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Documentation as a way to build Community

As a long time user and participant in open source communities, I've always known that documentation is far from being a solved problem. At least, that's the impression we get from many developers: "writing docs is boring"; "it's a chore, nobody likes to do it". I have come to realize I'm one of those rare people who likes to write both code and documentation.

Nobody will argue against documentation. It is clear that for an open-source software project, documentation is the public face of the project. The docs influence how people interact with the software and with the community. It sets the tone about inclusiveness, how people communicate and what users and contributors can do. Looking at the results of a “NumPy Tutorial” search on any search engine also gives an idea of the demand for this kind of content - it is possible to find documentation about how to read the NumPy documentation!

I've started working at Quansight in January, and I have started doing work related to the NumPy CZI Grant. As a former professor in mathematics, this seemed like an interesting project both because of its potential impact on the NumPy (and larger) community and because of its relevance to me, as I love writing educational material and documentation. Having official high-level documentation written using up-to-date content and techniques will certainly mean more users (and developers/contributors) are involved in the NumPy community.

So, if everybody agrees on its importance, why is it so hard to write good documentation?

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uarray: GSoC Participation

I'm pleased to announce that uarray is participating in GSoC '20 as a sub-organization under the umbrella of the Python Software Foundation. Our ideas page is up here, go take a look and see if you (or someone you know) is interested in participating, either as a student or as a mentor.

Prasun Anand and Peter Bell and myself will be mentoring, and we plan to take a maximum of two students, unless more community mentors show up.

There have been quite a few pull requests already to qualify from prospective students, some even going as far as to begin the work described in the idea they plan to work on.

We're quite excited by the number of students who have shown an interest in participating, and we look forward to seeing excellent applications! What's more exciting, though, are some of the first contributions from people not currently at Quansight, in the true spirit of open-source software!

Planned architectural work for PyData/Sparse

What have we been doing so far? 🤔

Research 📚

A lot of behind the scenes work has been taking place on PyData/Sparse. Not so much in terms of code, more in terms of research and community/team building. I've more-or-less decided to use the structure and the research behind the Tensor Algebra Compiler, the work of Fredrik Kjolstad and his collaborators at MIT. 🙇🏻‍♂️ To this end, I've read/watched the following talks and papers:

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metadsl PyData talk

metadsl PyData talk

PyData NYC just ended and I thought it would be good to collect my thoughts on metadsl based on the many conversations I had there surrounding it. This is a rather long post, so if you are just looking for some code here is a Binder link for my talk. Also, here is the talk I gave a month or so later on the same topic in Austin:

What is metadsl?

class Number(metadsl.Expression):
   def __add__(self, other: Number) -> Number:

   def from_int(cls, i: int) -> Number:

def add_zero(y: Number):
   yield Number.from_int(0) + y, y
   yield y + Number.from_int(0), y

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Variable Explorer improvements in Spyder 4

Spyder 4 will be released very soon with lots of interesting new features that you'll want to check out, reflecting years of effort by the team to improve the user experience. In this post, we will be talking about the improvements made to the Variable Explorer.

These include the brand new Object Explorer for inspecting arbitrary Python variables, full support for MultiIndex dataframes with multiple dimensions, and the ability to filter and search for variables by name and type, and much more.

It is important to mention that several of the above improvements were made possible through integrating the work of two other projects. Code from gtabview was used to implement the multi-dimensional Pandas indexes, while objbrowser was the foundation of the new Object Explorer.

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A new grant for NumPy and OpenBLAS!

I'm very pleased to announce that NumPy and OpenBLAS just received a $195,000 grant from the Chan Zuckerberg Initiative, through its Essential Open Source Software for Science (EOSS) program! This is good news for both projects, and I'm particularly excited about the types of activities we'll be undertaking, what this will mean in terms of growing the community, and to be part of the first round of funded projects of this visionary program.

The program

The press release gives a high level overview of the program, and the grantee website lists the 32 successful applications. Other projects that got funded include SciPy and Matplotlib (it's the very first significant funding for both projects!), Pandas, Zarr, scikit-image, JupyterHub, and Bioconda - we're in good company!

Nicholas Sofroniew and Dario Taborelli, two of the people driving the EOSS program, wrote a blog post that's well worth reading about the motivations for starting this program and the 42 projects that applied and got funded: The Invisible Foundations of Biomedicine.

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