I like Observable for sharing JS tutorials - was just updating https://observablehq.com/@lmeyerov/manipulating-flat-arrays-arrow-style https://observablehq.com

I like Observable for sharing JS tutorials - was just updating https://observablehq.com/@lmeyerov/manipulating-flat-arrays-arrow-style https://observablehq.com/@lmeyerov/manipulating-flat-arrays-... today. Observable does some things quite well for that use case: -- Easier dependencies: no need for 'npm install', just 'require(...)' -- URL publishing -- Collaborative merge flow However, Jupyter made some good decisions that make it win over Observable for our day-to-day data work: -- Manual reexecution vs. automatic: when working with big data, outside APIs, etc., Observable's automatic reexecution is a non-starter -- Fully open source, embeddable, and successful history of non-vc funding: Jupyter is organized and provided in a way companies ( who aren't Amazon ;-)) can rally around, evidenced by contributions by Bloomberg etc. -- Access to underlying unix/windows env and multiple environments (multiple Python versions, ...). As much as I wish Observable's choice of JS could provide a viable data environment, and I've personally invested in making it so and the path to making it first-class is clear, we need way more gov/google/nvidia/etc. support. Ultimately, for not-too-sensitive collaborative data work, we use Google Colab, then offline and sensitive commercial work via Jupyter (Graphistry ships with it preloaded for GPU dataframe & GPU visual graph analytics goodness!), and if we did more in JS tutorial land, Observable would be my first choice.