how to cache object using pickle in __new__ method? - python

I'd like to cache an object in __new__ method so that it can load the cache when a new object is constructed, but now the following code will got an exception:
RecursionError: maximum recursion depth exceeded while calling a Python object
I have no idea about how to break the recursion
import pickle
class Cache:
def __init__(self):
self.d = {}
def __setitem__(self, obj, val):
self.d[obj] = pickle.dumps(val)
def __getitem__(self, obj):
return pickle.loads(self.d[obj])
class Car:
cache = Cache()
def __reduce__(self):
return (self.__class__, (self.name,))
def __new__(cls, name):
try:
return cls.cache[name]
except KeyError:
return cls.new(name)
#classmethod
def new(cls, name):
car = object.__new__(cls)
car.init(name)
cls.cache[name] = car
return car
def init(self, name):
self.name = name
def __repr__(self):
return self.name
a = Car('audi')
b = Car('audi')

Have a try. This may fix this, but it may not be the proper solution. If anyone have any better idea, feel free to leave comments.
Just remove the __reduce__ method.
Then implement __getnewargs__ and __getnewargs_ex__
import pickle
class Cache:
def __init__(self):
self.d = {}
def __setitem__(self, obj, val):
self.d[obj] = pickle.dumps(val)
def __getitem__(self, obj):
return pickle.loads(self.d[obj])
def __contains__(self, x):
return x in self.d
class Car:
cache = Cache()
def __new__(cls, name, extra=None, _FORCE_CREATE=False):
if _FORCE_CREATE or name not in cls.cache:
car = object.__new__(cls)
car.init(name)
car.extra = extra
cls.cache[name] = car
return car
else:
return cls.cache[name]
def init(self, name):
self.name = name
def __repr__(self):
return self.name
def __getnewargs__(self):
return (self.name, None, True)
def __getnewargs_ex__(self):
# override __getnewargs_ex__ and __getnewargs__ to provide args for __new__
return (self.name, ), {"_FORCE_CREATE": True}
a = Car('audi', extra="extra_attr")
b = Car('audi')
print(id(a), a.extra) # 1921399938016 extra_attr
print(id(b), b.extra) # 1921399937728 extra_attr

Related

Python bypassing #property getter methods ambiguity

I know that this is a badly written code. But why does this behave this way?
class A:
def __init__(self, f, l):
self.first = f
self.last = l
#property
def first(self):
return self._first
#first.setter
def first(self, new):
self._first = new
a = A("ab", "cd")
print(a.first)
Why does this return "ab"? Shouldn't the #property getter method be invoked on a.first and raise an attribute error?

Ignore adapter creation when adaptee already of correct type

I have the following setup:
class Target(Base):
def __init__(name: str):
self.name = name
class Adapter(Target):
def __init__(self, adaptee: Base, name: str):
super().__init__(name=name)
self.adaptee = adaptee
def as_target(adaptee: Base, name: str):
if isinstance(adaptee, Target):
return adaptee
else:
return Adapter(adaptee, name)
I am wondering if I could get rid of as_target function and instead handle the logic on adapter creation.
Semantically, it would have the following meaning:
class Adapter(Target):
def __init__(self, adaptee: Base, name: str):
if isinstance(adaptee, Target):
self = adaptee
else:
super().__init__(name=name)
self.adaptee = adaptee
I've tried playing around with overriding __new__ but I wasn't able to make it work.
class Base:
pass
class Target(Base):
def __init__(self, name: str):
self.name = name
def __repr__(self):
return "{}({})".format(type(self).__name__, repr(self.name))
class Adapter(Target):
def __new__(cls, adaptee: Base, name: str):
if isinstance(adaptee, Target):
return adaptee
else:
return super().__new__(cls)
def __init__(self, adaptee: Base, name: str):
super().__init__(name=name)
self.adaptee = adaptee
print(Adapter(Base(), "a")) # Adapter('a')
print(Adapter(Target("b"), "c")) # Target('b')

