add(docstring): doc string on every class and functions

a_maze_ing.py

@@ -3,15 +3,24 @@ from src.AMazeIng import AMazeIng
 from src.parsing import Parsing
 from mlx import Mlx
 import numpy as np
-import math
 import time
 
 
 class MazeMLX:
+    """Render, animate, and interact with a maze using an MLX window."""
+
     def __init__(self, height: int, width: int) -> None:
+        """Initialize the MLX renderer and create the window and image buffer.
+
+        Args:
+            height: Height of the rendering area in pixels.
+            width: Width of the rendering area in pixels.
+        """
         self.mlx = Mlx()
         self.height = height
         self.width = width
+        self.print_path = False
+        self.color = [0x00, 0x00, 0xFF, 0xFF]
         self.mlx_ptr = self.mlx.mlx_init()
         self.win_ptr = self.mlx.mlx_new_window(
             self.mlx_ptr, width, height + 200, "A-Maze-Ing"
@@ -24,9 +33,23 @@ class MazeMLX:
         self.generator = None
 
     def close(self) -> None:
+        """Destroy the image used by the renderer."""
         self.mlx.mlx_destroy_image(self.mlx_ptr, self.img_ptr)
 
+    def close_loop(self, _: Any):
+        """Stop the MLX event loop.
+
+        Args:
+            _: Unused callback argument.
+        """
+        self.mlx.mlx_loop_exit(self.mlx_ptr)
+
+    def clear_image(self) -> None:
+        """Clear the image buffer."""
+        self.buf[:] = b"\x00" * len(self.buf)
+
     def redraw_image(self) -> None:
+        """Redraw the window contents and display the control help text."""
         self.mlx.mlx_clear_window(self.mlx_ptr, self.win_ptr)
         self.mlx.mlx_put_image_to_window(
             self.mlx_ptr, self.win_ptr, self.img_ptr, 0, 0
@@ -40,47 +63,146 @@ class MazeMLX:
             "1: regen; 2: path; 3: color; 4: quit;",
         )
 
-    def put_pixel(self, x, y) -> None:
+    def put_pixel(self, x, y, color: list | None = None) -> None:
+        """Draw a single pixel into the image buffer.
+
+        Args:
+            x: Horizontal pixel position.
+            y: Vertical pixel position.
+            color: Optional RGBA color list. If omitted, the current renderer
+                color is used.
+        """
+        if x < 0 or y < 0 or x >= self.width or y >= self.height:
+            return
         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
+        if color:
+            self.buf[offset + 0] = color[0]
+            self.buf[offset + 1] = color[1]
+            self.buf[offset + 2] = color[2]
+            if self.bpp >= 32:
+                self.buf[offset + 3] = color[3]
+        else:
+            self.buf[offset + 0] = self.color[0]
+            self.buf[offset + 1] = self.color[1]
+            self.buf[offset + 2] = self.color[2]
+            if self.bpp >= 32:
+                self.buf[offset + 3] = self.color[3]
 
-    def clear_image(self) -> None:
-        self.buf[:] = b"\x00" * len(self.buf)
+    def put_line(
+        self,
+        start: tuple[int, int],
+        end: tuple[int, int],
+        color: list | None = None,
+    ) -> None:
+        """Draw a horizontal or vertical line.
 
