Consider this small example:
import datetime as dt
class Timed(object):
def __init__(self, f):
self.func = f
def __call__(self, *args, **kwargs):
start = dt.datetime.now()
ret = self.func(*args, **kwargs)
time = dt.datetime.now() - start
ret["time"] = time
return ret
class Test(object):
def __init__(self):
super(Test, self).__init__()
@Timed
def decorated(self, *args, **kwargs):
print(self)
print(args)
print(kwargs)
return dict()
def call_deco(self):
self.decorated("Hello", world="World")
if __name__ == "__main__":
t = Test()
ret = t.call_deco()
which prints
Hello
()
{'world': 'World'}
Why is the self
parameter (which should be the Test obj instance) not passed as first argument to the decorated function decorated
?
If I do it manually, like :
def call_deco(self):
self.decorated(self, "Hello", world="World")
it works as expected. But if I must know in advance if a function is decorated or not, it defeats the whole purpose of decorators. What is the pattern to go here, or do I misunderstood something?
To decorate a method in a class, first use the '@' symbol followed by the name of the decorator function. A decorator is simply a function that takes a function as an argument and returns yet another function.
To decorate a function with a class, we must use the @syntax followed by our class name above the function definition. Following convention, we will use camel-case for our class name. In the class definition, we define two methods: the init constructor and the magic (or dunder) call method.
In Python, the @classmethod decorator is used to declare a method in the class as a class method that can be called using ClassName. MethodName() . The class method can also be called using an object of the class. The @classmethod is an alternative of the classmethod() function.
Inside Class A “fun1” Instance Method is calling the decorator function “Decorators” inside Class B “fun2”. Instance Method is calling the decorator function of Class A. To use the decorator of Class A, we must require using Class name in which decorator is present that's why we use “@A. Decorators” here.
tl;dr
You can fix this problem by making the Timed
class a descriptor and returning a partially applied function from __get__
which applies the Test
object as one of the arguments, like this
class Timed(object): def __init__(self, f): self.func = f def __call__(self, *args, **kwargs): print(self) start = dt.datetime.now() ret = self.func(*args, **kwargs) time = dt.datetime.now() - start ret["time"] = time return ret def __get__(self, instance, owner): from functools import partial return partial(self.__call__, instance)
The actual problem
Quoting Python documentation for decorator,
The decorator syntax is merely syntactic sugar, the following two function definitions are semantically equivalent:
def f(...): ... f = staticmethod(f) @staticmethod def f(...): ...
So, when you say,
@Timed def decorated(self, *args, **kwargs):
it is actually
decorated = Timed(decorated)
only the function object is passed to the Timed
, the object to which it is actually bound is not passed on along with it. So, when you invoke it like this
ret = self.func(*args, **kwargs)
self.func
will refer to the unbound function object and it is invoked with Hello
as the first argument. That is why self
prints as Hello
.
How can I fix this?
Since you have no reference to the Test
instance in the Timed
, the only way to do this would be to convert Timed
as a descriptor class. Quoting the documentation, Invoking descriptors section,
In general, a descriptor is an object attribute with “binding behavior”, one whose attribute access has been overridden by methods in the descriptor protocol:
__get__()
,__set__()
, and__delete__()
. If any of those methods are defined for an object, it is said to be a descriptor.The default behavior for attribute access is to get, set, or delete the attribute from an object’s dictionary. For instance,
a.x
has a lookup chain starting witha.__dict__['x']
, thentype(a).__dict__['x']
, and continuing through the base classes oftype(a)
excluding metaclasses.However, if the looked-up value is an object defining one of the descriptor methods, then Python may override the default behavior and invoke the descriptor method instead.
We can make Timed
a descriptor, by simply defining a method like this
def __get__(self, instance, owner): ...
Here, self
refers to the Timed
object itself, instance
refers to the actual object on which the attribute lookup is happening and owner
refers to the class corresponding to the instance
.
Now, when __call__
is invoked on Timed
, the __get__
method will be invoked. Now, somehow, we need to pass the first argument as the instance of Test
class (even before Hello
). So, we create another partially applied function, whose first parameter will be the Test
instance, like this
def __get__(self, instance, owner): from functools import partial return partial(self.__call__, instance)
Now, self.__call__
is a bound method (bound to Timed
instance) and the second parameter to partial
is the first argument to the self.__call__
call.
So, all these effectively translate like this
t.call_deco() self.decorated("Hello", world="World")
Now self.decorated
is actually Timed(decorated)
(this will be referred as TimedObject
from now on) object. Whenever we access it, the __get__
method defined in it will be invoked and it returns a partial
function. You can confirm that like this
def call_deco(self): print(self.decorated) self.decorated("Hello", world="World")
would print
<functools.partial object at 0x7fecbc59ad60> ...
So,
self.decorated("Hello", world="World")
gets translated to
Timed.__get__(TimedObject, <Test obj>, Test.__class__)("Hello", world="World")
Since we return a partial
function,
partial(TimedObject.__call__, <Test obj>)("Hello", world="World"))
which is actually
TimedObject.__call__(<Test obj>, 'Hello', world="World")
So, <Test obj>
also becomes a part of *args
, and when self.func
is invoked, the first argument will be the <Test obj>
.
You first have to understand how function become methods and how self
is "automagically" injected.
Once you know that, the "problem" is obvious: you are decorating the decorated
function with a Timed
instance - IOW, Test.decorated
is a Timed
instance, not a function
instance - and your Timed
class does not mimick the function
type's implementation of the descriptor
protocol. What you want looks like this:
import types class Timed(object): def __init__(self, f): self.func = f def __call__(self, *args, **kwargs): start = dt.datetime.now() ret = self.func(*args, **kwargs) time = dt.datetime.now() - start ret["time"] = time return ret def __get__(self, instance, cls): return types.MethodType(self, instance, cls)
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