Travis Oliphant wrote: > Sebastian Haase wrote: >> Hi! >> I just finished maybe a total of 5 hours tracking down a nasty bug. >> >> Finally I traced the problem down to a utility function: >> "is_number" - it is simply implemented as >> def is_number(val): >> return (type(val) in [type(0.0),type(0)]) >> >> As I said - now I finally saw that I always got >> False since the type of my number (0.025) is >> <type 'float64scalar'> >> and that's neither <type 'float'> nor <type 'int'> >> >> OK - how should this have been done right ? >> >> > > Code that depends on specific types like this is going to be hard to > maintain in Python because many types could reasonably act like a > number. I do see code like this pop up from time to time and it will > bite you more with NumPy (which has a whole slew of scalar types). > > The scalar-types are in a hierarchy and so you could replace the code with > > def is_number(val): > return isinstance(val, (int, float, numpy.number)) > > But, this will break with other "scalar-types" that it really should > work with. It's best to look at what is calling is_number and think > about what it wants to do with the object and just try it and catch the > exception. > > -Travis >
Thanks, I just found numpy.isscalar() and numpy.issctype() ? These sound like they would do what I need - what is the difference between the two ? (I found that issctype worked OK while isscalar gave some exception in some cases !? ) - Sebastian ------------------------------------------------------------------------- Take Surveys. Earn Cash. Influence the Future of IT Join SourceForge.net's Techsay panel and you'll get the chance to share your opinions on IT & business topics through brief surveys -- and earn cash http://www.techsay.com/default.php?page=join.php&p=sourceforge&CID=DEVDEV _______________________________________________ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
