Updated Michele Simionato's decorator.py module to 3.1.2.

I also moved it to external/decorator.py

IPython/external/decorator.py

@@ -0,0 +1,254 b''
+##########################     LICENCE     ###############################
+##
+##   Copyright (c) 2005, Michele Simionato
+##   All rights reserved.
+##
+##   Redistributions of source code must retain the above copyright 
+##   notice, this list of conditions and the following disclaimer.
+##   Redistributions in bytecode form must reproduce the above copyright
+##   notice, this list of conditions and the following disclaimer in
+##   the documentation and/or other materials provided with the
+##   distribution. 
+
+##   THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+##   "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+##   LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+##   A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
+##   HOLDERS OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
+##   INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
+##   BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS
+##   OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
+##   ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR
+##   TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE
+##   USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH
+##   DAMAGE.
+
+"""
+Decorator module, see http://pypi.python.org/pypi/decorator
+for the documentation.
+"""
+
+__all__ = ["decorator", "FunctionMaker", "partial",
+           "deprecated", "getinfo", "new_wrapper"]
+
+import os, sys, re, inspect, string, warnings
+try:
+    from functools import partial
+except ImportError: # for Python version < 2.5
+    class partial(object):
+        "A simple replacement of functools.partial"
+        def __init__(self, func, *args, **kw):
+            self.func = func
+            self.args = args                
+            self.keywords = kw
+        def __call__(self, *otherargs, **otherkw):
+            kw = self.keywords.copy()
+            kw.update(otherkw)
+            return self.func(*(self.args + otherargs), **kw)
+
+DEF = re.compile('\s*def\s*([_\w][_\w\d]*)\s*\(')
+
+# basic functionality
+class FunctionMaker(object):
+    """
+    An object with the ability to create functions with a given signature.
+    It has attributes name, doc, module, signature, defaults, dict and
+    methods update and make.
+    """
+    def __init__(self, func=None, name=None, signature=None,
+                 defaults=None, doc=None, module=None, funcdict=None):
+        if func:
+            # func can be a class or a callable, but not an instance method
+            self.name = func.__name__
+            if self.name == '<lambda>': # small hack for lambda functions
+                self.name = '_lambda_' 
+            self.doc = func.__doc__
+            self.module = func.__module__
+            if inspect.isfunction(func):
+                argspec = inspect.getargspec(func)
+                self.args, self.varargs, self.keywords, self.defaults = argspec
+                for i, arg in enumerate(self.args):
+                    setattr(self, 'arg%d' % i, arg)
+                self.signature = inspect.formatargspec(
+                    formatvalue=lambda val: "", *argspec)[1:-1]
+                self.dict = func.__dict__.copy()
+        if name:
+            self.name = name
+        if signature is not None:
+            self.signature = signature
+        if defaults:
+            self.defaults = defaults
+        if doc:
+            self.doc = doc
+        if module:
+            self.module = module
+        if funcdict:
+            self.dict = funcdict
+        # check existence required attributes
+        assert hasattr(self, 'name')
+        if not hasattr(self, 'signature'):
+            raise TypeError('You are decorating a non function: %s' % func)
+
+    def update(self, func, **kw):
+        "Update the signature of func with the data in self"
+        func.__name__ = self.name
+        func.__doc__ = getattr(self, 'doc', None)
+        func.__dict__ = getattr(self, 'dict', {})
+        func.func_defaults = getattr(self, 'defaults', ())
+        callermodule = sys._getframe(3).f_globals.get('__name__', '?')
+        func.__module__ = getattr(self, 'module', callermodule)
+        func.__dict__.update(kw)
+
+    def make(self, src_templ, evaldict=None, addsource=False, **attrs):
+        "Make a new function from a given template and update the signature"
+        src = src_templ % vars(self) # expand name and signature
+        evaldict = evaldict or {}
+        mo = DEF.match(src)
+        if mo is None:
+            raise SyntaxError('not a valid function template\n%s' % src)
+        name = mo.group(1) # extract the function name
+        reserved_names = set([name] + [
+            arg.strip(' *') for arg in self.signature.split(',')])
+        for n, v in evaldict.iteritems():
+            if n in reserved_names:
+                raise NameError('%s is overridden in\n%s' % (n, src))
+        if not src.endswith('\n'): # add a newline just for safety
+            src += '\n'
+        try:
+            code = compile(src, '<string>', 'single')
