On 2/23/07, Dino Viehland <[EMAIL PROTECTED]> wrote:
> We're basically doing the same thing that the array.py is doing - the 
> difference truly is just the item size.  Python is implicitly doing the check 
> by calling range(n) and doing the size check on each read.  We're reading 
> everything in at once and doing the same basic size check just doing it 
> before intsead of at each read.  They should both be equivalent though.
>
> Is there an issue w/ switching to using the I type for the array instead of 
> the L type?

I tried this but was unsuccessful.  It still results in the same
exception being thrown.  If I am understanding everything, the only
typecode that uses 8 bytes is floating point 'd'.

> If that seems too cumbersome we could consider changing the default size of L 
> to match CPython (I suspect this means 4 bytes on a 32-bit platform and 8 
> bytes on 64-bit but I don't have a 64-bit install of CPython).
>

This is an interesting solution and I wish others onlist that use
array could test also to provide additional feedback.  If I had more
time I could try to test with a rebuild of 1.1B and get back to you.
I am not sure if I would be modifying correctly though, at this point
I just quickly glanced at how you guys constructed the typecodes.

I wouldn't think that modeling CPython's 4 bytes would be a bad thing,
if an IP goal is to enable user modules to work both in IP and
CPython.  I think this is why many of us like IP because you can have
something in CPython and easily use it in a .NET platform, or IP to
CPython. I true cross-platform module would be my goal.

Thanks, Joe
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