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Stack OverflowHow can I make a chain of function decorators in Python?
[+1321] [12] Imran
[2009-04-11 07:05:31]
[ python decorator python-decorators ]
[ http://stackoverflow.com/questions/739654/how-can-i-make-a-chain-of-function-decorators-in-python ]

How can I make two decorators in Python that would do the following?

@makebold
@makeitalic
def say():
   return "Hello"

which should return

<b><i>Hello</i></b>

I'm not trying to make HTML this way in a real application, just trying to understand how decorators and decorator chaining works.

(16) Here's the most 'a-ha!' answer I've found so far: pythonconquerstheuniverse.wordpress.com/2012/04/29/… - takosuke
(3) If you need more help with decorators and annotations see my blog post here. blog.mattalcock.com/2013/1/5/decorates-and-annotations - Matt Alcock
(1) Adding a link: Understanding Python Decorators in 12 Easy Steps! - Grijesh Chauhan
[+2613] [2009-10-20 13:05:46] e-satis

If you are not into long explanations, see Paolo Bergantino’s answer [1].

Decorator Basics

Python’s functions are objects

To understand decorators, you must first understand that functions are objects in Python. This has important consequences. Let’s see why with a simple example :

def shout(word="yes"):
    return word.capitalize()+"!"

print shout()
# outputs : 'Yes!'

# As an object, you can assign the function to a variable like any
# other object 

scream = shout

# Notice we don't use parentheses: we are not calling the function, we are
# putting the function "shout" into the variable "scream". 
# It means you can then call "shout" from "scream":

print scream()
# outputs : 'Yes!'

# More than that, it means you can remove the old name 'shout', and
# the function will still be accessible from 'scream'

del shout
try:
    print shout()
except NameError, e:
    print e
    #outputs: "name 'shout' is not defined"

print scream()
# outputs: 'Yes!'

Okay! Keep this in mind. We’ll circle back to it shortly.

Another interesting property of Python functions is they can be defined... inside another function!

def talk():

    # You can define a function on the fly in "talk" ...
    def whisper(word="yes"):
        return word.lower()+"..."

    # ... and use it right away!

    print whisper()

# You call "talk", that defines "whisper" EVERY TIME you call it, then
# "whisper" is called in "talk". 
talk()
# outputs: 
# "yes..."

# But "whisper" DOES NOT EXIST outside "talk":

try:
    print whisper()
except NameError, e:
    print e
    #outputs : "name 'whisper' is not defined"*
    Python's functions are objects

Functions references

Okay, still here? Now the fun part...

You’ve seen that functions are objects. Therefore, functions:

  • can be assigned to a variable
  • can be defined in another function

That means that a function can return another function. Have a look! ☺

def getTalk(kind="shout"):

    # We define functions on the fly
    def shout(word="yes"):
        return word.capitalize()+"!"

    def whisper(word="yes") :
        return word.lower()+"...";

    # Then we return one of them
    if kind == "shout":
        # We don't use "()", we are not calling the function,
        # we are returning the function object
        return shout  
    else:
        return whisper

# How do you use this strange beast?

# Get the function and assign it to a variable
talk = getTalk()      

# You can see that "talk" is here a function object:
print talk
#outputs : <function shout at 0xb7ea817c>

# The object is the one returned by the function:
print talk()
#outputs : Yes!

# And you can even use it directly if you feel wild:
print getTalk("whisper")()
#outputs : yes...

But wait...there’s more!

If you can return a function, you can pass one as a parameter:

def doSomethingBefore(func): 
    print "I do something before then I call the function you gave me"
    print func()

doSomethingBefore(scream)
#outputs: 
#I do something before then I call the function you gave me
#Yes!

Well, you just have everything needed to understand decorators. You see, decorators are “wrappers”, which means that they let you execute code before and after the function they decorate without modifying the function itself.

Handcrafted decorators

How you’d do it manually:

# A decorator is a function that expects ANOTHER function as parameter
def my_shiny_new_decorator(a_function_to_decorate):

    # Inside, the decorator defines a function on the fly: the wrapper.
    # This function is going to be wrapped around the original function
    # so it can execute code before and after it.
    def the_wrapper_around_the_original_function():

        # Put here the code you want to be executed BEFORE the original 
        # function is called
        print "Before the function runs"

        # Call the function here (using parentheses)
        a_function_to_decorate()

        # Put here the code you want to be executed AFTER the original 
        # function is called
        print "After the function runs"

    # At this point, "a_function_to_decorate" HAS NEVER BEEN EXECUTED.
    # We return the wrapper function we have just created.
    # The wrapper contains the function and the code to execute before
    # and after. It’s ready to use!
    return the_wrapper_around_the_original_function

# Now imagine you create a function you don't want to ever touch again.
def a_stand_alone_function():
    print "I am a stand alone function, don't you dare modify me"

a_stand_alone_function() 
#outputs: I am a stand alone function, don't you dare modify me

# Well, you can decorate it to extend its behavior.
# Just pass it to the decorator, it will wrap it dynamically in 
# any code you want and return you a new function ready to be used:

a_stand_alone_function_decorated = my_shiny_new_decorator(a_stand_alone_function)
a_stand_alone_function_decorated()
#outputs:
#Before the function runs
#I am a stand alone function, don't you dare modify me
#After the function runs

Now, you probably want that every time you call a_stand_alone_function, a_stand_alone_function_decorated is called instead. That’s easy, just overwrite a_stand_alone_function with the function returned by my_shiny_new_decorator:

a_stand_alone_function = my_shiny_new_decorator(a_stand_alone_function)
a_stand_alone_function()
#outputs:
#Before the function runs
#I am a stand alone function, don't you dare modify me
#After the function runs

# And guess what? That’s EXACTLY what decorators do!

Decorators demystified

The previous example, using the decorator syntax:

@my_shiny_new_decorator
def another_stand_alone_function():
    print "Leave me alone"

another_stand_alone_function()  
#outputs:  
#Before the function runs
#Leave me alone
#After the function runs

Yes, that’s all, it’s that simple. @decorator is just a shortcut to:

another_stand_alone_function = my_shiny_new_decorator(another_stand_alone_function)

Decorators are just a pythonic variant of the decorator design pattern [2]. There are several classic design patterns embedded in Python to ease development (like iterators).

