TL;DR: Working in a notebook in a browser is a terrible way to write a program but a fantastic way to explore data.
Even though notebooks are a common cause of headache in my world (I work on ML deployment), I think they're an incredibly valuable tool, and the familiar, visual interface of the browser plays a big part.
It clicked for me when I took a statistical genetics class taught by a team member of Hail.is (open source genomic analysis library). Coming from a dev background, I found working in a browser to be a clunky, awful experience—until I saw the way my classmates, most of whom were scientists by focus, used it. My instinct is to think of code in terms of the architecture of a program, but for them, code blocks were like buttons on a calculator. The speed at which they could iterate, and their ability to jump around, really drove home the value of the browser interface.
Would I want to write an API in one? Absolutely not. But for tinkering with genomic data? They're ideal in many ways.
Even though notebooks are a common cause of headache in my world (I work on ML deployment), I think they're an incredibly valuable tool, and the familiar, visual interface of the browser plays a big part.
It clicked for me when I took a statistical genetics class taught by a team member of Hail.is (open source genomic analysis library). Coming from a dev background, I found working in a browser to be a clunky, awful experience—until I saw the way my classmates, most of whom were scientists by focus, used it. My instinct is to think of code in terms of the architecture of a program, but for them, code blocks were like buttons on a calculator. The speed at which they could iterate, and their ability to jump around, really drove home the value of the browser interface.
Would I want to write an API in one? Absolutely not. But for tinkering with genomic data? They're ideal in many ways.
Jeremy Howard of fast.ai talks about this a lot: https://twitter.com/jeremyphoward/status/1072555920029376512