It’s been a whirlwind of a summer, and now that it’s officially fall I think I should take a moment to mention one event I failed to document for posterity here on my blog. This summer I had the opportunity to present a core project of mine at SciPy 2016: datreant.
This project forms the core of my data analysis workflow these days, both automated and human components (also known as me). The talk functions as a nice 20-minute overview of datreant, what problem it addresses, and how it works. Give it a gander if you find yourself drowning in data but can’t really escape using the filesystem itself as your data store of choice.
Also, there’s now a citable paper for datreant. Check out the SciPy 2016 proceedings, and consider citing datreant if it proves useful to you in your work:
- D. L. Dotson, S. L. Seyler, M. Linke, R. J. Gowers, O. Beckstein. datreant: persistent, Pythonic trees for heterogeneous data. In S. Benthall and S. Rostrup, editors, Proceedings of the 15th Python in Science Conference, pages 51-56, Austin, TX, 2016. SciPy.
This conference was particularly interesting because I managed to convince not only my partner-in-crime and labmate Sean Seyler to attend, but also my mentor and PI Oliver Beckstein to check it out for the first time. I’m happy to say they came away very satisfied with the experience!
I should mention that Oliver also gave a very nice talk on MDAnalysis, giving special emphasis on our vibrant community of active developers and users. We also produced a proceedings publication that functions as an update to the original MDAnalysis paper, giving details on both new and upcoming functionality and design changes in the library since.
With that, it’s back to thesis writing. My projects are all nicely wrapped up at the moment and I’m currently in the throes of compiling it all into an exhausting…er, exhaustive document. I’ll be fun again after November 4th. :D