Of course, you can accumulate decorators:

def bread(func):
    def wrapper():
        print "</''''''\>"
        func()
        print "<\______/>"
    return wrapper

def ingredients(func):
    def wrapper():
        print "#tomatoes#"
        func()
        print "~salad~"
    return wrapper

def sandwich(food="--ham--"):
    print food

sandwich()
#outputs: --ham--
sandwich = bread(ingredients(sandwich))
sandwich()
#outputs:
#</''''''\>
# #tomatoes#
# --ham--
# ~salad~
#<\______/>

Using the Python decorator syntax:

@bread
@ingredients
def sandwich(food="--ham--"):
    print food

sandwich()
#outputs:
#</''''''\>
# #tomatoes#
# --ham--
# ~salad~
#<\______/>

The order you set the decorators MATTERS:

@ingredients
@bread
def strange_sandwich(food="--ham--"):
    print food

strange_sandwich()
#outputs:
##tomatoes#
#</''''''\>
# --ham--
#<\______/>
# ~salad~

Now: to answer the question...

As a conclusion, you can easily see how to answer the question:

# The decorator to make it bold
def makebold(fn):
    # The new function the decorator returns
    def wrapper():
        # Insertion of some code before and after
        return "<b>" + fn() + "</b>"
    return wrapper

# The decorator to make it italic
def makeitalic(fn):
    # The new function the decorator returns
    def wrapper():
        # Insertion of some code before and after
        return "<i>" + fn() + "</i>"
    return wrapper

@makebold
@makeitalic
def say():
    return "hello"

print say() 
#outputs: <b><i>hello</i></b>

# This is the exact equivalent to 
def say():
    return "hello"
say = makebold(makeitalic(say))

print say() 
#outputs: <b><i>hello</i></b>

You can now just leave happy, or burn your brain a little bit more and see advanced uses of decorators.


Taking decorators to the next level

Passing arguments to the decorated function

# It’s not black magic, you just have to let the wrapper 
# pass the argument:

def a_decorator_passing_arguments(function_to_decorate):
    def a_wrapper_accepting_arguments(arg1, arg2):
        print "I got args! Look:", arg1, arg2
        function_to_decorate(arg1, arg2)
    return a_wrapper_accepting_arguments

# Since when you are calling the function returned by the decorator, you are
# calling the wrapper, passing arguments to the wrapper will let it pass them to 
# the decorated function

@a_decorator_passing_arguments
def print_full_name(first_name, last_name):
    print "My name is", first_name, last_name

print_full_name("Peter", "Venkman")
# outputs:
#I got args! Look: Peter Venkman
#My name is Peter Venkman

Decorating methods

One nifty thing about Python is that methods and functions are really the same. The only difference is that methods expect that their first argument is a reference to the current object (self).

That means you can build a decorator for methods the same way! Just remember to take self into consideration:

def method_friendly_decorator(method_to_decorate):
    def wrapper(self, lie):
        lie = lie - 3 # very friendly, decrease age even more :-)
        return method_to_decorate(self, lie)
    return wrapper


class Lucy(object):

    def __init__(self):
        self.age = 32

    @method_friendly_decorator
    def sayYourAge(self, lie):
        print "I am %s, what did you think?" % (self.age + lie)

l = Lucy()
l.sayYourAge(-3)
#outputs: I am 26, what did you think?

If you’re making general-purpose decorator--one you’ll apply to any function or method, no matter its arguments--then just use *args, **kwargs:

def a_decorator_passing_arbitrary_arguments(function_to_decorate):
    # The wrapper accepts any arguments
    def a_wrapper_accepting_arbitrary_arguments(*args, **kwargs):
        print "Do I have args?:"
        print args
        print kwargs
        # Then you unpack the arguments, here *args, **kwargs
        # If you are not familiar with unpacking, check:
        # http://www.saltycrane.com/blog/2008/01/how-to-use-args-and-kwargs-in-python/
        function_to_decorate(*args, **kwargs)
    return a_wrapper_accepting_arbitrary_arguments

@a_decorator_passing_arbitrary_arguments
def function_with_no_argument():
    print "Python is cool, no argument here."

function_with_no_argument()
#outputs
#Do I have args?:
#()
#{}
#Python is cool, no argument here.

@a_decorator_passing_arbitrary_arguments
def function_with_arguments(a, b, c):
    print a, b, c

function_with_arguments(1,2,3)
#outputs
#Do I have args?:
#(1, 2, 3)
#{}
#1 2 3 

@a_decorator_passing_arbitrary_arguments
def function_with_named_arguments(a, b, c, platypus="Why not ?"):
    print "Do %s, %s and %s like platypus? %s" %\
    (a, b, c, platypus)

function_with_named_arguments("Bill", "Linus", "Steve", platypus="Indeed!")
#outputs
#Do I have args ? :
#('Bill', 'Linus', 'Steve')
#{'platypus': 'Indeed!'}
#Do Bill, Linus and Steve like platypus? Indeed!

class Mary(object):

    def __init__(self):
        self.age = 31

    @a_decorator_passing_arbitrary_arguments
    def sayYourAge(self, lie=-3): # You can now add a default value
        print "I am %s, what did you think ?" % (self.age + lie)

m = Mary()
m.sayYourAge()
#outputs
# Do I have args?:
#(<__main__.Mary object at 0xb7d303ac>,)
#{}
#I am 28, what did you think?

