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Is there a way to pass a function call to an inner object?

Is there a way in python to pass a function call to an inner object, maybe through a decorator or wrapper? In the example below, class A holds a list of class B objects, and one of the class B objects is selected as the active object. I want class A to function as a passthrough, just identifying which of the class B objects that the call goes to. However, class A doesn't know what type of class it is going to hold beforehand, so I can't just add a set_var function to class A. It has to work for any generic function that class B has. It will only have one type of class in its objects list, so it could take class B as an input when it is instantiated and dynamically create functions, if that's a possibility. The client wouldn't know whether it's dealing with class A or class B. The code below is as far as I got.
class A:
def __init__(self):
self.objects = []
self.current_object = 0
def add_object(self, object):
self.objects.append(object)
class B:
def __init__(self):
self.var = 10
def set_var(self, new_var):
self.var = new_var
a_obj = A()
b_obj1 = B()
b_obj2 = B()
a_obj.add_object(b_obj1)
a_obj.add_object(b_obj2)
a_obj.set_var(100)

You could use the generic __getattr__ to delegate to the wrapped object.
class A:
def __init__(self):
self.objects = []
self.current_object = 0
def add_object(self, obj):
self.objects.append(obj)
self.current_object = obj
def __getattr__(self, name):
return getattr(self.current_object, name)
class B:
def __init__(self):
self.var = 10
def set_var(self, new_var):
self.var = new_var
a_obj = A()
b_obj1 = B()
b_obj2 = B()
a_obj.add_object(b_obj1)
a_obj.add_object(b_obj2)
a_obj.set_var(100)
print(b_obj2.var)
That will print "100".
You will still get an AttributeError if the wrapped object doesn't have the expected method.

It was interesting to look at this, it is intentionally rough but it does indeed allow you to call one the B instance's set_var methods.
The code below uses sets as a quick and dirty way to see the difference in callable methods, and if there is; it sets the attribute based on that name. Binding the method to the A instance.
This would only bind set_var once from the first object given.
def add_object(self, object):
self.objects.append(object)
B_methods = set([m for m in dir(object) if callable(getattr(object, m))])
A_methods = set([m for m in dir(self) if callable(getattr(self, m))])
to_set = B_methods.difference(A_methods)
for method in to_set:
setattr(self, method, getattr(object, method))

Dynamically Create Methods for Class with list of values

I have a list of values that I want to use for a Builder object implementation that is in the works.
For example:
val_list = ["abc", "def", "ghi"]
What I want to do is dynamically create methods in a class that will allow for these to be callable and retrieved in an instance.
I'm vaguely familiar with doing this with setattr(...) but the next step Im stuck at is being able to do some processing inside the method. In the example below, if I was to do this with my ever growing list, it would a WHOLE BUNCH of code that does literally the same thing. It works for now but I want this list to be dynamic, as well as the class.
For example
def abc(self, value):
self.processing1 = value + "workworkwork"
return self
def def(self, value):
self.processing1 = value + "workworkwork"
return self
def ghi(self, value):
self.processing1 = value + "workworkwork"
return self

I haven't tried this before, but I wonder if it would work using lambdas
self.my_methods = {}
val_list = []
def new_method(self,method_name):
self.my_methods[method_name] = "lambda: self.general_method(some_value)"
def general_method(self, value):
print(value)
Honestly, I'm sure that won't work as written, but hopefully you see the train of thought if it looks of possible interest. Since I can't visualize the overall concept, it's a little tough.
But since it seems that the method name seems important, I'm not sure what to do. Perhaps this is an XY type question? Getting stuck on the how instead of the results?
I would think there has to be a way to make this work:
[Class definition]
...
def method(self,secret_method_name,arg1):
# do something based on method name if necessary
# do something based on args

