# Django 2.1.8.dev20190330215650 documentation

# Source code for django.utils.functional

    import copy
    import itertools
    import operator
    from functools import total_ordering, wraps

    # You can't trivially replace this with `functools.partial` because this binds
    # to classes and returns bound instances, whereas functools.partial (on
    # CPython) is a type and its instances don't bind.
    def curry(_curried_func, *args, **kwargs):
        def _curried(*moreargs, **morekwargs):
            return _curried_func(*args, *moreargs, **{**kwargs, **morekwargs})
        return _curried

    class cached_property:
        """
        Decorator that converts a method with a single self argument into a
        property cached on the instance.

        Optional ``name`` argument allows you to make cached properties of other
        methods. (e.g.  url = cached_property(get_absolute_url, name='url') )
        """
        def __init__(self, func, name=None):
            self.func = func
            self.__doc__ = getattr(func, '__doc__')
            self.name = name or func.__name__

        def __get__(self, instance, cls=None):
            """
            Call the function and put the return value in instance.__dict__ so that
            subsequent attribute access on the instance returns the cached value
            instead of calling cached_property.__get__().
            """
            if instance is None:
                return self
            res = instance.__dict__[self.name] = self.func(instance)
            return res

    class Promise:
        """
        Base class for the proxy class created in the closure of the lazy function.
        It's used to recognize promises in code.
        """
        pass

    def lazy(func, *resultclasses):
        """
        Turn any callable into a lazy evaluated callable. result classes or types
        is required -- 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.
        """

        @total_ordering
        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.
            """
            __prepared = False

            def __init__(self, args, kw):
                self.__args = args
                self.__kw = kw
                if not self.__prepared:
                    self.__prepare_class__()
                self.__prepared = True

            def __reduce__(self):
                return (
                    _lazy_proxy_unpickle,
                    (func, self.__args, self.__kw) + resultclasses
                )

            def __repr__(self):
                return repr(self.__cast())

            @classmethod
            def __prepare_class__(cls):
                for resultclass in resultclasses:
                    for type_ in resultclass.mro():
                        for method_name in type_.__dict__:
                            # All __promise__ return the same wrapper method, they
                            # look up the correct implementation when called.
                            if hasattr(cls, method_name):
                                continue
                            meth = cls.__promise__(method_name)
                            setattr(cls, method_name, meth)
                cls._delegate_bytes = bytes in resultclasses
                cls._delegate_text = str in resultclasses
                assert not (cls._delegate_bytes and cls._delegate_text), (
                    "Cannot call lazy() with both bytes and text return types.")
                if cls._delegate_text:
                    cls.__str__ = cls.__text_cast
                elif cls._delegate_bytes:
                    cls.__bytes__ = cls.__bytes_cast

            @classmethod
            def __promise__(cls, method_name):
                # Builds a wrapper around some magic method
                def __wrapper__(self, *args, **kw):
                    # Automatically triggers the evaluation of a lazy value and
                    # applies the given magic method of the result type.
                    res = func(*self.__args, **self.__kw)
                    return getattr(res, method_name)(*args, **kw)
                return __wrapper__

            def __text_cast(self):
                return func(*self.__args, **self.__kw)

            def __bytes_cast(self):
                return bytes(func(*self.__args, **self.__kw))

            def __bytes_cast_encoded(self):
                return func(*self.__args, **self.__kw).encode()

            def __cast(self):
                if self._delegate_bytes:
                    return self.__bytes_cast()
                elif self._delegate_text:
                    return self.__text_cast()
                else:
                    return func(*self.__args, **self.__kw)

            def __str__(self):
                # object defines __str__(), so __prepare_class__() won't overload
                # a __str__() method from the proxied class.
                return str(self.__cast())

            def __eq__(self, other):
                if isinstance(other, Promise):
                    other = other.__cast()
                return self.__cast() == other

            def __lt__(self, other):
                if isinstance(other, Promise):
                    other = other.__cast()
                return self.__cast() < other

            def __hash__(self):
                return hash(self.__cast())

            def __mod__(self, rhs):
                if self._delegate_text:
                    return str(self) % rhs
                return self.__cast() % rhs

            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

        @wraps(func)
        def __wrapper__(*args, **kw):
            # Creates the proxy object, instead of the actual value.
            return __proxy__(args, kw)

        return __wrapper__

    def _lazy_proxy_unpickle(func, args, kwargs, *resultclasses):
        return lazy(func, *resultclasses)(*args, **kwargs)

    def lazystr(text):
        """
        Shortcut for the common case of a lazy callable that returns str.
        """
        return lazy(str, str)(text)

    def keep_lazy(*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.
        """
        if not resultclasses:
            raise TypeError("You must pass at least one argument to keep_lazy().")

        def decorator(func):
            lazy_func = lazy(func, *resultclasses)

            @wraps(func)
            def wrapper(*args, **kwargs):
                if any(isinstance(arg, Promise) for arg in itertools.chain(args, kwargs.values())):
                    return lazy_func(*args, **kwargs)
                return func(*args, **kwargs)
            return wrapper
        return decorator

    def keep_lazy_text(func):
        """
        A decorator for functions that accept lazy arguments and return text.
        """
        return keep_lazy(str)(func)

    empty = object()

    def new_method_proxy(func):
        def inner(self, *args):
            if self._wrapped is empty:
                self._setup()
            return func(self._wrapped, *args)
        return inner

    class LazyObject:
        """
        A wrapper for another class that can be used to delay instantiation of the
        wrapped class.

