What does using `__get__` on a function do? - python

for the function,
def add(a, b):
return a + b
when I do,
add.__get__(object(), object)
<bound method add of <object object at 0x7f3c7af42b90>>
add.__get__(list(), list)
<bound method add of []>
add.__get__(bool(), bool)
<bound method add of False>
what is happening here?

Functions are descriptors and use the descriptor protocol to bind the instance the method is called on to the first argument. This is how "self works". So, if you look at the Descriptor HOWTO it gives you an example of how it would be implemented in Python:
class Function:
...
def __get__(self, obj, objtype=None):
"Simulate func_descr_get() in Objects/funcobject.c"
if obj is None:
return self
return MethodType(self, obj)
So, here are examples of calling the returned callable with different types of objects:
>>> def frobnicate(first):
... return first.foo + 1
...
>>> class Foo:
... foo = 42
...
>>> class Bar:
... foo = "bar"
...
>>> class Baz:
... bar = 42
...
>>> frobnicate.__get__(Foo())()
43
>>> frobnicate.__get__(Bar())()
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "<stdin>", line 2, in frobnicate
TypeError: can only concatenate str (not "int") to str
>>> frobnicate.__get__(Baz())()
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "<stdin>", line 2, in frobnicate
AttributeError: 'Baz' object has no attribute 'foo'
And of course, putting the function in some class namespace makes it act like any other method automatically:
>>> Foo.frobnicate = frobnicate
>>> Foo().frobnicate()
43
Note, you can mentally think of MethodType as just something like:
def bind_first(func, obj):
def bound(*args, **kwargs):
return func(obj, *args, **kwargs)
return bound
Although, if you check the link, it shows a closer implementation (in Python, instead of C):
Methods can be created manually with types.MethodType which is roughly equivalent to:
class MethodType:
"Emulate PyMethod_Type in Objects/classobject.c"
def __init__(self, func, obj):
self.__func__ = func
self.__self__ = obj
def __call__(self, *args, **kwargs):
func = self.__func__
obj = self.__self__
return func(obj, *args, **kwargs)
Which is basically doing the same thing as the bind_first function I gave as an example... (although, again, it's using a class and it also creates the __func__ and __self__ arguments that bound-methods have).

it appears that,
def f():
pass
when I do,
hasattr(f, '__get__')
then, it returns True
when I do,
class A:
pass
a = A()
f.__get__(a, A) # I think the second argument is optional here
# so, even, f.__get__(a) would give same result
it returns,
<bound method f of <__main__.A object at 0x7f9c7568dd10>>
which means that our function is similar to something like this,
class B:
def func_(self):
pass
b = B()
b.func_
<bound method B.func_ of <__main__.B object at 0x7f9c7563cc50>>
and then when I call the function on top,
f.__get__(a)()
then, it gives an error,
TypeError: f() takes 0 positional arguments but 1 was given
which means, that I am passing the instance here,
similar to func_, where,
the first argument self refers to the instance of the class B.
so, the function we have on top, becomes a bound method, and if I change it to,
def f(self):
print(self)
and then run,
f.__get__(a)()
it gives me,
<__main__.A object at 0x7f9c7568dd10>
one more thing to notice here is that we could bind our function to a class also, which would make it a class method,
f.__get__(A)
<bound method func of <class '__main__.A'>>
where,
f.__get__(A)()
gives,
<class '__main__.A'>
which is similar to,
class C:
#classmethod
def x(cls):
print(cls)
C.x
<bound method C.x of <class '__main__.C'>>
or we could keep our function as a static method, without binding it to an instance or a class.
f.__get__(1)
<bound method func of 1>
where,
f.__get__(1)()
gives,
1
here, f would be a function with the first argument equal to 1.