-    def put_line(self, start: tuple[int, int], end: tuple[int, int]) -> None:
+        Args:
+            start: Starting pixel coordinates.
+            end: Ending pixel coordinates.
+            color: Optional RGBA color list.
+        """
         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)
+                self.put_pixel(x, sy, color)
         if sx == ex:
             for y in range(min(sy, ey), max(sy, ey) + 1):
-                self.put_pixel(sx, y)
+                self.put_pixel(sx, y, color)
+
+    def put_block(
+        self,
+        ul: tuple[int, int],
+        dr: tuple[int, int],
+        color: list | None = None,
+    ) -> None:
+        """Draw a filled rectangular block.
+
+        Args:
+            ul: Upper-left corner coordinates.
+            dr: Lower-right corner coordinates.
+            color: Optional RGBA color list.
+        """
+        for y in range(min(ul[1], dr[1]), max(dr[1], ul[1])):
+            self.put_line(
+                (min(ul[0], dr[0]), y), (max(ul[0], dr[0]), y), color
+            )
+
+    @staticmethod
+    def random_color_ft() -> Any:
+        """Yield colors in a repeating sequence for the reserved pattern.
+
+        Yields:
+            RGBA color lists.
+        """
+        colors = [
+            [0xFF, 0xBF, 0x00, 0xFF],  # blue
+            [0x00, 0xFF, 0x40, 0xFF],  # green
+            [0xFF, 0x00, 0xFF, 0xFF],  # pink
+            [0x00, 0xFF, 0xFF, 0xFF],  # yellow
+        ]
+        while True:
+            for color in colors:
+                yield color
+
+    @staticmethod
+    def random_color() -> Any:
+        """Yield colors in a repeating sequence for maze rendering.
+
+        Yields:
+            RGBA color lists.
+        """
+        colors = [
+            [0xFF, 0x00, 0xFF, 0xFF],  # pink
+            [0x00, 0xFF, 0xFF, 0xFF],  # yellow
+            [0x00, 0xFF, 0x40, 0xFF],  # green
+            [0xFF, 0xBF, 0x00, 0xFF],  # blue
+            [0xFF, 0x00, 0x80, 0xFF],  # purple
+            [0x00, 0x00, 0xFF, 0xFF],  # red
+        ]
+        while True:
+            for color in colors:
+                yield color
+
+    def get_margin_line_len(self, maze: np.ndarray) -> tuple[int, int, int]:
+        """Compute the cell size and margins for centering the maze.
+
+        Args:
+            maze: Maze grid to render.
+
+        Returns:
+            A tuple containing the cell side length, horizontal margin, and
+            vertical margin.
+        """
+        rows = len(maze)
+        cols = len(maze[0])
+
+        line_len = min(self.width // cols, self.height // rows) - 1
+
+        maze_width = cols * line_len
+        maze_height = rows * line_len
+
+        margin_x = ((self.width - maze_width) // 2) + 1
+        margin_y = ((self.height - maze_height) // 2) + 1
+
+        return (line_len, margin_x, margin_y)
 
     def update_maze(self, maze: np.ndarray) -> None:
+        """Render the maze walls into the image buffer.
+
+        Args:
+            maze: Maze grid to render.
+        """
         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])
-            )
-        )
+
+        line_len, margin_x, margin_y = self.get_margin_line_len(maze)
         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
+                x0 = x * line_len + margin_x
+                y0 = y * line_len + margin_y
+                x1 = x * line_len + line_len + margin_x
+                y1 = y * line_len + line_len + margin_y
 
                 if maze[y][x].get_north():
                     self.put_line((x0, y0), (x1, y0))
@@ -90,13 +212,17 @@ class MazeMLX:
                     self.put_line((x0, y1), (x1, y1))
                 if maze[y][x].get_west():
                     self.put_line((x0, y0), (x0, y1))
-        self.redraw_image()
 
-    def put_block(self, ul: tuple[int, int], dr: tuple[int, int]) -> None:
-        for y in range(min(ul[1], dr[1]), max(dr[1], ul[1])):
-            self.put_line((min(ul[0], dr[0]), y), (max(ul[0], dr[0]), y))
+    def put_path(self, amazing: AMazeIng) -> Any:
+        """Animate the solution path inside the maze.
 
