Hi Naupaka-
Eric Ma is teaching a three-hour “Best Testing Practices for Data Science”
tutorial at PyCon next week ( description at
https://us.pycon.org/2017/schedule/presentation/182/ ).
PyCon tapes everything and posts it on YouTube, often within a few days. Check
for a PyCon 2017 channel on YouTube later this month.
Cheers-
Janet
------
Janet Riley
[email protected]
857-288-8428
On May 10, 2017 at 11:48:19 AM, Naupaka Zimmerman ([email protected]) wrote:
Hi all,
I'm been thinking recently about the best way to incorporate testing
(regression/unit/etc) into routine data analysis scripts, both for my own work
and when teaching (e.g. a graduate-level bioinformatics class).
Conceptually it seems straightforward to incorporate tests when developing a
package or series of functions meant for reuse, but I am wondering if there is
a community-endorsed best-practice way to incorporate this defensive
programming mentality into more ad-hoc analyses.
I'm most familiar with the defensive programming approaches in the R world
(stopifnot, testthat, assertr), but I'm most interested in general answers to
the question.
We had some discussion about this on an issue in the r-novice-gapminder repo a
while back.
Thanks in advance for any input!
Best,
Naupaka
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