In Python, a Decorator is a type of macro that allows you to inject or modify code in functions or classes. I was turned onto this by my friend Matt Chapman at ILM, but never fully grasped the importance.

class myDecorator(object):
    def __init__(self, f):
        self.f = f
    def __call__(self):
        print "Entering", self.f.__name__
        print "Exited", self.f.__name__

def aFunction():
    print "aFunction running"


When you run the code above you will see the following:

>>Entering aFunction
>>aFunction running
>>Exited aFunction

So when we call a decorated function, we get a completely different behavior. You can wrap any existing functions, here is an example of wrapping functions for error reporting:

class catchAll:
    def __init__(self, function):
        self.function = function

    def __call__(self, *args):
            return self.function(*args)
        except Exception, e:
            print "Error: %s" % (e)

def unsafe(x):
  return 1 / x

print "unsafe(1): ", unsafe(1)
print "unsafe(0): ", unsafe(0)

So when we run this and divide by zero we get:

unsafe(1):  1
unsafe(0):  Error: integer division or modulo by zero

Using decorators you can make sweeping changes to existing code with minimal effort, like the error reporting function above, you could go back and just sprinkle these in older code.

Example #1: Calculate how much time a function takes to execute.

import time

def timing_function(some_function):
    Outputs the time a function takes to execute.
    def wrapper():
        t1 = time.time()
        t2 = time.time()
        return "Time it took to run the function: " + str((t2-t1)) + "\n"
    return wrapper

def my_function():
    num_list = []
    for x in (range(0,10000)):
    print "\nSum of all the numbers: " +str((sum(num_list)))

print my_function()

This returns the time before you run my_function() as well as the time after. Then we simply subtract the two to see how long it took to run the function.

Example #2: Rate limiting the call to a function.

from time import sleep

def sleep_decorator(function):
Limits how fast the function is called.
    def wrapper(*args, **kwargs):
        return function(*args, **kwargs)
    return wrapper

def print_number(num):
    return num

print print_number(222)

for x in range(1,6):
    print print_number(x)

This decorator is used for rate limiting.

These examples have beem taken from the great article Primer on Python Decorators, check it out!

Example 3: If you need to debug by printing out the arguments a function was called with, you could write this:

def argument_printer(func):
    def _wrapper(*args, **kwargs):
        print "Called with positional arguments: %s" % list(args)
        print "And with keyword arguments: %s" % kwargs
        return func(*args, **kwargs)
    return _wrapper

def add(x, y):
    return x + y

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