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import copy
import operator
from functools import total_ordering, wraps
from django.utils import six
# 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), **dict(kwargs, **morekwargs))
return _curried
class cached_property(object):
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__') = name or func.__name__
def __get__(self, instance, cls=None):
if instance is None:
return self
res = instance.__dict__[] = self.func(instance)
return res
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.
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.
__prepared = False
def __init__(self, args, kw):
self.__args = args
self.__kw = kw
if not self.__prepared:
self.__prepared = True
def __reduce__(self):
return (
(func, self.__args, self.__kw) + resultclasses
def __prepare_class__(cls):
for resultclass in resultclasses:
for type_ in resultclass.mro():
for method_name in type_.__dict__.keys():
# All __promise__ return the same wrapper method, they
# look up the correct implementation when called.
if hasattr(cls, method_name):
meth = cls.__promise__(method_name)
setattr(cls, method_name, meth)
cls._delegate_bytes = bytes in resultclasses
cls._delegate_text = six.text_type 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:
if six.PY3:
cls.__str__ = cls.__text_cast
cls.__unicode__ = cls.__text_cast
cls.__str__ = cls.__bytes_cast_encoded
elif cls._delegate_bytes:
if six.PY3:
cls.__bytes__ = cls.__bytes_cast
cls.__str__ = cls.__bytes_cast
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('utf-8')
def __cast(self):
if self._delegate_bytes:
return self.__bytes_cast()
elif self._delegate_text:
return self.__text_cast()
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 __ne__(self, other):
if isinstance(other, Promise):
other = other.__cast()
return self.__cast() != other
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_bytes and six.PY2:
return bytes(self) % rhs
elif self._delegate_text:
return six.text_type(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
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 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.
lazy_func = lazy(func, *resultclasses)
def wrapper(*args, **kwargs):
for arg in list(args) + list(kwargs.values()):
if isinstance(arg, Promise):
return func(*args, **kwargs)
return lazy_func(*args, **kwargs)
return wrapper
empty = object()
def new_method_proxy(func):
def inner(self, *args):
if self._wrapped is empty:
return func(self._wrapped, *args)
return inner
class LazyObject(object):
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):
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
if self._wrapped is empty:
setattr(self._wrapped, name, value)
def __delattr__(self, name):
if name == "_wrapped":
raise TypeError("can't delete _wrapped.")
if self._wrapped is empty:
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:
return (unpickle_lazyobject, (self._wrapped,))
# We have to explicitly override __getstate__ so that older versions of
# pickle don't try to pickle the __dict__ (which in the case of a
# SimpleLazyObject may contain a lambda). The value will end up being
# ignored by our __reduce__ and custom unpickler.
def __getstate__(self):
return {}
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)
if six.PY3:
__bytes__ = new_method_proxy(bytes)
__str__ = new_method_proxy(str)
__bool__ = new_method_proxy(bool)
__str__ = new_method_proxy(str)
__unicode__ = new_method_proxy(unicode) # NOQA: unicode undefined on PY3
__nonzero__ = 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(
__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
self.__dict__['_setupfunc'] = func
super(SimpleLazyObject, self).__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
repr_attr = self._wrapped
return '<%s: %r>' % (type(self).__name__, repr_attr)
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)
class lazy_property(property):
A property that works with subclasses by wrapping the decorated
functions of the base class.
def __new__(cls, fget=None, fset=None, fdel=None, doc=None):
if fget is not None:
def fget(instance, instance_type=None, name=fget.__name__):
return getattr(instance, name)()
if fset is not None:
def fset(instance, value, name=fset.__name__):
return getattr(instance, name)(value)
if fdel is not None:
def fdel(instance, name=fdel.__name__):
return getattr(instance, name)()
return property(fget, fset, fdel, doc)
def partition(predicate, values):
Splits 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:
return results
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