관리-도구
편집 파일: decorators.py
""" Decorators for labeling and modifying behavior of test objects. Decorators that merely return a modified version of the original function object are straightforward. Decorators that return a new function object need to use :: nose.tools.make_decorator(original_function)(decorator) in returning the decorator, in order to preserve meta-data such as function name, setup and teardown functions and so on - see ``nose.tools`` for more information. """ from __future__ import division, absolute_import, print_function import collections from .utils import SkipTest, assert_warns def slow(t): """ Label a test as 'slow'. The exact definition of a slow test is obviously both subjective and hardware-dependent, but in general any individual test that requires more than a second or two should be labeled as slow (the whole suite consits of thousands of tests, so even a second is significant). Parameters ---------- t : callable The test to label as slow. Returns ------- t : callable The decorated test `t`. Examples -------- The `numpy.testing` module includes ``import decorators as dec``. A test can be decorated as slow like this:: from numpy.testing import * @dec.slow def test_big(self): print('Big, slow test') """ t.slow = True return t def setastest(tf=True): """ Signals to nose that this function is or is not a test. Parameters ---------- tf : bool If True, specifies that the decorated callable is a test. If False, specifies that the decorated callable is not a test. Default is True. Notes ----- This decorator can't use the nose namespace, because it can be called from a non-test module. See also ``istest`` and ``nottest`` in ``nose.tools``. Examples -------- `setastest` can be used in the following way:: from numpy.testing.decorators import setastest @setastest(False) def func_with_test_in_name(arg1, arg2): pass """ def set_test(t): t.__test__ = tf return t return set_test def skipif(skip_condition, msg=None): """ Make function raise SkipTest exception if a given condition is true. If the condition is a callable, it is used at runtime to dynamically make the decision. This is useful for tests that may require costly imports, to delay the cost until the test suite is actually executed. Parameters ---------- skip_condition : bool or callable Flag to determine whether to skip the decorated test. msg : str, optional Message to give on raising a SkipTest exception. Default is None. Returns ------- decorator : function Decorator which, when applied to a function, causes SkipTest to be raised when `skip_condition` is True, and the function to be called normally otherwise. Notes ----- The decorator itself is decorated with the ``nose.tools.make_decorator`` function in order to transmit function name, and various other metadata. """ def skip_decorator(f): # Local import to avoid a hard nose dependency and only incur the # import time overhead at actual test-time. import nose # Allow for both boolean or callable skip conditions. if isinstance(skip_condition, collections.Callable): skip_val = lambda: skip_condition() else: skip_val = lambda: skip_condition def get_msg(func,msg=None): """Skip message with information about function being skipped.""" if msg is None: out = 'Test skipped due to test condition' else: out = msg return "Skipping test: %s: %s" % (func.__name__, out) # We need to define *two* skippers because Python doesn't allow both # return with value and yield inside the same function. def skipper_func(*args, **kwargs): """Skipper for normal test functions.""" if skip_val(): raise SkipTest(get_msg(f, msg)) else: return f(*args, **kwargs) def skipper_gen(*args, **kwargs): """Skipper for test generators.""" if skip_val(): raise SkipTest(get_msg(f, msg)) else: for x in f(*args, **kwargs): yield x # Choose the right skipper to use when building the actual decorator. if nose.util.isgenerator(f): skipper = skipper_gen else: skipper = skipper_func return nose.tools.make_decorator(f)(skipper) return skip_decorator def knownfailureif(fail_condition, msg=None): """ Make function raise KnownFailureException exception if given condition is true. If the condition is a callable, it is used at runtime to dynamically make the decision. This is useful for tests that may require costly imports, to delay the cost until the test suite is actually executed. Parameters ---------- fail_condition : bool or callable Flag to determine whether to mark the decorated test as a known failure (if True) or not (if False). msg : str, optional Message to give on raising a KnownFailureException exception. Default is None. Returns ------- decorator : function Decorator, which, when applied to a function, causes KnownFailureException to be raised when `fail_condition` is True, and the function to be called normally otherwise. Notes ----- The decorator itself is decorated with the ``nose.tools.make_decorator`` function in order to transmit function name, and various other metadata. """ if msg is None: msg = 'Test skipped due to known failure' # Allow for both boolean or callable known failure conditions. if isinstance(fail_condition, collections.Callable): fail_val = lambda: fail_condition() else: fail_val = lambda: fail_condition def knownfail_decorator(f): # Local import to avoid a hard nose dependency and only incur the # import time overhead at actual test-time. import nose from .noseclasses import KnownFailureException def knownfailer(*args, **kwargs): if fail_val(): raise KnownFailureException(msg) else: return f(*args, **kwargs) return nose.tools.make_decorator(f)(knownfailer) return knownfail_decorator def deprecated(conditional=True): """ Filter deprecation warnings while running the test suite. This decorator can be used to filter DeprecationWarning's, to avoid printing them during the test suite run, while checking that the test actually raises a DeprecationWarning. Parameters ---------- conditional : bool or callable, optional Flag to determine whether to mark test as deprecated or not. If the condition is a callable, it is used at runtime to dynamically make the decision. Default is True. Returns ------- decorator : function The `deprecated` decorator itself. Notes ----- .. versionadded:: 1.4.0 """ def deprecate_decorator(f): # Local import to avoid a hard nose dependency and only incur the # import time overhead at actual test-time. import nose def _deprecated_imp(*args, **kwargs): # Poor man's replacement for the with statement with assert_warns(DeprecationWarning): f(*args, **kwargs) if isinstance(conditional, collections.Callable): cond = conditional() else: cond = conditional if cond: return nose.tools.make_decorator(f)(_deprecated_imp) else: return f return deprecate_decorator