You can't call a non-existing method on a object without wrapping it first, e.g:
# A legacy class
class dummy:
def foo(self):
return "I'm a dummy!"
obj = dummy()
obj.a("1") # You can't
You can do it using a wrapper class first, here's just a idea of how you can get it done:
# Creates a object you can append methods to
def buildable(cls):
class fake:
# This method will receive the class of the object to build
def __init__(self, cls):
self.cls = cls
# This will simulate a constructor of the underlying class
# Return the fake class so we can call methods on it
def __call__(self, *args, **kwargs):
self.obj = self.cls(*args, **kwargs)
return self
# Will be called whenever a property (existing or non-existing)
# is called on a instance of the fake class
def __getattr__(self, attr):
# If the underlying object has the called attribute,
# just return this attribute
if hasattr(self.obj, attr):
return getattr(self.obj, attr)
# Call the respective function on globals with the provided
# arguments and return the fake class so we can add more methods
def wrapper(*args, **kwargs):
globals()[attr](self.obj, *args, **kwargs)
return self
return wrapper
return fake(cls)
So, how does this work?
Decorate your legacy class:
#buildable
class dummy:
def foo(self):
return "I'm a dummy!"
Create the build methods that'll modify dummy:
def a(self, some):
self.a = some + 'a'
def b(self, some):
self.b = some + 'b'
def c(self, some):
self.c = some + 'c'
Modify it:
obj = dummy()
obj.a("1").b("2").c("3")
See the brand new attributes (and the old ones too!):
print(obj.a) # 1a
print(obj.b) # 2b
print(obj.c) # 3c
print(obj.foo()) # I'm a dummy!
Note that this has some important drawbacks, such as:
Calling a non-existing attribute on dummy will not raise AttributeError:
print(obj.nini) # <function buildable.<locals>.fake.__getattr__.<locals>.wrapper at 0x7f4794e663a0>
You can't do it with multiple objects:
obj1 = dummy()
obj1.a("1").b("2")
print(obj1.a) # 1a
print(obj1.b) # 2b
obj2 = dummy()
obj2.c("3")
print(obj2.c) # 3c
print(obj1.a) # <function buildable.<locals>.fake.__getattr__.<locals>.wrapper at 0x7f524ae16280>
print(obj1.b) # <function buildable.<locals>.fake.__getattr__.<locals>.wrapper at 0x7f524ae16280>
The type of obj will not be dummy:
print(type(obj)) # <class '__main__.buildable.<locals>.fake'>
print(type(obj.obj)) # <class '__main__.dummy'>
You can't call a build method with the same name of an already existing method:
def foo(bar):
self.foo = 'foo' + bar
obj.foo("bar")
print(obj.foo())
# raises TypeError: foo() takes 1 positional argument but 2 were
You can't do it with built-in classes:
list = buildable(list)
obj = list()
obj.a("4").b("5").c("6")
# raises AttributeError: 'list' object has no attribute 'a'

How to overwrite self after reading yaml? [duplicate]

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>

Apply a function to all instances of a class

I am looking for a way to apply a function to all instances of a class. An example:
class my_class:
def __init__(self, number):
self.my_value = number
self.double = number * 2
#staticmethod
def crunch_all():
# pseudocode starts here
for instances in my_class:
instance.new_value = instance.my_value + 1
So the command my_class.crunch_all() should add a new attribute new_value to all existing instances. I am guessing I will have to use #staticmethod to make it a "global" function.
I know I could keep track of the instances that are being defined by adding something like my_class.instances.append(number) in __init__ and then loop through my_class.instances, but I had no luck so far with that either. Also I am wondering if something more generic exists. Is this even possible?

Register objects with the class at initialisation (i.e. __init__) and define a class method (i.e. #classmethod) for the class:
class Foo(object):
objs = [] # registrar
def __init__(self, num):
# register the new object with the class
Foo.objs.append(self)
self.my_value = num
#classmethod
def crunch_all(cls):
for obj in cls.objs:
obj.new_value = obj.my_value + 1
example:
>>> a, b = Foo(5), Foo(7)
>>> Foo.crunch_all()
>>> a.new_value
6
>>> b.new_value
8

How to implement property() with dynamic name (in python)

I am programming a simulations for single neurons. Therefore I have to handle a lot of Parameters. Now the Idea is that I have two classes, one for a SingleParameter and a Collection of parameters. I use property() to access the parameter value easy and to make the code more readable. This works perfect for a sinlge parameter but I don't know how to implement it for the collection as I want to name the property in Collection after the SingleParameter. Here an example:
class SingleParameter(object):
def __init__(self, name, default_value=0, unit='not specified'):
self.name = name
self.default_value = default_value
self.unit = unit
self.set(default_value)
def get(self):
return self._v
def set(self, value):
self._v = value
v = property(fget=get, fset=set, doc='value of parameter')
par1 = SingleParameter(name='par1', default_value=10, unit='mV')
par2 = SingleParameter(name='par2', default_value=20, unit='mA')
# par1 and par2 I can access perfectly via 'p1.v = ...'
# or get its value with 'p1.v'
class Collection(object):
def __init__(self):
self.dict = {}
def __getitem__(self, name):
return self.dict[name] # get the whole object
# to get the value instead:
# return self.dict[name].v
def add(self, parameter):
self.dict[parameter.name] = parameter
# now comes the part that I don't know how to implement with property():
# It shoule be something like
# self.__dict__[parameter.name] = property(...) ?
col = Collection()
col.add(par1)
col.add(par2)
col['par1'] # gives the whole object
# Now here is what I would like to get:
# col.par1 -> should result like col['par1'].v
# col.par1 = 5 -> should result like col['par1'].v = 5
Other questions that I put to understand property():
Why do managed attributes just work for class attributes and not for instance attributes in python?
How can I assign a new class attribute via __dict__ in python?

