2024

advent/advent.py

@@ -13,6 +13,7 @@
     advent2021,
     advent2022,
     advent2023,
+    advent2024
 )
 
 logger = logging.getLogger("advent")
@@ -31,6 +32,7 @@ def __init__(self):
         self.days["2021"] = advent2021.days
         self.days["2022"] = advent2022.days
         self.days["2023"] = advent2023.days
+        self.days["2024"] = advent2024.days
 
     def run_day(self, year, day, part):
         yr = self.days[str(year)]

advent/advent2024/__init__.py

@@ -0,0 +1,3 @@
+from .day1 import Day1
+
+days = {1: Day1}

advent/advent2024/day1.py

@@ -0,0 +1,49 @@
+from advent.day import Day
+
+class Day1(Day):
+    year = 2024
+    day = 1
+
+    list_a = []
+    list_b = []
+
+    def _part1(self):
+        self.load_lists_from_input(self.input())
+        self.list_a.sort()
+        self.list_b.sort()
+        return self.get_total_distance_between_lists(self.list_a, self.list_b)
+
+    def _part2(self):
+        self.load_lists_from_input(self.input())
+        return self.get_similarity_score(self.list_a, self.list_b)
+
+    def reset_lists(self):
+        self.list_a = []
+        self.list_b = []
+
+    def load_lists_from_input(self, input):
+        for line in input.splitlines():
+            line_split = line.split()
+            self.list_a.append(int(line_split[0]))
+            self.list_b.append(int(line_split[1]))
+
+    def get_distance(self, a: int, b: int) -> int:
+        return abs(a - b)
+
+    def get_total_distance_between_lists(self, list_a: list[int], list_b: list[int]) -> int:
+        if len(list_a) != len(list_b):
+            raise ValueError("lists were not equal in length")
+
+        else:
+            total_distance = 0
+            for i in range(0, len(list_a)):
+                total_distance += self.get_distance(list_a[i], list_b[i])
+
+        return total_distance
+
+    def get_similarity_score(self, list_a: list[int], list_b: list[int]) -> int:
+        similarity_score = 0
+        for number in list_a:
+            similarity_score += number * list_b.count(number)
+
+        return similarity_score