Passing arguments to the decorator

Great, now what would you say about passing arguments to the decorator itself?

This can get somewhat twisted, since a decorator must accept a function as an argument. Therefore, you cannot pass the decorated function’s arguments directly to the decorator.

Before rushing to the solution, let’s write a little reminder:

# Decorators are ORDINARY functions
def my_decorator(func):
    print "I am an ordinary function"
    def wrapper():
        print "I am function returned by the decorator"
        func()
    return wrapper

# Therefore, you can call it without any "@"

def lazy_function():
    print "zzzzzzzz"

decorated_function = my_decorator(lazy_function)
#outputs: I am an ordinary function

# It outputs "I am an ordinary function", because that’s just what you do:
# calling a function. Nothing magic.

@my_decorator
def lazy_function():
    print "zzzzzzzz"

#outputs: I am an ordinary function

It’s exactly the same. "my_decorator" is called. So when you @my_decorator, you are telling Python to call the function 'labelled by the variable "my_decorator"'.

This is important! The label you give can point directly to the decorator—or not.

Let’s get evil. ☺

def decorator_maker():

    print "I make decorators! I am executed only once: "+\
          "when you make me create a decorator."

    def my_decorator(func):

        print "I am a decorator! I am executed only when you decorate a function."

        def wrapped():
            print ("I am the wrapper around the decorated function. "
                  "I am called when you call the decorated function. "
                  "As the wrapper, I return the RESULT of the decorated function.")
            return func()

        print "As the decorator, I return the wrapped function."

        return wrapped

    print "As a decorator maker, I return a decorator"
    return my_decorator

# Let’s create a decorator. It’s just a new function after all.
new_decorator = decorator_maker()       
#outputs:
#I make decorators! I am executed only once: when you make me create a decorator.
#As a decorator maker, I return a decorator

# Then we decorate the function

def decorated_function():
    print "I am the decorated function."

decorated_function = new_decorator(decorated_function)
#outputs:
#I am a decorator! I am executed only when you decorate a function.
#As the decorator, I return the wrapped function

# Let’s call the function:
decorated_function()
#outputs:
#I am the wrapper around the decorated function. I am called when you call the decorated function.
#As the wrapper, I return the RESULT of the decorated function.
#I am the decorated function.

No surprise here.

Let’s do EXACTLY the same thing, but skip all the pesky intermediate variables:

def decorated_function():
    print "I am the decorated function."
decorated_function = decorator_maker()(decorated_function)
#outputs:
#I make decorators! I am executed only once: when you make me create a decorator.
#As a decorator maker, I return a decorator
#I am a decorator! I am executed only when you decorate a function.
#As the decorator, I return the wrapped function.

# Finally:
decorated_function()    
#outputs:
#I am the wrapper around the decorated function. I am called when you call the decorated function.
#As the wrapper, I return the RESULT of the decorated function.
#I am the decorated function.

Let’s make it even shorter:

@decorator_maker()
def decorated_function():
    print "I am the decorated function."
#outputs:
#I make decorators! I am executed only once: when you make me create a decorator.
#As a decorator maker, I return a decorator
#I am a decorator! I am executed only when you decorate a function.
#As the decorator, I return the wrapped function.

#Eventually: 
decorated_function()    
#outputs:
#I am the wrapper around the decorated function. I am called when you call the decorated function.
#As the wrapper, I return the RESULT of the decorated function.
#I am the decorated function.

Hey, did you see that? We used a function call with the "@" syntax! :-)

So, back to decorators with arguments. If we can use functions to generate the decorator on the fly, we can pass arguments to that function, right?

def decorator_maker_with_arguments(decorator_arg1, decorator_arg2):

    print "I make decorators! And I accept arguments:", decorator_arg1, decorator_arg2

    def my_decorator(func):
        # The ability to pass arguments here is a gift from closures.
        # If you are not comfortable with closures, you can assume it’s ok,
        # or read: http://stackoverflow.com/questions/13857/can-you-explain-closures-as-they-relate-to-python
        print "I am the decorator. Somehow you passed me arguments:", decorator_arg1, decorator_arg2

        # Don't confuse decorator arguments and function arguments!
        def wrapped(function_arg1, function_arg2) :
            print ("I am the wrapper around the decorated function.\n"
                  "I can access all the variables\n"
                  "\t- from the decorator: {0} {1}\n"
                  "\t- from the function call: {2} {3}\n"
                  "Then I can pass them to the decorated function"
                  .format(decorator_arg1, decorator_arg2,
                          function_arg1, function_arg2))
            return func(function_arg1, function_arg2)

        return wrapped

    return my_decorator

@decorator_maker_with_arguments("Leonard", "Sheldon")
def decorated_function_with_arguments(function_arg1, function_arg2):
    print ("I am the decorated function and only knows about my arguments: {0}"
           " {1}".format(function_arg1, function_arg2))

decorated_function_with_arguments("Rajesh", "Howard")
#outputs:
#I make decorators! And I accept arguments: Leonard Sheldon
#I am the decorator. Somehow you passed me arguments: Leonard Sheldon
#I am the wrapper around the decorated function. 
#I can access all the variables 
#   - from the decorator: Leonard Sheldon 
#   - from the function call: Rajesh Howard 
#Then I can pass them to the decorated function
#I am the decorated function and only knows about my arguments: Rajesh Howard

Here it is: a decorator with arguments. Arguments can be set as variable:

c1 = "Penny"
c2 = "Leslie"

@decorator_maker_with_arguments("Leonard", c1)
def decorated_function_with_arguments(function_arg1, function_arg2):
    print ("I am the decorated function and only knows about my arguments:"
           " {0} {1}".format(function_arg1, function_arg2))

decorated_function_with_arguments(c2, "Howard")
#outputs:
#I make decorators! And I accept arguments: Leonard Penny
#I am the decorator. Somehow you passed me arguments: Leonard Penny
#I am the wrapper around the decorated function. 
#I can access all the variables 
#   - from the decorator: Leonard Penny 
#   - from the function call: Leslie Howard 
#Then I can pass them to the decorated function
#I am the decorated function and only knows about my arguments: Leslie Howard

As you can see, you can pass arguments to the decorator like any function using this trick. You can even use *args, **kwargs if you wish. But remember decorators are called only once. Just when Python imports the script. You can't dynamically set the arguments afterwards. When you do "import x", the function is already decorated, so you can't change anything.


