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# -*- coding: utf-8 -*-
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"""Decorators for labeling test objects.
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Decorators that merely return a modified version of the original function
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object are straightforward. Decorators that return a new function object need
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to use nose.tools.make_decorator(original_function)(decorator) in returning the
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decorator, in order to preserve metadata such as function name, setup and
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teardown functions and so on - see nose.tools for more information.
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This module provides a set of useful decorators meant to be ready to use in
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your own tests. See the bottom of the file for the ready-made ones, and if you
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find yourself writing a new one that may be of generic use, add it here.
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Included decorators:
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Lightweight testing that remains unittest-compatible.
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- An @as_unittest decorator can be used to tag any normal parameter-less
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function as a unittest TestCase. Then, both nose and normal unittest will
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recognize it as such. This will make it easier to migrate away from Nose if
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we ever need/want to while maintaining very lightweight tests.
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NOTE: This file contains IPython-specific decorators. Using the machinery in
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IPython.external.decorators, we import either numpy.testing.decorators if numpy is
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available, OR use equivalent code in IPython.external._decorators, which
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we've copied verbatim from numpy.
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Authors
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-------
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- Fernando Perez <Fernando.Perez@berkeley.edu>
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"""
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#-----------------------------------------------------------------------------
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# Copyright (C) 2009-2011 The IPython Development Team
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#
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# Distributed under the terms of the BSD License. The full license is in
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# the file COPYING, distributed as part of this software.
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#-----------------------------------------------------------------------------
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#-----------------------------------------------------------------------------
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# Imports
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#-----------------------------------------------------------------------------
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# Stdlib imports
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import sys
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import os
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import tempfile
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import unittest
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# Third-party imports
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# This is Michele Simionato's decorator module, kept verbatim.
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from IPython.external.decorator import decorator
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# Expose the unittest-driven decorators
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from ipunittest import ipdoctest, ipdocstring
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# Grab the numpy-specific decorators which we keep in a file that we
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# occasionally update from upstream: decorators.py is a copy of
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# numpy.testing.decorators, we expose all of it here.
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from IPython.external.decorators import *
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# For onlyif_cmd_exists decorator
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from IPython.utils.process import is_cmd_found
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#-----------------------------------------------------------------------------
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# Classes and functions
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#-----------------------------------------------------------------------------
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# Simple example of the basic idea
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def as_unittest(func):
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"""Decorator to make a simple function into a normal test via unittest."""
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class Tester(unittest.TestCase):
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def test(self):
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func()
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Tester.__name__ = func.__name__
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return Tester
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# Utility functions
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def apply_wrapper(wrapper,func):
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"""Apply a wrapper to a function for decoration.
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This mixes Michele Simionato's decorator tool with nose's make_decorator,
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to apply a wrapper in a decorator so that all nose attributes, as well as
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function signature and other properties, survive the decoration cleanly.
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This will ensure that wrapped functions can still be well introspected via
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IPython, for example.
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"""
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import nose.tools
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return decorator(wrapper,nose.tools.make_decorator(func)(wrapper))
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def make_label_dec(label,ds=None):
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"""Factory function to create a decorator that applies one or more labels.
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Parameters
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----------
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label : string or sequence
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One or more labels that will be applied by the decorator to the functions
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it decorates. Labels are attributes of the decorated function with their
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value set to True.
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ds : string
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An optional docstring for the resulting decorator. If not given, a
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default docstring is auto-generated.
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Returns
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-------
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A decorator.
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Examples
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--------
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A simple labeling decorator:
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>>> slow = make_label_dec('slow')
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>>> slow.__doc__
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"Labels a test as 'slow'."
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And one that uses multiple labels and a custom docstring:
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>>> rare = make_label_dec(['slow','hard'],
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... "Mix labels 'slow' and 'hard' for rare tests.")
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>>> rare.__doc__
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"Mix labels 'slow' and 'hard' for rare tests."
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Now, let's test using this one:
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>>> @rare
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... def f(): pass
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...
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>>>
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>>> f.slow
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True
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>>> f.hard
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True
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"""
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if isinstance(label,basestring):
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labels = [label]
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else:
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labels = label
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# Validate that the given label(s) are OK for use in setattr() by doing a
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# dry run on a dummy function.
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tmp = lambda : None
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for label in labels:
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setattr(tmp,label,True)
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# This is the actual decorator we'll return
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def decor(f):
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for label in labels:
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setattr(f,label,True)
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return f
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# Apply the user's docstring, or autogenerate a basic one
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if ds is None:
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ds = "Labels a test as %r." % label
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decor.__doc__ = ds
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return decor
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# Inspired by numpy's skipif, but uses the full apply_wrapper utility to
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# preserve function metadata better and allows the skip condition to be a
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# callable.
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def skipif(skip_condition, msg=None):
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''' Make function raise SkipTest exception if skip_condition is true
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Parameters
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----------
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skip_condition : bool or callable.
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Flag to determine whether to skip test. If the condition is a
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callable, it is used at runtime to dynamically make the decision. This
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is useful for tests that may require costly imports, to delay the cost
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until the test suite is actually executed.
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msg : string
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Message to give on raising a SkipTest exception
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Returns
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-------
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decorator : function
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Decorator, which, when applied to a function, causes SkipTest
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to be raised when the skip_condition was True, and the function
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to be called normally otherwise.
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Notes
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-----
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You will see from the code that we had to further decorate the
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decorator with the nose.tools.make_decorator function in order to
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transmit function name, and various other metadata.
