finish the animation generator maze

Basic main to display ascii print

.gitignore

@@ -214,4 +214,5 @@ __marimo__/
 
 # Streamlit
 .streamlit/secrets.toml
+test.txt
 

Makefile

@@ -1,9 +1,13 @@
 install:
 	uv sync
+	uv pip install mlx-2.2-py3-none-any.whl
 
 run: install
 	uv run python3 a_maze_ing.py config.txt
 
+run_windows:
+	.venv\Scripts\python -m a_maze_ing config.txt
+
 debug:
 	uv pdb python3 a_maze_ing.py config.txt
 
@@ -28,3 +32,5 @@ run_test_maze_gen:
 	PYTHONPATH=src uv run pytest tests/test_MazeGenerator.py
 run_test:
 	uv run pytest
+mlx:
+	uv run python3 test.py

a_maze_ing.py

@@ -1,23 +1,119 @@
-import os
-from src.amaz_lib import Maze
-from src.amaz_lib import MazeGenerator
-import src.amaz_lib as g
+from typing import Any
+from src.AMazeIng import AMazeIng
+from src.parsing import Parsing
+from mlx.mlx import Mlx
+import numpy as np
+import math
 
 
-def main(maze_gen: MazeGenerator) -> None:
-    # try:
-    maze = Maze(maze=None)
-    for alg in maze_gen.generator(10, 10):
-        maze.set_maze(alg)
-        os.system("clear")
-    maze.ascii_print()
-    # solver = AStar((1, 1), (14, 18))
-    # print(solver.solve(maze))
+class MazeMLX:
+    def __init__(self, height: int, width: int) -> None:
+        self.mlx = Mlx()
+        self.height = height
+        self.width = width
+        self.mlx_ptr = self.mlx.mlx_init()
+        self.generator = None
+        self.win_ptr = self.mlx.mlx_new_window(
+            self.mlx_ptr, width, height, "amazing"
+        )
+        self.img_ptr = self.mlx.mlx_new_image(self.mlx_ptr, width, height)
+        self.buf, self.bpp, self.size_line, self.format = (
+            self.mlx.mlx_get_data_addr(self.img_ptr)
+        )
+
+    def close(self) -> None:
+        self.mlx.mlx_destroy_image(self.mlx_ptr, self.img_ptr)
+
+    def put_pixel(self, x, y) -> None:
+        offset = y * self.size_line + x * (self.bpp // 8)
+
+        self.buf[offset + 0] = 0xFF
+        self.buf[offset + 1] = 0xFF
+        self.buf[offset + 2] = 0xFF
+        if self.bpp >= 32:
+            self.buf[offset + 3] = 0xFF
+
+    def clear_image(self) -> None:
+        self.buf[:] = b"\x00" * len(self.buf)
+        self.mlx.mlx_clear_window(self.mlx_ptr, self.win_ptr)
+
+    def put_line(self, start: tuple[int, int], end: tuple[int, int]) -> None:
+        sx, sy = start
+        ex, ey = end
+        if sy == ey:
+            for x in range(min(sx, ex), max(sx, ex) + 1):
+                self.put_pixel(x, sy)
+        if sx == ex:
+            for y in range(min(sy, ey), max(sy, ey) + 1):
+                self.put_pixel(sx, y)
+
+    def update_maze(self, maze: np.ndarray) -> None:
+        self.clear_image()
+        margin = math.trunc(
+            math.sqrt(self.width if self.width > self.height else self.height)
+            // 2
+        )
+        line_len = math.trunc(
+            (
+                (self.height - margin) // len(maze)
+                if self.height > self.width
+                else (self.width - margin) // len(maze[0])
+            )
+        )
+        for y in range(len(maze)):
+            for x in range(len(maze[0])):
+                x0 = x * line_len + margin
+                y0 = y * line_len + margin
+                x1 = x * line_len + line_len + margin
+                y1 = y * line_len + line_len + margin
+
+                if maze[y][x].get_north():
+                    self.put_line((x0, y0), (x1, y0))
+                if maze[y][x].get_est():
+                    self.put_line((x1, y0), (x1, y1))
+                if maze[y][x].get_south():
+                    self.put_line((x0, y1), (x1, y1))
+                if maze[y][x].get_west():
+                    self.put_line((x0, y0), (x0, y1))
+        self.mlx.mlx_put_image_to_window(
+            self.mlx_ptr, self.win_ptr, self.img_ptr, 0, 0)
+
+    def close_loop(self, _: Any):
+        self.mlx.mlx_loop_exit(self.mlx_ptr)
+
+    def gen_maze(self, amazing: AMazeIng) -> None:
+        self.generator = amazing.generate()
+
+    def start(self, amazing: AMazeIng) -> None:
+        self.gen_maze(amazing)
+        self.mlx.mlx_loop_hook(self.mlx_ptr, self.render, amazing)
+        self.mlx.mlx_hook(self.win_ptr, 33, 0, self.close_loop, None)
+        self.mlx.mlx_loop(self.mlx_ptr)
+
+    def render(self, amazing: AMazeIng):
+        try:
+            next(self.generator)
+            self.update_maze(amazing.maze.get_maze())
+            # time.sleep(0.01)
+        except StopIteration:
+            pass
 
