[Numpy-discussion] int32 twice in sctypes?

[Travis Oliphant]

Matthew Brett wrote:

>Hi,
>
>I was a bit confused by this on 32 bit linux:
>
>In [30]:sctypes['int']
>Out[30]:
>[<type 'numpy.int8'>,
> <type 'numpy.int16'>,
> <type 'numpy.int32'>,
> <type 'numpy.int64'>,
> <type 'numpy.int32'>]
>
>Is it easy to explain the two entries for int32 here?  I notice there
>is only one int32 entry for the same test on my 64 bit system.
>
>  
>
The mapping from c-types to bit-width types is not one-to-one.   All of 
the c-types have their own array-scalar.  Some of these have the same 
bit-width and thus are named similarly.

numpy.int32 refers to exactly one of these c-types, but on some systems 
(e.g. 32-bit), there will be another array scalar that also shows up 
with the name numpy.int32

The easiest way to see them all is to observe

id(dtype('byte').type)
id(dtype('short').type)
id(dtype('intc').type)
id(dtype('int').type)
id(dtype('longlong').type)

But then compare:

dtype('byte').type
dtype('short').type
dtype('intc').type
dtype('int').type
dtype('longlong').type

dtype('intp').type  will be one of the above as can be verified by 
looking at

id(dtype('intp').type)

The sctypes['int'] list is a list of all the c-type ints.  Thus, you 
could generate the id's of the first 5 typeobjects using:

[id(x) for x in sctypes['int']]


-Travis