For reference, here is the table that shows the actual changes between 1.5.1 and 1.6.1 at least on 64-bit platforms in terms of type-casting. I updated the comparison code to throw out changes that are just "spelling differences" (i.e. where 1.6.1 chooses to create an output dtype with an 'L' character code instead of a 'Q' which on 64-bit system is effectively the same).
1.5.1_to_1.6.1
Description: Binary data
Mostly I'm happy with the changes (after a cursory review). As I
expected, there are some real improvements. Of course, I haven't looked at
the changes that occur when the scalar being used does not fit in the range of
the array data-type. I don't see this change documented in the link that Mark
sent previously. Is it somewhere else? Also, it looks like previously
object arrays were returned for some coercions which now simply fail. Is that
an expected result?
At this point, I'm not going to recommend changes to 1.7 to deal with these
type-casting changes --- at least this thread will serve to show some of what
changes occurred if it bites anyone in the future.
However, I will have other changes to NumPy 1.X that I will be proposing and
writing (and directing other people to write as well). After some period of
quiet, this might be a refreshing change. But, not all may see it that way.
I'm confident that we can resolve any concerns people might have. Any feature
additions will preserve backward compatibility in NumPy 1.X. Mark W. will be
helping with some of these changes, but mostly he will be working on NumPy 2.0
which we have tentatively targeted for next January. We have a tentative
target for NumPy 1.8 in June/July. So far, there are three developers who
will be working on NumPy 1.8 (me, Francesc Alted, and Bryan Van de Ven). Mark
Wiebe is slated to help us, as well, but I would like to sponsor him as much as
possible on the work for NumPy 2.0. If anyone else would like to join us,
please let me know off-list. There is room for another talented person on
our team.
In addition to a few select features in NumPy 1.8 (a list of which will follow
in a later email), we will also be working on reviewing the list of bugs on
Trac and fixing them, writing tests, and improving docstrings. I would also
like to improve the state of the bug-tracker and get in place a continuous
integration system for NumPy. We will be advertising our NumPy 1.8 roadmap
and our NumPy 2.0 roadmap at PyCon, and are working on documents that describe
plans which we are hoping will be reviewed and discussed on this list.
I know that having more people working on the code-base for several months will
be a different scenario than what has transpired in the past. Hopefully, this
will be a productive time for everybody and our sometimes different
perspectives will be able to coalesce into a better result for more people.
Best regards,
-Travis
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