I'm writing a class that has a dict containing int to method mappings. However setting the values in this dict results in the dict being populated with unbound functions.
class A:
def meth_a: ...
def meth_b: ...
...
map = {1: meth_a, 2: meth_b, ...}
for int in ...:
map[int] = meth_x
This doesn't work for a few reasons:
The methods aren't bound when the class is initialized because they're not in the class dict?
I can't bind the methods manually using __get__ because the class name isn't bound to any namespace yet.
So:
How can I do this?
Do I have to drop out of the class and define the dict after the class has been initialized?
Is it really necessary to call __get__ on the methods to bind them?
Update0
The methods will be called like this:
def func(self, int):
return self.map[int]()
Also regarding the numeric indices/list: Not all indices will be present. I'm not aware that one can do list([1]=a, [2]=b, [1337]=leet) in Python, is there an equivalent? Should I just allocate a arbitrary length list and set specific values? The only interest I have here is in minimizing the lookup time, would it really be that different to the O(1) hash that is {}? I've ignored this for now as premature optimization.
I'm not sure exactly why you're doing what you're doing, but you certainly can do it right in the class definition; you don't need __init__.
class A:
def meth_a(self): pass
m = {1: meth_a}
def foo(self, number):
self.m[number](self)
a = A()
a.foo(1)
An "unbound" instance method simply needs you to pass it an instance of the class manually, and it works fine.
Also, please don't use int as the name of a variable, either, it's a builtin too.
A dictionary is absolutely the right type for this kind of thing.
Edit: This will also work for staticmethods and classmethods if you use new-style classes.
First of all Don't use variable "map" since build in python function map will be fetched.
You need to have init method and initialize your dictionary in the init method using self. The dictionary right now is only part of the class, and not part of instances of the class. If you want instances of the class to have the dictionary as well you need to make an init method and initialize your dictionary there. So you need to do this:
def __init__(self):
self.mymap[int] = self.meth_x
or if you want the dictionary to be a class variable, then this:
def __init__(self):
A.mymap[int] = self.meth_x
It's not totally clear just what you're trying to do. I suspect you want to write code something like
class Foo(object):
def __init__(self, name):
self.name = name
def method_1(self, bar):
print self.name, bar
# ... something here
my_foo = Foo('baz')
my_foo.methods[1]('quux')
# prints "baz quux"
so, that methods attribute needs to return a bound instance method somehow, but without being called directly. This is a good opportunity to use a descriptor. We need to do something that will return a special object when accessed through an instance, and we need that special object to return a bound method when indexed. Let's start from the inside and work our way out.
>>> import types
>>> class BindMapping(object):
... def __init__(self, instance, mapping):
... self.instance, self.mapping = instance, mapping
...
... def __getitem__(self, key):
... func = self.mapping[key]
... if isinstance(func, types.MethodType):
... return types.MethodType(func.im_func, self.instance, func.im_class)
... else:
... return types.MethodType(func, self.instance, type(self))
...
We're just implementing the barest minimum of the mapping protocol, and deferring completely to an underlying collection. here we make use of types.MethodType to get a real instance method when needed, including binding something that's already an instance method. We'll see how that's useful in a minute.
We could implement a descriptor directly, but for the purposes here, property already does everything we need out of a descriptor, so we'll just define one that returns a properly constructed BindMapping instance.
>>> class Foo(object):
... def method_1(self):
... print "1"
... def method_2(self):
... print "2"
...
... _mapping = [method_1, method_2]
...
... #property
... def mapping(self):
... return BindMapping(self, self._mapping)
...
Just for kicks, we also throw in some extra methods outside the class body. Notice how the the methods added inside the class body are functions, just like functions added outside; methods added outside the class body are actual instance methods (although unbound).
>>> def method_3(self):
... print "3"
...
>>> Foo._mapping.append(method_3)
>>> Foo._mapping.append(Foo.method_1)
>>> map(type, Foo._mapping)
[<type 'function'>, <type 'function'>, <type 'function'>, <type 'instancemethod'>]
And it works as advertised:
>>> f = Foo()
>>> for i in range(len(f._mapping)):
... f.mapping[i]()
...
1
2
3
1
>>>
This seems kind of convoluted to me. What is the ultimate goal?
If you really want do to this, you can take advantage of the fact that the methods are alreaday contained in a mapping (__dict__).
class A(object):
def meth_1(self):
print("method 1")
def meth_2(self):
print("method 2")
def func(self, i):
return getattr(self, "meth_{}".format(i))()
a = A()
a.func(2)
This pattern is found in some existing library modules.
