Monitor performance issues & errors in your code

What scientific computing can learn from CS

Episode #252, published Fri, Feb 21, 2020, recorded Thu, Jan 30, 2020

Did you come into Python from a computational science side of things? Were you just looking for something better than Excel or Matlab and got pulled in by all the Python has to offer?

That's great! But following that path often means some of the more formal practices from software development weren't part of the journey.

On this episode, you'll meet Martin Héroux, who does data science in the context of academic research. He's here to share his best practices and lessons for data scientists of all sorts.
Links from the show

Neuroscience Research Australia:
Martin Héroux:

Errors in science: I make them do you? Part 3:

PyPI Packages

Spreadsheet Blunders
12 of the Biggest Spreadsheet Fails:
Common spreadsheet errors:

Best Practices for Scientific Computing:
Good enough practices in scientific computing:
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Springboard bootcamp scholarships [code TALKPYTHONTOME]:
Episode transcripts:

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