Related

Make function in class only accessible without calling the class

Let's say I have this class:
class A:
def __init__(self, a):
self.a = a
#classmethod
def foo(self):
return 'hello world!'
I use #classmethod, so that I can directly call the function without calling the class:
>>> A.foo()
'hello world!'
>>>
But now I am wondering, since I still can access it with calling the class:
>>> A(1).foo()
'hello world!'
>>>
Would I be able to make it that it would raise an error if the function foo is called from a called class. And only let it to be called without calling the class, like A.foo().
So if I do:
A(1).foo()
It should give an error.
The functionality of how classmethod, staticmethod and in fact normal methods are lookedup / bound is implemented via descriptors. Similarly, one can define a descriptor that forbids lookup/binding on an instance.
A naive implementation of such a descriptor checks whether it is looked up via an instance and raises an error in this case:
class NoInstanceMethod:
"""Descriptor to forbid that other descriptors can be looked up on an instance"""
def __init__(self, descr, name=None):
self.descr = descr
self.name = name
def __set_name__(self, owner, name):
self.name = name
def __get__(self, instance, owner):
# enforce the instance cannot look up the attribute at all
if instance is not None:
raise AttributeError(f"{type(instance).__name__!r} has no attribute {self.name!r}")
# invoke any descriptor we are wrapping
return self.descr.__get__(instance, owner)
This can be applied on top of other descriptors to prevent them from being looked up on an instance. Prominently, it can be combined with classmethod or staticmethod to prevent using them on an instance:
class A:
def __init__(self, a):
self.a = a
#NoInstanceMethod
#classmethod
def foo(cls):
return 'hello world!'
A.foo() # Stdout: hello world!
A(1).foo() # AttributeError: 'A' object has no attribute 'foo'
The above NoInstanceMethod is "naive" in that it does not take care of propagating descriptor calls other than __get__ to its wrapped descriptor. For example, one could propagate __set_name__ calls to allow the wrapped descriptor to know its name.
Since descriptors are free to (not) implement any of the descriptor methods, this can be supported but needs appropriate error handling. Extend the NoInstanceMethod to support whatever descriptor methods are needed in practice.
A workaround is to override its value upon initialization of a class object to make sure it wouldn't be called from self.
def raise_(exc):
raise exc
class A:
STRICTLY_CLASS_METHODS = [
"foo",
]
def __init__(self, a):
self.a = a
for method in self.STRICTLY_CLASS_METHODS:
# Option 1: Using generator.throw() to raise exception. See https://www.python.org/dev/peps/pep-0342/#new-generator-method-throw-type-value-none-traceback-none
# setattr(self, method, lambda *args, **kwargs: (_ for _ in ()).throw(AttributeError(method)))
# Option 2: Using a function to raise exception
setattr(self, method, lambda *args, **kwargs: raise_(AttributeError(method)))
#classmethod
def foo(cls):
return 'hello world!'
def bar(self):
return 'hola mundo!', self.a
Output
>>> A.foo()
'hello world!'
>>> a = A(123)
>>> a.bar()
('hola mundo!', 123)
>>> a.foo()
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "<stdin>", line 11, in <lambda>
File "<stdin>", line 2, in raise_
AttributeError: foo
>>> a.bar()
('hola mundo!', 123)
>>> A(45).bar()
('hola mundo!', 45)
>>> A(6789).foo()
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "<stdin>", line 11, in <lambda>
File "<stdin>", line 2, in raise_
AttributeError: foo
>>> A.foo()
'hello world!'

Python 3: remove attributes from class before instancing it

I'm working with Python3, and I have a really heavy class with many functions as attributes:
Class A (object):
def __init__(self):
...
def method1(self):
...
def method2(self):
...
...
def methodN(self):
...
I would like to create an instance of class A that only has method1, for example. How could I do this?
Using inheritance, though it might be the most technically correct way, is not an option in my case - I can't modify the codebase so much.
I thought about decorating the class and deleting its attributes before __init__ is called, but I'm not even sure where to start tackling this. Any ideas?
You can modify the __getattribute__ method of the class to disallow access to those attributes (via normal instance.attribute access)
class A (object):
def __init__(self, x):
self.x = x
def method1(self):
...
def method2(self):
...
def __getattribute__(self, name):
if object.__getattribute__(self, 'x'):
if name == 'method2':
raise AttributeError("Cannot access method2 is self.x is True")
return object.__getattribute__(self, name)
>>> a = A(False)
>>> a.method1
<bound method A.method1 of <__main__.A object at 0x000001E25992F248>>
>>> a.method2
<bound method A.method2 of <__main__.A object at 0x000001E25992F248>>
>>> b = A(True)
>>> b.method1
<bound method A.method1 of <__main__.A object at 0x000001E25992F2C8>>
>>> b.method2
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "<stdin>", line 11, in __getattribute__
AttributeError: Cannot access method2 is self.x is True
Obviously, this gets pretty unwieldy and violates a lot of assumptions about what it means to be an instance of a class. I can't think of a good reason to do this in real code, as you can still access the methods through object.__getattribute__(b, 'method2')

