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I don't know of anything similar for Jupyter notebooks or sql either. I guess testing with simulated data designed to yield expected results would be the way I

• hjk05 7y ago
  Seems that bootstrapping and outlier detection is the way to go independent of what language of “editor”(Eg notebook use) you are using. The really cool thing here is that they parse the excel formula in order to automatically “figure out” how they can perform the bootstrapping.
• jnbiche 7y ago
  > I don't know of anything similar for Jupyter notebooks or sql either Exactly. It feels like we're falling into the exact same problem with Jupyter notebooks as with spreadsheets: they become increasingly used by professionals who code (but who aren't software devs) to create bug-ridden, unmaintainable, large-scale software because they become familiar with the tool they have at hand.
  • analog31 7y ago
    Yes, definitely. I'm guilty as charged to some extent. I'm a heavy user of Jupyter, and introduced Python to my workplace, where it is now used by a handful of scientists in R&D. I'm hesitant to blame the tool. Instead, I think it's a matter of our exuberance and interest in producing new results that causes us to get ahead of our software engineering skills and build things that get out of hand. Also, the professional developers are simply not available to help us improve things. We're on our own.