feat: add solution 2025/10

data/example/2025/10.txt

@@ -0,0 +1,3 @@
+[.##.] (3) (1,3) (2) (2,3) (0,2) (0,1) {3,5,4,7}
+[...#.] (0,2,3,4) (2,3) (0,4) (0,1,2) (1,2,3,4) {7,5,12,7,2}
+[.###.#] (0,1,2,3,4) (0,3,4) (0,1,2,4,5) (1,2) {10,11,11,5,10,5}

requirements.txt

@@ -1,2 +1,7 @@
+# cli
 python-dotenv==1.2.1
 requests==2.32.5
+
+# solutions
+numpy==2.3.5
+scipy==1.16.3

src/solution/year_2025/day_10.py

@@ -0,0 +1,98 @@
+import collections
+import re
+from typing import Any
+
+import numpy as np
+from scipy import optimize
+
+
+def _parse_input(input_data: str):
+    res: list[tuple[int, list[list[int]], list[int]]] = []
+
+    for line in input_data.splitlines():
+        _state = re.findall(r"\[([.#]*)\]", line)[0]
+        state = sum(1 << i for i, x in enumerate(_state) if x == "#")
+
+        _buttons = re.findall(r"\(([0-9,]*)\)", line)
+        buttons = [[int(n) for n in m.split(",")] for m in _buttons]
+
+        _joltage = re.findall(r" {([0-9,]*)}$", line)[0].strip()
+        joltage = list(map(int, _joltage.split(",")))
+
+        res.append((state, buttons, joltage))
+
+    return res
+
+
+def _bfs(end: int, neighs: list[int]) -> int:
+    start = 0
+
+    dq = collections.deque([(0, start)])
+    visited = {0}
+
+    while dq:
+        d, p = dq.popleft()
+
+        if p == end:
+            return d
+
+        for n in neighs:
+            np = p ^ n
+
+            if np in visited:
+                continue
+
+            visited.add(np)
+            dq.append((d + 1, np))
+
+    raise ValueError(f"unable to calibrate {end}")
+
+
+def _milp(vecs: list[list[int]], goal: list[int]) -> int:
+    n = len(goal)
+    m = len(vecs)
+
+    a = np.zeros((n, m), dtype=int)
+
+    for j, vec in enumerate(vecs):
+        for i in vec:
+            a[i][j] = 1
+
+    c = np.ones(m)
+    b = np.array(goal)
+
+    constraints = optimize.LinearConstraint(a, b, b)  # type: ignore
+    bounds = optimize.Bounds(0, np.inf)
+    integrality = np.ones(m)
+
+    result = optimize.milp(
+        c,
+        constraints=constraints,
+        bounds=bounds,
+        integrality=integrality,
+    )
+
+    return int(result.fun)
+
+
+def part_1(input_data: str) -> Any:
+    parsed = _parse_input(input_data)
+
+    s = 0
+    for end, switches, _ in parsed:
+        neighs = [sum(1 << n for n in m) for m in switches]
+        s += _bfs(end, neighs)
+
+    return s
+
+
+def part_2(input_data: str) -> Any:
+    return sum(_milp(vecs, goal) for _, vecs, goal in _parse_input(input_data))
+
+
+def test_part_1(example_data):
+    assert part_1(example_data) == 7
+
+
+def test_part_2(example_data):
+    assert part_2(example_data) == 33