I Don't Like Notebooks: https://docs.google.com/presentation/d/1n2RlMdmv1p25Xy5thJUhkKGvjtV-dkAIsUXP-AL4ffI/preview?slide=id.g362da58057_0_1
A good discussion of the limitations of Jupyter. It's a challenging design space: you want a helpful code sandbox without reinventing the IDE.
miniblog.
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Python's GIL is well known, but many languages have limitations on multithreading (e.g. JS, Ocaml).
Perhaps this is a consequence of C as a popular implementation language? A GIL could be less common when Rust is the implementation language.
The effectiveness of fuzzing, the limitations of current research, your best options today, and a worked example:
physical-cpu-count is a lovely example of small packages on npm doing one thing well. It's a cross-platform solution with clearly discussed limitations and design decisions regarding hyperthreading.