django-cacheops VS funcy

Here is an example of such thing https://github.com/Suor/django-cacheops/blob/8b3a79de29b2545...

django-cacheops is a great package https://github.com/Suor/django-cacheops

Nuts, I was hoping that this was an evolution of https://github.com/Suor/django-cacheops which uses Redis to cache and invalidate ORM result sets by an abstracted representation of filter values. It works, but has a lot of magic (as is the Django way) and takes some tending-to in production.

i came across this and this i am failing to understand what is the difference between the two and which is better.

The solution I recommend is setting up the caching backend using like redis then bringing in this awesome project django-cacheops! Takes 5 minutes to set up (literally) and you’re done!

We use django cacheops with redis and its incredible!

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