Decorators allow you to make simple modifications to callable objects (like functions, methods, or classes). We shall deal with functions for this tutorial. The syntax
@decorator
def functions(arg):
return "Return"
Is equivalent to:
def function(arg):
return "Return"
function=decorator(function) #this passes the function to the decorator, and reassigns it to the functions
As you may have seen, a decorator is just another function which takes a functions and returns one. For example you could do this:
def repeater(old_function):
def new_function(*args, **kwds): #See learnpython.org/page/Multiple%20Function%20Arguments for how *args and **kwds works
old_function(*args, **kwds) #we run the old function
old_function(*args, **kwds) #we do it twice
return new_function #we have to return the new_function, or it wouldn't reassign it to the value
This would make a function repeat twice.
>>> @repeater
def Multiply(num1, num2):
print num1*num2
>>> Multiply(2, 3)
6
6
You can also make it change the output
def Double_Out(old_function):
def new_function(*args, **kwds):
return 2*old_function(*args, **kwds) #modify the return value
return new_function
change input
def Double_In(old_function):
def new_function(arg): #only works if the old function has one argument
return old_function(arg*2) #modify the argument passed
return new_function
and do checking.
def Check(old_function):
def new_function(arg):
if arg<0: raise ValueError, "Negative Argument" #This causes an error, which is better than it doing the wrong thing
old_function(arg)
return new_function(arg)
Let's say you want to multiply the output by a variable amount. You could do
def Multiply(multiplier):
def Multiply_Generator(old_function):
def new_function(*args, **kwds):
return multiplier*old_function(*args, **kwds)
return new_function
return Mutliply_Generator #it returns the new generator
Now, you could do
@Mutliply(3) #Multiply is not a generator, but Multiply(3) is
def Num(num):
return num
You can do anything you want with the old function, even completely ignore it! Advanced decorators can also manipulate the doc string and argument number. For some snazzy decorators, go to http://wiki.python.org/moin/PythonDecoratorLibrary.
Make a decorator factory which returns a decorator that decorates functions with one argument. The factory should take one argument, a type, and then returns a decorator that makes function should check if the input is the correct type. If it is wrong, it should print "Bad Type". (In reality, it should raise an error, but error raising isn't in this tutorial.) Look at the tutorial code and expected output to see what it is if you are confused (I know I would be.) Using isintance(object, type_of_object) or type(object) might help.
def Type_Check(correct_type):
#put code here
@Type_Check(int)
def Times2(num):
return num*2
print Times2(2)
Times2('Not A Number')
@Type_Check(str)
def First_Letter(word):
return word[0]
print First_Letter('Hello World')
First_Letter(['Not', 'A', 'String'])
4
Bad Type
H
Bad Type