Init super with existing instance? - python

Suppose I have:
class Super:
def __init__(self,a):
self.a = a
#classmethod
def from_b(cls,b):
return cls(b.to_a())
class Regular(Super):
def __init__(self,b):
# how to set my super to the output of
super = super.from_b(b)
How do I correctly initialize the super class with the output of the super class method rather than init?
My OOP background is in C++ and I am continually getting into these scenarios due to the ability to overload constructors in C++, so a workaround for this would be awesome.

#shx2's answer works but wastefully/awkwardly creates a throw-away Super object just to initialize the new Regular object with its a attribute.
If you have control over the source of Super, you can make the from_b method create an instance of the given subclass, and have the subclass call the from_b method in its __new__ method instead, so that a Regular object can be both created and initialized directly:
class Super:
def __init__(self, a):
self.a = a
#classmethod
def from_b(cls, b):
obj = super().__new__(cls)
cls.__init__(obj, b.to_a())
return obj
class Regular(Super):
def __new__(cls, b):
return super().from_b(b)
so that the following assertions will pass:
from unittest.mock import Mock
obj = Regular(Mock())
assert type(obj) is Regular
assert obj.a.to_a.is_called()

This is slightly awkward (since what you're trying to do is slightly awkward), but it would work:
class Super:
def __init__(self,a):
self.a = a
#classmethod
def from_b(cls,b):
return cls(b.to_a())
class Regular(Super):
def __init__(self,b):
a = Super.from_b(b).a
super().__init__(a)
By the way, it might help keeping in mind that a "constructor" method such as from_b() (typically) returns a new object, while __init__() only initializes an object after it's been created.

Related

Tracking decorated methods of children classes in python

In python, how can I setup a parent class to track methods with a specific decorator for each child seperatly? A quick code snippet of what I am trying to do:
class Parent:
decorated_func_dict = {} #dictionary that stores name->func for decorated functions
def get_func_by_decorator_name(self, name):
#stuff
pass
class Child1(Parent):
#func_name("Bob")
def bob_func(self, *args):
pass
#func_name("Tom")
def func2(self, *args):
pass
class Child2(Parent):
#func_name("Bob")
def func_bob2(self, *args):
pass
foo = Child1()
bar = Child2()
foo.get_func_by_decorator_name("Bob")
#Returns foo.bob_func
bar.get_func_by_decorator_name("Bob")
#Returns bar.func_bob2
Using Python 3.9.
A decorator is not something that makes a function look pretty. It is a callable that ingests an object (not only functions), does some arbitrary operations, and returns a replacement object.
In this case, your decorator should be storing references to function objects in a dictionary somewhere. The problem is that you won't be able to reference the class in which the functions are defined until it is created, which happens well after the decorator is run. You can avoid this by storing the name of the class as well as the name of the function.
The final step here is to properly bind the function objects to methods on the right object. That is something that get_func_by_decorated_name can do for you.
In sum, you can write something like this:
decorated_func_dict = {}
def func_name(cls_name, func_name):
def decorator(func):
decorated_func_dict.setdefault(cls_name, {})[func_name] = func
return func
return decorator
class Parent:
def get_func_by_decorator_name(self, name):
return decorated_func_dict[type(self).__name__][name].__get__(self)
class Child1(Parent):
#func_name("Child1", "Bob")
def bob_func(self, *args):
pass
#func_name("Child1", "Tom")
def func2(self, *args):
pass
class Child2(Parent):
#func_name("Child2", "Bob")
def func_bob2(self, *args):
pass
And indeed you get:
>>> foo.get_func_by_decorator_name("Bob")
<bound method Child1.bob_func of <__main__.Child1 object at 0x000001D58181E070>>
>>> bar.get_func_by_decorator_name("Bob")
<bound method Child2.func_bob2 of <__main__.Child2 object at 0x000001D582041F10>>
Another way to do this is to give your functions a name attribute, which you can then aggregate into a mapping in __init_subclass__ in Parent. This allows you to make an interface a bit closer to what you originally intended:
def func_name(func_name):
def decorator(func):
func.special_name = func_name
return func
return decorator
class Parent:
def __init_subclass__(cls):
cls.decorated_func_dict = {}
for item in cls.__dict__.values():
if hasattr(item, 'special_name'):
cls.decorated_func_dict[item.special_name] = item
del item.special_name # optional
def get_func_by_decorator_name(self, name):
return self.decorated_func_dict[name].__get__(self)
class Child1(Parent):
#func_name("Bob")
def bob_func(self, *args):
pass
#func_name("Tom")
def func2(self, *args):
pass
class Child2(Parent):
#func_name("Bob")
def func_bob2(self, *args):
pass
The results are identical to the first example.
The easiest way would of course be to get access to the child's namespace before the class is created, e.g. with a metaclass.

