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Diffstat (limited to 'lib/spack/external/_pytest/python_api.py')
| -rw-r--r-- | lib/spack/external/_pytest/python_api.py | 626 |
1 files changed, 626 insertions, 0 deletions
diff --git a/lib/spack/external/_pytest/python_api.py b/lib/spack/external/_pytest/python_api.py new file mode 100644 index 0000000000..cfc01193b0 --- /dev/null +++ b/lib/spack/external/_pytest/python_api.py @@ -0,0 +1,626 @@ +import math +import sys + +import py + +from _pytest.compat import isclass, izip +from _pytest.outcomes import fail +import _pytest._code + + +def _cmp_raises_type_error(self, other): + """__cmp__ implementation which raises TypeError. Used + by Approx base classes to implement only == and != and raise a + TypeError for other comparisons. + + Needed in Python 2 only, Python 3 all it takes is not implementing the + other operators at all. + """ + __tracebackhide__ = True + raise TypeError('Comparison operators other than == and != not supported by approx objects') + + +# 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, nan_ok=False): + self.expected = expected + self.abs = abs + self.rel = rel + self.nan_ok = nan_ok + + def __repr__(self): + raise NotImplementedError + + 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) + + if sys.version_info[0] == 2: + __cmp__ = _cmp_raises_type_error + + def _approx_scalar(self, x): + return ApproxScalar(x, rel=self.rel, abs=self.abs, nan_ok=self.nan_ok) + + def _yield_comparisons(self, actual): + """ + Yield all the pairs of numbers to be compared. This is used to + implement the `__eq__` method. + """ + raise NotImplementedError + + +class ApproxNumpy(ApproxBase): + """ + Perform approximate comparisons for numpy arrays. + """ + + # Tell numpy to use our `__eq__` operator instead of its. + __array_priority__ = 100 + + def __repr__(self): + # It might be nice to rewrite this function to account for the + # shape of the array... + return "approx({0!r})".format(list( + self._approx_scalar(x) for x in self.expected)) + + if sys.version_info[0] == 2: + __cmp__ = _cmp_raises_type_error + + def __eq__(self, actual): + import numpy as np + + try: + actual = np.asarray(actual) + except: # noqa + raise TypeError("cannot compare '{0}' to numpy.ndarray".format(actual)) + + if actual.shape != self.expected.shape: + return False + + return ApproxBase.__eq__(self, actual) + + def _yield_comparisons(self, actual): + import numpy as np + + # 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] + + +class ApproxMapping(ApproxBase): + """ + Perform approximate comparisons for mappings where the values are numbers + (the keys can be anything). + """ + + def __repr__(self): + return "approx({0!r})".format(dict( + (k, self._approx_scalar(v)) + for k, v in self.expected.items())) + + def __eq__(self, actual): + if set(actual.keys()) != set(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. + """ + + # Tell numpy to use our `__eq__` operator instead of its. + __array_priority__ = 100 + + def __repr__(self): + seq_type = type(self.expected) + if seq_type not in (tuple, list, set): + seq_type = list + return "approx({0!r})".format(seq_type( + self._approx_scalar(x) for x in self.expected)) + + def __eq__(self, actual): + if len(actual) != len(self.expected): + return False + return ApproxBase.__eq__(self, actual) + + def _yield_comparisons(self, actual): + return izip(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. + """ + + # Short-circuit exact equality. + if actual == self.expected: + return True + + # Allow the user to control whether NaNs are considered equal to each + # other or not. The abs() calls are for compatibility with complex + # numbers. + if math.isnan(abs(self.expected)): + return self.nan_ok and math.isnan(abs(actual)) + + # 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. + """ + def set_default(x, default): + return 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: {0}".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: {0}".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, nan_ok=False): + """ + 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 for sequences of numbers:: + + >>> (0.1 + 0.2, 0.2 + 0.4) == approx((0.3, 0.6)) + True + + Dictionary *values*:: + + >>> {'a': 0.1 + 0.2, 'b': 0.2 + 0.4} == approx({'a': 0.3, 'b': 0.6}) + True + + And ``numpy`` arrays:: + + >>> import numpy as np # doctest: +SKIP + >>> np.array([0.1, 0.2]) + np.array([0.2, 0.4]) == approx(np.array([0.3, 0.6])) # doctest: +SKIP + 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. Infinity and NaN are special cases. Infinity is only considered + equal to itself, regardless of the relative tolerance. NaN is not + considered equal to anything by default, but you can make it be equal to + itself by setting the ``nan_ok`` argument to True. (This is meant to + facilitate comparing arrays that use NaN to mean "no data".) + + 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. + + .. warning:: + + .. versionchanged:: 3.2 + + In order to avoid inconsistent behavior, ``TypeError`` is + raised for ``>``, ``>=``, ``<`` and ``<=`` comparisons. + The example below illustrates the problem:: + + assert approx(0.1) > 0.1 + 1e-10 # calls approx(0.1).__gt__(0.1 + 1e-10) + assert 0.1 + 1e-10 > approx(0.1) # calls approx(0.1).__lt__(0.1 + 1e-10) + + In the second example one expects ``approx(0.1).__le__(0.1 + 1e-10)`` + to be called. But instead, ``approx(0.1).__lt__(0.1 + 1e-10)`` is used to + comparison. This is because the call hierarchy of rich comparisons + follows a fixed behavior. `More information...`__ + + __ https://docs.python.org/3/reference/datamodel.html#object.__ge__ + """ + + from collections import Mapping, Sequence + from _pytest.compat import STRING_TYPES as String + + # 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 _is_numpy_array(expected): + 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, nan_ok) + + +def _is_numpy_array(obj): + """ + Return true if the given object is a numpy array. Make a special effort to + avoid importing numpy unless it's really necessary. + """ + import inspect + + for cls in inspect.getmro(type(obj)): + if cls.__module__ == 'numpy': + try: + import numpy as np + return isinstance(obj, np.ndarray) + except ImportError: + pass + + return False + + +# 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 + + + Since version ``3.1`` 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") + + **Legacy forms** + + The forms below are fully supported but are discouraged for new code because the + context manager form is regarded as more readable and less error-prone. + + It is possible to specify a callable by passing a to-be-called lambda:: + + >>> raises(ZeroDivisionError, lambda: 1/0) + <ExceptionInfo ...> + + or you can specify an arbitrary callable with arguments:: + + >>> def f(x): return 1/x + ... + >>> raises(ZeroDivisionError, f, 0) + <ExceptionInfo ...> + >>> raises(ZeroDivisionError, f, x=0) + <ExceptionInfo ...> + + It is also possible to pass a string to be evaluated at runtime:: + + >>> raises(ZeroDivisionError, "f(0)") + <ExceptionInfo ...> + + The string will be evaluated using the same ``locals()`` and ``globals()`` + at the moment of the ``raises`` call. + + .. 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 |