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@@ -0,0 +1,254 b'' | |||
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1 | ########################## LICENCE ############################### | |
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2 | ## | |
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3 | ## Copyright (c) 2005, Michele Simionato | |
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4 | ## All rights reserved. | |
|
5 | ## | |
|
6 | ## Redistributions of source code must retain the above copyright | |
|
7 | ## notice, this list of conditions and the following disclaimer. | |
|
8 | ## Redistributions in bytecode form must reproduce the above copyright | |
|
9 | ## notice, this list of conditions and the following disclaimer in | |
|
10 | ## the documentation and/or other materials provided with the | |
|
11 | ## distribution. | |
|
12 | ||
|
13 | ## THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS | |
|
14 | ## "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT | |
|
15 | ## LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR | |
|
16 | ## A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT | |
|
17 | ## HOLDERS OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, | |
|
18 | ## INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, | |
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19 | ## BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS | |
|
20 | ## OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND | |
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21 | ## ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR | |
|
22 | ## TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE | |
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23 | ## USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH | |
|
24 | ## DAMAGE. | |
|
25 | ||
|
26 | """ | |
|
27 | Decorator module, see http://pypi.python.org/pypi/decorator | |
|
28 | for the documentation. | |
|
29 | """ | |
|
30 | ||
|
31 | __all__ = ["decorator", "FunctionMaker", "partial", | |
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32 | "deprecated", "getinfo", "new_wrapper"] | |
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33 | ||
|
34 | import os, sys, re, inspect, string, warnings | |
|
35 | try: | |
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36 | from functools import partial | |
|
37 | except ImportError: # for Python version < 2.5 | |
|
38 | class partial(object): | |
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39 | "A simple replacement of functools.partial" | |
|
40 | def __init__(self, func, *args, **kw): | |
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41 | self.func = func | |
|
42 | self.args = args | |
|
43 | self.keywords = kw | |
|
44 | def __call__(self, *otherargs, **otherkw): | |
|
45 | kw = self.keywords.copy() | |
|
46 | kw.update(otherkw) | |
|
47 | return self.func(*(self.args + otherargs), **kw) | |
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48 | ||
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49 | DEF = re.compile('\s*def\s*([_\w][_\w\d]*)\s*\(') | |
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50 | ||
|
51 | # basic functionality | |
|
52 | class FunctionMaker(object): | |
|
53 | """ | |
|
54 | An object with the ability to create functions with a given signature. | |
|
55 | It has attributes name, doc, module, signature, defaults, dict and | |
|
56 | methods update and make. | |
|
57 | """ | |
|
58 | def __init__(self, func=None, name=None, signature=None, | |
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59 | defaults=None, doc=None, module=None, funcdict=None): | |
|
60 | if func: | |
|
61 | # func can be a class or a callable, but not an instance method | |
|
62 | self.name = func.__name__ | |
|
63 | if self.name == '<lambda>': # small hack for lambda functions | |
|
64 | self.name = '_lambda_' | |
|
65 | self.doc = func.__doc__ | |
|
66 | self.module = func.__module__ | |
|
67 | if inspect.isfunction(func): | |
|
68 | argspec = inspect.getargspec(func) | |
|
69 | self.args, self.varargs, self.keywords, self.defaults = argspec | |
|
70 | for i, arg in enumerate(self.args): | |
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71 | setattr(self, 'arg%d' % i, arg) | |
|
72 | self.signature = inspect.formatargspec( | |
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73 | formatvalue=lambda val: "", *argspec)[1:-1] | |
|
74 | self.dict = func.__dict__.copy() | |
|
75 | if name: | |
|
76 | self.name = name | |
|
77 | if signature is not None: | |
|
78 | self.signature = signature | |
|
79 | if defaults: | |
|
80 | self.defaults = defaults | |
|
81 | if doc: | |
|
82 | self.doc = doc | |
|
83 | if module: | |
|
84 | self.module = module | |
|
85 | if funcdict: | |
|
86 | self.dict = funcdict | |
|
87 | # check existence required attributes | |
|
88 | assert hasattr(self, 'name') | |
|
89 | if not hasattr(self, 'signature'): | |
|
90 | raise TypeError('You are decorating a non function: %s' % func) | |
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91 | ||
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92 | def update(self, func, **kw): | |
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93 | "Update the signature of func with the data in self" | |
|
94 | func.__name__ = self.name | |
|
95 | func.__doc__ = getattr(self, 'doc', None) | |
|
96 | func.__dict__ = getattr(self, 'dict', {}) | |
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97 | func.func_defaults = getattr(self, 'defaults', ()) | |
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98 | callermodule = sys._getframe(3).f_globals.get('__name__', '?') | |
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99 | func.__module__ = getattr(self, 'module', callermodule) | |
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100 | func.__dict__.update(kw) | |
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101 | ||
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102 | def make(self, src_templ, evaldict=None, addsource=False, **attrs): | |
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103 | "Make a new function from a given template and update the signature" | |
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104 | src = src_templ % vars(self) # expand name and signature | |
