242 lines
10 KiB
Python
242 lines
10 KiB
Python
# License for code in this file that was taken from Python 2.5.
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# PYTHON SOFTWARE FOUNDATION LICENSE VERSION 2
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# --------------------------------------------
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#
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# 1. This LICENSE AGREEMENT is between the Python Software Foundation
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# ("PSF"), and the Individual or Organization ("Licensee") accessing and
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# otherwise using this software ("Python") in source or binary form and
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# its associated documentation.
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#
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# 2. Subject to the terms and conditions of this License Agreement, PSF
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# hereby grants Licensee a nonexclusive, royalty-free, world-wide
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# license to reproduce, analyze, test, perform and/or display publicly,
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# prepare derivative works, distribute, and otherwise use Python
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# alone or in any derivative version, provided, however, that PSF's
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# License Agreement and PSF's notice of copyright, i.e., "Copyright (c)
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# 2001, 2002, 2003, 2004, 2005, 2006, 2007 Python Software Foundation;
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# All Rights Reserved" are retained in Python alone or in any derivative
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# version prepared by Licensee.
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#
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# 3. In the event Licensee prepares a derivative work that is based on
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# or incorporates Python or any part thereof, and wants to make
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# the derivative work available to others as provided herein, then
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# Licensee hereby agrees to include in any such work a brief summary of
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# the changes made to Python.
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#
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# 4. PSF is making Python available to Licensee on an "AS IS"
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# basis. PSF MAKES NO REPRESENTATIONS OR WARRANTIES, EXPRESS OR
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# IMPLIED. BY WAY OF EXAMPLE, BUT NOT LIMITATION, PSF MAKES NO AND
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# DISCLAIMS ANY REPRESENTATION OR WARRANTY OF MERCHANTABILITY OR FITNESS
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# FOR ANY PARTICULAR PURPOSE OR THAT THE USE OF PYTHON WILL NOT
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# INFRINGE ANY THIRD PARTY RIGHTS.
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#
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# 5. PSF SHALL NOT BE LIABLE TO LICENSEE OR ANY OTHER USERS OF PYTHON
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# FOR ANY INCIDENTAL, SPECIAL, OR CONSEQUENTIAL DAMAGES OR LOSS AS
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# A RESULT OF MODIFYING, DISTRIBUTING, OR OTHERWISE USING PYTHON,
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# OR ANY DERIVATIVE THEREOF, EVEN IF ADVISED OF THE POSSIBILITY THEREOF.
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#
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# 6. This License Agreement will automatically terminate upon a material
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# breach of its terms and conditions.
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#
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# 7. Nothing in this License Agreement shall be deemed to create any
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# relationship of agency, partnership, or joint venture between PSF and
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# Licensee. This License Agreement does not grant permission to use PSF
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# trademarks or trade name in a trademark sense to endorse or promote
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# products or services of Licensee, or any third party.
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#
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# 8. By copying, installing or otherwise using Python, Licensee
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# agrees to be bound by the terms and conditions of this License
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# Agreement.
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def curry(_curried_func, *args, **kwargs):
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def _curried(*moreargs, **morekwargs):
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return _curried_func(*(args+moreargs), **dict(kwargs, **morekwargs))
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return _curried
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### Begin from Python 2.5 functools.py ########################################
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# Summary of changes made to the Python 2.5 code below:
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# * swapped ``partial`` for ``curry`` to maintain backwards-compatibility
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# in Django.
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# * Wrapped the ``setattr`` call in ``update_wrapper`` with a try-except
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# block to make it compatible with Python 2.3, which doesn't allow
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# assigning to ``__name__``.
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# Copyright (c) 2001, 2002, 2003, 2004, 2005, 2006, 2007 Python Software Foundation.
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# All Rights Reserved.
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###############################################################################
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# update_wrapper() and wraps() are tools to help write
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# wrapper functions that can handle naive introspection
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WRAPPER_ASSIGNMENTS = ('__module__', '__name__', '__doc__')
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WRAPPER_UPDATES = ('__dict__',)
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def update_wrapper(wrapper,
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wrapped,
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assigned = WRAPPER_ASSIGNMENTS,
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updated = WRAPPER_UPDATES):
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"""Update a wrapper function to look like the wrapped function
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wrapper is the function to be updated
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wrapped is the original function
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assigned is a tuple naming the attributes assigned directly
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from the wrapped function to the wrapper function (defaults to
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functools.WRAPPER_ASSIGNMENTS)
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updated is a tuple naming the attributes off the wrapper that
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are updated with the corresponding attribute from the wrapped
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function (defaults to functools.WRAPPER_UPDATES)
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"""
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for attr in assigned:
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try:
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setattr(wrapper, attr, getattr(wrapped, attr))
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except TypeError: # Python 2.3 doesn't allow assigning to __name__.
