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
 
@@ -18,5 +22,15 @@ lint-strict:
 	uv run flake8 .
 	uv run mypy . --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
+mlx:
+	uv run python3 test.py

a_maze_ing.py

@@ -1,23 +1,118 @@
-import os
+from typing import Any
-from numpy import ma
+from src.AMazeIng import AMazeIng
-from src.amaz_lib import MazeGenerator, Kruskal, AStar
+from src.parsing import Parsing
-from src.amaz_lib import Maze
+from mlx.mlx import Mlx
+import numpy as np
+import math
+
+
+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
 
 
 def main() -> None:
-    # try:
+    mlx = None
-    maze = Maze(maze=None)
+    try:
-    generator = Kruskal()
+        mlx = MazeMLX(1000, 1000)
-    for alg in generator.generator(20, 20):
+        config = Parsing.DataMaze.get_data_maze("config.txt")
-        maze.set_maze(alg)
+        amazing = AMazeIng(**config)
-        # os.system("clear")
+        mlx.start(amazing)
-        maze.ascii_print()
+        with open("test.txt", "w") as output:
-    # solver = AStar((1, 1), (14, 18))
+            output.write(amazing.__str__())
-    # print(solver.solve(maze))
+    except Exception as err:
-
+        print(err)
-
+    finally:
-# except Exception as err:
+        if mlx is not None:
-# print(err)
+            mlx.close()
 
 
 if __name__ == "__main__":

config.txt

@@ -1,6 +1,8 @@
-WIDTH=200
+WIDTH=20
-HEIGHT=100
+HEIGHT=20
-ENTRY=0,0
+ENTRY=1,1
-EXIT=19,14
+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 src.amaz_lib import Maze, MazeGenerator, MazeSolver
-from amaz_lib.Cell import Cell
 
 
 class AMazeIng(BaseModel):
-    width: int = Field(ge=3)
+    model_config = ConfigDict(arbitrary_types_allowed=True)
-    height: int = Field(ge=3)
+
+    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/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/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

@@ -1,5 +1,4 @@
 from abc import ABC, abstractmethod
-from dataclasses import dataclass
 from typing import Generator, Set
 import numpy as np
 from .Cell import Cell
@@ -7,17 +6,102 @@ 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
+        self, height: int, width: int, seed: int | None = None
     ) -> Generator[np.ndarray, None, np.ndarray]: ...
 
+    @staticmethod
+    def get_cell_ft(width: int, height: int) -> set:
+        forty_two = set()
+        y, x = (int(height / 2), int(width / 2))
+        forty_two.add((y, x - 1))
+        forty_two.add((y, x - 2))
+        forty_two.add((y, x - 3))
+        forty_two.add((y - 1, x - 3))
+        forty_two.add((y - 2, x - 3))
+        forty_two.add((y + 1, x - 1))
+        forty_two.add((y + 2, x - 1))
+        forty_two.add((y, x + 1))
+        forty_two.add((y, x + 2))
+        forty_two.add((y, x + 3))
+        forty_two.add((y - 1, x + 3))
+        forty_two.add((y - 2, x + 3))
+        forty_two.add((y - 2, x + 2))
+        forty_two.add((y - 2, x + 1))
+        forty_two.add((y + 1, x + 1))
+        forty_two.add((y + 2, x + 1))
+        forty_two.add((y + 2, x + 2))
+        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
 
+    class Sets:
+        def __init__(self, sets: list[Set]) -> None:
+            self.sets = sets
+
     @staticmethod
     def walls_to_maze(
         walls: np.ndarray, height: int, width: int
@@ -47,9 +131,9 @@ class Kruskal(MazeGenerator):
         return maze
 
     @staticmethod
-    def is_in_same_set(sets: np.ndarray, wall: tuple[int, int]) -> bool:
+    def is_in_same_set(sets: Sets, wall: tuple[int, int]) -> bool:
         a, b = wall
-        for set in sets:
+        for set in sets.sets:
             if a in set.cells and b in set.cells:
                 return True
             elif a in set.cells or b in set.cells:
@@ -57,22 +141,46 @@ class Kruskal(MazeGenerator):
         return False
 