__getattr__ returning lambda function requiring one argument does not work

I am in the process of learning Python 3 and just ran into the getattr function. From what I can tell, it is invoked when the attribute call is not found in the class definition as a function or a variable.
In order to understand the behaviour, I wrote the following test class (based on what I've read):
class Test(object):
def __init__(self, foo, bar):
self.foo = foo
self.bar = bar
def __getattr__(self, itm):
if itm is 'test':
return lambda x: "%s%s" % (x.foo, x.bar)
raise AttributeError(itm)
And I then initate my object and call the non-existent function test which, expectedly, returns the reference to the function:
t = Test("Foo", "Bar")
print(t.test)
<function Test.__getattr__.<locals>.<lambda> at 0x01A138E8>
However, if I call the function, the result is not the expected "FooBar", but an error:
print(t.test())
TypeError: <lambda>() missing 1 required positional argument: 'x'
In order to get my expected results, I need to call the function with the same object as the first parameter, like this:
print(t.test(t))
FooBar
I find this behaviour rather strange, as when calling p.some_function(), is said to add p as the first argument.
I would be grateful if someone could shine some light over this headache of mine. I am using PyDev in Eclipse.
__getattr__ return values are "raw", they don't behave like class attributes, invoking the descriptor protocol that plain methods involve that causes the creation of bound methods (where self is passed implicitly). To bind the function as a method, you need to perform the binding manually:
import types
...
def __getattr__(self, itm):
if itm is 'test': # Note: This should really be == 'test', not is 'test'
# Explicitly bind function to self
return types.MethodType(lambda x: "%s%s" % (x.foo, x.bar), self)
raise AttributeError(itm)
types.MethodType is poorly documented (the interactive help is more helpful), but basically, you pass it a user-defined function and an instance of a class and it returns a bound method that, when called, implicitly passes that instance as the first positional argument (the self argument).
Note that in your specific case, you could just rely on closure scope to make a zero-argument function continue to work:
def __getattr__(self, itm):
if itm is 'test': # Note: This should really be == 'test', not is 'test'
# No binding, but referring to self captures it in closure scope
return lambda: "%s%s" % (self.foo, self.bar)
raise AttributeError(itm)
Now it's not a bound method at all, just a function that happens to have captured self from the scope in which it was defined (the __getattr__ call). Which solution is best depends on your needs; creating a bound method is slightly slower, but gets a true bound method, while relying on closure scope is (trivially, ~10ns out of >400ns) faster, but returns a plain function (which may be a problem if, for example, it's passed as a callback to code that assumes it's a bound method and can have __self__ and __func__ extracted separately for instance).
To get what you want, you need a lambda that doesn't take arguments:
return lambda: "%s%s" % (self.foo, self.bar)
But you should really use a property for this, instead.
class Test(object):
def __init__(self, foo, bar):
self.foo = foo
self.bar = bar
#property
def test(self):
return "{}{}".format(self.foo, self.bar)
t = Test("Foo", "Bar")
print(t.test)
# FooBar
Note the lack of parentheses.
If you're absolutely determined that it must be a function, do this:
class Test(object):
def __init__(self, foo, bar):
self.foo = foo
self.bar = bar
#property
def test(self):
return lambda: "{}{}".format(self.foo, self.bar)
t = Test("Foo", "Bar")
print(t.test())
# FooBar
You need to create something that behaves like a bound method, you could simply use functools.partial to bind the instance to the function:
from functools import partial
class Test(object):
def __init__(self, foo, bar):
self.foo = foo
self.bar = bar
def __getattr__(self, itm):
if itm == 'test': # you shouldn't use "is" for comparisons!
return partial(lambda x: "%s%s" % (x.foo, x.bar), self)
raise AttributeError(itm)
The test:
t = Test("Foo", "Bar")
print(t.test)
# functools.partial(<function Test.__getattr__.<locals>.<lambda> at 0x0000020C70CA6510>, <__main__.Test object at 0x0000020C7217F8D0>)
print(t.test())
# FooBar
"I find this behaviour rather strange, as when calling
p.some_function(), is said to add p as the first argument."
some_function is actually a method, which is why it gets passed an instance implicitly when the method is "bound to an object." But plain functions don't work that way, only functions defined in the class body have this magic applied to them automagically. And actually, unbound methods (accessed via the class directly) function the same as normal functions! The terminology "bound and unbound" methods no longer applies, because in Python 3 we only have methods and functions (getting rid of the distinction between unbound methods and plain functions). When an instance is instantiated, accessing the attribute returns a method which implicitly calls the instance on invocation.
>>> class A:
... def method(self, x):
... return x
...
>>> a.method
<bound method A.method of <__main__.A object at 0x101a5b3c8>>
>>> type(a.method)
<class 'method'>
However, if you access the attribute of the class you'll see it's just a function:
>>> A.method
<function A.method at 0x101a64950>
>>> type(A.method)
<class 'function'>
>>> a = A()
Now, observe:
>>> bound = a.method
>>> bound(42)
42
>>> unbound = A.method
>>> unbound(42)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: method() missing 1 required positional argument: 'x'
But this is the magic of classes. Note, you can even add functions to classes dynamically, and they get magically turned into methods when you invoke them on an instance:
>>> A.method2 = lambda self, x: x*2
>>> a2 = A()
>>> a2.method2(4)
8
And, as one would hope, the behavior still applies to objects already created!
>>> a.method2(2)
4
Note, this doesn't work if you dynamically add to an instance:
>>> a.method3 = lambda self, x: x*3
>>> a.method3(3)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: <lambda>() missing 1 required positional argument: 'x'
You have to do the magic yourself:
>>> from types import MethodType
>>> a.method4 = MethodType((lambda self, x: x*4), a)
>>> a.method4(4)
16
>>>
Notice that if you do print(t.__getattr__) you get something like <bound method Test.__getattr__ of <__main__.Test object at 0x00000123FBAE4DA0>>. The key point is that methods defined on an object are said to be 'bound' and so always take the object as the first parameter. Your lambda function is just an anonymous function not 'bound' to anything, so for it to access the object it needs to be explicitly passed in.
I presume you are only doing this to experiment with using `__getattr__', as what you are doing could be much more easily achieved by making your lambda a method on the object.

