From 4147da1317c19fa61d6aa265e8370e63231f9207 Mon Sep 17 00:00:00 2001
From: Tom van der Lee <tom@glootie.lan.tomvanderlee.com>
Date: Sun, 19 Nov 2023 16:55:03 +0100
Subject: Initial commit

---
 aoc/mixins.py | 77 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 77 insertions(+)
 create mode 100644 aoc/mixins.py

(limited to 'aoc/mixins.py')

diff --git a/aoc/mixins.py b/aoc/mixins.py
new file mode 100644
index 0000000..5986b6e
--- /dev/null
+++ b/aoc/mixins.py
@@ -0,0 +1,77 @@
+# -*- coding: utf-8 -*-
+from math import floor, inf
+from typing import Tuple, TypeVar, Generic, Callable, Iterator, List, Dict
+
+Node = TypeVar("Node")
+
+
+class AStarMixin(Generic[Node]):
+    def _gen_path(self, current: Node, came_from: Dict[Node, Node]) -> List[Node]:
+        print("GENPATH")
+        path = [current]
+
+        while current in came_from:
+            current = came_from[current]
+            path = [current, *path]
+
+        return path
+
+    def a_star(
+        self,
+        start: Node,
+        end: Callable[[Node, Callable[[], List[Node]]], bool],
+        neighbours: Callable[[Node], Iterator[Node]],
+        distance: Callable[[Node, Node], int] = lambda a, b: 1,
+        heuristic: Callable[[Node], int] = lambda a: 0,
+    ) -> List[Node]:
+        open_nodes = {start}
+        came_from = {}
+
+        g_scores = {start: 0}
+
+        f_scores = {start: heuristic(start)}
+
+        while True:
+            try:
+                current = sorted(
+                    [item for item in open_nodes],
+                    key=lambda item: f_scores.get(item, inf),
+                )[0]
+            except IndexError:
+                raise RuntimeError("No path found")
+
+            if end(current, lambda: self._gen_path(current, came_from)):
+                return self._gen_path(current, came_from)
+
+            open_nodes.remove(current)
+
+            for neighbour in neighbours(current):
+                g_score = g_scores.get(current, inf) + distance(current, neighbour)
+
+                if g_score < g_scores.get(neighbour, inf):
+                    came_from[neighbour] = current
+                    g_scores[neighbour] = g_score
+                    f_scores[neighbour] = g_score + heuristic(neighbour)
+
+                    if neighbour not in open_nodes:
+                        open_nodes.add(neighbour)
+
+
+class BreathFirstSearchMixin(Generic[Node]):
+    @staticmethod
+    def bfs(
+        start: Node, neighbours: Callable[[Node], Iterator[Node]]
+    ) -> Iterator[Node]:
+        queue = [start]
+        searched = set()
+
+        while len(queue):
+            item = queue.pop(0)
+
+            for neighbour in neighbours(item):
+                if neighbour not in searched and neighbour not in set(queue):
+                    queue.append(neighbour)
+
+            searched.add(item)
+
+            yield item
-- 
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