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cf78ef9f04
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909b0d3b40
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#!/usr/bin/python3
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"""
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Jour 01 du défi Advent Of Code pour l'année 2024
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"""
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import os
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def read_sample():
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"""récupère les entrées depuis le fichier texte correspondant"""
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filename = os.path.join(os.path.dirname(__file__ ), "inputs", "day01.txt")
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with open(filename, 'r') as f:
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sample = f.read().split('\n')
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sample = [ list(map(int, i.split())) for i in sample if i != '' ]
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return sample
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def part1(sample):
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"""Partie 1 du défi"""
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l1, l2 = sorted([l[0] for l in sample]), sorted([l[1] for l in sample])
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return sum(abs(l1[i]-l2[i]) for i in range(len(l1)))
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def part2(sample):
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"""Partie 2 du défi"""
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l1, l2 = sorted([l[0] for l in sample]), sorted([l[1] for l in sample])
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pres = {}
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for i in l2:
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if i not in pres:
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pres[i] = 0
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pres[i] += 1
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score = 0
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for i in l1:
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if i in pres:
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score += pres[i]*i
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return score
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def main():
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"""Fonction principale"""
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sample = read_sample()
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print(f"part1: {part1(sample)}")
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print(f"part2: {part2(sample)}")
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if __name__ == "__main__":
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main()
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60
FICHE.md
60
FICHE.md
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# Fiche de solutions/ astuces fréquentes pour AoC
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Si on cherche à savoir quand qqchose va arriver et que ça arrive à la conjonction de plusieurs évènements
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```python
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math.lcm(*[_, _, ...])
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```
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quand on calcule les mêmes choses plein de fois (mais VRAIMENT les mêmes choses, pas un chouïa différent)
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```python
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from functools import cache
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@cache
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def ma_fonction(*args)
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```
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quand on doit calculer un truc très grand et que c'est un nb d'états finis (qui se répètent potentiellement)
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détection de cycle
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quand on doit calculer un truc très grand et que c'est un nb d'états infinis:
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```python
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snippets.lagrange_interpolation([(x1, y1), (x2, y2), ...], x0)
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```
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quand on doit calculer l'aire d'un polygone
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```python
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snippets.area([(x1, y1), (x2, y2), ...], count_border=True)
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```
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trop d'éléments en entrée: les considérer par ensembles si possible (genre séquences d'entiers)
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```python
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a = intervals.Interval(0, 5)
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b = intervals.Interval(10, 15)
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a.intersection(b) # None
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a.intersect(b) # False
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a = intervals.Interval(0, 5)
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b = intervals.Interval(4, 15)
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a.intersection(b) # [4, 5]
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a.intersect(b) # True
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```
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quand on a un parcours de graphe, utiliser Graph, et le compresser si nécessaire (attention, que non-orienté !)
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Trouver une instance qui satisfait plein de trucs et ça paraît impossible ? z3 ! `pip install z3-solver`
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```python
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px, py, pz, dx, dy, dz = z3.Ints("px py pz dx dy dz")
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collision = [z3.Int("t"+str(i)) for i in range(len(hailstones))]
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solver = z3.Solver()
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for i in range(len(hailstones)):
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h = hailstones[i]
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solver.add(px + dx*collision[i] == h.px + h.dx*collision[i])
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solver.add(py + dy*collision[i] == h.py + h.dy*collision[i])
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solver.add(pz + dz*collision[i] == h.pz + h.dz*collision[i])
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solver.check()
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return solver.model().evaluate(px + py + pz)
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```
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@ -7,7 +7,7 @@
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2020: ***~.....................
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2021: *******~~~...............
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2022: ***************~.*..*....
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2023: *************************
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2023: **********************~..
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.: nothing
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~: 1 star
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@ -3,4 +3,4 @@ z3-solver
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matplotlib
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networkx
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requests
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beautifulsoup4
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beautifulsoup
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@ -17,7 +17,7 @@ from bs4 import BeautifulSoup
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home = str(Path.home())
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with open(os.path.join(home, ".aoc-cookie"), "r", encoding='utf8') as file:
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cookie = file.read().replace("\n", " ").strip()
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cookie = file.read()
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session = requests.Session()
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session.cookies["session"] = cookie
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