Related
I think a code sample will better speak for itself:
class SomeClass:
example = create_get_method()
Yes, that's all – ideally.
In that case, create_get_method would add a get_example() to SomeClass in a way that it can be accessed via an instance of SomeClass:
obj = SomeClass()
obj.get_example() <- returns the value of self.example
(Of course, the idea is to implement a complex version of get_contact, that's why I want to do that in a non-repetitive way, and this is a simplified version that represents well the issue.)
I don't know if that's possible, because it require to have access to the property name (example) and the class (SomeClass) since these can not be guessed in advance (that function will be used on many and various classes).
I know it's something possible, because that's kind of what SQLAlchemy does with their relationship() function on a class:
class Model(BaseModel):
id = ...
contact_id = db.Integer(db.ForeignKey..)
contact = relationship('contact') <-- This !
How can this be done?
Objects bound to class-level variables can have a __set_name__ method that will be called immediately after the class object has been created. It will be called with two arguments, the class object, and the name of the variable the object is saved as in the class.
You could use this to create your extra getter method, though I'm not sure why exactly you want to (you could make the object a descriptor instead, which would probably be better than adding a separate getter function to the parent class).
class create_get_method:
def __set_name__(self, owner, name):
def getter(self):
return getattr(self, name)
getter_name = f"get_{name}"
getter.__name__ = getter_name
setattr(owner, getter_name, getter)
# you might also want a __get__ method here to give a default value (like None)
Here's how that would work:
>>> class Test:
... example = create_get_method()
...
>>> t = Test()
>>> print(t.get_example())
<__main__.create_get_method at 0x000001E0B4D41400>
>>> t.example = "foo"
>>> print(t.get_example())
foo
You could change the value returned by default (in the first print call), so that the create_get_method object isn't as exposed. Just add a __get__ method to the create_get_method class.
You can do this with a custom non-data descriptor, like a property, except that you don't need a __set__ method:
class ComplicatedDescriptor:
def __init__(self, name):
self.name = name
def __get__(self, owner, type):
# Here, `owner` is the instance of `SomeClass` that contains this descriptor
# Use `owner` to do some complicated stuff, like DB lookup or whatever
name = f'_{self.name}'
# These two lines for demo only
value = owner.__dict__.get(name, 0)
value += 1
setattr(owner, name, value)
return value
Now you can have any number of classes that use this descriptor:
class SomeClass:
example = ComplicatedDescriptor('example')
Now you can do something like:
>>> inst0 = SomeClass()
>>> inst1 = SomeClass()
>>> inst0.example
1
>>> inst1.example
1
>>> inst1.example
2
>>> inst0.example
2
The line name = f'_{self.name} is necessary because the descriptor here is a non-data descriptor: it has no __set__ method, so if you create inst0.__dict__['example'], the lookup will no longer happen: inst0.example will return inst0.__dict__['example'] instead of calling SomeClass.example.__get__(inst0, type(inst0)). One workaround is to store the value under the attribute name _example. The other is to make your descriptor into a data descriptor:
class ComplicatedDescriptor_v2:
def __init__(self, name):
self.name = name
def __get__(self, owner, type):
# Here, `owner` is the instance of `SomeClass` that contains this descriptor
# Use `owner` to do some complicated stuff, like DB lookup or whatever
# These two lines for demo only
value = owner.__dict__.get(self.name, 0)
value += 1
owner.__dict__[self.name] = value
return value
def __set__(self, *args):
raise AttributeError(f'{self.name} is a read-only attribute')
The usage is generally identical:
class SomeClass:
example = ComplicatedDescriptor_v2('example')
Except that now you can't accidentally override your attribute:
>>> inst = SomeClass()
>>> inst.example
1
>>> inst.example
2
>>> inst.example = 0
AttributeError: example is a read-only attribute
Descriptors are a fairly idiomatic way to get and set values in python. They are preferred to getters and setters in almost all cases. The simplest cases are handled by the built-in property. That being said, if you wanted to explicitly have a getter method, I would recommend doing something very similar, but just returning a method instead of calling __get__ directly.
