__`, this detail + usually doesn't matter. However, `numpy.ndarray.__eq__` raises an + error complaining that "the truth value of an array with more than + one element is ambiguous. Use a.any() or a.all()" when compared with a + custom class, so `b.__eq__` never gets called. + + The trick is that the priority rules change if `a` and `b` are related + by inheritance. Specifically, `b.__eq__` gets priority if `b` is a + subclass of `a`. So we can guarantee that `ApproxNumpy.__eq__` gets + called by inheriting from `numpy.ndarray`. + """ + + def __new__(cls, expected, rel=None, abs=None): + """ + Numpy uses __new__ (rather than __init__) to initialize objects. + + The `expected` argument must be a numpy array. This should be + ensured by the approx() delegator function. + """ + assert isinstance(expected, np.ndarray) + obj = super(ApproxNumpy, cls).__new__(cls, expected.shape) + obj.__init__(expected, rel, abs) + return obj + + def __repr__(self): + # It might be nice to rewrite this function to account for the + # shape of the array... + return '[' + ApproxBase.__repr__(self) + ']' + + def __eq__(self, actual): + try: + actual = np.array(actual) + except: + raise ValueError("cannot cast '{0}' to numpy.ndarray".format(actual)) + + if actual.shape != self.expected.shape: + return False + + return ApproxBase.__eq__(self, actual) + + def _yield_expected(self): + for x in self.expected: + yield x + + def _yield_comparisons(self, actual): + # We can be sure that `actual` is a numpy array, because it's + # casted in `__eq__` before being passed to `ApproxBase.__eq__`, + # which is the only method that calls this one. + for i in np.ndindex(self.expected.shape): + yield actual[i], self.expected[i] + + +except ImportError: + np = None + +class ApproxMapping(ApproxBase): + """ + Perform approximate comparisons for mappings where the values are numbers + (the keys can be anything). + """ + + def __repr__(self): + item = lambda k, v: "'{0}': {1}".format(k, self._approx_scalar(v)) + return '{' + ', '.join(item(k,v) for k,v in self.expected.items()) + '}' + + def __eq__(self, actual): + if actual.keys() != self.expected.keys(): + return False + + return ApproxBase.__eq__(self, actual) + + def _yield_comparisons(self, actual): + for k in self.expected.keys(): + yield actual[k], self.expected[k] + + +class ApproxSequence(ApproxBase): + """ + Perform approximate comparisons for sequences of numbers. + """ + + def __repr__(self): + open, close = '()' if isinstance(self.expected, tuple) else '[]' + return open + ApproxBase.__repr__(self) + close + + def __eq__(self, actual): + if len(actual) != len(self.expected): + return False + return ApproxBase.__eq__(self, actual) + + def _yield_expected(self): + return iter(self.expected) + + def _yield_comparisons(self, actual): + return zip(actual, self.expected) + + +class ApproxScalar(ApproxBase): + """ + Perform approximate comparisons for single numbers only. + """ + + def __repr__(self): + """ + Return a string communicating both the expected value and the tolerance + for the comparison being made, e.g. '1.0 +- 1e-6'. Use the unicode + plus/minus symbol if this is python3 (it's too hard to get right for + python2). + """ + if isinstance(self.expected, complex): + return str(self.expected) + + # Infinities aren't compared using tolerances, so don't show a + # tolerance. + if math.isinf(self.expected): + return str(self.expected) + + # If a sensible tolerance can't be calculated, self.tolerance will + # raise a ValueError. In this case, display '???'. + try: + vetted_tolerance = '{:.1e}'.format(self.tolerance) + except ValueError: + vetted_tolerance = '???' + + if sys.version_info[0] == 2: + return '{0} +- {1}'.format(self.expected, vetted_tolerance) + else: + return u'{0} \u00b1 {1}'.format(self.expected, vetted_tolerance) + + def __eq__(self, actual): + """ + Return true if the given value is equal to the expected value within + the pre-specified tolerance. + """ + from numbers import Number + + # Give a good error message we get values to compare that aren't + # numbers, rather than choking on them later on. + if not isinstance(actual, Number): + raise ValueError("approx can only compare numbers, not '{0}'".format(actual)) + if not isinstance(self.expected, Number): + raise ValueError("approx can only compare numbers, not '{0}'".format(self.expected)) + + # Short-circuit exact equality. + if actual == self.expected: + return True + + # Infinity shouldn't be approximately equal to anything but itself, but + # if there's a relative tolerance, it will be infinite and infinity + # will seem approximately equal to everything. The equal-to-itself + # case would have been short circuited above, so here we can just + # return false if the expected value is infinite. The abs() call is + # for