What is the pythonic way to overload class variables(properties)?

Hello!
I need each child class to has own set of constants. I've found a "proper" way with properties and overloading setter methods, but:
I need to define constructor in child classes (which I don't need) and assign values in constructor;
Every instance of class will have copy of this constants in memory (senseless resource consumption);
It looks weird when you define setter, getter and property at all just to use it as constant.
I've done something like this:
class BaseClass:
def get_a(self):
raise NotImplementedError("Oooops")
def get_b(self):
raise NotImplementedError("Oooops")
class FirstClass(BaseClass):
def get_a(self):
return "a"
def get_b(self):
return "b"
class SecondClass(BaseClass)
def get_a(self):
return "A"
def get_b(self):
return "B"
class SomeClass:
def some_method(self, class_param):
return "{}-{}".format(class_param.get_a, class_param.get_b)
This method also doesn't solve problems of method with properties (except last), just more compact. There's other way, which I find not good:
class BaseClass:
pass
class FirstClass(BaseClass):
A_CONST = "a"
B_CONST = "b"
class SecondClass(BaseClass)
A_CONST = "A"
B_CONST = "B"
class SomeClass:
def some_method(self, class_param):
return "{}-{}".format(class_param.A_CONST, class_param.B_CONST)
In fact, it solve all problems and pretty compact, BUT it violates rule of inheritance (isn't it?).
Question:
What is the proper way to do this?
P.S. Provided code is simplified example, base class contains methods which I use in child class, please don't write me that base class is useless here.
If you want your base class to indicate that it needs to be subclassed with certain attributes, you can make it an abstract base class.
from abc import ABC, abstractmethod
class Base(ABC):
#property
#abstractmethod
def a(self):
raise NotImplementedError
#property
#abstractmethod
def b(self):
raise NotImplementedError
You will then not be allowed to instantiate Base or its subclasses unless they override the abstract methods. You can do either
class First(Base):
a = 1
b = 2
to assign class attributes with those names, or
class Second(Base):
#Base.a.getter
def a(self):
return 3
#Base.b.getter
def b(self):
return 4
The benefit of the second approach is that it will raise an error if you try to assign to the property
Second().a = 5 # AttributeError
your second version looks fine to me… each language has their own conventions around what a "class" or "object" means, and this looks reasonably "Pythonic"
one minor comment about the first version, is that Python doesn't care about "overloading", you don't need to include:
class BaseClass:
def get_a(self):
raise NotImplementedError("Oooops")
at all, i.e. it's fine to have:
class BaseClass:
pass
as well in your first version.
another potentially useful tool here is the property decorator, e.g:
class FirstClass(BaseClass):
#property
def a(self):
return "a"
print(FirstClass().a)
would output "a"
If the key_name : [A_CONST, B_CONST] remains same for child classes, super() will take care of all your concerns (1., 2., 3.).
A 'pythonic' solution would include, to remove duplication's, of any, setter and getter in child classes and let BaseClass() handle these common-tasks.
class BaseClass(object):
def __init__(self, a, b):
self._a_const = a
self._b_const = b
#property
def A_CONST(self):
return self._a_const
#property
def B_CONST(self):
return self._b_const
class FirstClass(BaseClass):
def __init__(self, _aconst, _bconst):
# Let Base class object hold my constants but FirstClass Constructor
# is setting the value. Look SecondClass
super(FirstClass, self).__init__(_aconst, _bconst)
class SecondClass(BaseClass):
def __init__(self, _aconst, _bconst):
# Magic happens here
super(SecondClass, self).__init__(_aconst, _bconst)
class SomeClass():
def some_method(self, class_param):
return "{}-{}".format(class_param.A_CONST, class_param.B_CONST)
firstobj = FirstClass("a", "b")
secondobj = SecondClass("A", "B")
print(SomeClass().some_method(firstobj))
print(SomeClass().some_method(secondobj))

