Can one write something like:
class Test(object):
def _decorator(self, foo):
foo()
@self._decorator
def bar(self):
pass
This fails: self in @self is unknown
I also tried:
@Test._decorator(self)
which also fails: Test unknown
I would like to temporarily change some instance variables in the decorator and then run the decorated method, before changing them back.
In Python, decorators can be either functions or classes. In both cases, decorating adds functionality to existing functions. When we decorate a function with a class, that function becomes an instance of the class. We can add functionality to the function by defining methods in the decorating class.
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.
Chaining decorators means applying more than one decorator inside a function. Python allows us to implement more than one decorator to a function. It makes decorators useful for reusable building blocks as it accumulates several effects together. It is also known as nested decorators in Python.
Would something like this do what you need?
class Test(object):
def _decorator(foo):
def magic( self ) :
print "start magic"
foo( self )
print "end magic"
return magic
@_decorator
def bar( self ) :
print "normal call"
test = Test()
test.bar()
This avoids the call to self to access the decorator and leaves it hidden in the class namespace as a regular method.
>>> import stackoverflow
>>> test = stackoverflow.Test()
>>> test.bar()
start magic
normal call
end magic
>>>
edited to answer question in comments:
How to use the hidden decorator in another class
class Test(object):
def _decorator(foo):
def magic( self ) :
print "start magic"
foo( self )
print "end magic"
return magic
@_decorator
def bar( self ) :
print "normal call"
_decorator = staticmethod( _decorator )
class TestB( Test ):
@Test._decorator
def bar( self ):
print "override bar in"
super( TestB, self ).bar()
print "override bar out"
print "Normal:"
test = Test()
test.bar()
print
print "Inherited:"
b = TestB()
b.bar()
print
Output:
Normal:
start magic
normal call
end magic
Inherited:
start magic
override bar in
start magic
normal call
end magic
override bar out
end magic
What you're wanting to do isn't possible. Take, for instance, whether or not the code below looks valid:
class Test(object):
def _decorator(self, foo):
foo()
def bar(self):
pass
bar = self._decorator(bar)
It, of course, isn't valid since self
isn't defined at that point. The same goes for Test
as it won't be defined until the class itself is defined (which its in the process of). I'm showing you this code snippet because this is what your decorator snippet transforms into.
So, as you can see, accessing the instance in a decorator like that isn't really possible since decorators are applied during the definition of whatever function/method they are attached to and not during instantiation.
If you need class-level access, try this:
class Test(object):
@classmethod
def _decorator(cls, foo):
foo()
def bar(self):
pass
Test.bar = Test._decorator(Test.bar)
import functools
class Example:
def wrapper(func):
@functools.wraps(func)
def wrap(self, *args, **kwargs):
print("inside wrap")
return func(self, *args, **kwargs)
return wrap
@wrapper
def method(self):
print("METHOD")
wrapper = staticmethod(wrapper)
e = Example()
e.method()
This is one way to access(and have used) self
from inside a decorator
defined inside the same class:
class Thing(object):
def __init__(self, name):
self.name = name
def debug_name(function):
def debug_wrapper(*args):
self = args[0]
print 'self.name = ' + self.name
print 'running function {}()'.format(function.__name__)
function(*args)
print 'self.name = ' + self.name
return debug_wrapper
@debug_name
def set_name(self, new_name):
self.name = new_name
Output (tested on Python 2.7.10
):
>>> a = Thing('A')
>>> a.name
'A'
>>> a.set_name('B')
self.name = A
running function set_name()
self.name = B
>>> a.name
'B'
The example above is silly, but it works.
Here's an expansion on Michael Speer's answer to take it a few steps further:
An instance method decorator which takes arguments and acts on a function with arguments and a return value.
class Test(object):
"Prints if x == y. Throws an error otherwise."
def __init__(self, x):
self.x = x
def _outer_decorator(y):
def _decorator(foo):
def magic(self, *args, **kwargs) :
print("start magic")
if self.x == y:
return foo(self, *args, **kwargs)
else:
raise ValueError("x ({}) != y ({})".format(self.x, y))
print("end magic")
return magic
return _decorator
@_outer_decorator(y=3)
def bar(self, *args, **kwargs) :
print("normal call")
print("args: {}".format(args))
print("kwargs: {}".format(kwargs))
return 27
And then
In [2]:
test = Test(3)
test.bar(
13,
'Test',
q=9,
lollipop=[1,2,3]
)
start magic
normal call
args: (13, 'Test')
kwargs: {'q': 9, 'lollipop': [1, 2, 3]}
Out[2]:
27
In [3]:
test = Test(4)
test.bar(
13,
'Test',
q=9,
lollipop=[1,2,3]
)
start magic
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-3-576146b3d37e> in <module>()
4 'Test',
5 q=9,
----> 6 lollipop=[1,2,3]
7 )
<ipython-input-1-428f22ac6c9b> in magic(self, *args, **kwargs)
11 return foo(self, *args, **kwargs)
12 else:
---> 13 raise ValueError("x ({}) != y ({})".format(self.x, y))
14 print("end magic")
15 return magic
ValueError: x (4) != y (3)
I found this question while researching a very similar problem. My solution is to split the problem into two parts. First, you need to capture the data that you want to associate with the class methods. In this case, handler_for will associate a Unix command with handler for that command's output.