 
-# except Exception as err:
-# print(err)
+def main() -> None:
+    mlx = None
+    try:
+        mlx = MazeMLX(1000, 1000)
+        config = Parsing.DataMaze.get_data_maze("config.txt")
+        amazing = AMazeIng(**config)
+        mlx.start(amazing)
+        with open("test.txt", "w") as output:
+            output.write(amazing.__str__())
+    except Exception as err:
+        print(err)
+    finally:
+        if mlx is not None:
+            mlx.close()
 
 
 if __name__ == "__main__":
-    main(g.DepthFirstSearch())
+    main()

config.txt

@@ -1,6 +1,8 @@
-WIDTH=200
-HEIGHT=100
-ENTRY=0,0
-EXIT=19,14
+WIDTH=20
+HEIGHT=20
+ENTRY=1,1
+EXIT=2,2
 OUTPUT_FILE=maze.txt
-PERFECT=True
+PERFECT=False
+GENERATOR=DFS
+SOLVER=AStar

src/AMazeIng.py

@@ -1,22 +1,20 @@
-from dataclasses import field
-from os import eventfd_read
 from typing import Generator
-import numpy
 from typing_extensions import Self
-from pydantic import AfterValidator, BaseModel, Field, model_validator
+from pydantic import BaseModel, Field, model_validator, ConfigDict
 
-from amaz_lib import Maze, MazeGenerator, MazeSolver
-from amaz_lib.Cell import Cell
+from src.amaz_lib import Maze, MazeGenerator, MazeSolver
 
 
 class AMazeIng(BaseModel):
-    width: int = Field(ge=3)
-    height: int = Field(ge=3)
+    model_config = ConfigDict(arbitrary_types_allowed=True)
+
+    width: int = Field(ge=4)
+    height: int = Field(ge=4)
     entry: tuple[int, int]
     exit: tuple[int, int]
     output_file: str = Field(min_length=3)
     perfect: bool = Field(default=True)
-    maze: Maze = Field(default=Maze(maze=numpy.array([])))
+    maze: Maze = Field(default=Maze(None))
     generator: MazeGenerator
     solver: MazeSolver
 
@@ -32,6 +30,7 @@ class AMazeIng(BaseModel):
         for array in self.generator.generator(self.height, self.width):
             self.maze.set_maze(array)
             yield self.maze
+        return
 
     def solve_path(self) -> str:
         return self.solver.solve(self.maze)

src/amaz_lib/Maze.py

@@ -1,8 +1,6 @@
 from dataclasses import dataclass
 
 import numpy
-from .Cell import Cell
-from .MazeGenerator import MazeGenerator
 
 
 @dataclass

src/amaz_lib/MazeGenerator.py

@@ -6,9 +6,14 @@ import math
 
 
 class MazeGenerator(ABC):
+    def __init__(self, start: tuple, end: tuple, perfect: bool) -> None:
+        self.start = (start[0] - 1, start[1] - 1)
+        self.end = (end[0] - 1, end[1] - 1)
+        self.perfect = perfect
+
     @abstractmethod
     def generator(
-        self, height: int, width: int, seed: int = None
+        self, height: int, width: int, seed: int | None = None
     ) -> Generator[np.ndarray, None, np.ndarray]: ...
 
