[Numpy-discussion] Record arrays

Sebastian Haase haase@msg.ucsf....
Fri Jun 27 19:10:57 CDT 2008


On Fri, Jun 27, 2008 at 7:10 AM, Fernando Perez <fperez.net@gmail.com> wrote:
> On Thu, Jun 26, 2008 at 1:25 PM, Robert Kern <robert.kern@gmail.com> wrote:
>
>> One downside of this is that the attribute access feature slows down
>> all field accesses, even the r['foo'] form, because it sticks a bunch
>> of pure Python code in the middle. Much code won't notice this, but if
>> you end up having to iterate over an array of records (as I have),
>> this will be a hotspot for you.
>
> I wonder if it wouldn't be useful for *all* numpy arrays to have a .f
> attribute that would provide attribute access to fields for complex
> dtypes:
>
> In [13]: r['foo']
> Out[13]: array([1, 1, 1])
>
> In [14]: r.f.foo
> -> Hypothetically, same as [13] above
>
> This object would be in general an empty namespace, thus avoiding the
> potential for collisions that recarrays have, could normalize field
> names to be valid python identifiers (spaces to _, etc) and could
> provide name TAB completion. Since the .f object would be a *separate*
> object, the main array wouldn't need to have complex python code in
> the fast path and there would be no speed penalty for other uses of
> the top level object.
>
> I've never quite liked recarrays because of the fact that they blend
> the named fields with the main namespace, and because they don't tab
> complete.  I'd happily pay the price of accessing a sub-object for a
> cleaner and more useful access to fields (I could always do xf=x.f if
> I am really going to use the field object a lot).
>
> Just an idea, perhaps it's already been shut down in the past.
>
+ 1

-- Sebastian Haase


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