Let’s practice: decorating a decorator

Okay, as a bonus, I'll give you a snippet to make any decorator accept generically any argument. After all, in order to accept arguments, we created our decorator using another function.

We wrapped the decorator.

Anything else we saw recently that wrapped function?

Oh yes, decorators!

Let’s have some fun and write a decorator for the decorators:

def decorator_with_args(decorator_to_enhance):
    """ 
    This function is supposed to be used as a decorator.
    It must decorate an other function, that is intended to be used as a decorator.
    Take a cup of coffee.
    It will allow any decorator to accept an arbitrary number of arguments,
    saving you the headache to remember how to do that every time.
    """

    # We use the same trick we did to pass arguments
    def decorator_maker(*args, **kwargs):

        # We create on the fly a decorator that accepts only a function
        # but keeps the passed arguments from the maker.
        def decorator_wrapper(func):

            # We return the result of the original decorator, which, after all, 
            # IS JUST AN ORDINARY FUNCTION (which returns a function).
            # Only pitfall: the decorator must have this specific signature or it won't work:
            return decorator_to_enhance(func, *args, **kwargs)

        return decorator_wrapper

    return decorator_maker

It can be used as follows:

# You create the function you will use as a decorator. And stick a decorator on it :-)
# Don't forget, the signature is "decorator(func, *args, **kwargs)"
@decorator_with_args 
def decorated_decorator(func, *args, **kwargs): 
    def wrapper(function_arg1, function_arg2):
        print "Decorated with", args, kwargs
        return func(function_arg1, function_arg2)
    return wrapper

# Then you decorate the functions you wish with your brand new decorated decorator.

@decorated_decorator(42, 404, 1024)
def decorated_function(function_arg1, function_arg2):
    print "Hello", function_arg1, function_arg2

decorated_function("Universe and", "everything")
#outputs:
#Decorated with (42, 404, 1024) {}
#Hello Universe and everything

# Whoooot!

I know, the last time you had this feeling, it was after listening a guy saying: "before understanding recursion, you must first understand recursion". But now, don't you feel good about mastering this?


Best practices: decorators

  • Decorators were introduced in Python 2.4, so be sure your code will be run on >= 2.4.
  • Decorators slow down the function call. Keep that in mind.
  • You cannot un-decorate a function. (There are hacks to create decorators that can be removed, but nobody uses them.) So once a function is decorated, it’s decorated for all the code.
  • Decorators wrap functions, which can make them hard to debug. (This gets better from Python >= 2.5; see below.)

The functools module was introduced in Python 2.5. It includes the function functools.wraps(), which copies the name, module, and docstring of the decorated function to its wrapper.

(Fun fact: functools.wraps() is a decorator! ☺)

# For debugging, the stacktrace prints you the function __name__
def foo():
    print "foo"

print foo.__name__
#outputs: foo

# With a decorator, it gets messy    
def bar(func):
    def wrapper():
        print "bar"
        return func()
    return wrapper

@bar
def foo():
    print "foo"

print foo.__name__
#outputs: wrapper

# "functools" can help for that

import functools

def bar(func):
    # We say that "wrapper", is wrapping "func"
    # and the magic begins
    @functools.wraps(func)
    def wrapper():
        print "bar"
        return func()
    return wrapper

@bar
def foo():
    print "foo"

print foo.__name__
#outputs: foo

How can the decorators be useful?

Now the big question: What can I use decorators for?

Seem cool and powerful, but a practical example would be great. Well, there are 1000 possibilities. Classic uses are extending a function behavior from an external lib (you can't modify it), or for debugging (you don't want to modify it because it’s temporary).

You can use them to extend several functions in a DRY’s way, like so:

def benchmark(func):
    """
    A decorator that prints the time a function takes
    to execute.
    """
    import time
    def wrapper(*args, **kwargs):
        t = time.clock()
        res = func(*args, **kwargs)
        print func.__name__, time.clock()-t
        return res
    return wrapper


def logging(func):
    """
    A decorator that logs the activity of the script.
    (it actually just prints it, but it could be logging!)
    """
    def wrapper(*args, **kwargs):
        res = func(*args, **kwargs)
        print func.__name__, args, kwargs
        return res
    return wrapper


def counter(func):
    """
    A decorator that counts and prints the number of times a function has been executed
    """
    def wrapper(*args, **kwargs):
        wrapper.count = wrapper.count + 1
        res = func(*args, **kwargs)
        print "{0} has been used: {1}x".format(func.__name__, wrapper.count)
        return res
    wrapper.count = 0
    return wrapper

@counter
@benchmark
@logging
def reverse_string(string):
    return str(reversed(string))

print reverse_string("Able was I ere I saw Elba")
print reverse_string("A man, a plan, a canoe, pasta, heros, rajahs, a coloratura, maps, snipe, percale, macaroni, a gag, a banana bag, a tan, a tag, a banana bag again (or a camel), a crepe, pins, Spam, a rut, a Rolo, cash, a jar, sore hats, a peon, a canal: Panama!")

