# License for code in this file that was taken from Python 2.5.

# PYTHON SOFTWARE FOUNDATION LICENSE VERSION 2

# --------------------------------------------

#

# 1. This LICENSE AGREEMENT is between the Python Software Foundation

# ("PSF"), and the Individual or Organization ("Licensee") accessing and

# otherwise using this software ("Python") in source or binary form and

# its associated documentation.

#

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# hereby grants Licensee a nonexclusive, royalty-free, world-wide

# license to reproduce, analyze, test, perform and/or display publicly,

# prepare derivative works, distribute, and otherwise use Python

# alone or in any derivative version, provided, however, that PSF's

# License Agreement and PSF's notice of copyright, i.e., "Copyright (c)

# 2001, 2002, 2003, 2004, 2005, 2006, 2007 Python Software Foundation;

# All Rights Reserved" are retained in Python alone or in any derivative

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# or incorporates Python or any part thereof, and wants to make

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def curry(_curried_func, *args, **kwargs):

    def _curried(*moreargs, **morekwargs):

        return _curried_func(*(args+moreargs), **dict(kwargs, **morekwargs))

    return _curried

### Begin from Python 2.5 functools.py ########################################

# Summary of changes made to the Python 2.5 code below:

#   * swapped ``partial`` for ``curry`` to maintain backwards-compatibility

#     in Django.

#   * Wrapped the ``setattr`` call in ``update_wrapper`` with a try-except

#     block to make it compatible with Python 2.3, which doesn't allow

#     assigning to ``__name__``.

# Copyright (c) 2001, 2002, 2003, 2004, 2005, 2006, 2007 Python Software Foundation.

# All Rights Reserved.

###############################################################################

# update_wrapper() and wraps() are tools to help write

# wrapper functions that can handle naive introspection

WRAPPER_ASSIGNMENTS = ('__module__', '__name__', '__doc__')

WRAPPER_UPDATES = ('__dict__',)

def update_wrapper(wrapper,

                   wrapped,

                   assigned = WRAPPER_ASSIGNMENTS,

                   updated = WRAPPER_UPDATES):

    """Update a wrapper function to look like the wrapped function

       wrapper is the function to be updated

       wrapped is the original function

       assigned is a tuple naming the attributes assigned directly

       from the wrapped function to the wrapper function (defaults to

       functools.WRAPPER_ASSIGNMENTS)

       updated is a tuple naming the attributes off the wrapper that

       are updated with the corresponding attribute from the wrapped

       function (defaults to functools.WRAPPER_UPDATES)

    """

    for attr in assigned:

        try:

            setattr(wrapper, attr, getattr(wrapped, attr))

        except TypeError: # Python 2.3 doesn't allow assigning to __name__.

            pass

    for attr in updated:

        getattr(wrapper, attr).update(getattr(wrapped, attr))

    # Return the wrapper so this can be used as a decorator via curry()

    return wrapper

def wraps(wrapped,

          assigned = WRAPPER_ASSIGNMENTS,

          updated = WRAPPER_UPDATES):

    """Decorator factory to apply update_wrapper() to a wrapper function

       Returns a decorator that invokes update_wrapper() with the decorated

       function as the wrapper argument and the arguments to wraps() as the

       remaining arguments. Default arguments are as for update_wrapper().

       This is a convenience function to simplify applying curry() to

       update_wrapper().

    """

    return curry(update_wrapper, wrapped=wrapped,

                 assigned=assigned, updated=updated)

### End from Python 2.5 functools.py ##########################################

def memoize(func, cache, num_args):

    """

    Wrap a function so that results for any argument tuple are stored in

    'cache'. Note that the args to the function must be usable as dictionary

    keys.

    Only the first num_args are considered when creating the key.

    """

    def wrapper(*args):

        mem_args = args[:num_args]

        if mem_args in cache:

            return cache[mem_args]

        result = func(*args)

        cache[mem_args] = result

        return result

    return wraps(func)(wrapper)

class Promise(object):

    """

    This is just a base class for the proxy class created in

    the closure of the lazy function. It can be used to recognize

    promises in code.

    """

    pass

def lazy(func, *resultclasses):

    """

    Turns any callable into a lazy evaluated callable. You need to give result

    classes or types -- at least one is needed so that the automatic forcing of

    the lazy evaluation code is triggered. Results are not memoized; the

    function is evaluated on every access.

    """

    class __proxy__(Promise):

        # This inner class encapsulates the code that should be evaluated

        # lazily. On calling of one of the magic methods it will force

        # the evaluation and store the result. Afterwards, the result

        # is delivered directly. So the result is memoized.

        def __init__(self, args, kw):

            self.__func = func

            self.__args = args

            self.__kw = kw

            self.__dispatch = {}

            for resultclass in resultclasses:

                self.__dispatch[resultclass] = {}

                for (k, v) in resultclass.__dict__.items():

                    setattr(self, k, self.__promise__(resultclass, k, v))

            self._delegate_str = str in resultclasses

            self._delegate_unicode = unicode in resultclasses

            assert not (self._delegate_str and self._delegate_unicode), "Cannot call lazy() with both str and unicode return types."

            if self._delegate_unicode:

                # Each call to lazy() makes a new __proxy__ object, so this

                # doesn't interfere with any other lazy() results.

                __proxy__.__unicode__ = __proxy__.__unicode_cast

            elif self._delegate_str:

                __proxy__.__str__ = __proxy__.__str_cast

        def __promise__(self, klass, funcname, func):

            # Builds a wrapper around some magic method and registers that magic

            # method for the given type and method name.

            def __wrapper__(*args, **kw):

                # Automatically triggers the evaluation of a lazy value and

                # applies the given magic method of the result type.

                res = self.__func(*self.__args, **self.__kw)

                return self.__dispatch[type(res)][funcname](res, *args, **kw)

            if klass not in self.__dispatch:

                self.__dispatch[klass] = {}

            self.__dispatch[klass][funcname] = func

            return __wrapper__

        def __unicode_cast(self):

            return self.__func(*self.__args, **self.__kw)

        def __str_cast(self):

            return str(self.__func(*self.__args, **self.__kw))

        def __cmp__(self, rhs):

            if self._delegate_str:

                s = str(self.__func(*self.__args, **self.__kw))

            elif self._delegate_unicode:

                s = unicode(self.__func(*self.__args, **self.__kw))

            else:

                s = self.__func(*self.__args, **self.__kw)

            if isinstance(rhs, Promise):

                return -cmp(rhs, s)

            else:

                return cmp(s, rhs)

        def __mod__(self, rhs):

            if self._delegate_str:

                return str(self) % rhs

            elif self._delegate_unicode:

                return unicode(self) % rhs

            else:

                raise AssertionError('__mod__ not supported for non-string types')

        def __deepcopy__(self, memo):

            # Instances of this class are effectively immutable. It's just a

            # collection of functions. So we don't need to do anything

            # complicated for copying.

            memo[id(self)] = self

            return self

    def __wrapper__(*args, **kw):

        # Creates the proxy object, instead of the actual value.

        return __proxy__(args, kw)

    return wraps(func)(__wrapper__)

def allow_lazy(func, *resultclasses):

    """

    A decorator that allows a function to be called with one or more lazy

    arguments. If none of the args are lazy, the function is evaluated

    immediately, otherwise a __proxy__ is returned that will evaluate the

    function when needed.

    """

    def wrapper(*args, **kwargs):

        for arg in list(args) + kwargs.values():

            if isinstance(arg, Promise):

                break

        else:

            return func(*args, **kwargs)

        return lazy(func, *resultclasses)(*args, **kwargs)

    return wraps(func)(wrapper)