For example:
def __get__(self, owner, type):
def enclosed():
# Use `owner` to do some complicated stuff, like DB lookup or whatever
name = f'_{self.name}'
# These two lines for demo only
value = owner.__dict__.get(name, 0)
value += 1
setattr(owner, name, value)
return value
return enclosed
There is really no point to doing something like this unless you plan on really just want to be able to call inst.example().
I have a class factory method that is used to instantiate an object. With multiple objects are created through this method, I want to be able to compare the classes of the objects. When using isinstance, the comparison is False, as can be seen in the simple example below. Also running id(a.__class__) and id(b.__class__), gives different ids.
Is there a simple way of achieving this? I know that this does not exactly conform to duck-typing, however this is the easiest solution for the program I am writing.
def factory():
class MyClass(object):
def compare(self, other):
print('Comparison Result: {}'.format(isinstance(other, self.__class__)))
return MyClass()
a = factory()
b = factory()
print(a.compare(b))
The reason is that MyClass is created dynamically every time you run factory. If you print(id(MyClass)) inside factory you get different results:
>>> a = factory()
140465711359728
>>> b = factory()
140465712488632
This is because they are actually different classes, dynamically created and locally scoped at the time of the call.
One way to fix this is to return (or yield) multiple instances:
>>> def factory(n):
class MyClass(object):
def compare(self, other):
print('Comparison Result: {}'.format(isinstance(other, self.__class__)))
for i in range(n):
yield MyClass()
>>> a, b = factory(2)
>>> a.compare(b)
Comparison Result: True
is a possible implementation.
EDIT: If the instances are created dynamically, then the above solution is invalid. One way to do it is to create a superclass outside, then inside the factory function subclass from that superclass:
>>> class MyClass(object):
pass
>>> def factory():
class SubClass(MyClass):
def compare(self, other):
print('Comparison Result: {}'.format(isinstance(other, self.__class__)))
return SubClass()
However, this does not work because they are still different classes. So you need to change your comparison method to check against the first superclass:
isinstance(other, self.__class__.__mro__[1])
If your class definition is inside the factory function, than each instance of the class you create will be an instance of a separate class. That's because the class definition is a statement, that's executed just like any other assignment. The name and contents of the different classes will be the same, but their identities will be distinct.
I don't think there's any simple way to get around that without changing the structure of your code in some way. You've said that your actual factory function is a method of a class, which suggests that you might be able to move the class definition somewhere else so that it can be shared by multiple calls to the factory method. Depending on what information you expect the inner class to use from the outer class, you might define it at class level (so there'd be only one class definition used everywhere), or you could define it in another method, like __init__ (which would create a new inner class for every instance of the outer class).
Here's what that last approach might look like:
class Outer(object):
def __init__(self):
class Inner(object):
def compare(self, other):
print('Comparison Result: {}'.format(isinstance(other, self.__class__)))
self.Inner = Inner
def factory(self):
return self.Inner()
f = Outer()
a = f.factory()
b = f.factory()
print(a.compare(b)) # True
g = Outer() # create another instance of the outer class
c = g.factory()
print(a.compare(c)) # False
It's not entirely clear what you're asking. It seems to me you want a simpler version of the code you already posted. If that's incorrect, this answer is not relevant.
You can create classes dynamically by explicitly constructing a new instance of the type type.
def compare(self, other):
...
def factory():
return type("MyClass", (object,), { 'compare': compare }()
type takes three arguments: the name, the parents, and the predefined slots. So this will behave the same way as your previous code.
Working off the answer from #rassar, and adding some more detail to represent the actual implementation (e.g. the factory-method existing in a parent class), I have come up with a working example below.
From #rassar's answer, I realised that the class is dynamically created each time, and so defining it within the parent object (or even above that), means that it will be the same class definition each time it is called.
class Parent(object):
class MyClass(object):
def __init__(self, parent):
self.parent = parent
def compare(self, other):
print('Comparison Result: {}'.format(isinstance(other, self.__class__)))
def factory(self):
return self.MyClass(self)
a = Parent()
b = a.factory()
c = a.factory()
b.compare(c)
print(id(b.__class__))
print(id(c.__class__))
I have code that someone else wrote like this:
class MyClass(object):
def __init__(self, data):
self.data = data
#property
def attribute1(self):
return self.data.another_name1
#property
def attribute2(self):
return self.data.another_name2
and I want to automatically create the corresponding property setters at run time so I don't have to modify the other person's code. The property setters should look like this:
#attribute1.setter
def attribue1(self, val):
self.data.another_name1= val
#attribute2.setter
def attribue2(self, val):
self.data.another_name2= val
How do I dynamically add these setter methods to the class?
