fix the cell pydantic cause the program was too long

Makefile

@@ -20,3 +20,11 @@ lint-strict:
 
 run_test_parsing:
 	PYTHONPATH=src uv run pytest tests/test_parsing.py
+
+run_test_dfs:
+	PYTHONPATH=src uv run pytest tests/test_Depth.py
+
+run_test_maze_gen:
+	PYTHONPATH=src uv run pytest tests/test_MazeGenerator.py
+run_test:
+	uv run pytest

a_maze_ing.py

@@ -1,22 +1,21 @@
 import os
-from numpy import ma
-from src.amaz_lib import MazeGenerator
 from src.amaz_lib import Maze
+from src.amaz_lib import MazeGenerator
+import src.amaz_lib as g
 
 
-def main() -> None:
+def main(maze_gen: MazeGenerator) -> None:
     # try:
-    maze = Maze(maze=None, start=(1, 1), end=(16, 15))
+    maze = Maze(maze=None)
-    for alg in MazeGenerator.Kruskal.kruskal(20, 20):
+    gen = maze_gen.generator(100, 100)
+    for alg in gen:
         maze.set_maze(alg)
         os.system("clear")
         maze.ascii_print()
-    maze.export_maze("test.txt")
-
 
 # except Exception as err:
 # print(err)
 
 
 if __name__ == "__main__":
-    main()
+    main(g.DepthFirstSearch())

src/amaz_lib/Cell.py

@@ -1,8 +1,10 @@
-from pydantic import BaseModel, Field
+from dataclasses import dataclass
 
 
-class Cell(BaseModel):
+@dataclass
-    value: int = Field(ge=0, le=15)
+class Cell:
+    def __init__(self, value: int) -> None:
+        self.value = value
 
     def __str__(self) -> str:
         return hex(self.value).removeprefix("0x").upper()

src/amaz_lib/MazeGenerator.py

@@ -84,17 +84,118 @@ class Kruskal(MazeGenerator):
         return self.walls_to_maze(walls, height, width)
 
 
-def main():
+class DepthFirstSearch(MazeGenerator):
-    try:
-        for alg in MazeGenerator.Kruskal.kruskal(10, 10):
-            maze = alg
-            # print(maze)
-            # print()
-        print(maze)
 
-    except GeneratorExit as maze:
+    def generator(self, width: int, height: int
-        print(maze)
+                  ) -> Generator[np.ndarray, None, np.ndarray]:
+        maze = DepthFirstSearch.init_maze(width, height)
+        visited = np.zeros((height, width), dtype=bool)
+        path = list()
+        w_h = (width, height)
+        coord = (0, 0)
+        x, y = coord
+        first = True
 
+        while path or first:
+            first = False
+            visited[y, x] = True
+            path = DepthFirstSearch.add_cell_visited(coord, path)
+            random_c = DepthFirstSearch.random_cells(visited, coord, w_h)
+            if len(random_c) == 0:
+                path = DepthFirstSearch.back_on_step(path, w_h, visited)
+                if path:
+                    coord = path[-1]
+                random_c = DepthFirstSearch.random_cells(visited, coord, w_h)
+                x, y = coord
+                if not path:
+                    break
 