in Python 3, can a superclass polymorphically call a subclass's constructor

I want to create method (say copy) in a class (Parent) that will return an object of either the class or the subclass that invokes it. I want type(x) == type(x.copy()).
None of the approaches I tried were satisfactory.
Using the superclass constructor returns the superclass (make senses but I figured it was worth a try).
Creating a function init_me in each subclass that the super class uses but that defeats the purpose of inheritance.
I started to explore __new__ and __init__, but quickly decided Python must have a better way.
Sample code
class Parent(object):
def __init__(self, p1=p1_default, p2=p2_default, p3=p3_default):
... # common stuff
self._special_suff()
def copy_works_if_subclass_does_extra(self):
return self.init_me()
def copy_only_does_superclass(self):
return Parent()
def copy_with_init(self):
return self.__init__()
def whoami(self):
print('I am just a parent')
class Dad(Parent):
def _special_stuff():
... # Dad special stuff
return
def whoami(self):
print('I am a dad')
def init_me(self):
return Dad()
class Mom(Parent):
def _special_stuff():
... # Mom special stuff
return
def whoami(self):
print('I am a mom')
If I understand correctly, you're trying to write a copy method in your base class that will still work when called on an instance of a derived class. This can be made to work, but it's only easy if your child classes only expect the same set of arguments as the base class. If their __init__ method expects different arguments you'll need separate copy methods for each derived class.
Here's a quick example of how it can work. The trick is to call type(self) to get the right class, and then call the class with appropriate constructor arguments to get the new instance:
class Base(object):
def __init__(self, arg1, arg2, arg3):
self.attr1 = arg1
self.attr2 = arg2
self.attr3 = arg3
def copy(self):
cls = type(self)
return cls(self.attr1, self.attr2, self.attr3)
class Derived(Base):
def __init__(self, arg1, arg2, arg3):
super().__init__(arg1, arg2, arg3)
self.some_other_attr = "foo"
In practice this tends not to work as well, since the Derived class will usually want to take an extra argument to set up its extra attribute. An option that might work in that situation is to use the copy module rather than writing your own copy method. The function copy.copy will be able to copy many Python instances without any special support.
You are overcomplicating things a lot. Minimal example with a simple constructor implemented on the child class:
import copy
class Parent():
def whoami(self):
print('Just a parent')
def __init__(self, name):
self.name = name
def copy(self):
# Maybe copy.deepcopy instead
return copy.copy(self)
class Dad(Parent):
def whoami(self):
print('I am a dad')
def __init__(self, name):
super().__init__(name)
self.gender = 'Male'
You don't even need a constructor in Python if you don't need. Or you can have one on the superclass and nothing on the child.
Some usage:
>>> dad = Dad("Clark Griswold")
>>> dad.name
'Clark Griswold'
>>> dad.whoami()
I am a dad
>>> isinstance(dad, Dad)
True
>>> isinstance(dad, Parent)
True
>>> type(dad.copy()) == type(dad)
True

python: is this a good way to use the same function name for both classmethod and method?

class A(object):
#classmethod
def print(cls):
print 'A'
def __print(self):
print 'B'
def __init__(self):
self.print = self.__print
a = A()
a.print()
A.print()
I think it's too ugly, is there any other method to implement the same features? do not say combinemethod, because it creates an object every time.
The simplest solution is to create a descriptor decorator like classmethod but that also passes the instance to the method:
from functools import partial
class descriptormethod(object):
def __init__(self, fn):
self.fn = fn
def __get__(self, instance, owner):
return partial(self.fn, instance, owner)
class A(object):
#descriptormethod
def print_(self, cls):
print 'A' if self is None else 'B'
Don't worry about the overhead of the descriptor or partial objects; it's no different from what happens when you call an instance or class method normally.

