Python decorators allow functions to be replaced or wrapped at runtime. Decorators are functions that take a function as an argument and return a replacement function. Decorators provide a way to modify or extend the behavior of functions in a clean Pythonic way. Common uses of decorators include logging, timing, retrying functions, and implementing other cross-cutting concerns.

1. Python Decorators
Introduction to Python decorators
Rik van Achterberg
| 2013-12-04

2. You might have seen them

3. Some theory
● Introduced in Python 2.4.
● Decorators can be used to implement the
decorator pattern.
● Decorators are similar to annotations in
Java/C#.
● When compared to C, decorators are comparable
to preprocessor macros.
● Decorators are possible thanks to functions,
like everything else, being objects.

4. Decorators replace functions
Function being replaced by class
Function being replaced by
(inner) function

5. Decorators are just syntactic sugar
● A decorator is a function or class that
takes a function as an argument and
returns a replacement callable.
● The ‘@object’ syntax above functions is
not magic;
● It just provides a clean notation.

6. How decorators are being called
Identical behaviour with and without
decorators
Adding ‘logging’ argument:

7. Beginner’s mistake
This function based sleep decorator lacks
nesting.
Calls
broken_sleep_decorator(say_hello)
upon program initialization;
so sleep(1) is always called.
Function is not replaced

8. Working sleep decorator
Defines ‘wrapper’ and returns it as
replacement function
Calls original function
Executes
say_hello = sleep_decorator(say_hello)
Calls wrapper(“Byte”)
Call is equal to:
sleep_decorator(say_hello)(“Byte”)

9. Tunable sleep decorator
Accepts decorator arguments
Accepts function argument
Accepts arguments for function
Calls original function
Calls
tunable_sleep_decorator
(seconds=1)
(say_hello)
Calls wrapper(“Byte”)
Call is equal to:
tunable_sleep_decorator(seconds=1)(say_hello)(“Byte”)

10. Function vs Class decorators
● They can be written to have near
identical behaviour;
● However, classes allow storage of
state.
● It depends on the situation, really.

11. Function vs. class decorators
● Basic function vs. class example
● Note the difference in return values

12. Function vs. Class decorators
A counter that stores state

13. Debug decorator
Call function with args, surrounded by
print statements

14. Basic benchmark decorator

15. Retry decorator

16. Further reading
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http://www.python.org/dev/peps/pep-0318/
https://wiki.python.org/moin/PythonDecorators
https://wiki.python.org/moin/PythonDecoratorLibrary
http://www.artima.com/weblogs/viewpost.jsp?thread=240808
http://pythonconquerstheuniverse.wordpress.com/2012/04/29/python-decorators/
http://stackoverflow.com/questions/739654/how-can-i-make-a-chain-of-function-decorators-inpython/1594484#1594484
http://www.ibm.com/developerworks/library/l-cpdecor/
code examples from this presentation:
@rikva/decorators