Many beginners seem to take the concept of decorators as a fairly advanced and complex topic. It’s advanced alright but it probably is much simpler than you think.
Decorators Explained
Let’s say, we have a function which returns a message. But we want to also return the time with the message. So what can we do? We can modify the function’s source code to add the time with the message. But what if we can’t or don’t want to modify the source code but still want to extend/transform the functionality?
In that case, we can wrap it within another function, something like this:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 |
from datetime import datetime def greet(name): return "Greetings, {}!".format(name) def time_wrapper(fn): def new_function(*args, **kwargs): msg = fn(*args, **kwargs) new_msg = "Time: {} {} ".format(datetime.now(), msg) return new_msg return new_function greet = time_wrapper(greet) print(greet("masnun")) |
Here, greet
was our original function, which only returns a message but no time with it. So we be clever and write a wrapper – time_wrapper
. This wrapper function takes a function as it’s argument and returns the new_function
instead. This new function, when invoked, can access the original function we passed, get the message out and then add the time to it.
The interesting bit is here – greet = time_wrapper(greet)
. We’re passing greet
to time_wrapper
. The time_wrapper
function returns the new_function
. So greet
now points to the new_function
. When we call greet
, we actually call that function.
By definition, a Decorator is a callable
s which takes a callable
and returns a callable
. A callable
can be a few things but let’s not worry about that right now. In most cases, a decorator just takes a function, wraps it and returns the wrapped function. The wrapped function can access a reference to our original function and call it as necessary. In our case time_wrapper
is the decorator function which takes the greet
function and returns the new_function
.
The @
decorator syntax
But you might be wondering – “I see a lot of @
symbols while reading on decorators, how can there be a decorator without the @
?”. Well, before PEP 0318, we used to write decorators like that. But soon the wise people of the Python community realized that it would be a good idea to have a nicer syntax for decorators. So we got the @
. So how does the @
work?
1 2 3 4 5 6 7 |
@decorator_callable def awesome_func(): return True # Equivalent to: awesome_func = decorator_callable( awesome_func ) |
So when we add a callable
name prepended with a @
on top of a function, that function is passed to that callable. The return value from that callable becomes the new value of that function.
Writing our own decorators
Let’s say we want to write a decorator which will take a function and print the current time every time the function is executed. Let’s call our function timed
. This function will accept a parameter fn
which is the function we wrap. Since we need to return a function from the timed
function, we need to define that function too.
1 2 3 4 5 6 7 8 |
from datetime import datetime def timed(fn): def wrapped(): print("Current time: {}".format(datetime.now())) return fn() return wrapped |
In this example, the timed
function takes the fn
function and returns the wrapped
function. So by definition it’s a decorator. Within the wrapped
function, we’re first print
ing out the current time. And then we’re invoking the fn()
function. After the decorator is applied, this wrapped
function becomes the new fn
. So when we call fn
, we’re actually calling wrapped
.
Let’s see example of this decorator:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 |
from time import sleep from datetime import datetime def timed(fn): def wrapped(): print("Current time: {}".format(datetime.now())) return fn() return wrapped @timed def hello(): print("Hello world!") for x in range(5): hello() sleep(10) |
With the @timed
decorator applied to hello
, this happens: hello = timed(hello)
, hello
now points to the wrapped
function returned by timed
. Inside the for loop, every time we call, hello, it’s no longer the original hello function but the wrapped
function. The wrapped function calls the copy of the original hello
from it’s parent scope.
Two things you might have noticed – it is possible to nest functions and when we nest a function within a function, the inner function can access the parent scope too. You can learn more about the scope by reading on closure
.
Decorator Parameters
Decorators can take parameters too. Like this:
1 2 3 |
@sleeper(10) # sleep for 10 secs def say_hello(name): print("Hello {}!".format(name)) |
When a decorator takes a parameter, it’s executed like:
1 |
say_hello = sleeper(4)(say_hello) |
As we can see, it gets a level deeper. Here sleeper
has to take the parameter and return the actual decorator function which will transform our say_hello
function.
1 2 3 4 5 6 7 8 9 10 11 |
from time import sleep def sleeper(secs): def decorator(fn): def wrapped(*args, **kwargs): sleep(secs) fn(*args, **kwargs) return wrapped return decorator |
In this case, sleeper(4)
returns the decorator
function. We pass say_hello
to the decorator. The decorator wraps it inside the wrapped
function and returns wrapped
. So finally, say_hello
is actually the wrapped
function which gets fn
and secs
from the closure.
Chaining Decorators
We can chain multiple decorators. Like this:
1 2 3 4 5 6 7 8 9 |
@sleeper(10) @sleeper(5) def say_hello(name): print("Hello {}!".format(name)) # This is equivalent to: say_hello = sleeper(10)(sleeper(5)(say_hello)) |
The bottom most one gets executed first, then the returned function is passed to the decorator on top of that one. This way the chain of execution goes from bottom to top.
Using Classes as Decorators
In our previous examples, we have only focused on functions, but in Python, any callables can be used as decorator. That means we can uses Classes too. Let’s first see an example:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 |
from time import sleep from datetime import datetime class Sleeper: def __init__(self, secs): self.__secs = secs def __call__(self, fn): def wrapped(*args, **kwargs): sleep(self.__secs) return fn(*args, **kwargs) return wrapped @Sleeper(5) def say_hello(name): print("Hello {}, it is now: {}".format(name, datetime.now())) for x in range(5): say_hello("masnun") |
When we’re using the Sleeper
decorator, we are getting the parameter 5
to the constructor. We are storing it in an instance variable. The constructor returns an object instance, when we call it, it gets the function and returns a decorated, wrapped function.
This is just like before, say_hello = Sleeper(5)(say_hello)
. The first call is the constructor. The second call is made to the __call__
magic method.
Decorating Class and Class Methods
We can decorate any callables, so here’s an example where we’re decorating a Class to forcefully convert the age
argument to int
.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 |
def int_age(fn): def wrapped(**kwargs): kwargs['age'] = int(kwargs.get('age')) return fn(**kwargs) return wrapped @int_age class Person: def __init__(self, age): self.age = age def print_age(self): print(self.age) p = Person(age='12') p.print_age() |
We can decorate the methods as well. If you know Python’s OOP model well, you probably have already came across the @property
decorator. Or the @classmethod
and @staticmethod
decorators. These decorate methods.
3 replies on “Understanding Decorators in Python”
Using decorators may be easy, but implementing them correctly if you want them to behave properly as far as preserving introspection and descriptor behaviour is far from easy. For lots of information about the problem, read the blog series:
http://blog.dscpl.com.au/p/decorators-and-monkey-patching.html
As far as getting it right, the wrapt package gets closer than any other package available.
http://wrapt.readthedocs.org
You may like to write another blog post but show your same examples but using wrapt. 🙂
good one, Masnun vai.
plz keep it up (y)
[…] For details on this topic, check out Abu Ashraf Masnun's excellent introduction to decorators. […]