How to detect method overloading in subclasses in python?

I have a class that is a super-class to many other classes. I would like to know (in the __init__() of my super-class) if the subclass has overridden a specific method.
I tried to accomplish this with a class method, but the results were wrong:
class Super:
def __init__(self):
if self.method == Super.method:
print 'same'
else:
print 'different'
#classmethod
def method(cls):
pass
class Sub1(Super):
def method(self):
print 'hi'
class Sub2(Super):
pass
Super() # should be same
Sub1() # should be different
Sub2() # should be same
>>> same
>>> different
>>> different
Is there any way for a super-class to know if a sub-class has overridden a method?
It seems simplest and sufficient to do this by comparing the common subset of the dictionaries of an instance and the base class itself, e.g.:
def detect_overridden(cls, obj):
common = cls.__dict__.keys() & obj.__class__.__dict__.keys()
diff = [m for m in common if cls.__dict__[m] != obj.__class__.__dict__[m]]
print(diff)
def f1(self):
pass
class Foo:
def __init__(self):
detect_overridden(Foo, self)
def method1(self):
print("Hello foo")
method2=f1
class Bar(Foo):
def method1(self):
print("Hello bar")
method2=f1 # This is pointless but not an override
# def method2(self):
# pass
b=Bar()
f=Foo()
Runs and gives:
['method1']
[]
If you want to check for an overridden instance method in Python 3, you can do this using the type of self:
class Base:
def __init__(self):
if type(self).method == Base.method:
print('same')
else:
print('different')
def method(self):
print('Hello from Base')
class Sub1(Base):
def method(self):
print('Hello from Sub1')
class Sub2(Base):
pass
Now Base() and Sub2() should both print "same" while Sub1() prints "different". The classmethod decorator causes the first parameter to be bound to the type of self, and since the type of a subclass is by definition different to its base class, the two class methods will compare as not equal. By making the method an instance method and using the type of self, you're comparing a plain function against another plain function, and assuming functions (or unbound methods in this case if you're using Python 2) compare equal to themselves (which they do in the C Python implementation), the desired behavior will be produced.
You can use your own decorator. But this is a trick and will only work on classes where you control the implementation.
def override(method):
method.is_overridden = True
return method
class Super:
def __init__(self):
if hasattr(self.method, 'is_overridden'):
print 'different'
else:
print 'same'
#classmethod
def method(cls):
pass
class Sub1(Super):
#override
def method(self):
print 'hi'
class Sub2(Super):
pass
Super() # should be same
Sub1() # should be different
Sub2() # should be same
>>> same
>>> different
>>> same
In reply to answer https://stackoverflow.com/a/9437273/1258307, since I don't have enough credits yet to comment on it, it will not work under python 3 unless you replace im_func with __func__ and will also not work in python 3.4(and most likely onward) since functions no longer have the __func__ attribute, only bound methods.
EDIT: Here's the solution to the original question(which worked on 2.7 and 3.4, and I assume all other version in between):
class Super:
def __init__(self):
if self.method.__code__ is Super.method.__code__:
print('same')
else:
print('different')
#classmethod
def method(cls):
pass
class Sub1(Super):
def method(self):
print('hi')
class Sub2(Super):
pass
Super() # should be same
Sub1() # should be different
Sub2() # should be same
And here's the output:
same
different
same
You can compare whatever is in the class's __dict__ with the function inside the method
you can retrieve from the object -
the "detect_overriden" functionbellow does that - the trick is to pass
the "parent class" for its name, just as one does in a call to "super" -
else it is not easy to retrieve attributes from the parentclass itself
instead of those of the subclass:
# -*- coding: utf-8 -*-
from types import FunctionType
def detect_overriden(cls, obj):
res = []
for key, value in cls.__dict__.items():
if isinstance(value, classmethod):
value = getattr(cls, key).im_func
if isinstance(value, (FunctionType, classmethod)):
meth = getattr(obj, key)
if not meth.im_func is value:
res.append(key)