What is the hidden argument being passed to my `MethodType`?

I recently came across this recipe for making a "weakmethod" and thought it was the bees' knees; but there seems to be a mystery argument being passed to the resulting MethodType function that i can't seem to find:
from weakref import proxy
from types import MethodType
class Foo(object):
def __getattribute__(self, name):
if name.startswith('foo_'):
return MethodType(super(Foo, self).__getattribute__(name), proxy(self), self.__class__)
else:
return super(Foo, self).__getattribute__(name)
class Bar(Foo):
def my_func(self, a, b):
print a, b
def foo_my_func(self, a, b):
print 'FF Victory Theme'
>>> bar = Bar()
>>> bar.my_func(1, 2)
1 2
>>> weakmethod = bar.foo_my_func
>>> weakmethod(2, 3) # Or `bar.foo_my_func(2, 3)`
Traceback (most recent call last):
File "<pyshell#160>", line 1, in <module>
weakmethod(2, 3)
TypeError: foo_my_func() takes exactly 3 arguments (4 given)
What is this 4th argument that's being passed?
You used super(Foo, self).__getattribute__(name) to access the foo_my_func method. This already returns a MethodType object. You then wrap this object again.
So your returned object passes in proxy(self) to the wrapped method, which passes in another self argument. You started with a, b, and end up with self, proxy(self), a, b.
The recipe you linked to uses a decorator instead; this decorator is executed at class definition time, and wraps the function object. It is itself a descriptor, so it handles all the wrapping directly.
You'll want to either unwrap the result of super(Foo, self).__getattribute__(name) or don't use __getattribute__ at all.
Unwrapping can be done with accessing the __func__ attribute on a method:
class Foo(object):
def __getattribute__(self, name):
attr = super(Foo, self).__getattribute__(name)
if name.startswith('foo_'):
return MethodType(attr.__func__, proxy(self), self.__class__)
return attr
Not using __getattribute__ is done by just accessing the __dict__ mapping on the class directly:
class Foo(object):
def __getattribute__(self, name):
if name.startswith('foo_'):
for cls in type(self).__mro__:
if name in cls.__dict__:
return MethodType(cls.__dict__[name], proxy(self), self.__class__)
return super(Foo, self).__getattribute__(name)
where type(self).__mro__ lets you iterate over the class and it's base classes in method resolution order to manually search for the method.

