funcy VS django-auto-prefetching

On an unrelated note, Python folks should check out OP's library funcy [1]: "A collection of fancy functional tools focused on practicality. Inspired by clojure, underscore and my own abstractions."

Thanks for the library Suor!

[1] https://github.com/Suor/funcy

Functional semantics are available in Python, but IMO not that great. List, dict, and generator comprehensions allow you to perform most operations that you would use in a functional first programming language and there are third party libraries like toolz and funcy that implement some of the more advanced operations. The main issue I've found with using Python as a functional language is it doesn't support fluent syntax. With Scala you can do a relatively complex map/filter/reduce operation with syntactic ease list_of_ints.map(x => x*x).filter(x => x%2 ==0).reduce(x,y => x+y) With Python it's just clunky and less readable b/c of support of list comprehension syntax over fluent syntax. sum([x**2 for x in list_of_ints if x % 2 == 0]) A codebase with 5000 lines of the Scala style code will be much readable and maintainable than with the Python style code.

Also worse looking at: https://github.com/suor/funcy

Shameless plug - I ran into this while developing REST interfaces with Django and built django-auto-prefetching: https://github.com/GeeWee/django-auto-prefetching

It essentially travels your DRF serializer tree and builds an auto-prefetched query automatically without you needing to do any work.

Back when I still worked actively on it, I wanted to monkey-patch models to track whether or not n+1 was happening, and if it was, automatically do pre-fetching, so instead of an n+1 problem you'd end up with just a "3-4 queries when it could've been 1" problem - which is much more palatable. Never got around to that part though.