compatibility with complex numbers. + if math.isinf(abs(self.expected)): + return False + + # Return true if the two numbers are within the tolerance. + return abs(self.expected - actual) <= self.tolerance + + __hash__ = None + + @property + def tolerance(self): + """ + Return the tolerance for the comparison. This could be either an + absolute tolerance or a relative tolerance, depending on what the user + specified or which would be larger. + """ + set_default = lambda x, default: x if x is not None else default + + # Figure out what the absolute tolerance should be. ``self.abs`` is + # either None or a value specified by the user. + absolute_tolerance = set_default(self.abs, 1e-12) + + if absolute_tolerance < 0: + raise ValueError("absolute tolerance can't be negative: {}".format(absolute_tolerance)) + if math.isnan(absolute_tolerance): + raise ValueError("absolute tolerance can't be NaN.") + + # If the user specified an absolute tolerance but not a relative one, + # just return the absolute tolerance. + if self.rel is None: + if self.abs is not None: + return absolute_tolerance + + # Figure out what the relative tolerance should be. ``self.rel`` is + # either None or a value specified by the user. This is done after + # we've made sure the user didn't ask for an absolute tolerance only, + # because we don't want to raise errors about the relative tolerance if + # we aren't even going to use it. + relative_tolerance = set_default(self.rel, 1e-6) * abs(self.expected) + + if relative_tolerance < 0: + raise ValueError("relative tolerance can't be negative: {}".format(absolute_tolerance)) + if math.isnan(relative_tolerance): + raise ValueError("relative tolerance can't be NaN.") + + # Return the larger of the relative and absolute tolerances. + return max(relative_tolerance, absolute_tolerance) + + + +def approx(expected, rel=None, abs=None): + """ + Assert that two numbers (or two sets of numbers) are equal to each other + within some tolerance. + + Due to the `intricacies of floating-point arithmetic`__, numbers that we + would intuitively expect to be equal are not always so:: + + >>> 0.1 + 0.2 == 0.3 + False + + __ https://docs.python.org/3/tutorial/floatingpoint.html + + This problem is commonly encountered when writing tests, e.g. when making + sure that floating-point values are what you expect them to be. One way to + deal with this problem is to assert that two floating-point numbers are + equal to within some appropriate tolerance:: + + >>> abs((0.1 + 0.2) - 0.3) < 1e-6 + True + + However, comparisons like this are tedious to write and difficult to + understand. Furthermore, absolute comparisons like the one above are + usually discouraged because there's no tolerance that works well for all + situations. ``1e-6`` is good for numbers around ``1``, but too small for + very big numbers and too big for very small ones. It's better to express + the tolerance as a fraction of the expected value, but relative comparisons + like that are even more difficult to write correctly and concisely. + + The ``approx`` class performs floating-point comparisons using a syntax + that's as intuitive as possible:: + + >>> from pytest import approx + >>> 0.1 + 0.2 == approx(0.3) + True + + The same syntax also works on sequences of numbers:: + + >>> (0.1 + 0.2, 0.2 + 0.4) == approx((0.3, 0.6)) + True + >>> {'a': 0.1 + 0.2, 'b': 0.2 + 0.4} == approx({'a': 0.3, 'b': 0.6}) + True + + By default, ``approx`` considers numbers within a relative tolerance of + ``1e-6`` (i.e. one part in a million) of its expected value to be equal. + This treatment would lead to surprising results if the expected value was + ``0.0``, because nothing but ``0.0`` itself is relatively close to ``0.0``. + To handle this case less surprisingly, ``approx`` also considers numbers + within an absolute tolerance of ``1e-12`` of its expected value to be + equal. Infinite numbers are another special case. They are only + considered equal to themselves, regardless of the relative tolerance. Both + the relative and absolute tolerances can be changed by passing arguments to + the ``approx`` constructor:: + + >>> 1.0001 == approx(1) + False + >>> 1.0001 == approx(1, rel=1e-3) + True + >>> 1.0001 == approx(1, abs=1e-3) + True + + If you specify ``abs`` but not ``rel``, the comparison will not consider + the relative tolerance at all. In other words, two numbers that are within + the default relative tolerance of ``1e-6`` will still be considered unequal + if they exceed the specified absolute tolerance. If you specify both + ``abs`` and ``rel``, the numbers will be considered equal if either + tolerance is met:: + + >>> 1 + 1e-8 == approx(1) + True + >>> 1 + 1e-8 == approx(1, abs=1e-12) + False + >>> 1 + 1e-8 == approx(1, rel=1e-6, abs=1e-12) + True + + If you're