+            exec code in evaldict
+        except:
+            print >> sys.stderr, 'Error in generated code:'
+            print >> sys.stderr, src
+            raise
+        func = evaldict[name]
+        if addsource:
+            attrs['__source__'] = src
+        self.update(func, **attrs)
+        return func
+
+    @classmethod
+    def create(cls, obj, body, evaldict, defaults=None,
+               doc=None, module=None, addsource=True,**attrs):
+        """
+        Create a function from the strings name, signature and body.
+        evaldict is the evaluation dictionary. If addsource is true an attribute
+        __source__ is added to the result. The attributes attrs are added,
+        if any.
+        """
+        if isinstance(obj, str): # "name(signature)"
+            name, rest = obj.strip().split('(', 1)
+            signature = rest[:-1] #strip a right parens            
+            func = None
+        else: # a function
+            name = None
+            signature = None
+            func = obj
+        fun = cls(func, name, signature, defaults, doc, module)
+        ibody = '\n'.join('    ' + line for line in body.splitlines())
+        return fun.make('def %(name)s(%(signature)s):\n' + ibody, 
+                        evaldict, addsource, **attrs)
+  
+def decorator(caller, func=None):
+    """
+    decorator(caller) converts a caller function into a decorator;
+    decorator(caller, func) decorates a function using a caller.
+    """
+    if func is not None: # returns a decorated function
+        return FunctionMaker.create(
+            func, "return _call_(_func_, %(signature)s)",
+            dict(_call_=caller, _func_=func), undecorated=func)
+    else: # returns a decorator
+        if isinstance(caller, partial):
+            return partial(decorator, caller)
+        # otherwise assume caller is a function
+        f = inspect.getargspec(caller)[0][0] # first arg
+        return FunctionMaker.create(
+            '%s(%s)' % (caller.__name__, f), 
+            'return decorator(_call_, %s)' % f,
+            dict(_call_=caller, decorator=decorator), undecorated=caller,
+            doc=caller.__doc__, module=caller.__module__)
+
+###################### deprecated functionality #########################
+
+@decorator
+def deprecated(func, *args, **kw):
+    "A decorator for deprecated functions"
+    warnings.warn(
+        ('Calling the deprecated function %r\n'
+         'Downgrade to decorator 2.3 if you want to use this functionality')
+        % func.__name__, DeprecationWarning, stacklevel=3)
+    return func(*args, **kw)
+
+@deprecated
+def getinfo(func):
+    """
+    Returns an info dictionary containing:
+    - name (the name of the function : str)
+    - argnames (the names of the arguments : list)
+    - defaults (the values of the default arguments : tuple)
+    - signature (the signature : str)
+    - doc (the docstring : str)
+    - module (the module name : str)
+    - dict (the function __dict__ : str)
+    
+    >>> def f(self, x=1, y=2, *args, **kw): pass
+
+    >>> info = getinfo(f)
+
+    >>> info["name"]
+    'f'
+    >>> info["argnames"]
+    ['self', 'x', 'y', 'args', 'kw']
+    
+    >>> info["defaults"]
+    (1, 2)
+
+    >>> info["signature"]
+    'self, x, y, *args, **kw'
+    """
+    assert inspect.ismethod(func) or inspect.isfunction(func)
+    regargs, varargs, varkwargs, defaults = inspect.getargspec(func)
+    argnames = list(regargs)
+    if varargs:
+        argnames.append(varargs)
+    if varkwargs:
+        argnames.append(varkwargs)
+    signature = inspect.formatargspec(regargs, varargs, varkwargs, defaults,
+                                      formatvalue=lambda value: "")[1:-1]
+    return dict(name=func.__name__, argnames=argnames, signature=signature,
+                defaults = func.func_defaults, doc=func.__doc__,
+                module=func.__module__, dict=func.__dict__,
+                globals=func.func_globals, closure=func.func_closure)
+
+@deprecated
+def update_wrapper(wrapper, model, infodict=None):
+    "A replacement for functools.update_wrapper"
+    infodict = infodict or getinfo(model)
+    wrapper.__name__ = infodict['name']
+    wrapper.__doc__ = infodict['doc']
+    wrapper.__module__ = infodict['module']
+    wrapper.__dict__.update(infodict['dict'])
+    wrapper.func_defaults = infodict['defaults']
+    wrapper.undecorated = model
+    return wrapper
+
+@deprecated
+def new_wrapper(wrapper, model):
+    """
+    An improvement over functools.update_wrapper. The wrapper is a generic
+    callable object. It works by generating a copy of the wrapper with the 
+    right signature and by updating the copy, not the original.
+    Moreovoer, 'model' can be a dictionary with keys 'name', 'doc', 'module',
+    'dict', 'defaults'.
+    """
+    if isinstance(model, dict):
+        infodict = model
+    else: # assume model is a function
+        infodict = getinfo(model)
+    assert not '_wrapper_' in infodict["argnames"], (
+        '"_wrapper_" is a reserved argument name!')
+    src = "lambda %(signature)s: _wrapper_(%(signature)s)" % infodict
+    funcopy = eval(src, dict(_wrapper_=wrapper))
+    return update_wrapper(funcopy, model, infodict)
+

