Under Limitations: Datagram support

It appears you are correct. What an odd limitation!

Ok, so you don’t like standup meetings. If you’re actually doing agile, then you’re in luck, because the whole point is that the team is considered competent to pick their own process. In the next retrospective, get the others in the team to agree to skip them, and you’re done. Good luck with that if you’re in some Taylorist org. Now, of course, there’s also the case of getting the worst of two worlds, with Scrum handed down from on high. In that case I’d recommend just getting out.

I use it at work for a script that parses and analyzes some log files in an unusual format. Wrote a naive parser with a parsing combinator library. It was too slow to be usable with CPython. Tried PyPy and got a 50x speed increase (yes, 50 times faster). Very happy with the results, actually =)

Thanks for the feedback. It does seem like parsing logs and simulations is a sweet spot for PyPy

Simulations are, at least in my experience, numba’s [0] wheelhouse.

[0]: https://numba.pydata.org/

what cpython version and OS was that? I'd be very surprised if modern Python 3.11 has anything an order of magnitude slower like that. things have gotten much faster over the years in cpython

Selects via index occasionally does not find data when using serializable transaction isolation on Oracle, since about 25 years (see https://stackoverflow.com/questions/11826368/oracle-select-i... )