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# 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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""" |
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Encapsulate a function call and act as a proxy for methods that are |
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called on the result of that function. The function is not evaluated |
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until one of the methods on the result is called. |
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""" |
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__dispatch = None |
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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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if self.__dispatch is None: |
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self.__prepare_class__() |
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def __prepare_class__(cls): |
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cls.__dispatch = {} |
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for resultclass in resultclasses: |
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cls.__dispatch[resultclass] = {} |
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for (k, v) in resultclass.__dict__.items(): |
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if hasattr(cls, k): |
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continue |
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setattr(cls, k, cls.__promise__(resultclass, k, v)) |
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cls._delegate_str = str in resultclasses |
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cls._delegate_unicode = unicode in resultclasses |
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assert not (cls._delegate_str and cls._delegate_unicode), "Cannot call lazy() with both str and unicode return types." |
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if cls._delegate_unicode: |
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cls.__unicode__ = cls.__unicode_cast |
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elif cls._delegate_str: |
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cls.__str__ = cls.__str_cast |
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__prepare_class__ = classmethod(__prepare_class__) |
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def __promise__(cls, 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__(self, *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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for t in type(res).mro(): |
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if t in self.__dispatch: |
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return self.__dispatch[t][funcname](res, *args, **kw) |
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raise TypeError("Lazy object returned unexpected type.") |
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if klass not in cls.__dispatch: |
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cls.__dispatch[klass] = {} |
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cls.__dispatch[klass][funcname] = func |
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return __wrapper__ |
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__promise__ = classmethod(__promise__) |
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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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