     @staticmethod
@@ -35,8 +40,60 @@ class MazeGenerator(ABC):
         forty_two.add((y + 2, x + 3))
         return forty_two
 
+    @staticmethod
+    def unperfect_maze(width: int, height: int,
+                       maze: np.ndarray, forty_two: set | None,
+                       prob: float = 0.1
+                       ) -> Generator[np.ndarray, None, np.ndarray]:
+        directions = {
+            "N": (0, -1),
+            "S": (0, 1),
+            "W": (-1, 0),
+            "E": (1, 0)
+        }
+
+        reverse = {
+            "N": "S",
+            "S": "N",
+            "W": "E",
+            "E": "W"
+        }
+        min_break = 2
+        while True:
+            count = 0
+            for y in range(height):
+                for x in range(width):
+                    if forty_two and (x, y) in forty_two:
+                        continue
+                    for direc, (dx, dy) in directions.items():
+                        nx, ny = x + dx, y + dy
+                        if forty_two and (
+                            (y, x) in forty_two
+                            or (ny, nx) in forty_two
+                        ):
+                            continue
+                        if not (0 <= nx < width and 0 < ny < height):
+                            continue
+                        if direc in ["S", "E"]:
+                            continue
+                        if np.random.random() < prob:
+                            count += 1
+                            cell = maze[y][x]
+                            cell_n = maze[ny][nx]
+                            cell = DepthFirstSearch.broken_wall(cell, direc)
+                            cell_n = DepthFirstSearch.broken_wall(cell_n,
+                                                                  reverse[
+                                                                    direc])
+                            maze[y][x] = cell
+                            maze[ny][nx] = cell_n
+                            yield maze
+            if count > min_break:
+                break
+        return maze
+
 
 class Kruskal(MazeGenerator):
+
     class Set:
         def __init__(self, cells: list[int]) -> None:
             self.cells: list[int] = cells
@@ -100,9 +157,27 @@ class Kruskal(MazeGenerator):
                 return
         raise Exception("two sets not found")
 
+    @staticmethod
+    def touch_ft(
+        width: int,
+        wall: tuple[int, int],
+        cells_ft: None | set[tuple[int, int]],
+    ) -> bool:
+        if cells_ft is None:
+            return False
+        s1 = (math.trunc(wall[0] / width), wall[0] % width)
+        s2 = (math.trunc(wall[1] / width), wall[1] % width)
+        return s1 in cells_ft or s2 in cells_ft
+
     def generator(
-        self, height: int, width: int, seed: int = None
+        self, height: int, width: int, seed: int | None = None
     ) -> Generator[np.ndarray, None, np.ndarray]:
+        cells_ft = None
+        if height > 10 and width > 10:
+            cells_ft = self.get_cell_ft(width, height)
+        if cells_ft and (self.start in cells_ft or self.end in cells_ft):
+            cells_ft = None
+
         if seed is not None:
             np.random.seed(seed)
         sets = self.Sets([self.Set([i]) for i in range(height * width)])
@@ -113,23 +188,40 @@ class Kruskal(MazeGenerator):
         for h in range(height - 1):
             for w in range(width):
                 walls += [(w + (width * h), w + (width * (h + 1)))]
-        print(walls)
         np.random.shuffle(walls)
 
         yield self.walls_to_maze(walls, height, width)
-        while len(sets.sets) > 1:
+        while (len(sets.sets) != 1 and cells_ft is None) or (
+            len(sets.sets) != 19 and cells_ft is not None
+        ):
             for wall in walls:
-                if not self.is_in_same_set(sets, wall):
+                if not self.is_in_same_set(sets, wall) and not self.touch_ft(
+                    width, wall, cells_ft
+                ):
                     self.merge_sets(sets, wall)
                     walls.remove(wall)
                     yield self.walls_to_maze(walls, height, width)
-                if len(sets.sets) == 1:
+                if (len(sets.sets) == 1 and cells_ft is None) or (
+                    len(sets.sets) == 19 and cells_ft is not None
+                ):
                     break
         print(f"nb sets: {len(sets.sets)}")
-        return self.walls_to_maze(walls, height, width)
+        maze = self.walls_to_maze(walls, height, width)
+        if self.perfect is False:
+            gen = Kruskal.unperfect_maze(width, height, maze,
+                                         cells_ft)
+            for res in gen:
+                maze = res
+                yield maze
+        return maze
 
