[Tutor] array module

[Finn Mason]

array.array() is very limited in what it can do. Honestly, I'm not sure why
it's in the standard library when NumPy is so popular it can practically be
considered a core library.
Check out NumPy for arrays of numbers.


--
Finn Mason

On Tue, Oct 12, 2021, 5:24 AM Dennis Lee Bieber <wlfraed at ix.netcom.com>
wrote:

> On Tue, 12 Oct 2021 08:13:09 +0530, Manprit Singh
> <manpritsinghece at gmail.com> declaimed the following:
>
> >lst = list(range(100))
> >
> >import array
> >arr = array.array("h", range(100))
> >
> >sys.getsizeof(lst)
> >returns 856
> >
> >sys.getsizeof(arr)
> >returns 268
> >
> >Shows that the list lst and array arr both are having same data, but there
> >is huge difference in size bytes.  so for storing homogenous 1 D data
> >arrays are more good ,  Why they are not widely used ?
> >What are the specific use cases of this array module ?
>
>          They work with machine native NUMERIC data types, not Python
> objects.
> Unless you use only the methods documented
> https://docs.python.org/3/library/array.html you will require a
> C-extension
> to really take advantage of array.array() -- otherwise you are continuously
> converting between Python objects and processor native types. That is, you
> will be creating an object header, storage space, copying the native type
> into the new object (which includes conversion for short/long etc. to
> Python integers, for example); operating on the object, then converting it
> back to the array data size, copying the native value into the array, and
> disposing of the object header.
>
>         This is one of the problems with just focusing on one aspect of
> Python
> at a time with minimalistic examples.
>
>         Try running some moderately complex arithmetic using values
> contained
> in a list vs the same values contained in an array -- TIMING both. Heck,
> even computing squares of integers may be sufficient to show it:
>
> nlst = [x*x for x in olst]
>
> vs
>
> oarr = array.array("suitableCode", olst)
> narr = array.array("sameCode", (x*x for x in oarr))     #generator, not
> list
> comprehension, to avoid creating a list only to throw it away
>
> or
>
> oarr = array.array("suitableCode", olst)
> narr = array.array("sameCode")
> for itm in oarr:
>         narr.append(itm*itm)
>
>
> --
>         Wulfraed                 Dennis Lee Bieber         AF6VN
>         wlfraed at ix.netcom.com
> http://wlfraed.microdiversity.freeddns.org/
>
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