On Tue, Jan 25, 2011 at 5:18 PM, Charles R Harris <charlesr.harris@gmail.com
wrote:
On Tue, Jan 25, 2011 at 1:13 PM, Travis Oliphant <oliphant@enthought.com>wrote:
On Jan 25, 2011, at 10:42 AM, Charles R Harris wrote:
Hi All,
Just thought it was time to start discussing a release schedule for numpy 2.0 so we have something to aim at. I'm thinking sometime in the period April-June might be appropriate. There is a lot coming with the next release: the Enthought's numpy refactoring, Mark's float16 and iterator work, and support for IronPython. How do things look to the folks involved in those projects?
My suggestion is to do a 1.6 relatively soon, as the current trunk feels pretty stable to me, and it would be nice to release the features without having to go through the whole merging process.
I would target June / July at this point ;-) I know I deserve a "I told you so" from Chuck --- I will take it.
How much remains to get done?
My changes probably make merging the refactor more challenging too.
There is a bit of work that Mark is doing that would be good to include, also some modifications to the re-factoring that will support better small array performance.
Not everything needs to go into first release as long as the following releases are backward compatible. So the ABI needs it's final form as soon as possible. Is it still in flux?
I would suggest it is - there are a number of things I think could be improved in it, and it would be nice to bake in the underlying support features to make lazy/deferred evaluation of array expressions possible.
It may make sense for a NumPy 1.6 to come out in March / April in the
interim.
Pulling out the changes to attain backward compatibility isn't getting any easier. I'd rather shoot for 2.0 in June. What can the rest of us do to help move things along?
I took a shot at fixing the ABI compatibility, and if PyArray_ArrFunc was the main issue, then that might be done. An ABI compatible 1.6 with the datetime and half types should be doable, just some extensions might get confused if they encounter arrays made with the new data types. -Mark