 
 class DepthFirstSearch(MazeGenerator):
+    def __init__(self, start: bool, end: bool, perfect: bool) -> None:
+        self.start = (start[0] - 1, start[1] - 1)
+        self.end = (end[0] - 1, end[1] - 1)
+        self.perfect = perfect
+        self.forty_two: set | None = None
 
     def generator(
         self, height: int, width: int, seed: int = None
@@ -137,9 +229,15 @@ class DepthFirstSearch(MazeGenerator):
         if seed is not None:
             np.random.seed(seed)
         maze = self.init_maze(width, height)
-        forty_two = self.get_cell_ft(width, height)
+        if width > 9 and height > 9:
+            self.forty_two = self.get_cell_ft(width, height)
         visited = np.zeros((height, width), dtype=bool)
-        visited = self.lock_cell_ft(visited, forty_two)
+        if (
+            self.forty_two
+            and self.start not in self.forty_two
+            and self.end not in self.forty_two
+        ):
+            visited = self.lock_cell_ft(visited, self.forty_two)
         path = list()
         w_h = (width, height)
         coord = (0, 0)
@@ -170,6 +268,12 @@ class DepthFirstSearch(MazeGenerator):
             x, y = coord
             maze[y][x] = self.broken_wall(maze[y][x], wall_r)
             yield maze
+        if self.perfect is False:
+            gen = DepthFirstSearch.unperfect_maze(width, height, maze,
+                                                  self.forty_two)
+            for res in gen:
+                maze = res
+                yield maze
         return maze
 
     @staticmethod
@@ -230,7 +334,7 @@ class DepthFirstSearch(MazeGenerator):
         return {"N": "S", "S": "N", "W": "E", "E": "W"}[direction]
 
     @staticmethod
-    def back_on_step(path: list, w_h: tuple, visited: np.array) -> list:
+    def back_on_step(path: list, w_h: tuple, visited: np.ndarray) -> list:
         while path:
             last = path[-1]
             if DepthFirstSearch.random_cells(visited, last, w_h):
@@ -239,8 +343,9 @@ class DepthFirstSearch(MazeGenerator):
         return path
 
     @staticmethod
-    def lock_cell_ft(visited: np.ndarray, forty_two: set[tuple[int]]
-                     ) -> np.ndarray:
+    def lock_cell_ft(
+        visited: np.ndarray, forty_two: set[tuple[int]]
+    ) -> np.ndarray:
         tab = [cell for cell in forty_two]
         for cell in tab:
             visited[cell] = True

src/amaz_lib/MazeSolver.py

@@ -5,11 +5,12 @@ 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)
+        self.start = (start[1] - 1, start[0] - 1)
+        self.end = (end[1] - 1, end[0] - 1)
 
     @abstractmethod
-    def solve(self, maze: Maze) -> str: ...
+    def solve(self, maze: Maze, height: int = None,
+              width: int = None) -> str: ...
 
 
 class AStar(MazeSolver):
@@ -48,35 +49,39 @@ class AStar(MazeSolver):
             return 1000
 
     def best_path(
-        self, maze: np.ndarray, actual: tuple[int, int]
-    ) -> dict[str, int | None]:
-        print(actual)
+        self,
+        maze: np.ndarray,
+        actual: tuple[int, int],
+        last: str | None,
+    ) -> dict[str, int]:
         path = {
             "N": (
-                self.f((actual[1] - 1, actual[0]))
-                if not maze[actual[1]][actual[0]].get_north() and actual[0] > 0
+                self.f((actual[0], actual[1] - 1))
+                if not maze[actual[1]][actual[0]].get_north() and actual[1] > 0
                 else None
             ),
             "E": (
-                self.f((actual[1], actual[0] + 1))
+                self.f((actual[0] + 1, actual[1]))
                 if not maze[actual[1]][actual[0]].get_est()
-                and actual[1] < len(maze) - 1
+                and actual[0] < len(maze[0]) - 1
                 else None
             ),
             "S": (
-                self.f((actual[1] + 1, actual[0]))
+                self.f((actual[0], actual[1] + 1))
                 if not maze[actual[1]][actual[0]].get_south()
-                and actual[0] < len(maze) - 1
+                and actual[1] < len(maze) - 1
                 else None
             ),
             "W": (
-                self.f((actual[1], actual[0] - 1))
-                if not maze[actual[1]][actual[0]].get_west() and actual[1] > 0
+                self.f((actual[0] - 1, actual[1]))
+                if not maze[actual[1]][actual[0]].get_west() and actual[0] > 0
                 else None
             ),
         }
         return {
-            k: v for k, v in sorted(path.items(), key=lambda item: item[0])
+            k: v
+            for k, v in sorted(path.items(), key=lambda item: item[0])
+            if v is not None and k != last
         }
 