     @staticmethod
-    def merge_sets(sets: np.ndarray, wall: tuple[int, int]) -> None:
+    def merge_sets(sets: Sets, wall: tuple[int, int]) -> None:
         a, b = wall
         base_set = None
-        for i in range(len(sets)):
+        for i in range(len(sets.sets)):
-            if base_set is None and (a in sets[i].cells or b in sets[i].cells):
+            if base_set is None and (
-                base_set = sets[i]
+                a in sets.sets[i].cells or b in sets.sets[i].cells
-            elif base_set and (a in sets[i].cells or b in sets[i].cells):
+            ):
-                base_set.cells += sets[i].cells
+                base_set = sets.sets[i]
-                np.delete(sets, i)
+            elif base_set and (
+                a in sets.sets[i].cells or b in sets.sets[i].cells
+            ):
+                base_set.cells += sets.sets[i].cells
+                sets.sets.pop(i)
                 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
+        self, height: int, width: int, seed: int | None = None
     ) -> Generator[np.ndarray, None, np.ndarray]:
-        sets = np.array([self.Set([i]) for i in range(height * width)])
+        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)])
         walls = []
         for h in range(height):
             for w in range(width - 1):
@@ -80,14 +188,165 @@ 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)
-        for wall in walls:
+        while (len(sets.sets) != 1 and cells_ft is None) or (
-            if not self.is_in_same_set(sets, wall):
+            len(sets.sets) != 19 and cells_ft is not None
-                self.merge_sets(sets, wall)
+        ):
-                walls.remove(wall)
+            for wall in walls:
-                yield self.walls_to_maze(walls, height, width)
+                if not self.is_in_same_set(sets, wall) and not self.touch_ft(
-        print(f"nb sets: {len(sets)}")
+                    width, wall, cells_ft
-        return self.walls_to_maze(walls, height, width)
+                ):
+                    self.merge_sets(sets, wall)
+                    walls.remove(wall)
+                    yield self.walls_to_maze(walls, height, width)
+                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)}")
+        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
+    ) -> Generator[np.ndarray, None, np.ndarray]:
+        if seed is not None:
+            np.random.seed(seed)
+        maze = self.init_maze(width, height)
+        if width > 9 and height > 9:
+            self.forty_two = self.get_cell_ft(width, height)
+        visited = np.zeros((height, width), dtype=bool)
+        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)
+        x, y = coord
+        first_iteration = True
+
+        while path or first_iteration:
+            first_iteration = False
+
+            visited[y, x] = True
+            path = self.add_cell_visited(coord, path)
+
+            random_c = self.random_cells(visited, coord, w_h)
+
+            if not random_c:
+                path = self.back_on_step(path, w_h, visited)
+                if not path:
+                    break
+                coord = path[-1]
+                random_c = self.random_cells(visited, coord, w_h)
+                x, y = coord
+
+            wall = self.next_step(random_c)
+            maze[y][x] = self.broken_wall(maze[y][x], wall)
+
+            coord = self.next_cell(x, y, wall)
+            wall_r = self.reverse_path(wall)
+            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
+    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(direction: str) -> str:
+        return {"N": "S", "S": "N", "W": "E", "E": "W"}[direction]
+
+    @staticmethod
+    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):
+                break
+            path.pop()
+        return path
+
+    @staticmethod
+    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
+        return visited

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.start = (start[1] - 1, start[0] - 1)
-        self.end = (end[0] - 1, end[1] - 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]
+        self,
-    ) -> dict[str, int | None]:
+        maze: np.ndarray,
-        print(actual)
+        actual: tuple[int, int],
+        last: str | None,
+    ) -> dict[str, int]:
         path = {
             "N": (
                 self.f((actual[0], actual[1] - 1))
-                if not maze[actual[0]][actual[1]].get_north() and actual[1] > 0
+                if not maze[actual[1]][actual[0]].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()
+                if not maze[actual[1]][actual[0]].get_est()
-                and actual[0] < len(maze) - 1
+                and actual[0] < len(maze[0]) - 1
                 else None
             ),
             "S": (
                 self.f((actual[0], actual[1] + 1))
-                if not maze[actual[0]][actual[1]].get_south()
+                if not maze[actual[1]][actual[0]].get_south()
-                and actual[1] < len(maze[0]) - 1
+                and actual[1] < len(maze) - 1
                 else None
             ),
             "W": (
                 self.f((actual[0] - 1, actual[1]))
-                if not maze[actual[0]][actual[1]].get_west() and actual[0] > 0
+                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:
@@ -107,28 +112,126 @@ class AStar(MazeSolver):
             case _:
                 return actual
 