class OutputAnalysis(object):
"analyze the output of diagnostic commands"
def handler_for(name):
"decorator to associate a function with a command"
def wrapper(func):
func.handler_for = name
return func
return wrapper
# associate mount_p with 'mount_-p.txt'
@handler_for('mount -p')
def mount_p(self, slurped):
pass
Now that we've associated some data with each class method, we need to gather that data and store it in a class attribute.
OutputAnalysis.cmd_handler = {}
for value in OutputAnalysis.__dict__.itervalues():
try:
OutputAnalysis.cmd_handler[value.handler_for] = value
except AttributeError:
pass
I use this type of decorator in some debugging situations, it allows overriding class properties by decorating, without having to find the calling function.
class myclass(object):
def __init__(self):
self.property = "HELLO"
@adecorator(property="GOODBYE")
def method(self):
print self.property
Here is the decorator code
class adecorator (object):
def __init__ (self, *args, **kwargs):
# store arguments passed to the decorator
self.args = args
self.kwargs = kwargs
def __call__(self, func):
def newf(*args, **kwargs):
#the 'self' for a method function is passed as args[0]
slf = args[0]
# replace and store the attributes
saved = {}
for k,v in self.kwargs.items():
if hasattr(slf, k):
saved[k] = getattr(slf,k)
setattr(slf, k, v)
# call the method
ret = func(*args, **kwargs)
#put things back
for k,v in saved.items():
setattr(slf, k, v)
return ret
newf.__doc__ = func.__doc__
return newf
Note: because I've used a class decorator you'll need to use @adecorator() with the brackets on to decorate functions, even if you don't pass any arguments to the decorator class constructor.
The simple way to do it. All you need is to put the decorator method outside the class. You can still use it inside.
def my_decorator(func):
#this is the key line. There's the aditional self parameter
def wrap(self, *args, **kwargs):
# you can use self here as if you were inside the class
return func(self, *args, **kwargs)
return wrap
class Test(object):
@my_decorator
def bar(self):
pass
Declare in inner class. This solution is pretty solid and recommended.
class Test(object):
class Decorators(object):
@staticmethod
def decorator(foo):
def magic(self, *args, **kwargs) :
print("start magic")
foo(self, *args, **kwargs)
print("end magic")
return magic
@Decorators.decorator
def bar( self ) :
print("normal call")
test = Test()
test.bar()
The result:
>>> test = Test()
>>> test.bar()
start magic
normal call
end magic
>>>
Decorators seem better suited to modify the functionality of an entire object (including function objects) versus the functionality of an object method which in general will depend on instance attributes. For example:
def mod_bar(cls):
# returns modified class
def decorate(fcn):
# returns decorated function
def new_fcn(self):
print self.start_str
print fcn(self)
print self.end_str
return new_fcn
cls.bar = decorate(cls.bar)
return cls
@mod_bar
class Test(object):
def __init__(self):
self.start_str = "starting dec"
self.end_str = "ending dec"
def bar(self):
return "bar"
The output is:
>>> import Test
>>> a = Test()
>>> a.bar()
starting dec
bar
ending dec
I have a Implementation of Decorators that Might Help
import functools
import datetime
class Decorator(object):
def __init__(self):
pass
def execution_time(func):
@functools.wraps(func)
def wrap(self, *args, **kwargs):
""" Wrapper Function """
start = datetime.datetime.now()
Tem = func(self, *args, **kwargs)
end = datetime.datetime.now()
print("Exection Time:{}".format(end-start))
return Tem
return wrap
class Test(Decorator):
def __init__(self):
self._MethodName = Test.funca.__name__
@Decorator.execution_time
def funca(self):
print("Running Function : {}".format(self._MethodName))
return True
if __name__ == "__main__":
obj = Test()
data = obj.funca()
print(data)
You can decorate the decorator:
import decorator
class Test(object):
@decorator.decorator
def _decorator(foo, self):
foo(self)
@_decorator
def bar(self):
pass
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