     def get_opposit(self, dir: str) -> str:
@@ -108,14 +113,125 @@ class AStar(MazeSolver):
                 return actual
 
     def get_path(self, maze: np.ndarray) -> str | None:
-        actual = self.start
-        path = ""
+        path = [(self.start, self.best_path(maze, self.start, None))]
+        visited = [self.start]
+        while len(path) > 0 and path[-1][0] != self.end:
+            if len(path[-1][1]) == 0:
+                path.pop(-1)
+                if len(path) == 0:
+                    break
+                k = next(iter(path[-1][1]))
+                path[-1][1].pop(k)
+                continue
 
-        return None
+            while len(path[-1][1]) > 0:
+                next_pos = self.get_next_pos(
+                    list(path[-1][1].keys())[0], path[-1][0]
+                )
+                if next_pos in visited:
+                    k = next(iter(path[-1][1]))
+                    path[-1][1].pop(k)
+                else:
+                    break
+            if len(path[-1][1]) == 0:
+                path.pop(-1)
+                continue
+
+            pre = self.get_opposit(list(path[-1][1].keys())[0])
+            path.append(
+                (
+                    next_pos,
+                    self.best_path(maze, next_pos, pre),
+                )
+            )
+            visited += [next_pos]
+        if len(path) == 0:
+            return None
+        path[-1] = (self.end, {})
+        return "".join(
+            str(list(c[1].keys())[0]) for c in path if len(c[1]) > 0
+        )
 
     def solve(self, maze: Maze) -> str:
-        print(maze)
-        res = self.get_path(self.start, maze.get_maze(), None)
+        res = self.get_path(maze.get_maze())
         if res is None:
             raise Exception("Path not found")
         return res
+
+
+class DepthFirstSearchSolver(MazeSolver):
+    def __init__(self, start, end):
+        self.start = (start[1] - 1, start[0] - 1)
+        self.end = (end[1] - 1, end[0] - 1)
+
+    def solve(self, maze: Maze, height: int = None,
+              width: int = None) -> str:
+        path_str = ""
+        visited = np.zeros((height, width), dtype=bool)
+        path = list()
+        move = list()
+        maze_s = maze.get_maze()
+        coord = self.start
+        h_w = (height, width)
+        while coord != self.end:
+            visited[coord] = True
+            path.append(coord)
+            rand_p = self.random_path(visited, coord, maze_s, h_w)
+
+            if not rand_p:
+                path, move = self.back_on_step(path, visited, maze_s, h_w,
+                                               move)
+                if not path:
+                    break
+                coord = path[-1]
+                rand_p = self.random_path(visited, coord, maze_s, h_w)
+            next = self.next_path(rand_p)
+            move.append(next)
+            coord = self.next_cell(coord, next)
+        for m in move:
+            path_str += m
+        if not path:
+            raise Exception("Path not found")
+        return path_str
+
+    @staticmethod
+    def random_path(visited: np.ndarray, coord: tuple,
+                    maze: np.ndarray, h_w: tuple) -> list:
+        random_p = []
+        h, w = h_w
+        y, x = coord
+
+        if y - 1 >= 0 and not maze[y][x].get_north() and not visited[y - 1][x]:
+            random_p.append("N")
+
+        if y + 1 < h and not maze[y][x].get_south() and not visited[y + 1][x]:
+            random_p.append("S")
+
+        if x - 1 >= 0 and not maze[y][x].get_west() and not visited[y][x - 1]:
+            random_p.append("W")
+
+        if x + 1 < w and not maze[y][x].get_est() and not visited[y][x + 1]:
+            random_p.append("E")
+        return random_p
+
+    @staticmethod
+    def next_path(rand_path: list) -> str:
+        return np.random.choice(rand_path)
+
+    @staticmethod
+    def back_on_step(path: list, visited: np.ndarray,
+                     maze: np.ndarray, h_w: tuple, move: list) -> list:
+        while path:
+            last = path[-1]
+            if DepthFirstSearchSolver.random_path(visited, last, maze, h_w):
+                break
+            path.pop()
+            move.pop()
+        return path, move
+
+    @staticmethod
+    def next_cell(coord: tuple, next: str) -> tuple:
+        y, x = coord
+        next_step = {"N": (-1, 0), "S": (1, 0), "W": (0, -1), "E": (0, 1)}
+        add_y, add_x = next_step[next]
+        return (y + add_y, x + add_x)

