I saw you edited your post, which is great. Happy to chime in from the Python side: people complain a lot about the GIL but in practice a lot of the truly paral

I saw you edited your post, which is great. Happy to chime in from the Python side: people complain a lot about the GIL but in practice a lot of the truly parallel logic happens in C extensions, which are lately quite easy to write. This is where all the heavy lifting for machine learning happens; the I/O parallelism that one might see in e.g. a scraper is a different kind of thing (e.g. fibers). I don't know much about ractors but it's neat to see a GIL being lifted! Small nits: the image with fibonacci performance numbers needs a maximum number of significant digits. I think "implement" usually applies to an algorithm or idea; you might mean "use" Sidekiq? The thing I'm most curious about is how easy it is to write an extension in C/C++/Rust for Ruby (in comparison to cffi, pybind11, etc.). Best of luck! It's not easy to write a technical article and face criticism, but I appreciated reading it.