I'm trying to create a method inside my class that counts the complete run of a specific function. I want to use a simple decorator. I found this reference and rewrite this simple script:
class myclass:
def __init__(self):
self.cnt = 0
def counter(function):
"""
this method counts the runtime of a function
"""
def wrapper(self, **args):
function(**args)
self.counter += 1
return wrapper
#myclass.counter
def somefunc():
print("hello from somefunc")
if __name__ == "__main__":
obj = myclass()
# or if comment #myclass.counter
# somefunc = myclass.counter(somefunc)
somefunc()
And of course, I get:
TypeError: wrapper() missing 1 required positional argument: 'self'
I tried to rewrite the counter as a class method:
class myclass:
def __init__(self):
self.cnt = 0
def counter(self, function):
"""
this method counts the runtime of a function
"""
def wrapper(**args):
function(**args)
self.cnt += 1
return wrapper
def somefunc():
print("hello from somefunc")
if __name__ == "__main__":
obj = myclass()
somefunc = obj.counter(somefunc)
for i in range(10):
somefunc()
print(obj.cnt)
Which works fine but I think it is not a valid decorator definition. Is there any way to define the decorator inside the class method and pass the self-argument to its function? or defining a decorator inside a class is useless?
EDIT:------
First I can't define the decoration outside of the class method. Second I'm trying to make a scheduled class that runs a specific function (as input) for a fixed interval and a specific amount of time so I need to count it.
So I was able to draft up something for you, below is the code:
def count(func):
def wrapper(self):
TestClass.call_count += 1
func(self)
return wrapper
class TestClass(object):
call_count = 0
#count
def hello(self):
return 'hello'
if __name__ == '__main__':
x = TestClass()
for i in range(10):
x.hello()
print(TestClass.call_count)
Why would it cause problems to have the decorator in a class:
It's not straight forward to have a decorator function inside the class. The reasons are below:
Reason 1
Every class method must take an argument self which is the instance of the class through which the function is being called. Now if you make the decorator function take a self argument, the decorator call #count would fail as it get converted to count() which doesn't pass the self argument and hence the error:
TypeError: wrapper() missing 1 required positional argument: 'self'
Reason 2
Now to avoid that you can make your decorator as static by changing the declaration like below:
#staticmethod
def count(func):
pass
But then you have another error:
TypeError: 'staticmethod' object is not callable
Which means you can't have a static method as well. If you can't have a static method in a class, you have to pass the self instance to the method but if you pass the self instance to it, the #count decorator call wouldn't pass the self instance and hence it won't work.
So here is a blog that explains it quite well, the issues associated with it and what are the alternatives.
I personally prefer the option to have a helper class to hold all my decorators that can be used instead of the only class in which it's defined. This would give you the flexibility to reuse the decorators instead of redefining them which would follow the ideology
code once, reuse over and over again.
Your second code example is functionally equivalent to a standard decorator. The standard decorator syntax is just a shorthand for the same thing, namely, reassigning a function value equal to a closure (a function pointer with arguments predefined), where the closure is your decorator wrapper holding the original as its predefined argument.
Here's an equivalent with standard syntax. Notice you need to create the counter class instance in advance. The decorator syntax refers to that instance, because it must indicate the specific object which holds your counter, rather than just the class of the object:
class myclass:
def __init__(self):
self.cnt = 0
def counter(self,function):
"""
this method counts the number of runtime of a function
"""
def wrapper(**args):
function(self,**args)
self.cnt += 1
return wrapper
global counter_object
counter_object = myclass()
#counter_object.counter
def somefunc(self):
print("hello from somefunc")
if __name__ == "__main__":
for i in range(10):
somefunc()
print(counter_object.cnt)
Related
I have following code:
class SomeClass:
def __init__(self) -> None:
pass
def some_class_function(self, par):
print(par)
class SomeOtherClass:
def __init__(self) -> None:
pass
def some_other_class_function(self, par):
print(par+1)
if __name__ == "__main__":
sc = SomeClass()
sc.some_class_function = SomeOtherClass.some_other_class_function
sc.some_class_function(1)
When I execute the code I get
TypeError: some_other_class_function() missing 1 required positional argument: 'par'
How can I override the method of the first class with the method of the second class properly?
