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decorators.py
344 lines | 11.3 KiB | text/x-python | PythonLexer
Thomas Kluyver
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r3904 # -*- coding: utf-8 -*-
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r1420 """Decorators for labeling test objects.
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r1848 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 metadata such as function name, setup and
teardown functions and so on - see nose.tools for more information.
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r1420
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r1721 This module provides a set of useful decorators meant to be ready to use in
your own tests. See the bottom of the file for the ready-made ones, and if you
find yourself writing a new one that may be of generic use, add it here.
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r2368 Included decorators:
Lightweight testing that remains unittest-compatible.
- @parametric, for parametric test support that is vastly easier to use than
nose's for debugging. With ours, if a test fails, the stack under inspection
is that of the test and not that of the test framework.
- An @as_unittest decorator can be used to tag any normal parameter-less
function as a unittest TestCase. Then, both nose and normal unittest will
recognize it as such. This will make it easier to migrate away from Nose if
we ever need/want to while maintaining very lightweight tests.
Paul Ivanov
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r3511 NOTE: This file contains IPython-specific decorators. Using the machinery in
IPython.external.decorators, we import either numpy.testing.decorators if numpy is
available, OR use equivalent code in IPython.external._decorators, which
we've copied verbatim from numpy.
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r2368
Authors
-------
- Fernando Perez <Fernando.Perez@berkeley.edu>
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r1420 """
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r2368 #-----------------------------------------------------------------------------
Matthias BUSSONNIER
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r5390 # Copyright (C) 2009-2011 The IPython Development Team
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r2368 #
# Distributed under the terms of the BSD License. The full license is in
# the file COPYING, distributed as part of this software.
#-----------------------------------------------------------------------------
#-----------------------------------------------------------------------------
# Imports
#-----------------------------------------------------------------------------
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r1420 # Stdlib imports
import inspect
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r1721 import sys
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r3903 import tempfile
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r2368 import unittest
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# Third-party imports
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r2368 # This is Michele Simionato's decorator module, kept verbatim.
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r4053 from IPython.external.decorator import decorator
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r1420
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r2368 # We already have python3-compliant code for parametric tests
if sys.version[0]=='2':
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r2436 from _paramtestpy2 import parametric, ParametricTestCase
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r2368 else:
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r2436 from _paramtestpy3 import parametric, ParametricTestCase
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r2368
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r2414 # Expose the unittest-driven decorators
from ipunittest import ipdoctest, ipdocstring
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r1420 # Grab the numpy-specific decorators which we keep in a file that we
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r2368 # occasionally update from upstream: decorators.py is a copy of
# numpy.testing.decorators, we expose all of it here.
from IPython.external.decorators import *
#-----------------------------------------------------------------------------
# Classes and functions
#-----------------------------------------------------------------------------
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r1420
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r2368 # Simple example of the basic idea
def as_unittest(func):
"""Decorator to make a simple function into a normal test via unittest."""
class Tester(unittest.TestCase):
def test(self):
func()
Tester.__name__ = func.__name__
return Tester
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# Utility functions
def apply_wrapper(wrapper,func):
"""Apply a wrapper to a function for decoration.
This mixes Michele Simionato's decorator tool with nose's make_decorator,
to apply a wrapper in a decorator so that all nose attributes, as well as
function signature and other properties, survive the decoration cleanly.
This will ensure that wrapped functions can still be well introspected via
IPython, for example.
"""
import nose.tools
return decorator(wrapper,nose.tools.make_decorator(func)(wrapper))
def make_label_dec(label,ds=None):
"""Factory function to create a decorator that applies one or more labels.
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r2368 Parameters
----------
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r1420 label : string or sequence
One or more labels that will be applied by the decorator to the functions
it decorates. Labels are attributes of the decorated function with their
value set to True.
ds : string
An optional docstring for the resulting decorator. If not given, a
default docstring is auto-generated.
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r2368 Returns
-------
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r1420 A decorator.
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r2368 Examples
--------
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r1420
A simple labeling decorator:
>>> slow = make_label_dec('slow')
>>> print slow.__doc__
Labels a test as 'slow'.
And one that uses multiple labels and a custom docstring:
>>> rare = make_label_dec(['slow','hard'],
... "Mix labels 'slow' and 'hard' for rare tests.")
>>> print rare.__doc__
Mix labels 'slow' and 'hard' for rare tests.
Now, let's test using this one:
>>> @rare
... def f(): pass
...
>>>
>>> f.slow
True
>>> f.hard
True
"""
if isinstance(label,basestring):
labels = [label]
else:
labels = label
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r1420 # Validate that the given label(s) are OK for use in setattr() by doing a
# dry run on a dummy function.
tmp = lambda : None
for label in labels:
setattr(tmp,label,True)
# This is the actual decorator we'll return
def decor(f):
for label in labels:
setattr(f,label,True)
return f
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r1420 # Apply the user's docstring, or autogenerate a basic one
if ds is None:
ds = "Labels a test as %r." % label
decor.__doc__ = ds
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r1420 return decor
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r1848 # Inspired by numpy's skipif, but uses the full apply_wrapper utility to
# preserve function metadata better and allows the skip condition to be a
# callable.
def skipif(skip_condition, msg=None):
''' Make function raise SkipTest exception if skip_condition is true
Parameters
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r1850 ----------
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r4872 skip_condition : bool or callable.