IPython/testing/decorators.py

@@ -1,254 +1,254 b''
 """Decorators for labeling 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 metadata such as function name, setup and
 teardown functions and so on - see nose.tools for more information.
 
 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.
 
 NOTE: This file contains IPython-specific decorators and imports the
 numpy.testing.decorators file, which we've copied verbatim.  Any of our own
 code will be added at the bottom if we end up extending this.
 """
 
 # Stdlib imports
 import inspect
 import sys
 
 # Third-party imports
 
 # This is Michele Simionato's decorator module, also kept verbatim.
-from decorator_msim import decorator, update_wrapper
+from IPython.external.decorator import decorator, update_wrapper
 
 # Grab the numpy-specific decorators which we keep in a file that we
 # occasionally update from upstream: decorators_numpy.py is an IDENTICAL copy
 # of numpy.testing.decorators.
 from decorators_numpy import *
 
 ##############################################################################
 # Local code begins
 
 # 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.
 
     :Parameters:
       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.
 
     :Keywords:
       ds : string
       An optional docstring for the resulting decorator.  If not given, a
       default docstring is auto-generated.
 
     :Returns:
       A decorator.
 
     :Examples:
 
     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
         
     # 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
     
     # Apply the user's docstring, or autogenerate a basic one
     if ds is None:
         ds = "Labels a test as %r." % label
     decor.__doc__ = ds
     
     return decor
 
 
 # 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
     ----------
     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.        
     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):
         # 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 callable(skip_condition):
             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 nose.SkipTest(get_msg(f,msg))
             else:
                 return f(*args, **kwargs) 
 
         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
             
         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.
 
     :Parameters:
       msg : string
         Optional message to be added.
 
     :Returns:
        decorator : function
          Decorator, which, when applied to a function, causes SkipTest
          to be raised, with the optional message added.
       """
 
     return skipif(True,msg)
 
 
 #-----------------------------------------------------------------------------
 # Utility functions for decorators
 def numpy_not_available():
     """Can numpy be imported?  Returns true if numpy does NOT import.
 
     This is used to make a decorator to skip tests that require numpy to be
     available, but delay the 'import numpy' to test execution time.
     """
     try:
         import numpy
         np_not_avail = False
     except ImportError:
         np_not_avail = True
 
     return np_not_avail
 
 #-----------------------------------------------------------------------------
 # Decorators for public use
 
 skip_doctest = make_label_dec('skip_doctest',
     """Decorator - mark a function or method for skipping its doctest.
 
     This decorator allows you to mark a function whose docstring you wish to
     omit from testing, while preserving the docstring for introspection, help,
     etc.""")                              
 
 # Decorators to skip certain tests on specific platforms.
 skip_win32 = skipif(sys.platform == 'win32',
                     "This test does not run under Windows")
 skip_linux = skipif(sys.platform == 'linux2',
                     "This test does not run under Linux")
 skip_osx = skipif(sys.platform == 'darwin',"This test does not run under OS X")
 
 
 # Decorators to skip tests if not on specific platforms.
 skip_if_not_win32 = skipif(sys.platform != 'win32',
                            "This test only runs under Windows")
 skip_if_not_linux = skipif(sys.platform != 'linux2',
                            "This test only runs under Linux")
 skip_if_not_osx = skipif(sys.platform != 'darwin',
                          "This test only runs under OSX")
 
 # Other skip decorators
 skipif_not_numpy = skipif(numpy_not_available,"This test requires numpy")
 
 skipknownfailure = skip('This test is known to fail')