-    def put_path(self, amazing: AMazeIng):
+        Args:
+            amazing: Maze container with generation and solving logic.
+
+        Yields:
+            Control after each path segment so the animation can be rendered
+            progressively.
+        """
         path = amazing.solve_path()
         print(path)
         actual = amazing.entry
@@ -104,34 +230,23 @@ class MazeMLX:
         maze = amazing.maze.get_maze()
         if maze is None:
             return
-        margin = math.trunc(
-            math.sqrt(self.width if self.width > self.height else self.height)
-            // 2
-        )
-        cell_size = math.trunc(
-            (
-                (self.height - margin) // len(maze)
-                if self.height > self.width
-                else (self.width - margin) // len(maze[0])
-            )
-        )
-        self.update_maze(maze)
-        self.color_ft(maze)
+
+        line_len, margin_x, margin_y = self.get_margin_line_len(maze)
+
         for i in range(len(path)):
             ul = (
-                (actual[0]) * cell_size + margin + 12,
-                (actual[1]) * cell_size + 12 + margin,
+                (actual[0]) * line_len + margin_x + 12,
+                (actual[1]) * line_len + 12 + margin_y,
             )
             dr = (
-                (actual[0]) * cell_size + cell_size + margin - 12,
-                (actual[1]) * cell_size + cell_size - 12 + margin,
+                (actual[0]) * line_len + line_len + margin_x - 12,
+                (actual[1]) * line_len + line_len - 12 + margin_y,
             )
             self.put_block(ul, dr)
-            self.redraw_image()
-            x0 = actual[0] * cell_size + margin + 12
-            y0 = actual[1] * cell_size + margin + 12
-            x1 = actual[0] * cell_size + cell_size + margin - 12
-            y1 = actual[1] * cell_size + cell_size + margin - 12
+            x0 = actual[0] * line_len + margin_x + 12
+            y0 = actual[1] * line_len + margin_y + 12
+            x1 = actual[0] * line_len + line_len + margin_x - 12
+            y1 = actual[1] * line_len + line_len + margin_y - 12
             yield
             match path[i]:
                 case "N":
@@ -147,98 +262,217 @@ class MazeMLX:
                     self.put_block((x0, y0), (x0 - 24, y1))
                     actual = (actual[0] - 1, actual[1])
         ul = (
-            (actual[0]) * cell_size + margin + 12,
-            (actual[1]) * cell_size + 12 + margin,
+            (actual[0]) * line_len + margin_x + 12,
+            (actual[1]) * line_len + 12 + margin_y,
         )
         dr = (
-            (actual[0]) * cell_size + cell_size + margin - 12,
-            (actual[1]) * cell_size + cell_size - 12 + margin,
+            (actual[0]) * line_len + line_len + margin_x - 12,
+            (actual[1]) * line_len + line_len - 12 + margin_y,
         )
         self.put_block(ul, dr)
-        self.redraw_image()
         return
 
-    def color_ft(self, maze: np.ndarray):
-        self.clear_image()
-        margin = math.trunc(
-            math.sqrt(self.width if self.width > self.height else self.height)
-            // 2
+    def put_start_end(self, amazing: AMazeIng):
+        """Draw highlighted blocks for the maze entry and exit.
+
+        Args:
+            amazing: Maze container with current maze data.
+        """
+        entry = amazing.entry
+        exit = amazing.exit
+        maze = amazing.maze.get_maze()
+        if maze is None:
+            return
+
+        line_len, margin_x, margin_y = self.get_margin_line_len(maze)
+
+        ul = (
+            (entry[0] - 1) * line_len + margin_x + 3,
+            (entry[1] - 1) * line_len + 3 + margin_y,
         )
-        line_len = math.trunc(
-            (
-                (self.height - margin) // len(maze)
-                if self.height > self.width
-                else (self.width - margin) // len(maze[0])
-            )
+        dr = (
+            (entry[0] - 1) * line_len + line_len + margin_x - 3,
+            (entry[1] - 1) * line_len + line_len - 3 + margin_y,
         )
+        self.put_block(ul, dr, [0xFF, 0xBF, 0x00, 0x9F])
+
+        ul = (
+            (exit[0] - 1) * line_len + margin_x + 3,
+            (exit[1] - 1) * line_len + 3 + margin_y,
+        )
+        dr = (
+            (exit[0] - 1) * line_len + line_len + margin_x - 3,
+            (exit[1] - 1) * line_len + line_len - 3 + margin_y,
+        )
+        self.put_block(ul, dr, [0x00, 0xFF, 0x40, 0x9F])
+
+    def draw_ft(self, maze: np.ndarray, color: list | None = None):
+        """Draw filled cells corresponding to the reserved fully walled pattern.
+
+        Args:
+            maze: Maze grid to inspect.
+            color: Optional RGBA color list.
+        """
+        line_len, margin_x, margin_y = self.get_margin_line_len(maze)
+
         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))
                 if maze[y][x].value == 15:
-                    self.put_block((x0, y0), (x1, y1))
+                    x0 = x * line_len + margin_x
+                    y0 = y * line_len + margin_y
+                    x1 = x * line_len + line_len + margin_x
+                    y1 = y * line_len + line_len + margin_y
+                    self.put_block((x0, y0), (x1, y1), color)
+
+    def draw_image(self, amazing: AMazeIng) -> None:
+        """Main rendering callback used by the MLX loop.
+
+        Args:
+            amazing: Maze container to render.
+        """
+        if self.render_maze(amazing):
+            if self.path_printer and self.print_path:
+                if self.render_path():
+                    color = next(self.color_gen_ft)
+                    self.draw_ft(amazing.maze.get_maze(), color)
+                    next(self.timer_gen)
+            else:
+                self.time_gen()
+                self.update_maze(amazing.maze.get_maze())
+                self.draw_ft(amazing.maze.get_maze())
+            self.put_start_end(amazing)
         self.redraw_image()
 