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105 | evaldict = evaldict or {} | |
|
106 | mo = DEF.match(src) | |
|
107 | if mo is None: | |
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108 | raise SyntaxError('not a valid function template\n%s' % src) | |
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109 | name = mo.group(1) # extract the function name | |
|
110 | reserved_names = set([name] + [ | |
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111 | arg.strip(' *') for arg in self.signature.split(',')]) | |
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112 | for n, v in evaldict.iteritems(): | |
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113 | if n in reserved_names: | |
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114 | raise NameError('%s is overridden in\n%s' % (n, src)) | |
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115 | if not src.endswith('\n'): # add a newline just for safety | |
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116 | src += '\n' | |
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117 | try: | |
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118 | code = compile(src, '<string>', 'single') | |
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119 | exec code in evaldict | |
|
120 | except: | |
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121 | print >> sys.stderr, 'Error in generated code:' | |
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122 | print >> sys.stderr, src | |
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123 | raise | |
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124 | func = evaldict[name] | |
|
125 | if addsource: | |
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126 | attrs['__source__'] = src | |
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127 | self.update(func, **attrs) | |
|
128 | return func | |
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129 | ||
|
130 | @classmethod | |
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131 | def create(cls, obj, body, evaldict, defaults=None, | |
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132 | doc=None, module=None, addsource=True,**attrs): | |
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133 | """ | |
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134 | Create a function from the strings name, signature and body. | |
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135 | evaldict is the evaluation dictionary. If addsource is true an attribute | |
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136 | __source__ is added to the result. The attributes attrs are added, | |
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137 | if any. | |
|
138 | """ | |
|
139 | if isinstance(obj, str): # "name(signature)" | |
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140 | name, rest = obj.strip().split('(', 1) | |
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141 | signature = rest[:-1] #strip a right parens | |
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142 | func = None | |
|
143 | else: # a function | |
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144 | name = None | |
|
145 | signature = None | |
|
146 | func = obj | |
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147 | fun = cls(func, name, signature, defaults, doc, module) | |
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148 | ibody = '\n'.join(' ' + line for line in body.splitlines()) | |
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149 | return fun.make('def %(name)s(%(signature)s):\n' + ibody, | |
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150 | evaldict, addsource, **attrs) | |
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151 | ||
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152 | def decorator(caller, func=None): | |
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153 | """ | |
|
154 | decorator(caller) converts a caller function into a decorator; | |
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155 | decorator(caller, func) decorates a function using a caller. | |
|
156 | """ | |
|
157 | if func is not None: # returns a decorated function | |
|
158 | return FunctionMaker.create( | |
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159 | func, "return _call_(_func_, %(signature)s)", | |
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160 | dict(_call_=caller, _func_=func), undecorated=func) | |
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161 | else: # returns a decorator | |
|
162 | if isinstance(caller, partial): | |
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163 | return partial(decorator, caller) | |
|
164 | # otherwise assume caller is a function | |
|
165 | f = inspect.getargspec(caller)[0][0] # first arg | |
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166 | return FunctionMaker.create( | |
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167 | '%s(%s)' % (caller.__name__, f), | |
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168 | 'return decorator(_call_, %s)' % f, | |
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169 | dict(_call_=caller, decorator=decorator), undecorated=caller, | |
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170 | doc=caller.__doc__, module=caller.__module__) | |
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171 | ||
|
172 | ###################### deprecated functionality ######################### | |
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173 | ||
|
174 | @decorator | |
|
175 | def deprecated(func, *args, **kw): | |
|
176 | "A decorator for deprecated functions" | |
|
177 | warnings.warn( | |
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178 | ('Calling the deprecated function %r\n' | |
|
179 | 'Downgrade to decorator 2.3 if you want to use this functionality') | |
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180 | % func.__name__, DeprecationWarning, stacklevel=3) | |
|
181 | return func(*args, **kw) | |
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182 | ||
|
183 | @deprecated | |
|
184 | def getinfo(func): | |
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185 | """ | |
|
186 | Returns an info dictionary containing: | |