return res
# Test and example
class A(object):
def __init__(self):
print detect_overriden(A, self)
def a(self): pass
#classmethod
def b(self): pass
def c(self): pass
class B(A):
def a(self): pass
##classmethod
def b(self): pass
edit changed code to work fine with classmethods as well:
if it detects a classmethod on the parent class, extracts the underlying function before proceeding.
--
Another way of doing this, without having to hard code the class name, would be to follow the instance's class ( self.__class__) method resolution order (given by the __mro__ attribute) and search for duplicates of the methods and attributes defined in each class along the inheritance chain.
I'm using the following method to determine if a given bound method is overridden or originates from the parent class
class A():
def bla(self):
print("Original")
class B(A):
def bla(self):
print("Overridden")
class C(A):
pass
def isOverriddenFunc(func):
obj = func.__self__
prntM = getattr(super(type(obj), obj), func.__name__)
return func.__func__ != prntM.__func__
b = B()
c = C()
b.bla()
c.bla()
print(isOverriddenFunc(b.bla))
print(isOverriddenFunc(c.bla))
Result:
Overridden
Original
True
False
Of course, for this to work, the method must be defined in the base class.
You can also check if something is overridden from its parents, without knowing any of the classes involved using super:
class A:
def fuzz(self):
pass
class B(A):
def fuzz(self):
super().fuzz()
class C(A):
pass
>>> b = B(); c = C()
>>> b.__class__.fuzz is super(b.__class__, b).fuzz.__func__
False
>>> c.__class__.fuzz is super(c.__class__, c).fuzz.__func__
True
See this question for some more nuggets of information.
A general function:
def overrides(instance, function_name):
return getattr(instance.__class__, function_name) is not getattr(super(instance.__class__, instance), function_name).__func__
>>> overrides(b, "fuzz")
True
>>> overrides(c, "fuzz")
False
You can check to see if the function has been overridden by seeing if the function handle points to the Super class function or not. The function handler in the subclass object points either to the Super class function or to an overridden function in the Subclass. For example:
class Test:
def myfunc1(self):
pass
def myfunc2(self):
pass
class TestSub(Test):
def myfunc1(self):
print('Hello World')
>>> test = TestSub()
>>> test.myfunc1.__func__ is Test.myfunc1
False
>>> test.myfunc2.__func__ is Test.myfunc2
True
If the function handle does not point to the function in the Super class, then it has been overridden.
Not sure if this is what you're looking for but it helped me when I was looking for a similar solution.
class A:
def fuzz(self):
pass
class B(A):
def fuzz(self):
super().fuzz()
assert 'super' in B.__dict__['fuzz'].__code__.co_names
The top-trending answer and several others use some form of Sub.method == Base.method. However, this comparison can return a false negative if Sub and Base do not share the same import syntax. For example, see discussion here explaining a scenario where issubclass(Sub, Base) -> False.
This subtlety is not apparent when running many of the minimal examples here, but can show up in a more complex code base. The more reliable approach is to compare the method defined in the Sub.__bases__ entry corresponding to Base because __bases__ is guaranteed to use the same import path as Sub
import inspect
def method_overridden(cls, base, method):
"""Determine if class overriddes the implementation of specific base class method
:param type cls: Subclass inheriting (and potentially overriding) the method
:param type base: Base class where the method is inherited from
:param str method: Name of the inherited method
:return bool: Whether ``cls.method != base.method`` regardless of import
syntax used to create the two classes
:raises NameError: If ``base`` is not in the MRO of ``cls``
:raises AttributeError: If ``base.method`` is undefined
"""
# Figure out which base class from the MRO to compare against
base_cls = None
for parent in inspect.getmro(cls):
if parent.__name__ == base.__name__:
base_cls = parent
break
if base_cls is None:
raise NameError(f'{base.__name__} is not in the MRO for {cls}')
# Compare the method implementations
return getattr(cls, method) != getattr(base_cls, method)

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