You can write a custom Descriptor like this:
from operator import attrgetter
class CustomProperty(object):
def __init__(self, attr):
self.attr = attr
def __get__(self, ins, type):
print 'inside __get__'
if ins is None:
return self
else:
return attrgetter(self.attr)(ins)
def __set__(self, ins, value):
print 'inside __set__'
head, tail = self.attr.rsplit('.', 1)
obj = attrgetter(head)(ins)
setattr(obj, tail, value)
class MyClass(object):
def __init__(self, data):
self.data = data
attribute1 = CustomProperty('data.another_name1')
attribute2 = CustomProperty('data.another_name2')
Demo:
>>> class Foo():
... pass
...
>>> bar = MyClass(Foo())
>>>
>>> bar.attribute1 = 10
inside __set__
>>> bar.attribute2 = 20
inside __set__
>>> bar.attribute1
inside __get__
10
>>> bar.attribute2
inside __get__
20
>>> bar.data.another_name1
10
>>> bar.data.another_name2
20
This is the author of the question. I found out a very jerry-rigged solution, but I don't know another way to do it. (I am using python 3.4 by the way.)
I'll start with the problems I ran into.
First, I thought about overwriting the property entirely, something like this:
Given this class
class A(object):
def __init__(self):
self._value = 42
#property
def value(self):
return self._value
and you can over write the property entirely by doing something like this:
a = A()
A.value = 31 # This just redirects A.value from the #property to the int 31
a.value # Returns 31
The problem is that this is done at the class level and not at the instance level, so if I make a new instance of A then this happens:
a2 = A()
a.value # Returns 31, because the class itself was modified in the previous code block.
I want that to return a2._value because a2 is a totally new instance of A() and therefore shouldn't be influenced by what I did to a.
The solution to this was to overwrite A.value with a new property rather than whatever I wanted to assign the instance _value to. I learned that you can create a new property that instantiates itself from the old property using the special getter, setter, and deleter methods (see here). So I can overwrite A's value property and make a setter for it by doing this:
def make_setter(name):
def value_setter(self, val):
setattr(self, name, val)
return value_setter
my_setter = make_setter('_value')
A.value = A.value.setter(my_setter) # This takes the property defined in the above class and overwrites the setter with my_setter
setattr(A, 'value', getattr(A, 'value').setter(my_setter)) # This does the same thing as the line above I think so you only need one of them
This is all well and good as long as the original class has something extremely simple in the original class's property definition (in this case it was just return self._value). However, as soon as you get more complicated, to something like return self.data._value like I have, things get nasty -- like #BrenBarn said in his comment on my post. I used the inspect.getsourcelines(A.value.fget) function to get the source code line that contains the return value and parsed that. If I failed to parse the string, I raised an exception. The result looks something like this:
def make_setter(name, attrname=None):
def setter(self, val):
try:
split_name = name.split('.')
child_attr = getattr(self, split_name[0])
for i in range(len(split_name)-2):
child_attr = getattr(child_attr, split_name[i+1])
setattr(child_attr, split_name[-1], val)
except:
raise Exception("Failed to set property attribute {0}".format(name))
It seems to work but there are probably bugs.
Now the question is, what to do if the thing failed? That's up to you and sort of off track from this question. Personally, I did a bit of nasty stuff that involves creating a new class that inherits from A (let's call this class B). Then if the setter worked for A, it will work for the instance of B because A is a base class. However, if it didn't work (because the return value defined in A was something nasty), I ran a settattr(B, name, val) on the class B. This would normally change all other instances that were created from B (like in the 2nd code block in this post) but I dynamically create B using type('B', (A,), {}) and only use it once ever, so changing the class itself has no affect on anything else.
There is a lot of black-magic type stuff going on here I think, but it's pretty cool and quite versatile in the day or so I've been using it. None of this is copy-pastable code, but if you understand it then you can write your modifications.
I really hope/wish there is a better way, but I do not know of one. Maybe metaclasses or descriptors created from classes can do some nice magic for you, but I do not know enough about them yet to be sure.
Comments appreciated!
assume following class definition:
class A:
def f(self):
return 'this is f'
#staticmethod
def g():
return 'this is g'
a = A()
So f is a normal method and g is a static method.
Now, how can I check if the funcion objects a.f and a.g are static or not? Is there a "isstatic" funcion in Python?