thinking about using ``approx``, then you might want to know how + it compares to other good ways of comparing floating-point numbers. All of + these algorithms are based on relative and absolute tolerances and should + agree for the most part, but they do have meaningful differences: + + - ``math.isclose(a, b, rel_tol=1e-9, abs_tol=0.0)``: True if the relative + tolerance is met w.r.t. either ``a`` or ``b`` or if the absolute + tolerance is met. Because the relative tolerance is calculated w.r.t. + both ``a`` and ``b``, this test is symmetric (i.e. neither ``a`` nor + ``b`` is a "reference value"). You have to specify an absolute tolerance + if you want to compare to ``0.0`` because there is no tolerance by + default. Only available in python>=3.5. `More information...`__ + + __ https://docs.python.org/3/library/math.html#math.isclose + + - ``numpy.isclose(a, b, rtol=1e-5, atol=1e-8)``: True if the difference + between ``a`` and ``b`` is less that the sum of the relative tolerance + w.r.t. ``b`` and the absolute tolerance. Because the relative tolerance + is only calculated w.r.t. ``b``, this test is asymmetric and you can + think of ``b`` as the reference value. Support for comparing sequences + is provided by ``numpy.allclose``. `More information...`__ + + __ http://docs.scipy.org/doc/numpy-1.10.0/reference/generated/numpy.isclose.html + + - ``unittest.TestCase.assertAlmostEqual(a, b)``: True if ``a`` and ``b`` + are within an absolute tolerance of ``1e-7``. No relative tolerance is + considered and the absolute tolerance cannot be changed, so this function + is not appropriate for very large or very small numbers. Also, it's only + available in subclasses of ``unittest.TestCase`` and it's ugly because it + doesn't follow PEP8. `More information...`__ + + __ https://docs.python.org/3/library/unittest.html#unittest.TestCase.assertAlmostEqual + + - ``a == pytest.approx(b, rel=1e-6, abs=1e-12)``: True if the relative + tolerance is met w.r.t. ``b`` or if the absolute tolerance is met. + Because the relative tolerance is only calculated w.r.t. ``b``, this test + is asymmetric and you can think of ``b`` as the reference value. In the + special case that you explicitly specify an absolute tolerance but not a + relative tolerance, only the absolute tolerance is considered. + """ + + from collections import Mapping, Sequence + try: + String = basestring # python2 + except NameError: + String = str, bytes # python3 + + # Delegate the comparison to a class that knows how to deal with the type + # of the expected value (e.g. int, float, list, dict, numpy.array, etc). + # + # This architecture is really driven by the need to support numpy arrays. + # The only way to override `==` for arrays without requiring that approx be + # the left operand is to inherit the approx object from `numpy.ndarray`. + # But that can't be a general solution, because it requires (1) numpy to be + # installed and (2) the expected value to be a numpy array. So the general + # solution is to delegate each type of expected value to a different class. + # + # This has the advantage that it made it easy to support mapping types + # (i.e. dict). The old code accepted mapping types, but would only compare + # their keys, which is probably not what most people would expect. + + if np and isinstance(expected, np.ndarray): + cls = ApproxNumpy + elif isinstance(expected, Mapping): + cls = ApproxMapping + elif isinstance(expected, Sequence) and not isinstance(expected, String): + cls = ApproxSequence + else: + cls = ApproxScalar + + return cls(expected, rel, abs) + + +# builtin pytest.raises helper + +def raises(expected_exception, *args, **kwargs): + """ + Assert that a code block/function call raises ``expected_exception`` + and raise a failure exception otherwise. + + This helper produces a ``ExceptionInfo()`` object (see below). + + If using Python 2.5 or above, you may use this function as a + context manager:: + + >>> with raises(ZeroDivisionError): + ... 1/0 + + .. versionchanged:: 2.10 + + In the context manager form you may use the keyword argument + ``message`` to specify a custom failure message:: + + >>> with raises(ZeroDivisionError, message="Expecting ZeroDivisionError"): + ... pass + Traceback (most recent call last): + ... + Failed: Expecting ZeroDivisionError + + .. note:: + + When using ``pytest.raises`` as a context manager, it's worthwhile to + note that normal context manager rules apply and that the exception + raised *must* be the final line in the scope of the context manager. + Lines of code after that, within the scope of the context manager will + not be executed. For example:: + + >>> value = 15 + >>> with raises(ValueError) as exc_info: + ... if value > 10: + ... raise ValueError("value must be <= 10") + ... assert exc_info.type == ValueError # this will not execute + + Instead, the following approach must be taken (note the difference in + scope):: + + >>> with raises(ValueError) as exc_info: + ... if value > 10: + ... raise ValueError("value must be <= 10") + ... + >>> assert exc_info.type == ValueError + + Or you can use the keyword argument ``match`` to assert that the + exception matches a text or regex:: + + >>> with raises(ValueError, match='must be 0 or None'): + ... raise ValueError("value must be 0 or None") + + >>> with raises(ValueError, match=r'must be \d+$'): + ... raise ValueError("value must be 42") + + Or you can specify a callable by passing a to-be-called lambda:: + + >>> raises(ZeroDivisionError, lambda: 1/0) + + + or you can specify an arbitrary callable with arguments:: + + >>> def f(x): return 1/x + ... + >>> raises(ZeroDivisionError, f, 0) + + >>> raises(ZeroDivisionError, f, x=0) + + + A third possibility is to use a string to be executed:: + + >>> raises(ZeroDivisionError, "f(0)") + + + .. autoclass:: _pytest._code.ExceptionInfo + :members: + + .. note:: + Similar to caught exception objects in Python, explicitly clearing + local references to returned ``ExceptionInfo`` objects can + help the Python interpreter speed up its garbage collection. + + Clearing those references breaks a reference cycle + (``ExceptionInfo`` --> caught exception --> frame stack raising + the exception --> current frame stack --> local variables --> + ``ExceptionInfo``) which makes Python keep all objects referenced + from that cycle (including all local variables in the current + frame) alive until the next cyclic garbage collection run. See the + official Python ``try`` statement documentation for more detailed + information. + + """ + __tracebackhide__ = True + msg = ("exceptions must be old-style classes or" + " derived from BaseException, not %s") + if isinstance(expected_exception, tuple): + for exc in expected_exception: + if not isclass(exc): + raise TypeError(msg % type(exc)) + elif not isclass(expected_exception): + raise TypeError(msg % type(expected_exception)) + + message = "DID NOT RAISE {0}".format(expected_exception) + match_expr = None + + if not args: + if "message" in kwargs: + message = kwargs.pop("message") + if "match" in kwargs: + match_expr = kwargs.pop("match") + message += " matching '{0}'".format(match_expr) + return RaisesContext(expected_exception, message, match_expr) + elif isinstance(args[0], str): + code, = args + assert isinstance(code, str) + frame = sys._getframe(1) + loc = frame.f_locals.copy() + loc.update(kwargs) + #print "raises frame scope: %r" % frame.f_locals + try: + code = _pytest._code.Source(code).compile() + py.builtin.exec_(code, frame.f_globals, loc) + # XXX didn'T mean f_globals == f_locals something special? + # this is destroyed here ... + except expected_exception: + return _pytest._code.ExceptionInfo() + else: + func = args[0] + try: + func(*args[1:], **kwargs) + except expected_exception: + return _pytest._code.ExceptionInfo() + fail(message) + +raises.Exception = fail.Exception + +class RaisesContext(object): + def __init__(self, expected_exception, message, match_expr): + self.expected_exception = expected_exception + self.message = message + self.match_expr = match_expr + self.excinfo = None + + def __enter__(self): + self.excinfo = object.__new__(_pytest._code.ExceptionInfo) + return self.excinfo + + def __exit__(self, *tp): + __tracebackhide__ = True + if tp[0] is None: + fail(self.message) + if sys.version_info < (2, 7): + # py26: on __exit__() exc_value often does not contain the + # exception value. + # http://bugs.python.org/issue7853 + if not isinstance(tp[1], BaseException): + exc_type, value, traceback = tp + tp = exc_type, exc_type(value), traceback + self.excinfo.__init__(tp) + suppress_exception = issubclass(self.excinfo.type, self.expected_exception) + if sys.version_info[0] == 2 and suppress_exception: + sys.exc_clear() + if self.match_expr: + self.excinfo.match(self.match_expr) + return suppress_exception diff --git a/changelog/2489.trivial b/changelog/2489.trivial new file mode 100644 index 000000000..c997d7e1e --- /dev/null +++ b/changelog/2489.trivial @@ -0,0 +1 @@ +Internal code move: move code for pytest.approx/pytest.raises to own files in order to cut down the size of python.py \ No newline at end of file diff --git a/pytest.py b/pytest.py index 4e4ccb32d..da6b64910 100644 --- a/pytest.py +++ b/pytest.py @@ -22,10 +22,11 @@ from _pytest.skipping import xfail from _pytest.main import Item, Collector, File, Session from _pytest.fixtures import fillfixtures as _fillfuncargs from _pytest.python import ( - raises, approx, Module, Class, Instance, Function, Generator, ) +from _pytest.python_api import approx, raises + set_trace = __pytestPDB.set_trace __all__ = [