-    def get_path(
+    def get_path(self, maze: np.ndarray) -> str | None:
-        self, actual: tuple[int, int], maze: np.ndarray, pre: str | None
+        path = [(self.start, self.best_path(maze, self.start, None))]
-    ) -> str | None:
+        visited = [self.start]
-        if actual == self.end:
+        while len(path) > 0 and path[-1][0] != self.end:
-            return ""
+            if len(path[-1][1]) == 0:
-        paths = self.best_path(maze, actual)
+                path.pop(-1)
-        for path in paths:
+                if len(path) == 0:
-            if paths[path] is None:
+                    break
+                k = next(iter(path[-1][1]))
+                path[-1][1].pop(k)
                 continue
-            if path != pre:
+
-                temp = self.get_path(
+            while len(path[-1][1]) > 0:
-                    self.get_next_pos(path, actual),
+                next_pos = self.get_next_pos(
-                    maze,
+                    list(path[-1][1].keys())[0], path[-1][0]
-                    self.get_opposit(path),
                 )
-                if not temp is None:
+                if next_pos in visited:
-                    return path + temp
+                    k = next(iter(path[-1][1]))
-        return None
+                    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(maze.get_maze())
-        res = self.get_path(self.start, maze.get_maze(), None)
         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

@@ -1,8 +1,10 @@
 from .Cell import Cell
 from .Maze import Maze
-from .MazeGenerator import MazeGenerator, Kruskal
+from .MazeGenerator import MazeGenerator, DepthFirstSearch
-from .MazeSolver import MazeSolver, AStar
+from .MazeGenerator import Kruskal
+from .MazeSolver import MazeSolver, AStar, DepthFirstSearchSolver
 
 __version__ = "1.0.0"
 __author__ = "us"
-__all__ = ["Cell", "Maze", "MazeGenerator", "MazeSolver", "AStar", "Kruskal"]
+__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 = [
+        tmp2 = [value.split("=", 1) for value in tmp if "=" in value]
-            value.split("=", 1) for value in tmp
+        data_t = {value[0]: value[1] for value in tmp2}
-        ]
-        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"
+            "WIDTH",
-        }
+            "HEIGHT",
-        set_key = {
+            "ENTRY",
-            key for key in data.keys()
+            "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 "
+            raise KeyError(
-                           f"do not correspond the keys: {res_key}")
+                "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 "
+            print(
-                  f"be splited by '=' because '=' was not present: {e}")
+                "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 "
+            print("Error on the " f"funciton get_data_maze : {e}")
-                  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
+B9153957955513953953
-3D12C3903BD03AD4178D
+AEA96A9569792C6BAAD6
-2BAEBEEEAA92EED547C9
+C5443AA9169281102C53
-2287ED17AAAC5393FFF0
+95556A82816C2AC2A952
-6C6951292A87D2AEBD30
+A93916A86A956C3A86D6
-37D43E8686E93AABAB8C
+AEC6C542944513806953
-21516D2D47FEE8284049
+C395553AC393C2AC787A
-6C7857C3FB9116C696D8
+BC69512C7AAC56855692
-751453D6D2AAC57BE970
+A952BAAF96AFFFAD53AE
-3BA952D17EA83BD05470
+A810686FC5057FC516C3
-22AAD2907BAE86967B74
+AAC4543FFFAFFFB96952
-2AA83C2EFC69696FBC35
+AC5553817FAFD52ABC3A
-686EE96FD7D4783FAD21
+815552843FEFFF80296A
-7ED17ED3D57D3EC52FA0
+AC553A85413D55406C12
-7B943D16FB7BABD3AFC8
+C53BAAC392C3953C13AA
-7407C5297EB82EB84174
+9386AC386A9683C56AAA
-392D53C6912EE9447E9D
+846903AE96C568517C2A
-62A952BBAAC13EFD7B89
+AD3A82C385397C3C5546
-3AAC3EC6EABAAD557824
+C12AA87AA94293AD5513
-66C7C7D7D6C6C7D556CD
+D46C6C5446D46C45556E
 
 1,1
-16,15
+2,2
+SSEEENENWWWS

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 +1,18 @@
 import numpy
-from amaz_lib.MazeGenerator import Kruskal
+from amaz_lib.MazeGenerator import DepthFirstSearch, MazeGenerator
 
 
-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 = (10, 10)
+        maze = numpy.array([])
+        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