#outputs:
#reverse_string ('Able was I ere I saw Elba',) {}
#wrapper 0.0
#wrapper has been used: 1x 
#ablE was I ere I saw elbA
#reverse_string ('A man, a plan, a canoe, pasta, heros, rajahs, a coloratura, maps, snipe, percale, macaroni, a gag, a banana bag, a tan, a tag, a banana bag again (or a camel), a crepe, pins, Spam, a rut, a Rolo, cash, a jar, sore hats, a peon, a canal: Panama!',) {}
#wrapper 0.0
#wrapper has been used: 2x
#!amanaP :lanac a ,noep a ,stah eros ,raj a ,hsac ,oloR a ,tur a ,mapS ,snip ,eperc a ,)lemac a ro( niaga gab ananab a ,gat a ,nat a ,gab ananab a ,gag a ,inoracam ,elacrep ,epins ,spam ,arutaroloc a ,shajar ,soreh ,atsap ,eonac a ,nalp a ,nam A

Of course the good thing with decorators is that you can use them right away on almost anything without rewriting. DRY, I said:

@counter
@benchmark
@logging
def get_random_futurama_quote():
    from urllib import urlopen
    result = urlopen("http://subfusion.net/cgi-bin/quote.pl?quote=futurama").read()
    try:
        value = result.split("<br><b><hr><br>")[1].split("<br><br><hr>")[0]
        return value.strip()
    except:
        return "No, I'm ... doesn't!"


print get_random_futurama_quote()
print get_random_futurama_quote()

#outputs:
#get_random_futurama_quote () {}
#wrapper 0.02
#wrapper has been used: 1x
#The laws of science be a harsh mistress.
#get_random_futurama_quote () {}
#wrapper 0.01
#wrapper has been used: 2x
#Curse you, merciful Poseidon!

Python itself provides several decorators: property, staticmethod, etc.

  • Django uses decorators to manage caching and view permissions.
  • Twisted to fake inlining asynchronous functions calls.

This really is a large playground.

[1] http://stackoverflow.com/questions/739654/understanding-python-decorators#answer-739665
[2] http://en.wikipedia.org/wiki/Decorator_pattern