        By subclassing, you have the opportunity to intercept and alter the
        instantiation. If you don't need to do that, use SimpleLazyObject.
        """

        # Avoid infinite recursion when tracing __init__ (#19456).
        _wrapped = None

        def __init__(self):
            # Note: if a subclass overrides __init__(), it will likely need to
            # override __copy__() and __deepcopy__() as well.
            self._wrapped = empty

        __getattr__ = new_method_proxy(getattr)

        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 empty:
                    self._setup()
                setattr(self._wrapped, name, value)

        def __delattr__(self, name):
            if name == "_wrapped":
                raise TypeError("can't delete _wrapped.")
            if self._wrapped is empty:
                self._setup()
            delattr(self._wrapped, name)

        def _setup(self):
            """
            Must be implemented by subclasses to initialize the wrapped object.
            """
            raise NotImplementedError('subclasses of LazyObject must provide a _setup() method')

        # Because we have messed with __class__ below, we confuse pickle as to what
        # class we are pickling. We're going to have to initialize the wrapped
        # object to successfully pickle it, so we might as well just pickle the
        # wrapped object since they're supposed to act the same way.
        #
        # Unfortunately, if we try to simply act like the wrapped object, the ruse
        # will break down when pickle gets our id(). Thus we end up with pickle
        # thinking, in effect, that we are a distinct object from the wrapped
        # object, but with the same __dict__. This can cause problems (see #25389).
        #
        # So instead, we define our own __reduce__ method and custom unpickler. We
        # pickle the wrapped object as the unpickler's argument, so that pickle
        # will pickle it normally, and then the unpickler simply returns its
        # argument.
        def __reduce__(self):
            if self._wrapped is empty:
                self._setup()
            return (unpickle_lazyobject, (self._wrapped,))

        def __copy__(self):
            if self._wrapped is empty:
                # If uninitialized, copy the wrapper. Use type(self), not
                # self.__class__, because the latter is proxied.
                return type(self)()
            else:
                # If initialized, return a copy of the wrapped object.
                return copy.copy(self._wrapped)

        def __deepcopy__(self, memo):
            if self._wrapped is empty:
                # We have to use type(self), not self.__class__, because the
                # latter is proxied.
                result = type(self)()
                memo[id(self)] = result
                return result
            return copy.deepcopy(self._wrapped, memo)

        __bytes__ = new_method_proxy(bytes)
        __str__ = new_method_proxy(str)
        __bool__ = new_method_proxy(bool)

        # Introspection support
        __dir__ = new_method_proxy(dir)

        # Need to pretend to be the wrapped class, for the sake of objects that
        # care about this (especially in equality tests)
        __class__ = property(new_method_proxy(operator.attrgetter("__class__")))
        __eq__ = new_method_proxy(operator.eq)
        __ne__ = new_method_proxy(operator.ne)
        __hash__ = new_method_proxy(hash)

        # List/Tuple/Dictionary methods support
        __getitem__ = new_method_proxy(operator.getitem)
        __setitem__ = new_method_proxy(operator.setitem)
        __delitem__ = new_method_proxy(operator.delitem)
        __iter__ = new_method_proxy(iter)
        __len__ = new_method_proxy(len)
        __contains__ = new_method_proxy(operator.contains)

    def unpickle_lazyobject(wrapped):
        """
        Used to unpickle lazy objects. Just return its argument, which will be the
        wrapped object.
        """
        return wrapped

    class SimpleLazyObject(LazyObject):
        """
        A lazy object initialized from any function.

        Designed for compound objects of unknown type. For builtins or objects of
        known type, use django.utils.functional.lazy.
        """
        def __init__(self, func):
            """
            Pass in a callable that returns the object to be wrapped.

            If copies are made of the resulting SimpleLazyObject, which can happen
            in various circumstances within Django, then you must ensure that the
            callable can be safely run more than once and will return the same
            value.
            """
            self.__dict__['_setupfunc'] = func
            super().__init__()

        def _setup(self):
            self._wrapped = self._setupfunc()

        # Return a meaningful representation of the lazy object for debugging
        # without evaluating the wrapped object.
        def __repr__(self):
            if self._wrapped is empty:
                repr_attr = self._setupfunc
            else:
                repr_attr = self._wrapped
            return '<%s: %r>' % (type(self).__name__, repr_attr)

        def __copy__(self):
            if self._wrapped is empty:
                # If uninitialized, copy the wrapper. Use SimpleLazyObject, not
                # self.__class__, because the latter is proxied.
                return SimpleLazyObject(self._setupfunc)
            else:
                # If initialized, return a copy of the wrapped object.
                return copy.copy(self._wrapped)

        def __deepcopy__(self, memo):
            if self._wrapped is empty:
                # We have to use SimpleLazyObject, not self.__class__, because the
                # latter is proxied.
                result = SimpleLazyObject(self._setupfunc)
                memo[id(self)] = result
                return result
            return copy.deepcopy(self._wrapped, memo)

    def partition(predicate, values):
        """
        Split the values into two sets, based on the return value of the function
        (True/False). e.g.:

            >>> partition(lambda x: x > 3, range(5))
            [0, 1, 2, 3], [4]
        """
        results = ([], [])
        for item in values:
            results[predicate(item)].append(item)
        return results