django1/django/utils/functional.py

# 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.
#
# 2. Subject to the terms and conditions of this License Agreement, PSF
# 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
# version prepared by Licensee.
#
# 3. In the event Licensee prepares a derivative work that is based on
# or incorporates Python or any part thereof, and wants to make
# the derivative work available to others as provided herein, then
# Licensee hereby agrees to include in any such work a brief summary of
# the changes made to Python.
#
# 4. PSF is making Python available to Licensee on an "AS IS"
# basis.  PSF MAKES NO REPRESENTATIONS OR WARRANTIES, EXPRESS OR
# IMPLIED.  BY WAY OF EXAMPLE, BUT NOT LIMITATION, PSF MAKES NO AND
# DISCLAIMS ANY REPRESENTATION OR WARRANTY OF MERCHANTABILITY OR FITNESS
# FOR ANY PARTICULAR PURPOSE OR THAT THE USE OF PYTHON WILL NOT
# INFRINGE ANY THIRD PARTY RIGHTS.
#
# 5. PSF SHALL NOT BE LIABLE TO LICENSEE OR ANY OTHER USERS OF PYTHON
# FOR ANY INCIDENTAL, SPECIAL, OR CONSEQUENTIAL DAMAGES OR LOSS AS
# A RESULT OF MODIFYING, DISTRIBUTING, OR OTHERWISE USING PYTHON,
# OR ANY DERIVATIVE THEREOF, EVEN IF ADVISED OF THE POSSIBILITY THEREOF.
#
# 6. This License Agreement will automatically terminate upon a material
# breach of its terms and conditions.
#
# 7. Nothing in this License Agreement shall be deemed to create any
# relationship of agency, partnership, or joint venture between PSF and
# Licensee.  This License Agreement does not grant permission to use PSF
# trademarks or trade name in a trademark sense to endorse or promote
# products or services of Licensee, or any third party.
#
# 8. By copying, installing or otherwise using Python, Licensee
# agrees to be bound by the terms and conditions of this License
# Agreement.


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)