src/amaz_lib/__init__.py

@@ -2,9 +2,9 @@ from .Cell import Cell
 from .Maze import Maze
 from .MazeGenerator import MazeGenerator, DepthFirstSearch
 from .MazeGenerator import Kruskal
-from .MazeSolver import MazeSolver, AStar
+from .MazeSolver import MazeSolver, AStar, DepthFirstSearchSolver
 
 __version__ = "1.0.0"
 __author__ = "us"
-__all__ = ["Cell", "Maze", "MazeGenerator",
+__all__ = ["Cell", "Maze", "MazeGenerator", "DepthFirstSearchSolver",
            "MazeSolver", "AStar", "Kruskal", "DepthFirstSearch"]

src/parsing/Parsing.py

@@ -1,3 +1,7 @@
+from src.amaz_lib.MazeGenerator import DepthFirstSearch, Kruskal
+from src.amaz_lib.MazeSolver import AStar
+
+
 class DataMaze:
 
     @staticmethod
@@ -11,28 +15,30 @@ class DataMaze:
     @staticmethod
     def transform_data(data: str) -> dict:
         tmp = data.split("\n")
-        tmp2 = [
-            value.split("=", 1) for value in tmp
-        ]
-        data_t = {
-            value[0]: value[1] for value in tmp2
-        }
+        tmp2 = [value.split("=", 1) for value in tmp if "=" in value]
+        data_t = {value[0]: value[1] for value in tmp2}
         return data_t
 
     @staticmethod
     def verif_key_data(data: dict) -> None:
         key_test = {
-            "WIDTH", "HEIGHT", "ENTRY", "EXIT", "OUTPUT_FILE", "PERFECT"
-        }
-        set_key = {
-            key for key in data.keys()
+            "WIDTH",
+            "HEIGHT",
+            "ENTRY",
+            "EXIT",
+            "OUTPUT_FILE",
+            "PERFECT",
+            "GENERATOR",
+            "SOLVER",
         }
+        set_key = {key for key in data.keys()}
         if len(set_key) != len(key_test):
             raise KeyError("Missing some data the len do not correspond")
         res_key = {key for key in set_key if key not in key_test}
         if len(res_key) != 0:
-            raise KeyError("Some Key "
-                           f"do not correspond the keys: {res_key}")
+            raise KeyError(
+                "Some Key " f"do not correspond the keys: {res_key}"
+            )
 
     @staticmethod
     def convert_values(data: dict):
@@ -47,8 +53,47 @@ class DataMaze:
         for key in key_bool:
             res.update({key: DataMaze.convert_bool(data[key])})
         res.update({"OUTPUT_FILE": data["OUTPUT_FILE"]})
+        res.update(
+            DataMaze.get_solver_generator(data, res["ENTRY"], res["EXIT"],
+                                          res["PERFECT"])
+        )
         return res
 
