First solution to part2

It's kind of a time hog, though

day5/data.py

@@ -30,7 +30,7 @@ def extract(input_file: str) -> Tuple[List[int], Dict[str, List[AlmanacMap]]]:
         "humidity-to-location": [],
     }
 
-    with open("input.txt") as input:
+    with open(input_file) as input:
         current_map = {}
         while line := input.readline():
             if match := re.match("seeds: (.*)", line):

day5/part1.py

@@ -10,7 +10,7 @@ for seed in seeds:
     soil_maps = list(filter(lambda soil_map: soil_map.is_mapped(seed), maps["seed-to-soil"]))
     soil = seed if soil_maps == [] else soil_maps[0].mapped_value(seed)
     fertilizer_maps = list(filter(lambda fertilizer_map: fertilizer_map.is_mapped(soil), maps["soil-to-fertilizer"]))
-    print(fertilizer_maps)
+    #print(fertilizer_maps)
     fertilizer = soil if fertilizer_maps == [] else fertilizer_maps[0].mapped_value(soil)
     water_maps = list(filter(lambda water_map: water_map.is_mapped(fertilizer), maps["fertilizer-to-water"]))
     water = fertilizer if water_maps == [] else water_maps[0].mapped_value(fertilizer)

day5/part2_time_hog.py

@@ -0,0 +1,46 @@
+#!/usr/bin/env python3.11
+# Is killed on WSL2 after vmmem increase to 16GB
+from data import extract
+import concurrent.futures
+
+def seed_to_location(seed, maps):
+    print(seed)
+    soil_maps = list(filter(lambda soil_map: soil_map.is_mapped(seed), maps["seed-to-soil"]))
+    soil = seed if soil_maps == [] else soil_maps[0].mapped_value(seed)
+    fertilizer_maps = list(filter(lambda fertilizer_map: fertilizer_map.is_mapped(soil), maps["soil-to-fertilizer"]))
+    #print(fertilizer_maps)
+    fertilizer = soil if fertilizer_maps == [] else fertilizer_maps[0].mapped_value(soil)
+    water_maps = list(filter(lambda water_map: water_map.is_mapped(fertilizer), maps["fertilizer-to-water"]))
+    water = fertilizer if water_maps == [] else water_maps[0].mapped_value(fertilizer)
+    light_maps = list(filter(lambda light_map: light_map.is_mapped(water), maps["water-to-light"]))
+    light = water if light_maps == [] else light_maps[0].mapped_value(water)
+    temperature_maps = list(filter(lambda temperature_map: temperature_map.is_mapped(light), maps["light-to-temperature"]))
+    temperature = light if temperature_maps == [] else temperature_maps[0].mapped_value(light)
+    humidity_maps = list(filter(lambda humidity_map: humidity_map.is_mapped(temperature), maps["temperature-to-humidity"]))
+    humidity = temperature if humidity_maps == [] else humidity_maps[0].mapped_value(temperature)
+    location_maps = list(filter(lambda location_map: location_map.is_mapped(humidity), maps["humidity-to-location"]))
+    location = humidity if location_maps == [] else location_maps[0].mapped_value(humidity)
+    return location
+
+def parallel_loop(seeds, maps, index):
+    lowest_location = None
+    for seed_idx in range(seeds[index]):
+        seed = seeds[index] + seed_idx
+        location = seed_to_location(seed, maps)
+        if lowest_location is not None:
+            lowest_location = min(lowest_location, location)
+        else:
+            lowest_location = location
+seeds, maps = extract("input.txt")
+print(seeds)
+
+
+minimums = []
+with concurrent.futures.ThreadPoolExecutor(max_workers=10) as executor:
+    for idx in range(0, len(seeds), 2):
+        minimum = executor.submit(parallel_loop, seeds, maps, idx)
+        minimums.append(minimum)
+
+
+
+print(min(minimums))