(48) You wrote this somewhere else or disabled the javascript preview to write this, didn't you? - voyager
(11) @voyager : I have the FF add-on "It's all text". @gath1 : I can only explain something that way if I put some handcrafted code using the concept in production. It's not the case with metaclass yet. - e-satis
(274) thank you, it's one of the best answers I have ever encountered on SO. - alexandrul
(4) Great answer, helped me understand decorators a lot better than I did before! - David Reynolds
I think there is a typo in here: # Get the function and assign it to a variable talk = getTalk(). It should read talk = getTalk, without the parenthesis. - user126284
(2) Nope. Read the example again. - e-satis
(3) Nice. You taught me HOW to fish with answer! Thanks for the time spent. - Dustin
(11) I can only give one vote. Could have given 10 more if allowed. Well done. Thanks. - Mohsin Hijazee
(2) Woah, woah, woah! I can't digest that much knowledge so fast! Excellent answer, thanks :). - Gerardo Marset
Thanks you all. I listen to @gath and made a similar anwser about metaclasses. I added a link to it at the end of the post. - e-satis
(27) As somebody who is not new to programming (C, bash, sed, awk) but just starting to learn python due to its sheer power, I feel like this post just leveled me up 10x. It's like stumbling upon a mid-game item in the first hour of gameplay and making a mockery out of the NPCs for the next week of play. - SiegeX
(2) There is no memoize decorator provided by Python. I definitely had to write my own, because I couldn't find it in the standard library. For what its worth: pastebin.com/2TRkCGYY - Nick Zalutskiy
My mistake. I'm so used to Django I missed the fact that it's a django goodies: from django.utils.functional import memoize. - e-satis
(7) Actually, I started writting a book :-p. Wether or not I finish it is a whole other issue. - e-satis
(4) Your examples are sublime. I wish I could give +1 for each little nugget of awesome: the "strange sandwich", the age-regressing woman, the epic palindrome... Book deal indeed! - Justin ᚅᚔᚈᚄᚒᚔ
It feels really good to still have such friendly comments so long after having written this answer. Thank you all. - e-satis
(2) I'm reading all of your (excellent) answers. I agree with the rest: where's the book already? - juliomalegria
(1) Going ou mid next year... in France :-p - e-satis
(1) At the risk of being a jerk, there's still so much that this answer doesn't cover: what about class-based decorators? What about decorators that can work with either functions or class methods? What about all of the above, but with decorators that take arguments? - Adam Parkin
(2) Sure. And decorators that act like context managers as well. Decorators are a broad subject in Python. You can always ask these questions, I'll be please to answer them if I notice them. - e-satis
@e-satis: ok, done: stackoverflow.com/questions/9416947/… :D Thanks! - Adam Parkin
Wouldn't it be better to attach the count to the wrapper, instead of to the decorator? Otherwise the behavior of counter doesn't quite match the docstring: it displays the number of times the counter is used for any function. I added my own 2c below. - marqueed
@marqueed: right. fixed. - e-satis
@e-satis: well, now you'll have the same behavior if you decorate a function twice, like fc1 = counter(func); fc2 = counter(func). You could instead set count on wrapped, but I can't think of a lot of reasons why you'd want to do what I described, anyway. Thanks for a great explanation! - marqueed
@marqueed: Good point. - e-satis
(2) Maybe I should add a note about that: your comment has a real added value to the post. It shows a very common issue with decorators: one can easily get confused with the reference to the wrapper, the decorator and the wrapped function. And order matters. - e-satis
I am missing an important part about using decorators - it messes with func.__name__ and func.__doc__ - and how to solve this problem (for example with functools.wraps). - schlamar
What part of "Best practices while using decorators" is lacking of the information you need ? - e-satis
Whoa! Decorators now stand in front of me like a mice, so tiny and puny. Thanks for the excellent explanation. - tushartyagi
this really helped improved my understand of python decorators... although,i might need to read this again, the advanced part just all went over my head. and Thank you! - ultrajohn
+1 for the "able was I ere I saw Elba". Until now I thought I was the only one that knew that. Anyway, also the explanations is really good :) - Bakuriu
Tried to make an edit: "outputs : Yes!" for the first print talk() line in section 2: Functions references. --X-[-But I get the message: body is limited to 30000 characters; you entered 30006.---]- Also added indentation spaces which was causing the problem. Edit made. - aneroid
(2) I wish I could "follow" people on SO so I could see all your recent answers whenever I hit the main page. - katy lavallee
(1) You are so brilliant in explaining things to layman..Love it..Hope I have the same skill and patience.. - user1050619
(1) I was convinced this was Peter Norvig answering as I read this, but wrong. An excellent answer, thank you very much. - Sean
(2) This is a article more than a answer. - jtianling
@e-satis. can you also add the explanation for class decorators as well. You have made so sticky that now i can't understand from anyhwere else beside your explanantions :) - user2134226
Just wow. I think I just doubled my Python-fu. PS. get_random_futurama_quote is misspelled as get_random_furturama_quote in the last example. - nikc.org
What a great post!. Just one thing, import time should be outside benchmark as it is going to be called each time the decorator is applied. - jmdana
(1) @hiwaylon: This guy would never be given a book deal, because he explains too well too short. Books always have to be 400 pages lol. Thanks a lot for this short and well explained tutorial! I've read it twice already, just to refresh :P - Sam Stoelinga
(1) This is the best answer to a SO question I have ever seen. Thank you very much, you just made my programming problem MUCH easier! - Leo
One more example to use decorators I link here - Grijesh Chauhan
(1) @NikolayZalutskiy: There is a memoization decorator at functools.lru_cache. - Kritzefitz
@IchUndNichtDu "New in version 3.2" Good to know though, thank you. - Nick Zalutskiy
(3) Can you please stop changing the style of the writting ? I know it's a community site, but since I took a LONG time to write that, I'd like to at least have it written the way I said it, even if it does not fit your idea of perfection. - e-satis
Well done brother.. I hope it helped hundreds and thousands of the people like me... - Tirthajust4u
Is it possible to use a base class method as a decorator in derived classes? - gliese581g
Hey @e-satis, I couldn't find anything about it online, hence I ask it here… Did you ever publish the book you mentioned? Even if it's only published in French, I'd just learn that language to read your book. This answer is amazing. - timvermeulen
(1) Got one chapter left to write. But it's for python beginers. - e-satis
Oh okay :) So, you won't be covering stuff similar to what you did in this answer? - timvermeulen
(1) Not in the first book, but if I got a good feedback for it, I'll make a book with advanced Python tricks only, with the same style of writting. Although, it's not for tomorrow. - e-satis
@e-satis I recommend flagging this answer to have the "community wiki" removed. It is an acceptable request, and it could end your rollback war. - Honest Abe
(1) @Zearin "Editing is welcomed and encouraged. However, if the author of the post is resistant to your editing changes, even a perfectly legitimate edit... be the bigger man (or woman) and let them have it their way. Our goal here is not to cause friction between users, or to make everything perfect overnight. All we aim to do is gradually clean up and improve questions and answers together. When in doubt, just move on! There will be plenty of other posts and other edits you can make." - Jeff Atwood (source) - Honest Abe
I though about it, but then I realized the community in SO has now changed a lot and is not the friendly and fun community it started with. I just decided to give up. I won't write on So anymore. - e-satis
I obvously don't mean there are not competent friendly people like you anymore on the site, I'm just saying the ratio mindless-drone / nice guys on the site just went above my tolerance limit. - e-satis
@HonestAbe Whoa. (1) I want to thank you for the excellent (sourced!) quote. (2) I remember this article, but I edited it a while ago. I honestly don’t remember much about it; if I behaved stubbornly, then I apologize to anyone for whom I caused friction. Especially for this answer! The one thing I do recall is that this is almost certainly among the best answers on all of SO. - Zearin
@e-satis My memory regarding this article is a bit fuzzy, but if I started an edit war back when I was editing this article, I’m sorry. I do hold some very strong opinions about grammar, good formatting, the use of headings, etc… It’s very possible I let those opinions get the better of me when I edited this, and I didn’t mean to piss anyone off. I usually try to avoid pissing people off whenever possible, but I can easily get pretty obsessive about editing, so that’s where I was coming from. I’m not a mindless drone—promise! Communities change, but please don’t become jaded on my account. - Zearin
@e-satis I just checked the history, and saw what I did. I really do love this answer! I had hoped to make it even better for other readers, but I disrespected your wishes in the process. I apologize for that. I’d like to talk to you more off-site! Please contact me via Gmail; my gmail username is ''.join(['t','good','child']). :) - Zearin
(1) It's ok. It's not you in particular. Thanks for you friendlyness. No need to use emails. - e-satis
A great explanation for decorator. I was looking for the same and this post explained me A2Z of decorator. Thanks for this. - G Mann
Insanely great answer! Thank you! - the.malkolm
1
[+1895] [2009-04-11 07:16:18] Paolo Bergantino [ACCEPTED]

Check out the documentation [1] to see how decorators work. Here is what you asked for:

def makebold(fn):
    def wrapped():
        return "<b>" + fn() + "</b>"
    return wrapped

def makeitalic(fn):
    def wrapped():
        return "<i>" + fn() + "</i>"
    return wrapped

@makebold
@makeitalic
def hello():
    return "hello world"

print hello() ## returns <b><i>hello world</i></b>
[1] http://docs.python.org/reference/compound%5Fstmts.html#function

