That's something I hadn't thought of. Thanks

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Many great things to consider in this thread. Many thanks to you and others that put their thoughts down.

I agree. Another example, Linus T wrote git from scratch to hosting the Linux kernel in 2.5 months. I'd say 10x is a low estimate.

I've worked with a guy who wrote great code like he was typing an email.

Everyone has a ceiling of the complexity of problems they can handle, some programmers are outliers in this regard.

Bit of an aside, but writing an email is its own art. Not many developers know how to write an email that a busy, non-technical VP will read, understand and act on in the way they intended. (Then again, neither do many managers.)

This was born out of necessity as data comes from multiple systems and takes around 4 minutes per run. Now I can iterate in like 5 seconds

Not something I seen, a decorator used only for development that is deployed in production.

Thoughts?

Interesting project! I like the config file. The readme also has a good example.

Can you go a bit more into detail as to why I would pick this over functional.lru_cache?

Thanks for checking it out!

Good question, this is slightly different than lru_cache in that it persists to disk so it retrieves from the cache even when you rerun the Python interpreter.

Also it gives you a bit of flexibility as when to refresh the cache and to use or ignore function parameters. I often make a change in one 'group', db data for example, and am able to just refresh those methods that gather data from the db.