+    @staticmethod
+    def get_solver_generator(data: dict, entry: tuple, exit: tuple,
+                             perfect: bool) -> dict:
+        available_generator = {
+            "Kruskal": Kruskal,
+            "DFS": DepthFirstSearch,
+        }
+        available_solver = {
+            "AStar": AStar,
+        }
+        res = {}
+        res["GENERATOR"] = available_generator[data["GENERATOR"]](entry, exit,
+                                                                  perfect)
+        res["SOLVER"] = available_solver[data["SOLVER"]](entry, exit)
+        return res
+
+    @staticmethod
+    def convert_tuple(data: str) -> tuple:
+        data_t = data.split(",")
+        if len(data_t) != 2:
+            raise ValueError(
+                "There is too much " "argument in the coordinate given"
+            )
+        x, y = data_t
+        tup = (int(x), int(y))
+        return tup
+
+    @staticmethod
+    def convert_bool(data: str) -> bool:
+        if data != "True" and data != "False":
+            raise ValueError("This is not True or False")
+        if data == "True":
+            return True
+        return False
+
     @staticmethod
     def get_data_maze(name_file: str) -> dict:
         try:
@@ -56,7 +101,7 @@ class DataMaze:
             data_dict = DataMaze.transform_data(data_str)
             DataMaze.verif_key_data(data_dict)
             data_maze = DataMaze.convert_values(data_dict)
-            return data_maze
+            return {k.lower(): v for k, v in data_maze.items()}
         except FileNotFoundError:
             print("The file do not exist")
             exit()
@@ -70,28 +115,11 @@ class DataMaze:
             print(f"Error on the key in the file: {e}")
             exit()
         except IndexError as e:
-            print("In the function transform Data some data cannot "
-                  f"be splited by '=' because '=' was not present: {e}")
+            print(
+                "In the function transform Data some data cannot "
+                f"be splited by '=' because '=' was not present: {e}"
+            )
             exit()
         except AttributeError as e:
-            print("Error on the "
-                  f"funciton get_data_maze : {e}")
+            print("Error on the " f"funciton get_data_maze : {e}")
             exit()
-
-    @staticmethod
-    def convert_tuple(data: str) -> tuple:
-        data_t = data.split(",")
-        if len(data_t) != 2:
-            raise ValueError("There is too much "
-                             "argument in the coordinate given")
-        x, y = data_t
-        tup = (int(x), int(y))
-        return tup
-
-    @staticmethod
-    def convert_bool(data: str) -> bool:
-        if data != "True" and data != "False":
-            raise ValueError("This is not True or False")
-        if data == "True":
-            return True
-        return False

test.txt

@@ -1,23 +1,24 @@
-7D53BFD3D57951517D1D
-3D12C3903BD03AD4178D
-2BAEBEEEAA92EED547C9
-2287ED17AAAC5393FFF0
-6C6951292A87D2AEBD30
-37D43E8686E93AABAB8C
-21516D2D47FEE8284049
-6C7857C3FB9116C696D8
-751453D6D2AAC57BE970
-3BA952D17EA83BD05470
-22AAD2907BAE86967B74
-2AA83C2EFC69696FBC35
-686EE96FD7D4783FAD21
-7ED17ED3D57D3EC52FA0
-7B943D16FB7BABD3AFC8
-7407C5297EB82EB84174
-392D53C6912EE9447E9D
-62A952BBAAC13EFD7B89
-3AAC3EC6EABAAD557824
-66C7C7D7D6C6C7D556CD
+B9153957955513953953
+AEA96A9569792C6BAAD6
+C5443AA9169281102C53
+95556A82816C2AC2A952
+A93916A86A956C3A86D6
+AEC6C542944513806953
+C395553AC393C2AC787A
+BC69512C7AAC56855692
+A952BAAF96AFFFAD53AE
+A810686FC5057FC516C3
+AAC4543FFFAFFFB96952
+AC5553817FAFD52ABC3A
+815552843FEFFF80296A
+AC553A85413D55406C12
+C53BAAC392C3953C13AA
+9386AC386A9683C56AAA
+846903AE96C568517C2A
+AD3A82C385397C3C5546
+C12AA87AA94293AD5513
+D46C6C5446D46C45556E
 
 1,1
-16,15
+2,2
+SSEEENENWWWS

tests/test_MazeGenerator.py

@@ -1,14 +1,18 @@
 import numpy
-from amaz_lib.MazeGenerator import DepthFirstSearch
+from amaz_lib.MazeGenerator import DepthFirstSearch, MazeGenerator
 
 
 class TestMazeGenerator:
 
     def test_generator(self) -> None:
-        w_h = (300, 300)
+        w_h = (10, 10)
         maze = numpy.array([])
-        generator = DepthFirstSearch().generator(*w_h)
+        generator = DepthFirstSearch((1, 1), (2, 2), True).generator(*w_h)
         for output in generator:
             maze = output
 
         assert maze.shape == w_h
+
+    def test_gen_broken(self) -> None:
+        test = MazeGenerator.gen_broken_set(50, 50)
+        assert len(test) > 0