As you have noted in the comments, you are interested in adding method that will use sc as the "self" instance.
To that end, see this post. To summarize, you can either add a function to the class definition (affecting future instances of the same class), or bind the function to the particular instance.
As an example, consider the following class and function.
class Test():
def __init__(self):
self.phrase = "hello world"
def func(self):
print("this is the old method")
def test_func(self):
print(self.phrase)
For the first approach, we could do the following
test = Test()
Test.func = test_func
test.func()
Note that future instances of Test will have this function as an attribute. For example, running Test().func() will still result in the same output, even though the method is being used on a new class instance.
For the second, we could do the following.
import types
test = Test()
test.func = types.MethodType(test_func, test)
test.func()
In this case, running the line Test().func() will result in the output "this is the old method" because func has not been overwritten for new instances.
You need to initialize the class to call its method.
sc = SomeClass()
sco = SomeOtherClass() # initialize the second call to call it's method
sc.some_class_function = sco.some_other_class_function
sc.some_class_function(1)
Suppose I have this decorator:
def decorator(f):
def f_wrap(*args):
for item in args:
print(args)
return f(*args)
return f_wrap
When used as "permanent" decorators with the # syntax, args retrieves the arguments of the wrapped function. For example, when used with the class below, I receive the instance of MyObject.
Class MyObject(object):
def __init__(self):
pass
#decorator
def function(self):
return
How can I achieve the same result using a "fluid" decorator. Or a decorator that is not permanently bound to the function it is decorating? For example:
def decorator(f):
def f_wrap(*args):
if (not args):
print("Nothing in args")
return f(*args)
return f_wrap
class MyClass(object):
def __init__(self):
pass
def function(self):
return
if __name__ == "__main__":
myobj = MyClass()
myobj.function = decorator(myobj.function)
myobj.function()
In this case, the args tuple always returns empty (I always get "Nothing in args"), even though I anticipated that it would return the instance variable myobj.
EDIT:
In case it was not clear from #AChampion's post the solution is to simply call the fluid-decoratored method as an "unbound" method. E.g.,
from types import MethodType
def decorator(f):
def f_wrap(*args):
# I replaced this with an iteration through
# args. It's a bit more demonstrative.
for item in args:
print(item)
return f(*args)
return f_wrap
class MyClass(object):
def __init__(self):
pass
def function(self):
return
if __name__ == "__main__":
myobj = MyClass()
myobj.function = MethodType(decorator(MyClass.function), myobj)
myobj.function()
The reason for the difference is that you are wrapping different things, a unbound method vs a bound method:
class MyObject(object):
#decorator
def function(self):
pass
Is equivalent to:
import types
class MyClass(object):
def function(self):
pass
m = MyClass(object)
m.function = types.MethodType(decorator(MyClass.function), m)
Not:
m.function = decorator(m.function)
The first being an unbound method, the second being a bound method.
You aren't using all properly. all returns a bool on whether all conditions are met inside what you are checking for in all. In your case, you aren't really doing anything. You will always evaluate to True with how you are using all.
I believe what you are looking for is simply this:
if not args:
Now, ultimately what this checks is if the method you are executing has *args. For the case of the function you have, you aren't passing any arguments, therefore, with the if not args check, you will actually get:
"Nothing in args"
However, if you add an argument to your method as such:
def function(self, x):
return
Then call: myobj.function(1)
You will not get "Nothing in args".
To answer your last question about not getting your instance. If you print out f using this method of calling your decorator:
myobj.function = decorator(myobj.function)
myobj.function()
You will get a bound method:
<bound method MyClass.function of <__main__.MyClass object at 0x102002390>>
Now, set up your decorator as such:
#decorator
def function(self):
return
You will see you get a function attached to your class object:
<function MyClass.function at 0x102001620>
Hence showing that they aren't doing the exact same thing you would expect. Hope this helps clarify a bit.
