CSE : Python Programming. Decorators. Announcements. The decorator pattern. The decorator pattern. The decorator pattern

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1 CSE : Python Programming Lecture 12: Decorators April 9, Announcements Projects (code and documentation) are due: April 20, 200 at pm There will be informal presentations to help give me a sense of what exactly you have done As before, send me with times you can meet I will probably schedule these to last 30 minutes code and documentation one day in advance Ideally schedule these before April 19 2 Window Decorators 4 Window Window BorderedWindow BorderedWindow ScrollableWindow 4 4

2 Window If all those arrows represent subclass relationships, this gets unwieldy quickly BorderedWindow ScrollableWindow BorderedScrollableWindow 4 If all those arrows represent subclass relationships, this gets unwieldy quickly Turn each of these into wrapper classes If all those arrows represent subclass relationships, this gets unwieldy quickly Turn each of these into wrapper classes Constructor takes as an argument a Window Implements a Window, except with additional functionality Good example: Input/Output Streams in Java Constructor takes as an argument a Window Implements a Window, except with additional functionality Decorators in Python Despite the name, these are not exactly like the decorator pattern described on the previous slide At the moment, a Python decorator modifies the behavior of a function or method In the future, possibly add support for classes What kind of things can you imagine doing with these? You wrote a function, why not just build in the additional behavior you want? 6

3 Each decorator comes before the function (or method) it modifies Each decorator starts with an Decorators themselves are simply functions 8 Decorators themselves are simply functions Thus, they can take arguments 8 >>> silly(1.2, 2, 3) Traceback (most recent call last): AssertionError: return value does not match <type 'int'> 9 Decorators: Internal translation Decorators: Internal translation The decorator syntax saves you from having to do the assignment yourself 10 10

4 Decorators: Internal translation The decorator syntax saves you from having to do the assignment yourself So order matters! 10 >>> silly(1.2, 2, 3) Traceback (most recent call last): AssertionError: return value does not match <type 'int'> 11 >>> silly(1.2, 2, 3) Traceback (most recent call last): returns is a normal function which takes one argument returns(int) returns a function the decorator 13 14

5 We get back a function, which we pass off to debug now Ultimately, decorators are simply higher-order functions One argument: The function being decorated 1 We need to return a function. Also, set the name of the function we return. 18 This specifies how we wrap f. 19

6 Ultimate result: We print a message before we call f, and after the call returns This decorator takes an single argument so the function we define has to build and return the decorator itself. Otherwise, everything is as it was before

7 2 >>> silly(1.2, 2, 3) Traceback (most recent call last): 26 So why use decorators? One last example: Static methods You want to modify the input/output behavior of a function without cluttering the function definition Debugging output Uniformly add "access control" checks Check input / output types Decorators provide a nice, declarative way of modifying a functions behavior class def example(cls, i, j): print "Class argument:", cls return i + j >>> Baz.example(2, 3) Class argument: main.baz 2 28 One last example: Static methods class def example(cls, i, j): print "Class argument:", cls return i + j >>> Baz.example(2, 3) Class argument: main.baz Instead of self, this is the class object for this method. Overloading, or How to Make Code Unreadable 28

8 Python Lang. Ref.: The index Python Lang. Ref.: The index 30 Some of these look somewhat interesting 30 Python and "built-ins" A lot of functionality which appears to be built-in simply calls specially named methods on objects With statements: enter, exit Iterable objects: iter If you really want to use a piece of built-in syntax for your objects, simply override the appropriate * method Python's dictionaries >>> d = {} >>> d[0] Traceback (most recent call last): File "<stdin>", line 1, in <module> KeyError: "Dictionaries" with default values class MyDict(): def init (self): self.d = {} def getitem (self, key): if key not in self.d: return None else: return self.d[key] def setitem (self, key, value): self.d[key] = value "Dictionaries" with default values class MyDict(): def init (self): self.d = {} def getitem (self, key): if key not in self.d: return None else: return self.d[key] def setitem (self, key, value): self.d[key] = value A real implementation would need to do much more. >>> d = MyDict() >>> d[0] >>> d[2] = 3 >>> d[2] 3 33 >>> d = MyDict() >>> d[0] >>> d[2] = 3 >>> d[2] 3 33

9 Making objects look like functions class Callable(): def call (self, *args, **kwords): print "I'm a function!?" print "Args:", args print "Keword args:", kwords >>> c = Callable() >>> c(2, 3, 4) I'm a function!? Args: (2, 3, 4) Keword args: {} Making code unreadable One school of thought says that it should be blindingly obvious what a piece of code does Therefore, overloading the meanings of built-in things like '+' is a bad idea Another school of thought says that code should look as natural as possible If you'd use '+' on paper, try to use '+' in code 34 3 Next time The last and final lecture 36