On Tue, Apr 21, 2015 at 2:33 AM, Cory Benfield <c...@lukasa.co.uk> wrote:
> It seems like the only place the type annotations will get used is in > relatively trivial cases where the types are obvious anyway. I don't > deny that *some* bugs will be caught, but I suspect they'll > overwhelmingly be crass ones that would have been caught quickly > anyway. Well, it'll catch passing in a string instead of a sequence of strings -- one of teh common and semi-insidious type errors I see a lot (at least with newbies). Oh wait, maybe it won't -- a string IS a sequence of strings. That's why this is an insidioous bug in teh first place: List[string] will work, yes -- but now I'm locked down the user to an actual, list, yes? So I try: Iterable[string] ah yes -- now users can use tuples of strings, or a custom class, or -- but wait, darn it, a string IS an iterable of strings.. SIGH. NOTE: I've thought for years that Python should have a character type for this reason, but that's a side note. Oh, and I'm a heavy numpy user. And, in fact, I write a lot of functions that are essentially statically typed -- i.e. they will only work with a Nx3 array of float64 for instance. However, in this case, I want run-time type checking, and I DON'T want the API to be statically typed, so I use something like: the_arr = np.asarray( input_object, dypte-np.float64).reshape(-1, 3) and in my docstring: :param input_object: the input data to compute something from :type input_object: (Nx3) numpy array or floats or somethign that can be turned into one. Is there any way for type hinting to help here??? - Chris -- Christopher Barker, Ph.D. Oceanographer Emergency Response Division NOAA/NOS/OR&R (206) 526-6959 voice 7600 Sand Point Way NE (206) 526-6329 fax Seattle, WA 98115 (206) 526-6317 main reception chris.bar...@noaa.gov
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