(122) Consider using functools.wraps or, better yet, the decorator module from PyPI: they preserve certain important metadata (such as __name__ and, speaking about the decorator package, function signature). - Marius Gedminas
(26) What the hell! Most elaborate to the point explanation on Python decorators. Well done! - Mohsin Hijazee
@dosomething applies to the function defined below it, right? - Kwpolska
(16) Finally I understand them. And more importantly, why to use them. Thanks Paolo Bergantino. - Alan
WOW BEST Decorator Example Ever! all the books i bought cant give clear example like you do Thanks A LOT! - V3ss0n
(1) a bunch of useful decorators on the python wiki: wiki.python.org/moin/PythonDecorators - Naveen
(2) Finally, an example that's real and makes sense. Your main function is being decorated. I want my main function to receive a zipped dictionary, so I can pull out database row column values by name, rather than relying on index position. Thanks. - octopusgrabbus
Can you declare decorator functions in a parent class and use it in a child class? - rdodev
2
[+85] [2009-04-11 07:32:15] Trevor

Alternatively, you could write a factory function which return a decorator which wraps the return value of the decorated function in a tag passed to the factory function. For example:

from functools import wraps

def wrap_in_tag(tag):
    def factory(func):
        @wraps(func)
        def decorator():
            return '<%(tag)s>%(rv)s</%(tag)s>' % (
                {'tag': tag, 'rv': func()})
        return decorator
    return factory

This enables you to write:

@wrap_in_tag('b')
@wrap_in_tag('i')
def say():
    return 'hello'

or

makebold = wrap_in_tag('b')
makeitalic = wrap_in_tag('i')

@makebold
@makeitalic
def say():
    return 'hello'

Personally I would have written the decorator somewhat differently:

from functools import wraps

def wrap_in_tag(tag):
    def factory(func):
        @wraps(func)
        def decorator(val):
            return func('<%(tag)s>%(val)s</%(tag)s>' %
                        {'tag': tag, 'val': val})
        return decorator
    return factory

which would yield:

@wrap_in_tag('b')
@wrap_in_tag('i')
def say(val):
    return val
say('hello')

Don't forget the construction for which decorator syntax is a shorthand:

say = wrap_in_tag('b')(wrap_in_tag('i')(say)))

(3) This answer solved a question I had about passing parameters into a funtools.wraps decorator. Thanks - Kinlan
(6) This sentence, is absolutely correct, but made me chuckle: "Alternatively, you could write a factory function which return a decorator which wraps the return value of the decorated function in a tag passed to the factory function." - Agrajag
Even more generic. I love your wrap_in_tag technique. - Stephane Rolland
In my opinion, it is better to avoid more than one decorator as far as possible. If i had to write a factory function i would code it with *kwargs like def wrap_in_tag(*kwargs) then @wrap_in_tag('b','i') - guneysus
3
[+52] [2009-04-11 08:00:42] Unknown

It looks like the other people have already told you how to solve the problem. I hope this will help you understand what decorators are.

Decorators are just syntactical sugar.

This

@decorator
def func():
    ...

expands to

def func():
    ...
func = decorator(func)

(3) This is really the simplest explanation to what decorators do, I like it! - rednaw
(3) Actually these two examples are not exactly the same. Suppose func makes a recursive call to itself. In the first example, that recursive call invokes the decorated version; in the second, the undecorated version. So when decorating recursive functions, it's important to consider which behavior you want, and decorate it one way or the other. - wberry
@wberry No. A self-recursive call is not a special, it looks up the function to call in the surrounding context, just like any other function call. I just tried this and the first and second form both wrap all levels of recursion (on Python 2.6.6). - clacke
@clacke I don't have a 2.6 interpreter handy but in 2.7 the behavior is different. I used a decorator that prints "foo" but otherwise preserves behavior, and two identical factorial functions, one decorated and one manually wrapped as in this answer. The decorated one prints "foo" N times, the undecorated one prints it once. - wberry
(1) @wberry Ok, thanks for clarifying. Ha! I used a factorial function too. :-) - clacke
Probably one of the simplest and best explanations I have found till date on SO :) - Sushant Gupta
4
[+38] [2009-04-11 07:19:12] abhinav

Python decorators add extra functionality to another function

An italics decorator could be like

def makeitalic(fn):
    def newFunc():
        return "<i>" + fn() + "</i>"
    return newFunc

Note that a function is defined inside a function. What it basically does is replace a function with the newly defined one. For example, I have this class

class foo:
    def bar(self):
        print "hi"
    def foobar(self):
        print "hi again"

Now say, I want both functions to print "---" after and before they are done. I could add a print "---" before and after each print statement. But because I don't like repeating myself, I will make a decorator

def addDashes(fn): # notice it takes a function as an argument
    def newFunction(self): # define a new function
        print "---"
        fn(self) # call the original function
        print "---"
    return newFunction
    # Return the newly defined function - it will "replace" the original

So now I can change my class to

class foo:
    @addDashes
    def bar(self):
        print "hi"

    @addDashes
    def foobar(self):
        print "hi again"

For more on decorators, check http://www.ibm.com/developerworks/linux/library/l-cpdecor.html


Note as elegant as the lambda functions proposed by @Rune Kaagaard - rds
what is the work of self keyword here ? - Phoenix
(1) @Phoenix: The self argument is needed because the newFunction() defined in addDashes() was specifically designed to be a method decorator not a general function decorator. The self argument represents the class instance and is passed to class methods whether they use it or not -- see the section titled Decorating methods in @e-satis's answer. - martineau
5
[+37] [2010-10-25 06:18:12] Rune Kaagaard

And of course you can return lambdas as well from a decorator function:

def makebold(f): 
    return lambda: "<b>" + f() + "</b>"
def makeitalic(f): 
    return lambda: "<i>" + f() + "</i>"

@makebold
@makeitalic
def say():
    return "Hello"

print say()