Flag to determine whether to skip test. 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.
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Update decorators and test scripts.
r1848 msg : string
Message to give on raising a SkipTest exception
Returns
-------
decorator : function
Decorator, which, when applied to a function, causes SkipTest
to be raised when the skip_condition was True, and the function
to be called normally otherwise.
Notes
-----
You will see from the code that we had to further decorate the
decorator with the nose.tools.make_decorator function in order to
transmit function name, and various other metadata.
'''
def skip_decorator(f):
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r4872 # Local import to avoid a hard nose dependency and only incur the
# import time overhead at actual test-time.
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r1848 import nose
# Allow for both boolean or callable skip conditions.
if callable(skip_condition):
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r2452 skip_val = skip_condition
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r1848 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 nose.SkipTest(get_msg(f,msg))
else:
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r4872 return f(*args, **kwargs)
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r1848
def skipper_gen(*args, **kwargs):
"""Skipper for test generators."""
if skip_val():
raise nose.SkipTest(get_msg(f,msg))
else:
for x in f(*args, **kwargs):
yield x
# Choose the right skipper to use when building the actual generator.
if nose.util.isgenerator(f):
skipper = skipper_gen
else:
skipper = skipper_func
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r1848 return nose.tools.make_decorator(f)(skipper)
return skip_decorator
# A version with the condition set to true, common case just to attacha message
# to a skip decorator
def skip(msg=None):
"""Decorator factory - mark a test function for skipping from test suite.
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r1721
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r2368 Parameters
----------
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r1560 msg : string
Optional message to be added.
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r1848
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r2368 Returns
-------
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r1848 decorator : function
Decorator, which, when applied to a function, causes SkipTest
to be raised, with the optional message added.
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r1560 """
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r1420
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r1848 return skipif(True,msg)
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r1505
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r1577
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r2452 def onlyif(condition, msg):
"""The reverse from skipif, see skipif for details."""
if callable(condition):
skip_condition = lambda : not condition()
else:
skip_condition = lambda : not condition
return skipif(skip_condition, msg)
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r1848 #-----------------------------------------------------------------------------
# Utility functions for decorators
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r3504 def module_not_available(module):
"""Can module be imported? Returns true if module does NOT import.
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r1577
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r3504 This is used to make a decorator to skip tests that require module to be
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r1848 available, but delay the 'import numpy' to test execution time.
"""
try:
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r3504 mod = __import__(module)
mod_not_avail = False
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r1848 except ImportError:
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r3504 mod_not_avail = True
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r1848
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r3505 return mod_not_avail
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r1848
#-----------------------------------------------------------------------------
# Decorators for public use
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r1721 # Decorators to skip certain tests on specific platforms.
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r1872 skip_win32 = skipif(sys.platform == 'win32',
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r1848 "This test does not run under Windows")
MinRK
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r4138 skip_linux = skipif(sys.platform.startswith('linux'),
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r1872 "This test does not run under Linux")
skip_osx = skipif(sys.platform == 'darwin',"This test does not run under OS X")
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r1848
Jorgen Stenarson
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r1803 # Decorators to skip tests if not on specific platforms.
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r1872 skip_if_not_win32 = skipif(sys.platform != 'win32',
"This test only runs under Windows")
MinRK
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r4138 skip_if_not_linux = skipif(not sys.platform.startswith('linux'),
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r1872 "This test only runs under Linux")
skip_if_not_osx = skipif(sys.platform != 'darwin',
"This test only runs under OSX")
# Other skip decorators
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r1848
MinRK
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r5146 # generic skip without module
skip_without = lambda mod: skipif(module_not_available(mod), "This test requires %s" % mod)
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r4788
MinRK
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r5146 skipif_not_numpy = skip_without('numpy')
skipif_not_matplotlib = skip_without('matplotlib')
skipif_not_sympy = skip_without('sympy')
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r3504
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r3511 skip_known_failure = knownfailureif(True,'This test is known to fail')
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r2461
Thomas Kluyver
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r5204 known_failure_py3 = knownfailureif(sys.version_info[0] >= 3,
'This test is known to fail on Python 3.')
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r2461 # A null 'decorator', useful to make more readable code that needs to pick
# between different decorators based on OS or other conditions
null_deco = lambda f: f
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r3903
# Some tests only run where we can use unicode paths. Note that we can't just
# check os.path.supports_unicode_filenames, which is always False on Linux.
try:
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r3904 f = tempfile.NamedTemporaryFile(prefix=u"tmp€")
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r3903 except UnicodeEncodeError:
unicode_paths = False
else:
unicode_paths = True
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r3904 f.close()
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r3903
onlyif_unicode_paths = onlyif(unicode_paths, ("This test is only applicable "
"where we can use unicode in filenames."))