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'''
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def skip_decorator(f):
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# Local import to avoid a hard nose dependency and only incur the
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# import time overhead at actual test-time.
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import nose
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# Allow for both boolean or callable skip conditions.
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if callable(skip_condition):
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skip_val = skip_condition
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else:
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skip_val = lambda : skip_condition
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def get_msg(func,msg=None):
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"""Skip message with information about function being skipped."""
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if msg is None: out = 'Test skipped due to test condition.'
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else: out = msg
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return "Skipping test: %s. %s" % (func.__name__,out)
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# We need to define *two* skippers because Python doesn't allow both
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# return with value and yield inside the same function.
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def skipper_func(*args, **kwargs):
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"""Skipper for normal test functions."""
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if skip_val():
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raise nose.SkipTest(get_msg(f,msg))
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else:
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return f(*args, **kwargs)
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def skipper_gen(*args, **kwargs):
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"""Skipper for test generators."""
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if skip_val():
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raise nose.SkipTest(get_msg(f,msg))
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else:
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for x in f(*args, **kwargs):
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yield x
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# Choose the right skipper to use when building the actual generator.
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if nose.util.isgenerator(f):
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skipper = skipper_gen
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else:
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skipper = skipper_func
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return nose.tools.make_decorator(f)(skipper)
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return skip_decorator
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# A version with the condition set to true, common case just to attach a message
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# to a skip decorator
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def skip(msg=None):
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"""Decorator factory - mark a test function for skipping from test suite.
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Parameters
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----------
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msg : string
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Optional message to be added.
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Returns
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-------
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decorator : function
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Decorator, which, when applied to a function, causes SkipTest
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to be raised, with the optional message added.
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"""
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return skipif(True,msg)
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def onlyif(condition, msg):
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"""The reverse from skipif, see skipif for details."""
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if callable(condition):
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skip_condition = lambda : not condition()
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else:
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skip_condition = lambda : not condition
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return skipif(skip_condition, msg)
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#-----------------------------------------------------------------------------
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# Utility functions for decorators
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def module_not_available(module):
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"""Can module be imported? Returns true if module does NOT import.
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This is used to make a decorator to skip tests that require module to be
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available, but delay the 'import numpy' to test execution time.
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"""
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try:
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mod = __import__(module)
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mod_not_avail = False
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except ImportError:
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mod_not_avail = True
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return mod_not_avail
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def decorated_dummy(dec, name):
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"""Return a dummy function decorated with dec, with the given name.
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Examples
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--------
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import IPython.testing.decorators as dec
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setup = dec.decorated_dummy(dec.skip_if_no_x11, __name__)
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"""
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dummy = lambda: None
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dummy.__name__ = name
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return dec(dummy)
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#-----------------------------------------------------------------------------
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# Decorators for public use
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# Decorators to skip certain tests on specific platforms.
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skip_win32 = skipif(sys.platform == 'win32',
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"This test does not run under Windows")
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skip_linux = skipif(sys.platform.startswith('linux'),
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"This test does not run under Linux")
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skip_osx = skipif(sys.platform == 'darwin',"This test does not run under OS X")
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# Decorators to skip tests if not on specific platforms.
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skip_if_not_win32 = skipif(sys.platform != 'win32',
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"This test only runs under Windows")
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skip_if_not_linux = skipif(not sys.platform.startswith('linux'),
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"This test only runs under Linux")
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skip_if_not_osx = skipif(sys.platform != 'darwin',
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"This test only runs under OSX")
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_x11_skip_cond = (sys.platform not in ('darwin', 'win32') and
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os.environ.get('DISPLAY', '') == '')
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_x11_skip_msg = "Skipped under *nix when X11/XOrg not available"
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skip_if_no_x11 = skipif(_x11_skip_cond, _x11_skip_msg)
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# not a decorator itself, returns a dummy function to be used as setup
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def skip_file_no_x11(name):
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return decorated_dummy(skip_if_no_x11, name) if _x11_skip_cond else None
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# Other skip decorators
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# generic skip without module
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skip_without = lambda mod: skipif(module_not_available(mod), "This test requires %s" % mod)
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skipif_not_numpy = skip_without('numpy')
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skipif_not_matplotlib = skip_without('matplotlib')
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skipif_not_sympy = skip_without('sympy')
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skip_known_failure = knownfailureif(True,'This test is known to fail')
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known_failure_py3 = knownfailureif(sys.version_info[0] >= 3,
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'This test is known to fail on Python 3.')
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# A null 'decorator', useful to make more readable code that needs to pick
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# between different decorators based on OS or other conditions
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null_deco = lambda f: f
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# Some tests only run where we can use unicode paths. Note that we can't just
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# check os.path.supports_unicode_filenames, which is always False on Linux.
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try:
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f = tempfile.NamedTemporaryFile(prefix=u"tmp€")
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except UnicodeEncodeError:
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unicode_paths = False
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else:
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unicode_paths = True
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f.close()
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onlyif_unicode_paths = onlyif(unicode_paths, ("This test is only applicable "
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"where we can use unicode in filenames."))
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def onlyif_cmds_exist(*commands):
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"""
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Decorator to skip test when at least one of `commands` is not found.
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"""
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for cmd in commands:
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try:
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if not is_cmd_found(cmd):
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return skip("This test runs only if command '{0}' "
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"is installed".format(cmd))
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except ImportError as e:
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# is_cmd_found uses pywin32 on windows, which might not be available
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if sys.platform == 'win32' and 'pywin32' in e.message:
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return skip("This test runs only if pywin32 and command '{0}' "
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"is installed".format(cmd))
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raise e
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return null_deco
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