Zac Hatfield-Dodds

Zac is a researcher at the Australian National University’s 3A Institute, which is building a new applied science to 'manage the machines' - AI, cyber-physical systems, and other new technologies.

He started using Python to analyse huge environmental datasets, and contributing to libraries like Xarray to make such analysis easier for all scientists. Now, as a maintainer of Hypothesis, Pytest, and Trio, Zac is still passionate about making it easy to write software you can understand and rely on.

When not at a computer he can usually be found surrounded by books of all kinds, the Australian bush, or both.

The speaker's profile picture

Twitter handle Twitter handle Homepage

https://3ainstitute.cecs.anu.edu.au

Homepage

https://3ainstitute.cecs.anu.edu.au

Git*hub|lab

https://github.com/Zac-HD

Git*hub|lab

https://github.com/Zac-HD

Institute / Company

@3Ainstitute, Australian National University

Institute / Company

@3Ainstitute, Australian National University


Sessions

09-04
11:30
30min
Sufficiently Advanced Testing with Hypothesis
Zac Hatfield-Dodds

Testing research code can be difficult, but is essential for robust results. Using Hypothesis, a tool for property-based testing, I'll show how testing can be both easier and dramatically more powerful - even for complex "black box" codes.

Track 3 (Oteiza)
09-03
09:00
90min
Sufficiently Advanced Testing with Hypothesis
Zac Hatfield-Dodds

Testing research code can be difficult, but is essential for robust results. Using Hypothesis, a tool for property-based testing, I'll show how testing can be both easier and dramatically more powerful - even for complex "black box" codes.

Track 3 (Oteiza)