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Does that also hold for people doing data science in Jupyter notebooks? They're also programmers, arguably. At this point in the trajectory of software enginee
by c7b 4y ago
Does that also hold for people doing data science in Jupyter notebooks? They're also programmers, arguably.
At this point in the trajectory of software engineering, it's fair to assume that most of the low-hanging fruits have been picked, and solutions that are unequivocally better would have to bring something fundamentally new to the table (which types are not at all). Most solutions will be picking a particular point on a trade-off isocurve.
Apart from that, it's always fair to ask someone who's strongly proposing something what the downsides are.
- jolux 4y ago> Does that also hold for people doing data science in Jupyter notebooks? They're also programmers, arguably. Yeah they’re definitely programmers, but anyone who’s had to maintain and deploy what a data scientist came up with in a notebook will question whether they should really be using types.
- hardwaregeek 4y agoWhy are you sure that all of the low hanging fruits have been picked? The origins of software development are pretty much still within living memory. We’re still extremely new to programming. I wouldn’t be surprised if the field looks completely different in 50 years. As for types, I’m not saying they’re flawless. I’m pointing out that in the transition from assembly to high level languages there were flaws and criticisms that came out. But looking back fifty years, were these flaws and criticisms genuine tradeoffs that kept assembly as a reasonable option for most developers? No, they were not. Now we look back on programmers who insisted on writing assembly as oddities, as niche figures. I cannot say if this will be the case for types, but I won’t rule it out.