I have to know this because I have lists containing many different function (method) objects, and to call them I have to know if they are expecting "self" as a parameter or not.
Lets experiment a bit:
>>> import types
>>> class A:
... def f(self):
... return 'this is f'
... #staticmethod
... def g():
... return 'this is g'
...
>>> a = A()
>>> a.f
<bound method A.f of <__main__.A instance at 0x800f21320>>
>>> a.g
<function g at 0x800eb28c0>
>>> isinstance(a.g, types.FunctionType)
True
>>> isinstance(a.f, types.FunctionType)
False
So it looks like you can use types.FunctionType to distinguish static methods.
Your approach seems a bit flawed to me, but you can check class attributes:
(in Python 2.7):
>>> type(A.f)
<type 'instancemethod'>
>>> type(A.g)
<type 'function'>
or instance attributes in Python 3.x
>>> a = A()
>>> type(a.f)
<type 'method'>
>>> type(a.g)
<type 'function'>
To supplement the answers here, in Python 3 the best way is like so:
import inspect
class Test:
#staticmethod
def test(): pass
isstatic = isinstance(inspect.getattr_static(Test, "test"), staticmethod)
We use getattr_static rather than getattr, since getattr will retrieve the bound method or function, not the staticmethod class object. You can do a similar check for classmethod types and property's (e.g. attributes defined using the #property decorator)
Note that even though it is a staticmethod, don't assume it was defined inside the class. The method source may have originated from another class. To get the true source, you can look at the underlying function's qualified name and module. For example:
class A:
#staticmethod:
def test(): pass
class B: pass
B.test = inspect.getattr_static(A, "test")
print("true source: ", B.test.__qualname__)
Technically, any method can be used as "static" methods, so long as they are called on the class itself, so just keep that in mind. For example, this will work perfectly fine:
class Test:
def test():
print("works!")
Test.test()
That example will not work with instances of Test, since the method will be bound to the instance and called as Test.test(self) instead.
Instance and class methods can be used as static methods as well in some cases, so long as the first arg is handled properly.
class Test:
def test(self):
print("works!")
Test.test(None)
Perhaps another rare case is a staticmethod that is also bound to a class or instance. For example:
class Test:
#classmethod
def test(cls): pass
Test.static_test = staticmethod(Test.test)
Though technically it is a staticmethod, it is really behaving like a classmethod. So in your introspection, you may consider checking the __self__ (recursively on __func__) to see if the method is bound to a class or instance.
I happens to have a module to solve this. And it's Python2/3 compatible solution. And it allows to test with method inherit from parent class.
Plus, this module can also test:
regular attribute
property style method
regular method
staticmethod
classmethod
For example:
class Base(object):
attribute = "attribute"
#property
def property_method(self):
return "property_method"
def regular_method(self):
return "regular_method"
#staticmethod
def static_method():
return "static_method"
#classmethod
def class_method(cls):
return "class_method"
class MyClass(Base):
pass
Here's the solution for staticmethod only. But I recommend to use the module posted here.
import inspect
def is_static_method(klass, attr, value=None):
"""Test if a value of a class is static method.
example::
class MyClass(object):
#staticmethod
def method():
...
:param klass: the class
:param attr: attribute name
:param value: attribute value
"""
if value is None:
value = getattr(klass, attr)
assert getattr(klass, attr) == value
for cls in inspect.getmro(klass):
if inspect.isroutine(value):
if attr in cls.__dict__:
bound_value = cls.__dict__[attr]
if isinstance(bound_value, staticmethod):
return True
return False
Why bother? You can just call g like you call f:
a = A()
a.f()
a.g()
I would like to replace an object instance by another instance inside a method like this:
class A:
def method1(self):
self = func(self)
The object is retrieved from a database.
It is unlikely that replacing the 'self' variable will accomplish whatever you're trying to do, that couldn't just be accomplished by storing the result of func(self) in a different variable. 'self' is effectively a local variable only defined for the duration of the method call, used to pass in the instance of the class which is being operated upon. Replacing self will not actually replace references to the original instance of the class held by other objects, nor will it create a lasting reference to the new instance which was assigned to it.
As far as I understand, If you are trying to replace the current object with another object of same type (assuming func won't change the object type) from an member function. I think this will achieve that:
class A:
def method1(self):
newObj = func(self)
self.__dict__.update(newObj.__dict__)
It is not a direct answer to the question, but in the posts below there's a solution for what amirouche tried to do:
Python object conversion
Can I dynamically convert an instance of one class to another?
