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import copy
import operator
import sys
from functools import wraps
from django.utils import six
from django.utils.six.moves import copyreg
# 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, type=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 __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(six.itervalues(kwargs)):
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. It also appears to stop __reduce__ from being
# called. So, we define __getstate__ in a way that cooperates with the way
# that pickle interprets this class. This fails when the wrapped class is
# a builtin, but it is better than nothing.
def __getstate__(self):
if self._wrapped is empty:
return self._wrapped.__dict__
# Python 3.3 will call __reduce__ when pickling; this method is needed
# to serialize and deserialize correctly.
def __newobj__(cls, *args):
return cls.__new__(cls, *args)
def __reduce_ex__(self, proto):
if proto >= 2:
# On Py3, since the default protocol is 3, pickle uses the
# ``__newobj__`` method (& more efficient opcodes) for writing.
return (self.__newobj__, (self.__class__,), self.__getstate__())
# On Py2, the default protocol is 0 (for back-compat) & the above
# code fails miserably (see regression test). Instead, we return
# exactly what's returned if there's no ``__reduce__`` method at
# all.
return (copyreg._reconstructor, (self.__class__, object, None), self.__getstate__())
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)
__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)
# Dictionary methods support
__getitem__ = new_method_proxy(operator.getitem)
__setitem__ = new_method_proxy(operator.setitem)
__delitem__ = new_method_proxy(operator.delitem)
__len__ = new_method_proxy(len)
__contains__ = new_method_proxy(operator.contains)
# Workaround for
_super = super
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
if sys.version_info >= (2, 7, 2):
from functools import total_ordering
# For Python < 2.7.2. total_ordering in versions prior to 2.7.2 is buggy.
# See for details. For these versions use
# code borrowed from Python 2.7.3.
def total_ordering(cls):
"""Class decorator that fills in missing ordering methods"""
convert = {
'__lt__': [('__gt__', lambda self, other: not (self < other or self == other)),
('__le__', lambda self, other: self < other or self == other),
('__ge__', lambda self, other: not self < other)],
'__le__': [('__ge__', lambda self, other: not self <= other or self == other),
('__lt__', lambda self, other: self <= other and not self == other),
('__gt__', lambda self, other: not self <= other)],
'__gt__': [('__lt__', lambda self, other: not (self > other or self == other)),
('__ge__', lambda self, other: self > other or self == other),
('__le__', lambda self, other: not self > other)],
'__ge__': [('__le__', lambda self, other: (not self >= other) or self == other),
('__gt__', lambda self, other: self >= other and not self == other),
('__lt__', lambda self, other: not self >= other)]
roots = set(dir(cls)) & set(convert)
if not roots:
raise ValueError('must define at least one ordering operation: < > <= >=')
root = max(roots) # prefer __lt__ to __le__ to __gt__ to __ge__
for opname, opfunc in convert[root]:
if opname not in roots:
opfunc.__name__ = opname
opfunc.__doc__ = getattr(int, opname).__doc__
setattr(cls, opname, opfunc)
return cls
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