-if __name__ == "__main__":
+            wall = DepthFirstSearch.next_step(random_c)
-    main()
+            maze[y][x] = DepthFirstSearch.broken_wall(maze[y][x], wall)
+
+            coord = DepthFirstSearch.next_cell(x, y, wall)
+            wall_r = DepthFirstSearch.reverse_path(wall)
+            x, y = coord
+            maze[y][x] = DepthFirstSearch.broken_wall(maze[y][x], wall_r)
+            yield maze
+        return maze
+
+    @staticmethod
+    def init_maze(width: int, height: int) -> np.ndarray:
+        maze = np.array([[Cell(value=15) for _ in range(width)]
+                        for _ in range(height)])
+        return maze
+
+    @staticmethod
+    def add_cell_visited(coord: tuple, path: set) -> list:
+        path.append(coord)
+        return path
+
+    @staticmethod
+    def random_cells(visited: np.array, coord: tuple, w_h: tuple) -> list:
+        rand_cell = []
+        x, y = coord
+        width, height = w_h
+
+        if y - 1 >= 0 and not visited[y - 1][x]:
+            rand_cell.append("N")
+
+        if y + 1 < height and not visited[y + 1][x]:
+            rand_cell.append("S")
+
+        if x - 1 >= 0 and not visited[y][x - 1]:
+            rand_cell.append("W")
+
+        if x + 1 < width and not visited[y][x + 1]:
+            rand_cell.append("E")
+        return rand_cell
+
+    @staticmethod
+    def next_step(rand_cell: list) -> str:
+        return np.random.choice(rand_cell)
+
+    @staticmethod
+    def broken_wall(cell: Cell, wall: str) -> Cell:
+        if wall == "N":
+            cell.set_north(False)
+        elif wall == "S":
+            cell.set_south(False)
+        elif wall == "W":
+            cell.set_west(False)
+        elif wall == "E":
+            cell.set_est(False)
+        return cell
+
+    @staticmethod
+    def next_cell(x: int, y: int, next: str) -> tuple:
+        next_step = {
+            "N": (0, -1),
+            "S": (0, 1),
+            "W": (-1, 0),
+            "E": (1, 0)
+        }
+        add_x, add_y = next_step[next]
+        return (x + add_x, y + add_y)
+
+    @staticmethod
+    def reverse_path(next: str) -> str:
+        reverse = {
+            "N": "S",
+            "S": "N",
+            "W": "E",
+            "E": "W"
+        }
+        return reverse[next]
+
+    @staticmethod
+    def back_on_step(path: list, w_h: tuple, visited: np.array) -> list:
+        last = path[-1]
+        r_cells = DepthFirstSearch.random_cells(visited,  last, w_h)
+        while len(path) > 0:
+            path.pop()
+            if path:
+                last = path[-1]
+            r_cells = DepthFirstSearch.random_cells(visited,  last, w_h)
+            if r_cells:
+                break
+        return path

src/amaz_lib/MazeSolver.py

@@ -1,7 +1,134 @@
 from abc import ABC, abstractmethod
 from .Maze import Maze
+import numpy as np
 
 
 class MazeSolver(ABC):
+    def __init__(self, start: tuple[int, int], end: tuple[int, int]) -> None:
+        self.start = (start[0] - 1, start[1] - 1)
+        self.end = (end[0] - 1, end[1] - 1)
+
     @abstractmethod
     def solve(self, maze: Maze) -> str: ...
+
+
+class AStar(MazeSolver):
+
+    def __init__(self, start: tuple[int, int], end: tuple[int, int]) -> None:
+        super().__init__(start, end)
+
+    def f(self, n):
+        def g(n: tuple[int, int]) -> int:
+            res = 0
+            if n[0] < self.start[0]:
+                res += self.start[0] - n[0]
+            else:
+                res += n[0] - self.start[0]
+            if n[1] < self.start[1]:
+                res += self.start[1] - n[1]
+            else:
+                res += n[1] - self.start[1]
+            return res
+
+        def h(n: tuple[int, int]) -> int:
+            res = 0
+            if n[0] < self.end[0]:
+                res += self.end[0] - n[0]
+            else:
+                res += n[0] - self.end[0]
+            if n[1] < self.end[1]:
+                res += self.end[1] - n[1]
+            else:
+                res += n[1] - self.end[1]
+            return res
+
+        try:
+            return g(n) + h(n)
+        except Exception:
+            return 1000
+
+    def best_path(
+        self, maze: np.ndarray, actual: tuple[int, int]
+    ) -> dict[str, int | None]:
+        print(actual)
+        path = {
+            "N": (
+                self.f((actual[0], actual[1] - 1))
+                if not maze[actual[0]][actual[1]].get_north() and actual[1] > 0
+                else None
+            ),
+            "E": (
+                self.f((actual[0] + 1, actual[1]))
+                if not maze[actual[0]][actual[1]].get_est()
+                and actual[0] < len(maze) - 1
+                else None
+            ),
+            "S": (
+                self.f((actual[0], actual[1] + 1))
+                if not maze[actual[0]][actual[1]].get_south()
+                and actual[1] < len(maze[0]) - 1
+                else None
+            ),
+            "W": (
+                self.f((actual[0] - 1, actual[1]))
+                if not maze[actual[0]][actual[1]].get_west() and actual[0] > 0
+                else None
+            ),
+        }
+        return {
+            k: v for k, v in sorted(path.items(), key=lambda item: item[0])
+        }
+
+    def get_opposit(self, dir: str) -> str:
+        match dir:
+            case "N":
+                return "S"
+            case "E":
+                return "W"
+            case "S":
+                return "N"
+            case "W":
+                return "E"
+            case _:
+                return ""
+
+    def get_next_pos(
+        self, dir: str, actual: tuple[int, int]
+    ) -> tuple[int, int]:
+        match dir:
+            case "N":
+                return (actual[0], actual[1] - 1)
+            case "E":
+                return (actual[0] + 1, actual[1])
+            case "S":
+                return (actual[0], actual[1] + 1)
+            case "W":
+                return (actual[0] - 1, actual[1])
+            case _:
+                return actual
+
+    def get_path(
+        self, actual: tuple[int, int], maze: np.ndarray, pre: str | None
+    ) -> str | None:
+        if actual == self.end:
+            return ""
+        paths = self.best_path(maze, actual)
+        for path in paths:
+            if paths[path] is None:
+                continue
+            if path != pre:
+                temp = self.get_path(
+                    self.get_next_pos(path, actual),
+                    maze,
+                    self.get_opposit(path),
+                )
+                if not temp is None:
+                    return path + temp
+        return None
+
+    def solve(self, maze: Maze) -> str:
+        print(maze)
+        res = self.get_path(self.start, maze.get_maze(), None)
+        if res is None:
+            raise Exception("Path not found")
+        return res

