I\'ve read that it is possible to add a method to an existing object (i.e., not in the class definition) in Python.
I understand that it\'s not always good to do so
I think that the above answers missed the key point.
Let's have a class with a method:
class A(object):
def m(self):
pass
Now, let's play with it in ipython:
In [2]: A.m
Out[2]: <unbound method A.m>
Ok, so m() somehow becomes an unbound method of A. But is it really like that?
In [5]: A.__dict__['m']
Out[5]: <function m at 0xa66b8b4>
It turns out that m() is just a function, reference to which is added to A class dictionary - there's no magic. Then why A.m gives us an unbound method? It's because the dot is not translated to a simple dictionary lookup. It's de facto a call of A.__class__.__getattribute__(A, 'm'):
In [11]: class MetaA(type):
....: def __getattribute__(self, attr_name):
....: print str(self), '-', attr_name
In [12]: class A(object):
....: __metaclass__ = MetaA
In [23]: A.m
<class '__main__.A'> - m
<class '__main__.A'> - m
Now, I'm not sure out of the top of my head why the last line is printed twice, but still it's clear what's going on there.
Now, what the default __getattribute__ does is that it checks if the attribute is a so-called descriptor or not, i.e. if it implements a special __get__ method. If it implements that method, then what is returned is the result of calling that __get__ method. Going back to the first version of our A class, this is what we have:
In [28]: A.__dict__['m'].__get__(None, A)
Out[28]: <unbound method A.m>
And because Python functions implement the descriptor protocol, if they are called on behalf of an object, they bind themselves to that object in their __get__ method.
Ok, so how to add a method to an existing object? Assuming you don't mind patching class, it's as simple as:
B.m = m
Then B.m "becomes" an unbound method, thanks to the descriptor magic.
And if you want to add a method just to a single object, then you have to emulate the machinery yourself, by using types.MethodType:
b.m = types.MethodType(m, b)
By the way:
In [2]: A.m
Out[2]: <unbound method A.m>
In [59]: type(A.m)
Out[59]: <type 'instancemethod'>
In [60]: type(b.m)
Out[60]: <type 'instancemethod'>
In [61]: types.MethodType
Out[61]: <type 'instancemethod'>
Since this question asked for non-Python versions, here's JavaScript:
a.methodname = function () { console.log("Yay, a new method!") }
Module new is deprecated since python 2.6 and removed in 3.0, use types
see http://docs.python.org/library/new.html
In the example below I've deliberately removed return value from patch_me()
function.
I think that giving return value may make one believe that patch returns a new object, which is not true - it modifies the incoming one. Probably this can facilitate a more disciplined use of monkeypatching.
import types
class A(object):#but seems to work for old style objects too
pass
def patch_me(target):
def method(target,x):
print "x=",x
print "called from", target
target.method = types.MethodType(method,target)
#add more if needed
a = A()
print a
#out: <__main__.A object at 0x2b73ac88bfd0>
patch_me(a) #patch instance
a.method(5)
#out: x= 5
#out: called from <__main__.A object at 0x2b73ac88bfd0>
patch_me(A)
A.method(6) #can patch class too
#out: x= 6
#out: called from <class '__main__.A'>
In Python, there is a difference between functions and bound methods.
>>> def foo():
... print "foo"
...
>>> class A:
... def bar( self ):
... print "bar"
...
>>> a = A()
>>> foo
<function foo at 0x00A98D70>
>>> a.bar
<bound method A.bar of <__main__.A instance at 0x00A9BC88>>
>>>
Bound methods have been "bound" (how descriptive) to an instance, and that instance will be passed as the first argument whenever the method is called.
Callables that are attributes of a class (as opposed to an instance) are still unbound, though, so you can modify the class definition whenever you want:
>>> def fooFighters( self ):
... print "fooFighters"
...
>>> A.fooFighters = fooFighters
>>> a2 = A()
>>> a2.fooFighters
<bound method A.fooFighters of <__main__.A instance at 0x00A9BEB8>>
>>> a2.fooFighters()
fooFighters
Previously defined instances are updated as well (as long as they haven't overridden the attribute themselves):
>>> a.fooFighters()
fooFighters
The problem comes when you want to attach a method to a single instance:
>>> def barFighters( self ):
... print "barFighters"
...
>>> a.barFighters = barFighters
>>> a.barFighters()
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: barFighters() takes exactly 1 argument (0 given)
The function is not automatically bound when it's attached directly to an instance:
>>> a.barFighters
<function barFighters at 0x00A98EF0>
To bind it, we can use the MethodType function in the types module:
>>> import types
>>> a.barFighters = types.MethodType( barFighters, a )
>>> a.barFighters
<bound method ?.barFighters of <__main__.A instance at 0x00A9BC88>>
>>> a.barFighters()
barFighters
This time other instances of the class have not been affected:
>>> a2.barFighters()
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
AttributeError: A instance has no attribute 'barFighters'
More information can be found by reading about descriptors and metaclass programming.
This question was opened years ago, but hey, there's an easy way to simulate the binding of a function to a class instance using decorators:
def binder (function, instance):
copy_of_function = type (function) (function.func_code, {})
copy_of_function.__bind_to__ = instance
def bound_function (*args, **kwargs):
return copy_of_function (copy_of_function.__bind_to__, *args, **kwargs)
return bound_function
class SupaClass (object):
def __init__ (self):
self.supaAttribute = 42
def new_method (self):
print self.supaAttribute
supaInstance = SupaClass ()
supaInstance.supMethod = binder (new_method, supaInstance)
otherInstance = SupaClass ()
otherInstance.supaAttribute = 72
otherInstance.supMethod = binder (new_method, otherInstance)
otherInstance.supMethod ()
supaInstance.supMethod ()
There, when you pass the function and the instance to the binder decorator, it will create a new function, with the same code object as the first one. Then, the given instance of the class is stored in an attribute of the newly created function. The decorator return a (third) function calling automatically the copied function, giving the instance as the first parameter.
In conclusion you get a function simulating it's binding to the class instance. Letting the original function unchanged.
In Python monkeypatching generally works by overwriting a class or function's signature with your own. Below is an example from the Zope Wiki:
from SomeOtherProduct.SomeModule import SomeClass
def speak(self):
return "ook ook eee eee eee!"
SomeClass.speak = speak
This code will overwrite/create a method called peak
in the class. In Jeff Atwood's recent post on monkey patching, he showed an example in C# 3.0 which is the current language I use for work.