Re:Advent of Code 2024
by anonu on Sunday December 01, 2024 @09:27AM
(#42288602)
Python looks excruciatingly slow to me. If you want fast I believe you need to think and write in vector languages like kdb+/q. I am not a kdb+ expert by any means and my code can probably use more q primitives, but here was my solution in ~2 minutes:
[ Parent
| on HN ]
That’s cool, but horribly ugly! What does production kdb+ look like? Is it similarly terse, maybe Perl-ish, or was this purely for speed?
What does each flip asc do?
i1 is Nx2. asc each i1 sorts each N in ascending order. flip transposes to 2xN.
Re:Advent of Code 2024
by vjerancrnjak on Sunday December 01, 2024 @02:22PM
(#42290116)
Everything autocompletes in Python.
from collections import *
xys = list(map(int, open(0).read().split()))
xs = xys[::2]
ys = xys[1::2]
xs.sort()
ys.sort()
print(sum(abs(x-y) for x,y in zip(xs,ys)))
yc = Counter(ys)
print(sum(((yc[x])*x for x in xs)))this is the least amount of loc I can think of rn
data = { i+1 : sorted([ x for x in list(map(int, open('input').read().split()))[i::2]]) for i in range(2) }
total_distance = sum(list(map(lambda x: abs(x[0]-x[1]), zip(data[1], data[2]))))
print("part 1:", total_distance)
similarity_score = sum(list(map(lambda x: (x*data[2].count(x))*data[1].count(x), set(data[1]).intersection(data[2]))))
print("part 2:", similarity_score)