[Numpy-discussion] Feature requests/Enhancements for upper-level engineering students

[Charles R Harris]

On Thu, Aug 20, 2020 at 11:11 AM cooperrc <ryan.c.cooper at uconn.edu> wrote:

> Greetings,
> As the Fall semester is fast approaching (10 days away for us at UConn), we
> are looking for senior design (also called capstone) projects for the
> 2020-2021 school year. The COVID situation has strengthened the need for
> remote work.
> The process here is that students are assigned to projects by late
> September. Then, they have 6 main deliverables over the course of 2
> semesters:
> 1. Initial Fall Presentation (~Oct)
> 2. Final Fall Presentation (~Dec)
> 3. Mid-year report (~Jan)
> 4. Initial Spring Presentation (~Mar)
> 5. Final Spring Presntation (~Apr)
> 6. Final report (~May)
>
> My question to the NumPy community is: Are there any features or
> enhancements that would be nice to have, but might not have a team
> dedicated
> to the idea?
>
> I would be happy to advise any projects that people are interested in
> proposing. I would like to hear what people think would be worthwhile for
> students to build together. Some background, these students have all used
> Python and Matlab for mechanical engineering applications like linear
> regression, modal analyses, ode integration, and root solving. They learn
> quickly, but may not be interested in UX/UI design problems.
>
>
>
Thanks for the inquiry. We are always looking for new people who have the
time and inclination to make a contribution to NumPy, but NumPy core
probably isn't a good choice for class projects. Work on NumPy core
requires C and CPython C-API expertise and experienced programmers
generally take 3-6 months to come up to speed, the learning curve is just
too steep for most students. NumPy also needs to be very careful about
maintaining compatibility with existing downstream projects and in
introducing new features. I suspect students would enjoy a
faster moving project.

There is a lot of work on the website and online documentation that is
moving faster than NumPy core, but that sounds like it might be out of
scope for your classes. If not, let us know.

If you can think of new projects based on NumPy, that might work better.
They could be written in Python and the students could release them on PyPI
if so inclined. I suspect there are several ongoing projects that are more
engineering oriented than NumPy and the current Python Science stack could
use more engineering applications. Perhaps others more familiar with that
area could make suggestions.

Chuck
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