memoize VS ReducePy

memoize

• Good and Bad Elixir
  1 project | news.ycombinator.com | 10 Jun 2021

  I totally agree, though I think those articles are a lot harder (eg requiring more skill) to write well because you need to quickly ramp your readers on all of whatever the context is that's necessary to actually appreciate the nuance of the design decisions under discussion. You're basically by definitely going to be out of the realm of "just follow best practice X" or "apply pattern Y or you're doing it wrong."

  As a small example, I've been working on a small asyncio-based web service (Python) which is oriented around an expensive process that generates a result, where the result is stashed in sqlite and returned. I knew upfront that I needed a way to track when a particular result was already being prepared so that if I got a second request for it, it would collapse it into the first one and only do the work once. I wrote this as a twenty line memoizing decorator, but it turns out this issue as a name— cache stampeding. Once I realized that, I discovered that there are existing (and much more complicated/tunable) solutions to this problem, such as https://github.com/DreamLab/memoize/, but the article pitching that solution spends quite a bit of time getting to it— enough so that if I'd discovered it before building my own, I'm not sure I would even have appreciated its applicability:

  https://tech.ringieraxelspringer.com/blog/open-source/cachin...

ReducePy

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