Python: changing methods and attributes at runtime

I wish to create a class in Python that I can add and remove attributes and methods. How can I acomplish that?
Oh, and please don't ask why.
This example shows the differences between adding a method to a class and to an instance.
>>> class Dog():
... def __init__(self, name):
... self.name = name
...
>>> skip = Dog('Skip')
>>> spot = Dog('Spot')
>>> def talk(self):
... print 'Hi, my name is ' + self.name
...
>>> Dog.talk = talk # add method to class
>>> skip.talk()
Hi, my name is Skip
>>> spot.talk()
Hi, my name is Spot
>>> del Dog.talk # remove method from class
>>> skip.talk() # won't work anymore
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
AttributeError: Dog instance has no attribute 'talk'
>>> import types
>>> f = types.MethodType(talk, skip, Dog)
>>> skip.talk = f # add method to specific instance
>>> skip.talk()
Hi, my name is Skip
>>> spot.talk() # won't work, since we only modified skip
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
AttributeError: Dog instance has no attribute 'talk'
I wish to create a class in Python that I can add and remove attributes and methods.
import types
class SpecialClass(object):
#classmethod
def removeVariable(cls, name):
return delattr(cls, name)
#classmethod
def addMethod(cls, func):
return setattr(cls, func.__name__, types.MethodType(func, cls))
def hello(self, n):
print n
instance = SpecialClass()
SpecialClass.addMethod(hello)
>>> SpecialClass.hello(5)
5
>>> instance.hello(6)
6
>>> SpecialClass.removeVariable("hello")
>>> instance.hello(7)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
AttributeError: 'SpecialClass' object has no attribute 'hello'
>>> SpecialClass.hello(8)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
AttributeError: type object 'SpecialClass' has no attribute 'hello'
A possibly interesting alternative to using types.MethodType in:
>>> f = types.MethodType(talk, puppy, Dog)
>>> puppy.talk = f # add method to specific instance
would be to exploit the fact that functions are descriptors:
>>> puppy.talk = talk.__get__(puppy, Dog)
I wish to create a class in Python that I can add and remove attributes and methods. How can I acomplish that?
You can add and remove attributes and methods to any class, and they'll be available to all instances of the class:
>>> def method1(self):
pass
>>> def method1(self):
print "method1"
>>> def method2(self):
print "method2"
>>> class C():
pass
>>> c = C()
>>> c.method()
Traceback (most recent call last):
File "<pyshell#62>", line 1, in <module>
c.method()
AttributeError: C instance has no attribute 'method'
>>> C.method = method1
>>> c.method()
method1
>>> C.method = method2
>>> c.method()
method2
>>> del C.method
>>> c.method()
Traceback (most recent call last):
File "<pyshell#68>", line 1, in <module>
c.method()
AttributeError: C instance has no attribute 'method'
>>> C.attribute = "foo"
>>> c.attribute
'foo'
>>> c.attribute = "bar"
>>> c.attribute
'bar'
you can just assign directly to the class (either by accessing the original class name or via __class__ ):
class a : pass
ob=a()
ob.__class__.blah=lambda self,k: (3, self,k)
ob.blah(5)
ob2=a()
ob2.blah(7)
will print
(3, <__main__.a instance at 0x7f18e3c345f0>, 5)
(3, <__main__.a instance at 0x7f18e3c344d0>, 7)
Simply:
f1 = lambda:0 #method for instances
f2 = lambda _:0 #method for class
class C: pass #class
c1,c2 = C(),C() #instances
print dir(c1),dir(c2)
#add to the Instances
c1.func = f1
c1.any = 1.23
print dir(c1),dir(c2)
print c1.func(),c1.any
del c1.func,c1.any
#add to the Class
C.func = f2
C.any = 1.23
print dir(c1),dir(c2)
print c1.func(),c1.any
print c2.func(),c2.any
which results in:
['__doc__', '__module__'] ['__doc__', '__module__']
['__doc__', '__module__', 'any', 'func'] ['__doc__', '__module__']
0 1.23
['__doc__', '__module__', 'any', 'func'] ['__doc__', '__module__', 'any', 'func']
0 1.23
0 1.23
another alternative, if you need to replace the class wholesale is to modify the class attribute:
>>> class A(object):
... def foo(self):
... print 'A'
...
>>> class B(object):
... def foo(self):
... print 'Bar'
...
>>> a = A()
>>> a.foo()
A
>>> a.__class__ = B
>>> a.foo()
Bar
Does the class itself necessarily need to be modified? Or is the goal simply to replace what object.method() does at a particular point during runtime?
I ask because I sidestep the problem of actually modifying the class to monkey patch specific method calls in my framework with getattribute and a Runtime Decorator on my Base inheritance object.
Methods retrieved by a Base object in getattribute are wrapped in a Runtime_Decorator that parses the method calls keyword arguments for decorators/monkey patches to apply.
This enables you to utilize the syntax object.method(monkey_patch="mypatch"), object.method(decorator="mydecorator"), and even object.method(decorators=my_decorator_list).
