Specifically the ":int" part...
I assumed it somehow checked the type of the parameter at the time the function is called and perhaps raised an exception in the case of a violation. But the following run without problems:
def some_method(param:str):
print("blah")
some_method(1)
def some_method(param:int):
print("blah")
some_method("asdfaslkj")
In both cases "blah" is printed - no exception raised.
I'm not sure what the name of the feature is so I wasn't sure what to google.
EDIT: OK, so it's http://www.python.org/dev/peps/pep-3107/. I can see how it'd be useful in frameworks that utilize metadata. It's not what I assumed it was. Thanks for the responses!
FOLLOW-UP QUESTION - Any thoughts on whether it's a good idea or bad idea to define my functions as def some_method(param:int) if I really only can handle int inputs - even if, as pep 3107 explains, it's just metadata - no enforcement as I originally assumed? At least the consumers of the methods will see clearly what I intended. It's an alternative to documentation. Think this is good/bad/waste of time? Granted, good parameter naming (unlike my contrived example) usually makes it clear what types are meant to be passed in.
it's not used for anything much - it's just there for experimentation (you can read them from within python if you want, for example). they are called "function annotations" and are described in pep 3107.
i wrote a library that builds on it to do things like type checking (and more - for example you can map more easily from JSON to python objects) called pytyp (more info), but it's not very popular... (i should also add that the type checking part of pytyp is not at all efficient - it can be useful for tracking down a bug, but you wouldn't want to use it across an entire program).
[update: i would not recommend using function annotations in general (ie with no particular use in mind, just as docs) because (1) they might eventually get used in a way that you didn't expect and (2) the exact type of things is often not that important in python (more exactly, it's not always clear how best to specify the type of something in a useful way - objects can be quite complex, and often only "parts" are used by any one function, with multiple classes implementing those parts in different ways...). this is a consequence of duck typing - see the "more info" link for related discussion on how python's abstract base classes could be used to tackle this...]
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