Look at built-in functions getattr and setattr. You'll probably be a lot happier.

Using the same get/set functions for both classes forces you into an ugly hack with the argument list. Very sketchy, this is how I would do it:
In class SingleParameter, define get and set as usual:
def get(self):
return self._s
def set(self, value):
self._s = value
In class Collection, you cannot know the information until you create the property, so you define the metaset/metaget function and particularize them only later with a lambda function:
def metaget(self, par):
return par.s
def metaset(self, value, par):
par.s = value
def add(self, par):
self[par.name] = par
setattr(Collection, par.name,
property(
fget=lambda x : Collection.metaget(x, par),
fset=lambda x, y : Collection.metaset(x,y, par))

Properties are meant to dynamically evaluate attributes or to make them read-only. What you need is customizing attribute access. __getattr__ and __setattr__ do that really fine, and there's also __getattribute__ if __getattr__ is not enough.
See Python docs on customizing attribute access for details.

Have you looked at the traits package? It seems that you are reinventing the wheel here with your parameter classes. Traits also have additional features that might be useful for your type of application (incidently I know a person that happily uses traits in neural simulations).

Now I implemented a solution with set-/getattr:
class Collection(object):
...
def __setattr__(self, name, value):
if 'dict' in self.__dict__:
if name in self.dict:
self[name].v = value
else:
self.__dict__[name] = value
def __getattr__(self, name):
return self[name].v
There is one thing I quite don't like that much: The attributes are not in the __dict__. And if I have them there as well I would have a copy of the value - which can be dangerous...

Finally I succeded to implement the classes with property(). Thanks a lot for the advice. It took me quite a bit to work it out - but I can promise you that this exercise helps you to understand better pythons OOP.
I implemented it also with __getattr__ and __setattr__ but still don't know the advantages and disadvantages to the property-solution. But this seems to be worth another question. The property-solutions seems to be quit clean.
So here is the code:
class SingleParameter(object):
def __init__(self, name, default_value=0, unit='not specified'):
self.name = name
self.default_value = default_value
self.unit = unit
self.set(default_value)
def get(*args):
self = args[0]
print "get(): "
print args
return self._v
def set(*args):
print "set(): "
print args
self = args[0]
value = args[-1]
self._v = value
v = property(fget=get, fset=set, doc='value of parameter')
class Collection(dict):
# inheriting from dict saves the methods: __getitem__ and __init__
def add(self, par):
self[par.name] = par
# Now here comes the tricky part.
# (Note: this property call the get() and set() methods with one
# more argument than the property of SingleParameter)
setattr(Collection, par.name,
property(fget=par.get, fset=par.set))
# Applying the classes:
par1 = SingleParameter(name='par1', default_value=10, unit='mV')
par2 = SingleParameter(name='par2', default_value=20, unit='mA')
col = Collection()
col.add(par1)
col.add(par2)
# Setting parameter values:
par1.v = 13
col.par1 = 14
# Getting parameter values:
par1.v
col.par1
# checking identity:
par1.v is col.par1
# to access the whole object:
col['par1']
As I am new I am not sure how to move on:
how to treat follow up questions (like this itself):
get() is seems to be called twice - why?
oop-design: property vs. "__getattr__ & __setattr__" - when should I use what?
is it rude to check the own answer to the own question as accepted?
is it recommended to rename the title in order to put correlated questions or questions elaborated with the same example into the same context?
Other questions that I put to understand property():
Why do managed attributes just work for class attributes and not for instance attributes in python?
How can I assign a new class attribute via __dict__ in python?

I have a class that does something similar, but I did the following in the collection object:
setattr(self, par.name, par.v)