Property setter not working in Python class

I am using a class (MainClass) over which I have no control. I want to base my class on MainClass but to add extra functionality. I have added an attribute (index) to my class (SuperClass), but when I try convert index to a property, the #.setter seems to be ignored. What is wrong here?
class MainClass(object):
def __init__(self):
self.name = 'abc'
class SuperClass(object):
def __init__(self, main, *args, **kwargs):
super(SuperClass, self).__init__(*args, **kwargs)
self.__main = main
self._index = 0
def __getattr__(self, attr):
return getattr(self.__main, attr)
def __setattr__(self, attr, val):
if attr == '_SuperClass__main':
object.__setattr__(self, attr, val)
return setattr(self.__main, attr, val)
#property
def index(self):
return self._index
#index.setter
def index(self, value):
self._index = value
main_object = MainClass()
super_object = SuperClass(main_object)
print('x', super_object.index, super_object.name)
super_object.index = 3
print('y', super_object.index)
super_object.index += 2
print('z', super_object.index)
__getattr__ is only used when the normal lookup mechanism fails.
__setattr__, however, is called for all attempts to set an attribute. This means your current definition creates an attribute named index on the
MainClass instance, rather than accessing the property's setter.
>>> super_object._SuperClass__main.index
2
Because __setattr__ always calls setattr(self.__main, attr, val), += is effectively treated as =.
__setattr__ has to handle three cases:
The attribute _SuperClass__main itself, for when you assign to self.__main in __init__.
Assignments to attributes that exist on self.__main
Assignments to attributes specific to SuperClass.
With that in mind, try
def __setattr__(self, attr, val):
if attr == '_SuperClass__main':
super().__setattr__(attr, val)
elif hasattr(self.__main, attr):
setattr(self.__main, attr, val)
else:
super().__setattr__(attr, val)
The __setattr__ method you have defined is taking precedence over the #index.setter
Simplify the code and it should work:
class MainClass(object):
def __init__(self):
self.name = 'abc'
class SuperClass(object):
def __init__(self, main, *args, **kwargs):
super(SuperClass, self).__init__(*args, **kwargs)
self.__main = main
self._index = 0
#property
def name(self):
return self.__main.name
#name.setter
def name(self):
return self.__main.name
#property
def index(self):
return self._index
#index.setter
def index(self, value):
self._index = value
main_object = MainClass()
super_object = SuperClass(main_object)
print('x', super_object.index, super_object.name)
super_object.index = 3
print('y', super_object.index)
super_object.index += 2
print('z', super_object.index)
Output:
x 0 abc
y 3
z 5
I would also suggest the simpler option of just inheriting from MainClass instead of using composition and delegation:
class SuperClass(MainClass):
def __init__(self):
super().__init__()
self._index = 0
#property
def index(self):
return self._index
#index.setter
def index(self, value):
self._index = value

How to cancel class decorators in constructor

Lets take the following example of class decorators (origin http://www.informit.com/articles/article.aspx?p=1309289&seqNum=4):
class GenericDescriptor:
def __init__(self, getter, setter):
self.getter = getter
self.setter = setter
def __get__(self, instance, owner=None):
if instance is None:
return self
return self.getter(instance)
def __set__(self, instance, value):
return self.setter(instance, value)
def valid_string(attr_name, empty_allowed=True, regex=None,
acceptable=None):
def decorator(cls):
name = "__" + attr_name
def getter(self):
return getattr(self, name)
def setter(self, value):
assert isinstance(value, str), (attr_name +
" must be a string")
if not empty_allowed and not value:
raise ValueError("{0} may not be empty".format(
attr_name))
if ((acceptable is not None and value not in acceptable) or
(regex is not None and not regex.match(value))):
raise ValueError("{attr_name} cannot be set to "
"{value}".format(**locals()))
setattr(self, name, value)
setattr(cls, attr_name, GenericDescriptor(getter, setter))
return cls
return decorator
#valid_string("name", empty_allowed=False)
class StockItem:
name = None
def __init__(self, **kwargs):
if kwargs.get('second_call'):
pass
# proceed normally without calling #valid_string
self.name = kwargs.get('name', None)
self.price = kwargs.get('price', None)
self.quantity = kwargs.get('quantity', None)
if __name__ == "__main__":
import doctest
doctest.testmod()
# valid value for name
cameras1 = StockItem(name="Camera", price=45.99, quatity=2)
# invalid value for name according to #valid_string but I need this to be also valid if 'second_call'
cameras2 = StockItem(name=67, price=45.99, quatity=2, second_call=True)
The StockItem class constructor is invoked twice and on the second turn I want the #valid_string decorator to be somehow canceled (I don't want name attribute's value to be altered anymore).

