Every once in a while I have to recognize the beauty that is a high level language.
Consider this code snippet:
def square(x): return x**2 l = [1, 2, 3, 4] for x in map(square, l): print(x)
And this one:
from multiprocessing import Pool def square(x): return x**2 l = [1, 2, 3, 4] for x in Pool().map(square, l): print(x)
Discounting the import line (Because I’m trying to make a point here, dammit!), the diff is a total of 7 characters. Of course, if you recall your Computer Science operating systems 101, the complexity that is hidden here is breath taking. And yet, Python multiprocessing exposes an API that is identical to Python’s good old ‘map’. It does so and manages to keep it boring, without exposing the caller to messy internals and endless complications that are usually involved whenever we dive in to the world of multi processing.
Even more impressive is the fact that I exploited this abstraction in a real world app that does honest to Zeus useful things, and it “just worked”. The processing time was cut by half and I didn’t need to worry about forking, sockets, PIDs, creating and managing processes or any of that mess. All I had to do was focus on the subject matter and not the underlying code. That is the beauty of a high level language. You don’t have to use up cognitive load thinking about memory management, the syntax of templates meta programming, or the depth of pointer dereferencing required, instead you can focus on getting something useful done.
* Herein lies a vim vs. Emacs type disclaimer: Every tool has its place. I would never dream of using Python for a demanding mobile game (Or a cloud operating system, for that matter), but wow is Python fun when you’re parsing and processing tens of thousands of JSON files.