[Numpy-discussion] Looking for the most important bugs, documentation needs, etc.

Ralf Gommers ralf.gommers@googlemail....
Tue Jul 10 04:01:14 CDT 2012


On Tue, Jul 10, 2012 at 4:20 AM, Six Silberman <silberman.six@gmail.com>wrote:

> Hi all,
> Some colleagues and I are interested in contributing to numpy.

That's great, welcome!

> We have a range of backgrounds -- I for example am new to contributing to
> open
> source software but have a (small) bit of background in scientific
> computation, while others have extensive experience contributing to
> open source projects. We've looked at the issue tracker and submitted
> a couple patches today but we would be interested to hear what active
> contributors to the project consider the most pressing, important,
> and/or interesting needs at the moment. I personally am quite
> interested in hearing about the most pressing documentation needs
> (including example code).

For documentation we have docstrings for each function and tutorial-style
docs (http://docs.scipy.org/doc/numpy/user/,
http://scipy-lectures.github.com/intro/numpy/index.html) . All docstrings
should have clear usage examples, but I'm actually finding it quite hard to
find functions that don't have any right now. The only one I could dig up
so quickly is corrcoef(). There must be a few more.

There are two ways to contribute to the docs, either send a pull request on
Github if you familiar with git (or want to learn it), or use our doc wiki:
In the doc wiki you can immediate see if the rendered version looks OK. You
have to register a username and then ask on this list for edit rights if
you want to use the wiki.

Besides those few docstrings that miss examples it's mainly the user guide
that needs some work I think. For example the "performance" section is
still empty. Filling that in will require some in-depth numpy/python
knowledge though.

If you would like like to work on improving the documentation with
examples, my suggestion would be to actually work on a part of scipy that
interests you. We aim to get the scipy docstrings to the same level of
quality as the numpy ones, and there's a lot to do there. Most docstrings
miss examples, and some even miss more basic stuff (parameter/return value
descriptions, formatting issues). This is a good overview of important
docstrings per topic: docs.scipy.org/scipy/Milestones/

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