src/amaz_lib/__init__.py

@@ -1,8 +1,10 @@
 from .Cell import Cell
 from .Maze import Maze
-from .MazeGenerator import MazeGenerator
+from .MazeGenerator import MazeGenerator, DepthFirstSearch
-from .MazeSolver import MazeSolver
+from .MazeGenerator import Kruskal
+from .MazeSolver import MazeSolver, AStar
 
 __version__ = "1.0.0"
 __author__ = "us"
-__all__ = ["Cell", "Maze", "MazeGenerator", "MazeSolver"]
+__all__ = ["Cell", "Maze", "MazeGenerator",
+           "MazeSolver", "AStar", "Kruskal", "DepthFirstSearch"]

tests/test_Depth.py

@@ -0,0 +1,27 @@
+from amaz_lib.MazeGenerator import DepthFirstSearch
+from amaz_lib.Cell import Cell
+import numpy as np
+
+
+class TestDepth:
+
+    def test_init_maze(self) -> None:
+        maze = DepthFirstSearch.init_maze(10, 10)
+        cell = Cell(value=15)
+        maze[1][1].set_est(False)
+        assert maze[0][0].value == cell.value
+
+    def test_rand_cells(self) -> None:
+        w_h = (10, 10)
+        lst = np.zeros((10, 10), dtype=bool)
+        lst[0, 0] = True
+        rand_cells = DepthFirstSearch.random_cells(lst, (0, 1), w_h)
+        assert len(rand_cells) == 2
+
+    def test_next_cell(self) -> None:
+        coord = (5, 4)
+        x, y = coord
+        assert DepthFirstSearch.next_cell(x, y, "N") == (2, 3)
+
+    def test_reverse_path(self) -> None:
+        assert DepthFirstSearch.reverse_path("N") == "S"

tests/test_Maze.py

@@ -15,7 +15,7 @@ def test_maze_setter_getter() -> None:
     )
 
     maze.set_maze(test)
-    assert numpy.array_equal(maze.get_maze(), test) == True
+    assert numpy.array_equal(maze.get_maze(), test) is True
 
 
 def test_maze_str() -> None:

tests/test_MazeGenerator.py

@@ -1,11 +1,14 @@
 import numpy
-from amaz_lib.MazeGenerator import Kruskal
+from amaz_lib.MazeGenerator import DepthFirstSearch
 
 
-def test_kruskal_output_shape() -> None:
+class TestMazeGenerator:
-    generator = Kruskal()
-    maze = numpy.array([])
-    for output in generator.generator(10, 10):
-        maze = output
 
-    assert maze.shape == (10, 10)
+    def test_generator(self) -> None:
+        w_h = (300, 300)
+        maze = numpy.array([])
+        generator = DepthFirstSearch().generator(*w_h)
+        for output in generator:
+            maze = output
+
+        assert maze.shape == w_h

tests/test_MazeSolver.py

@@ -0,0 +1,19 @@
+from amaz_lib.Cell import Cell
+import numpy as np
+from amaz_lib import AStar, Maze, MazeSolver
+
+
+def test_solver() -> None:
+    maze = Maze(
+        np.array(
+            [
+                [Cell(value=13), Cell(value=3), Cell(value=11)],
+                [Cell(value=9), Cell(value=4), Cell(value=6)],
+                [Cell(value=12), Cell(value=5), Cell(value=7)],
+            ]
+        )
+    )
+    print(maze)
+    solver = AStar((1, 1), (3, 3))
+    res = solver.solve(maze)
+    assert res == "ESWSEE"