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187 | - name (the name of the function : str) | |
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188 | - argnames (the names of the arguments : list) | |
|
189 | - defaults (the values of the default arguments : tuple) | |
|
190 | - signature (the signature : str) | |
|
191 | - doc (the docstring : str) | |
|
192 | - module (the module name : str) | |
|
193 | - dict (the function __dict__ : str) | |
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194 | ||
|
195 | >>> def f(self, x=1, y=2, *args, **kw): pass | |
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196 | ||
|
197 | >>> info = getinfo(f) | |
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198 | ||
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199 | >>> info["name"] | |
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200 | 'f' | |
|
201 | >>> info["argnames"] | |
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202 | ['self', 'x', 'y', 'args', 'kw'] | |
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203 | ||
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204 | >>> info["defaults"] | |
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205 | (1, 2) | |
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206 | ||
|
207 | >>> info["signature"] | |
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208 | 'self, x, y, *args, **kw' | |
|
209 | """ | |
|
210 | assert inspect.ismethod(func) or inspect.isfunction(func) | |
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211 | regargs, varargs, varkwargs, defaults = inspect.getargspec(func) | |
|
212 | argnames = list(regargs) | |
|
213 | if varargs: | |
|
214 | argnames.append(varargs) | |
|
215 | if varkwargs: | |
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216 | argnames.append(varkwargs) | |
|
217 | signature = inspect.formatargspec(regargs, varargs, varkwargs, defaults, | |
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218 | formatvalue=lambda value: "")[1:-1] | |
|
219 | return dict(name=func.__name__, argnames=argnames, signature=signature, | |
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220 | defaults = func.func_defaults, doc=func.__doc__, | |
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221 | module=func.__module__, dict=func.__dict__, | |
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222 | globals=func.func_globals, closure=func.func_closure) | |
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223 | ||
|
224 | @deprecated | |
|
225 | def update_wrapper(wrapper, model, infodict=None): | |
|
226 | "A replacement for functools.update_wrapper" | |
|
227 | infodict = infodict or getinfo(model) | |
|
228 | wrapper.__name__ = infodict['name'] | |
|
229 | wrapper.__doc__ = infodict['doc'] | |
|
230 | wrapper.__module__ = infodict['module'] | |
|
231 | wrapper.__dict__.update(infodict['dict']) | |
|
232 | wrapper.func_defaults = infodict['defaults'] | |
|
233 | wrapper.undecorated = model | |
|
234 | return wrapper | |
|
235 | ||
|
236 | @deprecated | |
|
237 | def new_wrapper(wrapper, model): | |
|
238 | """ | |
|
239 | An improvement over functools.update_wrapper. The wrapper is a generic | |
|
240 | callable object. It works by generating a copy of the wrapper with the | |
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241 | right signature and by updating the copy, not the original. | |
|
242 | Moreovoer, 'model' can be a dictionary with keys 'name', 'doc', 'module', | |
|
243 | 'dict', 'defaults'. | |
|
244 | """ | |
|
245 | if isinstance(model, dict): | |
|
246 | infodict = model | |
|
247 | else: # assume model is a function | |
|
248 | infodict = getinfo(model) | |
|
249 | assert not '_wrapper_' in infodict["argnames"], ( | |
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250 | '"_wrapper_" is a reserved argument name!') | |
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251 | src = "lambda %(signature)s: _wrapper_(%(signature)s)" % infodict | |
|
252 | funcopy = eval(src, dict(_wrapper_=wrapper)) | |
|
253 | return update_wrapper(funcopy, model, infodict) | |
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254 |
@@ -1,254 +1,254 b'' | |||
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1 | 1 | """Decorators for labeling test objects. |
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2 | 2 | |
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3 | 3 | Decorators that merely return a modified version of the original function |
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4 | 4 | object are straightforward. Decorators that return a new function object need |
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5 | 5 | to use nose.tools.make_decorator(original_function)(decorator) in returning the |
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6 | 6 | decorator, in order to preserve metadata such as function name, setup and |
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7 | 7 | teardown functions and so on - see nose.tools for more information. |
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8 | 8 | |
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9 | 9 | This module provides a set of useful decorators meant to be ready to use in |
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10 | 10 | your own tests. See the bottom of the file for the ready-made ones, and if you |
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11 | 11 | find yourself writing a new one that may be of generic use, add it here. |
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12 | 12 | |
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13 | 13 | NOTE: This file contains IPython-specific decorators and imports the |
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14 | 14 | numpy.testing.decorators file, which we've copied verbatim. Any of our own |
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15 | 15 | code will be added at the bottom if we end up extending this. |
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16 | 16 | """ |
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17 | 17 | |
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18 | 18 | # Stdlib imports |
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19 | 19 | import inspect |
