It's been a little while since we wrote about NumPy on PyPy, so we wanted to give everyone an update on what we've been up to, and what's up next for us.
We would also like to note that we're launching a funding campaign for NumPy support in PyPy. Details can be found on the donation page.
Some of the things that have happened since last we wrote are:
- We added dtype support, meaning you can now create arrays of a bunch of different types, including bools, ints of a various sizes, and floats.
- More array methods and ufuncs, including things like comparison methods (==, >, etc.)
- Support for more and more argument types, for example you can index by a tuple now (only works with tuples of length one, since we only have single-dimension arrays thus far).
Some of the things we're working on at the moment:
- More dtypes, including complex values and user-defined dtypes.
- Subscripting arrays by other array as indices, and by bool arrays as masks.
- Starting to reuse Python code from the original numpy.
Some of the things on the near horizon are:
- Better support for scalar data, for example did you know that numpy.array([True], dtype=bool) doesn't return a bool object? Instead it returns a numpy.bool_.
- Multi-dimensional array support.
If you're interested in helping out, we always love more contributors, Alex, Maciej, Justin, and the whole PyPy team