Python descriptor for type checks and immutability

Read the Python Cookbook and saw descriptors, particularly the example for enforcing types when using class attributes. I am writing a few classes where that would be useful, but I would also like to enforce immutability. How to do it? Type checking descriptor adapted from the book:
class Descriptor(object):
def __init__(self, name=None, **kwargs):
self.name = name
for key, value in kwargs.items():
setattr(self, key, value)
def __set__(self, instance, value):
instance.__dict__[self.name] = value
# by default allows None
class Typed(Descriptor):
def __init__(self, expected_types=None, **kwargs):
self.expected_types = expected_types
super().__init__(**kwargs)
def __set__(self, instance, value):
if value is not None and not isinstance(value, self.expected_types):
raise TypeError('Expected: {}'.format(str(self.expected_types)))
super(Typed, self).__set__(instance, value)
class T(object):
v = Typed(int)
def __init__(self, v):
self.v = v
Attempt #1: add a self.is_set attribute to Typed
# by default allows None
class ImmutableTyped(Descriptor):
def __init__(self, expected_types=None, **kwargs):
self.expected_types = expected_types
self.is_set = False
super().__init__(**kwargs)
def __set__(self, instance, value):
if self.is_set:
raise ImmutableException(...)
if value is not None and not isinstance(value, self.expected_types):
raise TypeError('Expected: {}'.format(str(self.expected_types)))
self.is_set = True
super(Typed, self).__set__(instance, value)
Wrong, because when doing the following, ImmutableTyped is 'global' in the sense that it's a singleton throughout all instances of the class. When t2 is instantiated, is_set is already True from the previous object.
class T(object):
v = ImmutableTyped(int)
def __init__(self, v):
self.v = v
t1 = T()
t2 = T() # fail when instantiating
Attempt #2: Thought instance in __set__ refers to the class containing the attribute so tried to check if instance.__dict__[self.name] is still a Typed. That is also wrong.
Idea #3: Make Typed be used more similar to #property by accepting a 'fget' method returning the __dict__ of T instances. This would require the definition of a function in T similar to:
#Typed
def v(self):
return self.__dict__
which seems wrong.
How to implement immutability AND type checking as a descriptor?
Now this is my approach to the problem:
class ImmutableTyped:
def __set_name__(self, owner, name):
self.name = name
def __init__(self, *, immutable=False, types=None)
self.immutable == immutable is True
self.types = types if types else []
def __get__(self, instance, owner):
return instance.__dict__[self.name]
def __set__(self, instance, value):
if self.immutable is True:
raise TypeError('read-only attribute')
elif not any(isinstance(value, cls)
for cls in self.types):
raise TypeError('invalid argument type')
else:
instance.__dict__[self.name] = value
Side note: __set_name__ can be used to allow you to not specify the attribute name in initialisation. This means you can just do:
class Foo:
bar = ImmutableTyped()
and the instance of ImmutableTyped will automatically have the name attribute bar since I typed for that to occur in the __set_name__ method.
Could not succeed in making such a descriptor. Perhaps it's also unnecessarily complicated. The following method + property use suffices.
# this also allows None to go through
def check_type(data, expected_types):
if data is not None and not isinstance(data, expected_types):
raise TypeError('Expected: {}'.format(str(expected_types)))
return data
class A():
def __init__(self, value=None):
self._value = check_type(value, (str, bytes))
#property
def value(self):
return self._value
foo = A()
print(foo.value) # None
foo.value = 'bla' # AttributeError
bar = A('goosfraba')
print(bar.value) # goosfraba
bar.value = 'bla' # AttributeError
class ImmutableTyped(object):
def __set_name__(self, owner, name):
self.name = name
def __init__(self, *, types=None):
self.types = tuple(types or [])
self.instances = {}
return None
def __get__(self, instance, owner):
return instance.__dict__[self.name]
def __set__(self, instance, value):
is_set = self.instances.setdefault(id(instance), False)
if is_set:
raise AttributeError("read-only attribute '%s'" % (self.name))
if self.types:
if not isinstance(value, self.types):
raise TypeError("invalid argument type '%s' for '%s'" % (type(value), self.name))
self.instances[id(instance)] = True
instance.__dict__[self.name] = value
return None
Examples:
class Something(object):
prop1 = ImmutableTyped(types=[int])
something = Something()
something.prop1 = "1"
Will give:
TypeError: invalid argument type '<class 'str'>' for 'prop1'
And:
something = Something()
something.prop1 = 1
something.prop1 = 2
Will give:
TypeError: read-only attribute 'prop1'

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