Numpy status update and developer announcement
Hello, some good news!
First the update:
- dtype support - NumPy on PyPy now supports non-native storage formats. Due to a lack of true support for longdoubles in rpython, we decided to back out the support of longdouble-as-double which was misleading.
- missing ndarray attributes - work has been made toward supporting the complete set of attributes on ndarrays. We are progressing alphabetically, and have made it to d. Unsupported attributes, and unsupported arguments to attribute calls will raise a NotImplementedError.
- pickling support for numarray - hasn't started yet, but next on the list
- There has been some work on exposing FFI routines in numpypy.
- Brian Kearns has made progress in improving the numpypy namespace. The python numpypy submodules now more closely resemble their numpy counterparts. Also, translated _numpypy submodules are now more properly mapped to the numpy core c-based submodules, furthering the goal of being able to install numpy as a pure-python module with few modifications.
And now the good news:
While our funding drive over 2012 did not reach our goal, we still managed to raise a fair amount of money in donations. So far we only managed to spend around $10 000 of it. We issued a call for additional developers, and are glad to welcome Romain Guillebert and Ronan Lamy to the numpypy team. Hopefully we will be able to report on speedier progress soon.
Cheers,
Matti Picus, Maciej Fijalkowski
Comments
Regarding long double, that's clearly something you should not waste your time on. I think the way it was implemented in numpy is not good, and I generally advise against it (the only real use I can see is if you need to interoperate with binary formats that use it, but even there, the complete platform specificity of it is a killer).
Joining of two additional developers is a good sign for Numpy and so we hope that they will now focus on speedier progress soon.