And here's working code sample (Python 3.2.5).
class Men:
def __init__(self, name):
self.name = name
def who_are_you(self):
print("I'm a men! My name is " + self.name)
def cast_to(self, sex, name):
self.__class__ = sex
self.name = name
def method_unique_to_men(self):
print('I made The Matrix')
class Women:
def __init__(self, name):
self.name = name
def who_are_you(self):
print("I'm a women! My name is " + self.name)
def cast_to(self, sex, name):
self.__class__ = sex
self.name = name
def method_unique_to_women(self):
print('I made Cloud Atlas')
men = Men('Larry')
men.who_are_you()
#>>> I'm a men! My name is Larry
men.method_unique_to_men()
#>>> I made The Matrix
men.cast_to(Women, 'Lana')
men.who_are_you()
#>>> I'm a women! My name is Lana
men.method_unique_to_women()
#>>> I made Cloud Atlas
Note the self.__class__ and not self.__class__.__name__. I.e. this technique not only replaces class name, but actually converts an instance of a class (at least both of them have same id()). Also, 1) I don't know whether it is "safe to replace a self object by another object of the same type in [an object own] method"; 2) it works with different types of objects, not only with ones that are of the same type; 3) it works not exactly like amirouche wanted: you can't init class like Class(args), only Class() (I'm not a pro and can't answer why it's like this).
Yes, all that will happen is that you won't be able to reference the current instance of your class A (unless you set another variable to self before you change it.) I wouldn't recommend it though, it makes for less readable code.
Note that you're only changing a variable, just like any other. Doing self = 123 is the same as doing abc = 123. self is only a reference to the current instance within the method. You can't change your instance by setting self.
What func(self) should do is to change the variables of your instance:
def func(obj):
obj.var_a = 123
obj.var_b = 'abc'
Then do this:
class A:
def method1(self):
func(self) # No need to assign self here
In many cases, a good way to achieve what you want is to call __init__ again. For example:
class MyList(list):
def trim(self,n):
self.__init__(self[:-n])
x = MyList([1,2,3,4])
x.trim(2)
assert type(x) == MyList
assert x == [1,2]
Note that this comes with a few assumptions such as the all that you want to change about the object being set in __init__. Also beware that this could cause problems with inheriting classes that redefine __init__ in an incompatible manner.
Yes, there is nothing wrong with this. Haters gonna hate. (Looking at you Pycharm with your in most cases imaginable, there's no point in such reassignment and it indicates an error).
A situation where you could do this is:
some_method(self, ...):
...
if(some_condition):
self = self.some_other_method()
...
return ...
Sure, you could start the method body by reassigning self to some other variable, but if you wouldn't normally do that with other parametres, why do it with self?
One can use the self assignment in a method, to change the class of instance to a derived class.
Of course one could assign it to a new object, but then the use of the new object ripples through the rest of code in the method. Reassiging it to self, leaves the rest of the method untouched.
class aclass:
def methodA(self):
...
if condition:
self = replace_by_derived(self)
# self is now referencing to an instance of a derived class
# with probably the same values for its data attributes
# all code here remains untouched
...
self.methodB() # calls the methodB of derivedclass is condition is True
...
def methodB(self):
# methodB of class aclass
...
class derivedclass(aclass):
def methodB(self):
#methodB of class derivedclass
...
But apart from such a special use case, I don't see any advantages to replace self.
You can make the instance a singleton element of the class
and mark the methods with #classmethod.
from enum import IntEnum
from collections import namedtuple
class kind(IntEnum):
circle = 1
square = 2
def attr(y): return [getattr(y, x) for x in 'k l b u r'.split()]
class Shape(namedtuple('Shape', 'k,l,b,u,r')):
self = None
#classmethod
def __repr__(cls):
return "<Shape({},{},{},{},{}) object at {}>".format(
*(attr(cls.self)+[id(cls.self)]))
#classmethod
def transform(cls, func):
cls.self = cls.self._replace(**func(cls.self))
Shape.self = Shape(k=1, l=2, b=3, u=4, r=5)
s = Shape.self
def nextkind(self):
return {'k': self.k+1}
print(repr(s)) # <Shape(1,2,3,4,5) object at 139766656561792>
s.transform(nextkind)
print(repr(s)) # <Shape(2,2,3,4,5) object at 139766656561888>