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20 | 20 | import sys |
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21 | 21 | |
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22 | 22 | # Third-party imports |
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23 | 23 | |
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24 | 24 | # This is Michele Simionato's decorator module, also kept verbatim. |
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25 |
from decorator |
|
|
25 | from IPython.external.decorator import decorator, update_wrapper | |
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26 | 26 | |
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27 | 27 | # Grab the numpy-specific decorators which we keep in a file that we |
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28 | 28 | # occasionally update from upstream: decorators_numpy.py is an IDENTICAL copy |
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29 | 29 | # of numpy.testing.decorators. |
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30 | 30 | from decorators_numpy import * |
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31 | 31 | |
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32 | 32 | ############################################################################## |
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33 | 33 | # Local code begins |
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34 | 34 | |
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35 | 35 | # Utility functions |
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36 | 36 | |
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37 | 37 | def apply_wrapper(wrapper,func): |
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38 | 38 | """Apply a wrapper to a function for decoration. |
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39 | 39 | |
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40 | 40 | This mixes Michele Simionato's decorator tool with nose's make_decorator, |
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41 | 41 | to apply a wrapper in a decorator so that all nose attributes, as well as |
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42 | 42 | function signature and other properties, survive the decoration cleanly. |
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43 | 43 | This will ensure that wrapped functions can still be well introspected via |
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44 | 44 | IPython, for example. |
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45 | 45 | """ |
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46 | 46 | import nose.tools |
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47 | 47 | |
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48 | 48 | return decorator(wrapper,nose.tools.make_decorator(func)(wrapper)) |
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49 | 49 | |
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50 | 50 | |
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51 | 51 | def make_label_dec(label,ds=None): |
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52 | 52 | """Factory function to create a decorator that applies one or more labels. |
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53 | 53 | |
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54 | 54 | :Parameters: |
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55 | 55 | label : string or sequence |
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56 | 56 | One or more labels that will be applied by the decorator to the functions |
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57 | 57 | it decorates. Labels are attributes of the decorated function with their |
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58 | 58 | value set to True. |
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59 | 59 | |
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60 | 60 | :Keywords: |
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61 | 61 | ds : string |
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62 | 62 | An optional docstring for the resulting decorator. If not given, a |
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63 | 63 | default docstring is auto-generated. |
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64 | 64 | |
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65 | 65 | :Returns: |
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66 | 66 | A decorator. |
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67 | 67 | |
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68 | 68 | :Examples: |
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69 | 69 | |
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70 | 70 | A simple labeling decorator: |
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71 | 71 | >>> slow = make_label_dec('slow') |
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72 | 72 | >>> print slow.__doc__ |
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73 | 73 | Labels a test as 'slow'. |
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74 | 74 | |
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75 | 75 | And one that uses multiple labels and a custom docstring: |
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76 | 76 | >>> rare = make_label_dec(['slow','hard'], |
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77 | 77 | ... "Mix labels 'slow' and 'hard' for rare tests.") |
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78 | 78 | >>> print rare.__doc__ |
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79 | 79 | Mix labels 'slow' and 'hard' for rare tests. |
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80 | 80 | |
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81 | 81 | Now, let's test using this one: |
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82 | 82 | >>> @rare |
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83 | 83 | ... def f(): pass |
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84 | 84 | ... |
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85 | 85 | >>> |
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86 | 86 | >>> f.slow |
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87 | 87 | True |