This works for any individual method call (I leave out magic methods), does so without actually modifying any class/instance attributes, can utilize arbitrary, even foreign methods to patch, and will work transparently on sublcasses that inherit from Base (provided they don't override getattribute of course).
import trace
def monkey_patched(self, *args, **kwargs):
print self, "Tried to call a method, but it was monkey patched instead"
return "and now for something completely different"
class Base(object):
def __init__(self):
super(Base, self).__init__()
def testmethod(self):
print "%s test method" % self
def __getattribute__(self, attribute):
value = super(Base, self).__getattribute__(attribute)
if "__" not in attribute and callable(value):
value = Runtime_Decorator(value)
return value
class Runtime_Decorator(object):
def __init__(self, function):
self.function = function
def __call__(self, *args, **kwargs):
if kwargs.has_key("monkey_patch"):
module_name, patch_name = self._resolve_string(kwargs.pop("monkey_patch"))
module = self._get_module(module_name)
monkey_patch = getattr(module, patch_name)
return monkey_patch(self.function.im_self, *args, **kwargs)
if kwargs.has_key('decorator'):
decorator_type = str(kwargs['decorator'])
module_name, decorator_name = self._resolve_string(decorator_type)
decorator = self._get_decorator(decorator_name, module_name)
wrapped_function = decorator(self.function)
del kwargs['decorator']
return wrapped_function(*args, **kwargs)
elif kwargs.has_key('decorators'):
decorators = []
for item in kwargs['decorators']:
module_name, decorator_name = self._resolve_string(item)
decorator = self._get_decorator(decorator_name, module_name)
decorators.append(decorator)
wrapped_function = self.function
for item in reversed(decorators):
wrapped_function = item(wrapped_function)
del kwargs['decorators']
return wrapped_function(*args, **kwargs)
else:
return self.function(*args, **kwargs)
def _resolve_string(self, string):
try: # attempt to split the string into a module and attribute
module_name, decorator_name = string.split(".")
except ValueError: # there was no ".", it's just a single attribute
module_name = "__main__"
decorator_name = string
finally:
return module_name, decorator_name
def _get_module(self, module_name):
try: # attempt to load the module if it exists already
module = modules[module_name]
except KeyError: # import it if it doesn't
module = __import__(module_name)
finally:
return module
def _get_decorator(self, decorator_name, module_name):
module = self._get_module(module_name)
try: # attempt to procure the decorator class
decorator_wrap = getattr(module, decorator_name)
except AttributeError: # decorator not found in module
print("failed to locate decorators %s for function %s." %\
(kwargs["decorator"], self.function))
else:
return decorator_wrap # instantiate the class with self.function
class Tracer(object):
def __init__(self, function):
self.function = function
def __call__(self, *args, **kwargs):
tracer = trace.Trace(trace=1)
tracer.runfunc(self.function, *args, **kwargs)
b = Base()
b.testmethod(monkey_patch="monkey_patched")
b.testmethod(decorator="Tracer")
#b.testmethod(monkey_patch="external_module.my_patch")
The downside to this approach is getattribute hooks all access to attributes, so the checking of and potential wrapping of methods occurs even for attributes that are not methods + won't be utilizing the feature for the particular call in question. And using getattribute at all is inherently somewhat complicated.
The actual impact of this overhead in my experience/for my purposes has been negligible, and my machine runs a dual core Celeron. The previous implementation I used introspected methods upon object init and bound the Runtime_Decorator to methods then. Doing things that way eliminated the need to utilize getattribute and reduced the overhead mentioned previously... however, it also breaks pickle (maybe not dill) and is less dynamic then this approach.
The only use cases I have actually come across "in the wild" with this technique were with timing and tracing decorators. However, the possibilities it opens up are extremely wide ranging.
If you have a preexisting class that cannot be made to inherit from a different base (or utilize the technique it's own class definition or in it's base class'), then the whole thing simply does not apply to your issue at all unfortunately.
I don't think setting/removing non-callable attributes on a class at runtime is necessarily so challenging? unless you want classes that inherit from the modified class to automatically reflect the changes in themselves as well... That'd be a whole 'nother can o' worms by the sound of it though.

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