I'm using Python and I have two classes. I want to import a function for a class but with the ability of adding things to that function.
class Main(self):
def __init__(self):
thingstodo()
def function(self, keypressed):
#LOTS OF CODE
keyname = keypressed
if keyname = "Escape":
dosomething()
class Main2(Main):
def __init(self):
Main.__init__(self)
def function(self, keypressed):
Main.function(self, keypressed)
if keyname = "control":
dootherthing()
Basic principles
You cannot access local variables from one function (or method) in another function. This is by design.
This class Main(self): is wrong. In Python 3 do class Main:. While using self as the name of the first argument in method is a strong convention, self is just an ordinary name not a reserved keyword or built-in.
There are several problems here:
def __init(self):
Main.__init__(self)
a. The method name needs to __init__() not __init.
b. Don't hardwire the name of the parent class with Main.__init__(self) use super().__init__().
c. If you don't do anything extra in the __init__() of Main2, than you don't need to implement the __init__() at all.
Possible solution
For your problem, using a dictionary with the key press names as keys and the functions for the actions as values seems useful.
First define a few small helper functions:
def thingstodo():
print('thingstodo')
def dosomething():
print('something')
def dootherthing():
print('dootherthing')
Now your main class:
class KeyAction: # Python 3
def __init__(self):
thingstodo()
self.key_actions = {'Escape': dosomething}
def handel_key_press(self, keypressed):
#LOTS OF CODE
keyname = keypressed
func = self.key_actions.get(keyname)
if func is not None:
func()
Names are important, therefore I use KeyAction instead of Main.
This line self.key_actions = {'Escape': dosomething} is the core of this solution. Here self.key_actions is a dictionary that maps names of key press events to functions. Note dosomething without the () because I put the function object into the dictionary rather than calling this function.
Calling this function is a bit different:
func = self.key_actions.get(keyname)
if func is not None:
func()
I use the get() method of the dictionary. This returns the value for the key if the key is in it and None if not. Now func holds either a reference to the function dosomething if the key was Escape or None. If it is a function I call it with func().
An alternative here could be a try-except:
def handel_key_press(self, keypressed):
#LOTS OF CODE
keyname = keypressed
try:
self.key_actions[keyname]()
except KeyError:
pass
Now, in your child class, you only need to add another key-value pair to self.key_actions to extend its functionality:
class ExtendedKeyAction(KeyAction):
def __init__(self):
super().__init__()
self.key_actions['control'] = dootherthing
Make two instances and test your code:
key_action = KeyAction()
key_action.handel_key_press('Escape')
key_action.handel_key_press('undefined')
extended_key_action = ExtendedKeyAction()
extended_key_action.handel_key_press('Escape')
extended_key_action.handel_key_press('control')
extended_key_action.handel_key_press('undefined')
prints:
thingstodo
something
thingstodo
something
dootherthing
I have a class where I have multiple methods. I want to use one of the methods as a decorator for other methods. For this I am using following syntax:
#self.action
def execute(self,req):
where action is other method in my class. But it doesn't work and throws exception as
name 'self' is not defined
You cannot use a method of the class while defining it; there is no self within the class nor is the class 'baked' yet to even access any class.
You can treat methods as functions to use as a decorator:
class SomeClass():
def action(func):
# decorate
return wrapper
#action
def execute(self, req):
# something
If action is defined on a base class, then you'd have to refer to the name via the base class:
class Base():
#staticmethod
def action(func):
# decorate
return wrapper
class Derived(Base):
#Base.action
def execute(self, req):
# something
For Python 2, you'd have to make action a static method here, as otherwise you get an unbound method that'll complain you cannot call it without an instance as the first argument. In Python 3, you can leave off the #staticmethod decorator there, at least for the purposes of the decorator.
But note that action cannot then be used as a method directly; perhaps it should not be part of the class at all at that point. It is not part of the end-user API here, presumably the decorator is not used by consumers of the instances of these classes.
Just beware that both the decorator and the decorated function are unbound methods, so you can only access the self (or cls for classmethods) in the inner scope of the decorator, and must manually bind the decorated method to the instance bound in the inner decorator.
class A:
x = 5
y = 6
def decorate(unbound):
def _decorator(self):
bound = unbound.__get__(self)
return bound() * self.x
return _decorator
#decorate
def func(self):
return self.y
A().func() # 30!!
