Toolz VS funcy

My favourite lib would probably be toolz, it's just so elegant and fun to use. But it's more functional approach is not always the best fit for the time, so in practice I mostly use it in research, prototyping, console and notebooks.

I am not new to Python but only used it to write scripts. Should I start a Python book and then a PySpark book or go directly to PySpark? When reading the legacy code, I found there are usages like GitHub - pytoolz/toolz: A functional standard library for Python. I never heard of.

toolz is wildly useful https://github.com/pytoolz/toolz

Maybe the toolz[0] family would cover your use cases? There is also a Cython implementation if you need better performance.

[0] https://github.com/pytoolz/toolz/

You'll probably enjoy toolz.

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