# 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

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# 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):

        """

        Encapsulate a function call and act as a proxy for methods that are

        called on the result of that function. The function is not evaluated

        until one of the methods on the result is called.

        """

        __dispatch = None

        def __init__(self, args, kw):

            self.__func = func

            self.__args = args

            self.__kw = kw

            if self.__dispatch is None:

                self.__prepare_class__()

        def __prepare_class__(cls):

            cls.__dispatch = {}

            for resultclass in resultclasses:

                cls.__dispatch[resultclass] = {}

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

                    if hasattr(cls, k):

                        continue

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

            cls._delegate_str = str in resultclasses

            cls._delegate_unicode = unicode in resultclasses

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

            if cls._delegate_unicode:

                cls.__unicode__ = cls.__unicode_cast

            elif cls._delegate_str:

                cls.__str__ = cls.__str_cast

        __prepare_class__ = classmethod(__prepare_class__)

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

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

            # method for the given type and method name.

            def __wrapper__(self, *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)

                for t in type(res).mro():

                    if t in self.__dispatch:

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

                raise TypeError("Lazy object returned unexpected type.")

            if klass not in cls.__dispatch:

                cls.__dispatch[klass] = {}

            cls.__dispatch[klass][funcname] = func

            return __wrapper__

        __promise__ = classmethod(__promise__)

        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)

class LazyObject(object):

    """

    A wrapper for another class that can be used to delay instantiation of the

    wrapped class.

    This is useful, for example, if the wrapped class needs to use Django

    settings at creation time: we want to permit it to be imported without

    accessing settings.

    """

    def __init__(self):

        self._wrapped = None

    def __getattr__(self, name):

        if self._wrapped is None:

            self._setup()

        if name == "__members__":

            # Used to implement dir(obj)

            return self._wrapped.get_all_members()

        return getattr(self._wrapped, name)

    def __setattr__(self, name, value):

        if name == "_wrapped":

            # Assign to __dict__ to avoid infinite __setattr__ loops.

            self.__dict__["_wrapped"] = value

        else:

            if self._wrapped is None:

                self._setup()

            setattr(self._wrapped, name, value)

    def _setup(self):

        """

        Must be implemented by subclasses to initialise the wrapped object.

        """

        raise NotImplementedError