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88 | 88 | >>> f.hard |
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89 | 89 | True |
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90 | 90 | """ |
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91 | 91 | |
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92 | 92 | if isinstance(label,basestring): |
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93 | 93 | labels = [label] |
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94 | 94 | else: |
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95 | 95 | labels = label |
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96 | 96 | |
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97 | 97 | # Validate that the given label(s) are OK for use in setattr() by doing a |
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98 | 98 | # dry run on a dummy function. |
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99 | 99 | tmp = lambda : None |
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100 | 100 | for label in labels: |
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101 | 101 | setattr(tmp,label,True) |
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102 | 102 | |
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103 | 103 | # This is the actual decorator we'll return |
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104 | 104 | def decor(f): |
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105 | 105 | for label in labels: |
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106 | 106 | setattr(f,label,True) |
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107 | 107 | return f |
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108 | 108 | |
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109 | 109 | # Apply the user's docstring, or autogenerate a basic one |
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110 | 110 | if ds is None: |
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111 | 111 | ds = "Labels a test as %r." % label |
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112 | 112 | decor.__doc__ = ds |
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113 | 113 | |
|
114 | 114 | return decor |
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115 | 115 | |
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116 | 116 | |
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117 | 117 | # Inspired by numpy's skipif, but uses the full apply_wrapper utility to |
|
118 | 118 | # preserve function metadata better and allows the skip condition to be a |
|
119 | 119 | # callable. |
|
120 | 120 | def skipif(skip_condition, msg=None): |
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121 | 121 | ''' Make function raise SkipTest exception if skip_condition is true |
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122 | 122 | |
|
123 | 123 | Parameters |
|
124 | 124 | ---------- |
|
125 | 125 | skip_condition : bool or callable. |
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126 | 126 | Flag to determine whether to skip test. If the condition is a |
|
127 | 127 | callable, it is used at runtime to dynamically make the decision. This |
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128 | 128 | is useful for tests that may require costly imports, to delay the cost |
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129 | 129 | until the test suite is actually executed. |
|
130 | 130 | msg : string |
|
131 | 131 | Message to give on raising a SkipTest exception |
|
132 | 132 | |
|
133 | 133 | Returns |
|
134 | 134 | ------- |
|
135 | 135 | decorator : function |
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136 | 136 | Decorator, which, when applied to a function, causes SkipTest |
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137 | 137 | to be raised when the skip_condition was True, and the function |
|
138 | 138 | to be called normally otherwise. |
|
139 | 139 | |
|
140 | 140 | Notes |
|
141 | 141 | ----- |
|
142 | 142 | You will see from the code that we had to further decorate the |
|
143 | 143 | decorator with the nose.tools.make_decorator function in order to |
|
144 | 144 | transmit function name, and various other metadata. |
|
145 | 145 | ''' |
|
146 | 146 | |
|
147 | 147 | def skip_decorator(f): |
|
148 | 148 | # Local import to avoid a hard nose dependency and only incur the |
|
149 | 149 | # import time overhead at actual test-time. |
|
150 | 150 | import nose |
|
151 | 151 | |
|
152 | 152 | # Allow for both boolean or callable skip conditions. |
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153 | 153 | if callable(skip_condition): |
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154 | 154 | skip_val = lambda : skip_condition() |
|
155 | 155 | else: |
|
156 | 156 | skip_val = lambda : skip_condition |
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157 | 157 | |
|
158 | 158 | def get_msg(func,msg=None): |
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159 | 159 | """Skip message with information about function being skipped.""" |
|
160 | 160 | if msg is None: out = 'Test skipped due to test condition.' |
|
161 | 161 | else: out = msg |
|
162 | 162 | return "Skipping test: %s. %s" % (func.__name__,out) |
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163 | 163 | |
|
164 | 164 | # We need to define *two* skippers because Python doesn't allow both |
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165 | 165 | # return with value and yield inside the same function. |
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166 | 166 | def skipper_func(*args, **kwargs): |
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167 | 167 | """Skipper for normal test functions.""" |
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168 | 168 | if skip_val(): |
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169 | 169 | raise nose.SkipTest(get_msg(f,msg)) |
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170 | 170 | else: |
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171 | 171 | return f(*args, **kwargs) |
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172 | 172 | |
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173 | 173 | def skipper_gen(*args, **kwargs): |
|
174 | 174 | """Skipper for test generators.""" |
