Jes Ford - Getting Started Testing in Data Science - PyCon 2019

This talk had me pumped when I got back to work after watching Jes Ford demonstrate the hypothesis library to fabricate a test pandas dataframe. I also think that getting some testing practices into folks doing data science is long overdue. What a fantastic presentation!

Fantastic presentation. Not only is it a nice introduction to testing generally, and then specific libraries, it's also a nice peak at a couple practical analytical methodologies.

Please don't use "asserts" in production code. Try catch and properly handle exceptions.

An excellent talk! A different wording from Jes but I think she would agree with me; data scientists in many situations do two jobs, science and engineering. I myself practice TDD for engineering and quick defensive programming for science. As Jes noted, science part is too exploratory to do TDD, it's just not well suited for TDD. However, you will thank yourself if you write tests for engineering part such as feature engineering.

Fantastic and very practical presentation. I really loved the division of work into 3 buckets - one-off, exploratory and defined work and applying slightly different testing strategies for each one of them, rather than being pedantic about testing. I learnt a number of useful ideas to improve my pandas testing. I am gonna checkout Hypothesis library

Very well presented. Many thanks for presenting this, especially the section of testing dataframes, quite clear and succinct