This is well-written. I could follow along quite nicely, from the setup through the bottlenecks and onto the resolution of the performance bug. Even the PRs are very pleasant to read: the majority of them is just a handful of changed lines with an added tests and a bit of documentation.
I was taken aback for a moment that this work originated from a report on StackOverflow. I had thought SO was effectively dead and abandoned by its community. But maybe I shouldn't project my own experience onto everyone else.
SO is dead and abandoned by its community, and the data proves it. https://data.stackexchange.com/stackoverflow/query/1882532/q...
or maybe SO is back to its community sans clout chasers and tourists? If a vaninishing minority drive a given community in content generation and discourse, then lurkers etc leaving isnt as meaningful. you could lose 99% of users on many platforms without disrupting the core community and often having the added benefit of imoroving SNR.
It's a less marketable product in the modern attention economy, but that isnt the same as a dead community. It would be interesting to see a plot of posts/discussion liveliness per unit time and seeing is quality and depth of both questions and answers has changed and how they have changed.
I’m not sure why it took me, a NumPy developer, looking at the benchmark numbers and saying “hmm, this is a bug”. But that is what it took. People are sometimes slow to treat behavior in dependencies like NumPy as bugs.