(5) And one step further: makebold = lambda f : lambda "<b>" + f() + "</b>" - Robᵩ
(4) @Robᵩ: To be syntactically correct: makebold = lambda f: lambda: "<b>" + f() + "</b>" - martineau
6
[+10] [2011-12-26 06:13:01] qed

Another way of doing the same thing:

class bol(object):
  def __init__(self, f):
    self.f = f
  def __call__(self):
    return "<b>{}</b>".format(self.f())


class ita(object):
  def __init__(self, f):
    self.f = f
  def __call__(self):
    return "<i>{}</i>".format(self.f())


@bol
@ita
def sayhi():
  return 'hi'

Or, more flexibly:

class sty(object):
  def __init__(self, tag):
    self.tag = tag
  def __call__(self, f):
    def newf():
      return "<{tag}>{res}</{tag}>".format(res=f(), tag=self.tag)
    return newf


@sty('b')
@sty('i')
def sayhi():
  return 'hi'

7
[+6] [2012-07-26 16:11:42] Davoud Taghawi-Nejad

A decorator takes the function definition and creates a new function that executes this function and transforms the result.

@deco
def do():
    ...

is eqivarent to:

do = deco(do)

Example:

def deco(func):
    def inner(letter):
        return func(letter).upper()  #upper
    return inner

This

@deco
def do(number):
    return chr(number)  # number to letter

is eqivalent to this def do2(number): return chr(number)

do2 = deco(do2)

65 <=> 'a'

print(do(65))
print(do2(65))
>>> B
>>> B

To understand the decorator, it is important to notice, that decorator created a new function do which is inner that executes func and transforms the result.


8
[+2] [2012-03-02 21:47:17] marqueed

Speaking of the counter example - as given above, the counter will be shared between all functions that use the decorator:

def counter(func):
    def wrapped(*args, **kws):
        print 'Called #%i' % wrapped.count
        wrapped.count += 1
        return func(*args, **kws)
    wrapped.count = 0
    return wrapped

That way, your decorator can be reused for different functions (or used to decorate the same function multiple times: func_counter1 = counter(func); func_counter2 = counter(func)), and the counter variable will remain private to each.


9
[+2] [2013-06-17 04:43:25] Chris Seddon

Here is a simple example of chaining decorators. Note the last line - it shows what is going on under the covers.

############################################################
#
#    decorators
#
############################################################

def bold(fn):
    def decorate():
        # surround with bold tags before calling original function
        return "<b>" + fn() + "</b>"
    return decorate


def uk(fn):
    def decorate():
        # swap month and day
        fields = fn().split('/')
        date = fields[1] + "/" + fields[0] + "/" + fields[2]
        return date
    return decorate

import datetime
def getDate():
    now = datetime.datetime.now()
    return "%d/%d/%d" % (now.day, now.month, now.year)

@bold
def getBoldDate(): 
    return getDate()

@uk
def getUkDate():
    return getDate()

@bold
@uk
def getBoldUkDate():
    return getDate()


print getDate()
print getBoldDate()
print getUkDate()
print getBoldUkDate()
# what is happening under the covers
print bold(uk(getDate))()

The output looks like:

17/6/2013
<b>17/6/2013</b>
6/17/2013
<b>6/17/2013</b>
<b>6/17/2013</b>

10
[+1] [2013-04-05 18:18:08] rabin utam

Decorate functions with different number of arguments:

def frame_tests(fn):
    def wrapper(*args):
        print "\nStart: %s" %(fn.__name__)
        fn(*args)
        print "End: %s\n" %(fn.__name__)
    return wrapper

@frame_tests
def test_fn1():
    print "This is only a test!"

@frame_tests
def test_fn2(s1):
    print "This is only a test! %s" %(s1)

@frame_tests
def test_fn3(s1, s2):
    print "This is only a test! %s %s" %(s1, s2)

if __name__ == "__main__":
    test_fn1()
    test_fn2('OK!')
    test_fn3('OK!', 'Just a test!')

Result:

Start: test_fn1  
This is only a test!  
End: test_fn1  


Start: test_fn2  
This is only a test! OK!  
End: test_fn2  


Start: test_fn3  
This is only a test! OK! Just a test!  
End: test_fn3  

11
[+1] [2014-04-03 09:43:12] nickleefly
#decorator.py
def makeHtmlTag(tag, *args, **kwds):
    def real_decorator(fn):
        css_class = " class='{0}'".format(kwds["css_class"]) \
                                 if "css_class" in kwds else ""
        def wrapped(*args, **kwds):
            return "<"+tag+css_class+">" + fn(*args, **kwds) + "</"+tag+">"
        return wrapped
    # return decorator dont call it
    return real_decorator

@makeHtmlTag(tag="b", css_class="bold_css")
@makeHtmlTag(tag="i", css_class="italic_css")
def hello():
    return "hello world"

print hello()

You can also write decorator in Class

#class.py
class makeHtmlTagClass(object):

def __init__(self, tag, css_class=""):
    self._tag = tag
    self._css_class = " class='{0}'".format(css_class) \
                                   if css_class !="" else ""

def __call__(self, fn):
    def wrapped(*args, **kwargs):
        return "<" + self._tag + self._css_class+">"  \
                   + fn(*args, **kwargs) + "</" + self._tag + ">"
    return wrapped

@makeHtmlTagClass(tag="b", css_class="bold_css")
@makeHtmlTagClass(tag="i", css_class="italic_css")
def hello(name):
    return "Hello, {}".format(name)

print hello("Your name")

The reason to like a class here is that there is clearly related behavior, with two instances. You can actually get your two decorators by assigning the constructed classes to the names you wanted, rather than re-iterating the parameters. This is harder to do with a function. Adding it to the example would point out why this is not just redundant. - Jon Jay Obermark
12