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pass
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for attr in updated:
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getattr(wrapper, attr).update(getattr(wrapped, attr))
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# Return the wrapper so this can be used as a decorator via curry()
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return wrapper
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def wraps(wrapped,
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assigned = WRAPPER_ASSIGNMENTS,
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updated = WRAPPER_UPDATES):
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"""Decorator factory to apply update_wrapper() to a wrapper function
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Returns a decorator that invokes update_wrapper() with the decorated
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function as the wrapper argument and the arguments to wraps() as the
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remaining arguments. Default arguments are as for update_wrapper().
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This is a convenience function to simplify applying curry() to
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update_wrapper().
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"""
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return curry(update_wrapper, wrapped=wrapped,
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assigned=assigned, updated=updated)
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### End from Python 2.5 functools.py ##########################################
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def memoize(func, cache, num_args):
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"""
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Wrap a function so that results for any argument tuple are stored in
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'cache'. Note that the args to the function must be usable as dictionary
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keys.
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Only the first num_args are considered when creating the key.
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"""
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def wrapper(*args):
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mem_args = args[:num_args]
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if mem_args in cache:
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return cache[mem_args]
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result = func(*args)
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cache[mem_args] = result
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return result
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return wraps(func)(wrapper)
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class Promise(object):
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"""
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This is just a base class for the proxy class created in
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the closure of the lazy function. It can be used to recognize
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promises in code.
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"""
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pass
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def lazy(func, *resultclasses):
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"""
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Turns any callable into a lazy evaluated callable. You need to give result
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classes or types -- at least one is needed so that the automatic forcing of
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the lazy evaluation code is triggered. Results are not memoized; the
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function is evaluated on every access.
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"""
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class __proxy__(Promise):
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# This inner class encapsulates the code that should be evaluated
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# lazily. On calling of one of the magic methods it will force
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# the evaluation and store the result. Afterwards, the result
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# is delivered directly. So the result is memoized.
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def __init__(self, args, kw):
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self.__func = func
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self.__args = args
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self.__kw = kw
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self.__dispatch = {}
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for resultclass in resultclasses:
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self.__dispatch[resultclass] = {}
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for (k, v) in resultclass.__dict__.items():
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setattr(self, k, self.__promise__(resultclass, k, v))
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self._delegate_str = str in resultclasses
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self._delegate_unicode = unicode in resultclasses
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assert not (self._delegate_str and self._delegate_unicode), "Cannot call lazy() with both str and unicode return types."
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if self._delegate_unicode:
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# Each call to lazy() makes a new __proxy__ object, so this
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# doesn't interfere with any other lazy() results.
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__proxy__.__unicode__ = __proxy__.__unicode_cast
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elif self._delegate_str:
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__proxy__.__str__ = __proxy__.__str_cast
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def __promise__(self, klass, funcname, func):
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# Builds a wrapper around some magic method and registers that magic
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# method for the given type and method name.
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def __wrapper__(*args, **kw):
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# Automatically triggers the evaluation of a lazy value and
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# applies the given magic method of the result type.
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res = self.__func(*self.__args, **self.__kw)
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return self.__dispatch[type(res)][funcname](res, *args, **kw)
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if klass not in self.__dispatch:
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self.__dispatch[klass] = {}
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self.__dispatch[klass][funcname] = func
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return __wrapper__
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def __unicode_cast(self):
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return self.__func(*self.__args, **self.__kw)
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def __str_cast(self):
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return str(self.__func(*self.__args, **self.__kw))
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def __cmp__(self, rhs):
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if self._delegate_str:
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s = str(self.__func(*self.__args, **self.__kw))
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elif self._delegate_unicode:
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s = unicode(self.__func(*self.__args, **self.__kw))
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else:
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s = self.__func(*self.__args, **self.__kw)
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if isinstance(rhs, Promise):
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return -cmp(rhs, s)
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else:
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return cmp(s, rhs)
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def __mod__(self, rhs):
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if self._delegate_str:
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return str(self) % rhs
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elif self._delegate_unicode:
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return unicode(self) % rhs
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else:
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raise AssertionError('__mod__ not supported for non-string types')
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def __deepcopy__(self, memo):
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# Instances of this class are effectively immutable. It's just a
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# collection of functions. So we don't need to do anything
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# complicated for copying.
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memo[id(self)] = self
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return self
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def __wrapper__(*args, **kw):
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# Creates the proxy object, instead of the actual value.
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return __proxy__(args, kw)
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return wraps(func)(__wrapper__)
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def allow_lazy(func, *resultclasses):
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"""
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A decorator that allows a function to be called with one or more lazy
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arguments. If none of the args are lazy, the function is evaluated
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immediately, otherwise a __proxy__ is returned that will evaluate the
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function when needed.
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"""
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def wrapper(*args, **kwargs):
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for arg in list(args) + kwargs.values():
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if isinstance(arg, Promise):
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break
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else:
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return func(*args, **kwargs)
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return lazy(func, *resultclasses)(*args, **kwargs)
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return wraps(func)(wrapper)
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