|
175 | 175 | if skip_val(): |
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176 | 176 | raise nose.SkipTest(get_msg(f,msg)) |
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177 | 177 | else: |
|
178 | 178 | for x in f(*args, **kwargs): |
|
179 | 179 | yield x |
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180 | 180 | |
|
181 | 181 | # Choose the right skipper to use when building the actual generator. |
|
182 | 182 | if nose.util.isgenerator(f): |
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183 | 183 | skipper = skipper_gen |
|
184 | 184 | else: |
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185 | 185 | skipper = skipper_func |
|
186 | 186 | |
|
187 | 187 | return nose.tools.make_decorator(f)(skipper) |
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188 | 188 | |
|
189 | 189 | return skip_decorator |
|
190 | 190 | |
|
191 | 191 | # A version with the condition set to true, common case just to attacha message |
|
192 | 192 | # to a skip decorator |
|
193 | 193 | def skip(msg=None): |
|
194 | 194 | """Decorator factory - mark a test function for skipping from test suite. |
|
195 | 195 | |
|
196 | 196 | :Parameters: |
|
197 | 197 | msg : string |
|
198 | 198 | Optional message to be added. |
|
199 | 199 | |
|
200 | 200 | :Returns: |
|
201 | 201 | decorator : function |
|
202 | 202 | Decorator, which, when applied to a function, causes SkipTest |
|
203 | 203 | to be raised, with the optional message added. |
|
204 | 204 | """ |
|
205 | 205 | |
|
206 | 206 | return skipif(True,msg) |
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207 | 207 | |
|
208 | 208 | |
|
209 | 209 | #----------------------------------------------------------------------------- |
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210 | 210 | # Utility functions for decorators |
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211 | 211 | def numpy_not_available(): |
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212 | 212 | """Can numpy be imported? Returns true if numpy does NOT import. |
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213 | 213 | |
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214 | 214 | This is used to make a decorator to skip tests that require numpy to be |
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215 | 215 | available, but delay the 'import numpy' to test execution time. |
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216 | 216 | """ |
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217 | 217 | try: |
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218 | 218 | import numpy |
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219 | 219 | np_not_avail = False |
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220 | 220 | except ImportError: |
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221 | 221 | np_not_avail = True |
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222 | 222 | |
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223 | 223 | return np_not_avail |
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224 | 224 | |
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225 | 225 | #----------------------------------------------------------------------------- |
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226 | 226 | # Decorators for public use |
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227 | 227 | |
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228 | 228 | skip_doctest = make_label_dec('skip_doctest', |
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229 | 229 | """Decorator - mark a function or method for skipping its doctest. |
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230 | 230 | |
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231 | 231 | This decorator allows you to mark a function whose docstring you wish to |
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232 | 232 | omit from testing, while preserving the docstring for introspection, help, |
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233 | 233 | etc.""") |
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234 | 234 | |
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235 | 235 | # Decorators to skip certain tests on specific platforms. |
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236 | 236 | skip_win32 = skipif(sys.platform == 'win32', |
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237 | 237 | "This test does not run under Windows") |
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238 | 238 | skip_linux = skipif(sys.platform == 'linux2', |
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239 | 239 | "This test does not run under Linux") |
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240 | 240 | skip_osx = skipif(sys.platform == 'darwin',"This test does not run under OS X") |
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241 | 241 | |
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242 | 242 | |
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243 | 243 | # Decorators to skip tests if not on specific platforms. |
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244 | 244 | skip_if_not_win32 = skipif(sys.platform != 'win32', |
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245 | 245 | "This test only runs under Windows") |
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246 | 246 | skip_if_not_linux = skipif(sys.platform != 'linux2', |
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247 | 247 | "This test only runs under Linux") |
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248 | 248 | skip_if_not_osx = skipif(sys.platform != 'darwin', |
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249 | 249 | "This test only runs under OSX") |
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250 | 250 | |
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251 | 251 | # Other skip decorators |
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252 | 252 | skipif_not_numpy = skipif(numpy_not_available,"This test requires numpy") |
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253 | 253 | |
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254 | 254 | skipknownfailure = skip('This test is known to fail') |
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