Still trying to wrap my head around how decorators could be inherited and overridden.
Beware that for the decorator to work it can't be bound to an instance. That is: there is no way to make this work
a = A()
#a.decorate
def func(*args):
return 1
Despite this pattern is much more common than the asked here.
At this point the question raises: is it a method at all or just code that you happen to hide in a class?
The only way to prevent the decorator being wrongfully bound is to declare it as a staticmethod, but then it must be in a previous super class because to be used it must be bound to the static class reference which would not be yet defined, just as the self.
class A:
x = 1
#staticmethod
def decorate(unbound):
def _decorator(self):
bound = unbound.__get__(self)
return bound() * self.x
return _decorator
class B(A):
#A.decorate
def func(self):
return 1
class C():
x = 2
#B.decorate
def func(self):
return 1
a = A()
class D():
x = 3
#a.decorate
def func(self):
return 1
B().func() # 1
C().func() # 2
D().func() # 3
But as you can see, there is no way for the decorator to use the state of its own class. class A from this last example just happens to be a mixin with a default x variable and an "unrelated" static decorator.
So, again, is it a method?
To overcome all of this, you can bind the staticmethod in your same class to an arbitrary type. Namely, the builtin type will do.
class A:
x = 1
#staticmethod
def decorate(unbound):
def _decorator(self):
bound = unbound.__get__(self)
return bound() * self.x
return _decorator
#decorate.__get__(type)
def func(self):
return 1
class B:
x = 2
#A.decorate
def func(self):
return 1
class C:
x = 3
#(A().decorate) # Only for Python 3.9+, see PEP-614
def func(self):
return 1
A().func() # 1
B().func() # 2
C().func() # 3
But this features too much magic for my taste. And still not a method for my gut.
In python "self" is passed to instance methods as an argument (the first), "self" is just a convention is possible to call it "foobarbaz" (of course it would be silly)… the point is that, from the outside "self" is not defined (because its scope is the method)… you can't decorate class methods with other class methods, instead you have to write a separate class!
I have a class which maintains a list of functions. These functions are just objects sitting in a queue and every so often the class pops one off and executes it. However, there are times when I would like to print out this list, and I'm imagining code as follows:
for function in self.control_queue:
print function.summarize()
if function.ready():
function()
In other words, I would like to call methods called summarize() and ready(), that I want to define somewhere, on these function objects. Also, I would like to be able to toss anonymous functions on this queue - i.e., generate everything dynamically.
you can make it a class and define __call__
class MyClass():
def summarize(self):
#summarize stuff
pass
def ready(self):
#ready stuff
pass
def _call__(self):
#put the code here, for when you call myClass()
pass
How you run it:
function = MyClass()
print function.summarize()
if function.ready():
function()
You have a couple possible approaches.
You could add the definitions to functions.
def foo():
pass
# later..
foo.summarize = lambda: "To pair with bar"
foo.ready = lambda: True
You could create class objects to wrap the function operation.
class Func():
def summarize(self):
return "Function!"
def ready(self):
return self.ready
def __call__(self):
# Act as a function
Or you can have a function which checks the function label for these capabilities.
def summarize_func(func):
return func.__name__ # Or branch here on specific names/attributes
def ready_func(func):
return True # Or branch on names/attributes
Finally to accommodate anonymous functions you can check for prescience of these attributes and return optimistically if the attributes are absent. Then you can combine above approaches with something that will work on any function.
def summarize_func(func):
if hasattr(func, summarize):
return func.summarize()
else:
# Note this will just be '<lambda>' for anonymous funcs
return func.__name__
def ready_func(func):
if hasattr(func, ready):
return func.ready()
else:
return True
One option is to implement function as a class instance:
class Function(object):
def summarize(self): pass # some relevant code here
def __call__(self): pass # and there
and use it later with
function = Function()
With __call__ magic method implemented, this function becomes a callable object.
For sure, you can assign attributes to functions, but it is rather obscure and conterintuitive:
>>> def summ(a): return sum(a)
...
>>> def function(a): return a
...
>>> function.sum=summ
>>> function.sum([1,2,3])
6