-    def close_loop(self, _: Any):
-        self.mlx.mlx_loop_exit(self.mlx_ptr)
+    def shift_color(self):
+        """Reset the maze color generator."""
+        self.color_gen = self.random_color()
+
+    def shift_color_ft(self):
+        """Reset the reserved-pattern color generator."""
+        self.color_gen_ft = self.random_color_ft()
+
+    def time_gen(self):
+        """Reset the timing generator used for animation pacing."""
+        self.timer_gen = self.time_generator()
+
+    def restart_maze(self, amazing: AMazeIng) -> None:
+        """Restart maze generation.
+
+        Args:
+            amazing: Maze container providing the generation generator.
+        """
+        self.generator = amazing.generate()
+
+    def time_generator(self) -> Any:
+        """Yield regularly with a fixed delay for animation timing.
+
+        Yields:
+            ``None`` at each step after sleeping.
+        """
+        yield
+        while True:
+            time.sleep(0.3)
+            yield
+
+    def restart_path(self, amazing: AMazeIng) -> None:
+        """Restart solution path animation.
+
+        Args:
+            amazing: Maze container providing the solution path.
+        """
+        self.path_printer = self.put_path(amazing)
+
+    def render_path(self) -> bool:
+        """Advance the path animation by one step.
+
+        Returns:
+            ``True`` if the path animation is complete, otherwise ``False``.
+        """
+        try:
+            next(self.path_printer)
+            time.sleep(0.03)
+            return False
+        except StopIteration:
+            pass
+        return True
+
+    def render_maze(self, amazing: AMazeIng) -> bool:
+        """Advance maze generation by one step and redraw it.
+
+        Args:
+            amazing: Maze container being generated.
+
+        Returns:
+            ``True`` if maze generation is complete, otherwise ``False``.
+        """
+        try:
+            next(self.generator)
+            self.update_maze(amazing.maze.get_maze())
+            return False
+        except StopIteration:
+            pass
+        return True
 
     def handle_key_press(self, keycode: int, amazing: AMazeIng) -> None:
+        """Handle keyboard input for one keycode mapping.
+
+        Args:
+            keycode: Key code received from MLX.
+            amazing: Maze container to update or render.
+        """
         if keycode == 49:
             self.restart_maze(amazing)
+            self.print_path = False
         if keycode == 50:
             self.restart_path(amazing)
+            self.print_path = True if self.print_path is False else False
         if keycode == 51:
-            pass
+            self.print_path = False
+            self.color = next(self.color_gen)
         if keycode == 52:
             self.close_loop(None)
 
+    def handle_key_press_mteriier(
+        self, keycode: int, amazing: AMazeIng
+    ) -> None:
+        """Handle keyboard input for an alternative keycode mapping.
+
+        Args:
+            keycode: Key code received from MLX.
+            amazing: Maze container to update or render.
+        """
+        if keycode == 38:
+            self.restart_maze(amazing)
+            self.print_path = False
+        if keycode == 233:
+            self.restart_path(amazing)
+            self.print_path = True if self.print_path is False else False
+        if keycode == 34:
+            self.print_path = False
+            self.color = next(self.color_gen)
+        if keycode == 39:
+            self.close_loop(None)
+
     def start(self, amazing: AMazeIng) -> None:
+        """Start the MLX rendering loop.
+
+        Args:
+            amazing: Maze container to generate, solve, and display.
+        """
         self.restart_maze(amazing)
-        self.mlx.mlx_loop_hook(self.mlx_ptr, self.render_maze, amazing)
+        self.shift_color()
+        self.shift_color_ft()
+        self.time_gen()
+        self.mlx.mlx_loop_hook(self.mlx_ptr, self.draw_image, amazing)
         self.mlx.mlx_hook(self.win_ptr, 33, 0, self.close_loop, None)
         self.mlx.mlx_hook(
             self.win_ptr, 2, 1 << 0, self.handle_key_press, amazing
         )
         self.mlx.mlx_loop(self.mlx_ptr)
 
-    def restart_maze(self, amazing: AMazeIng) -> None:
-        self.generator = amazing.generate()
-
-    def restart_path(self, amazing: AMazeIng) -> None:
-        self.path_printer = self.put_path(amazing)
-
-    def render_path(self):
-        try:
-            next(self.path_printer)
-            time.sleep(0.03)
-        except StopIteration:
-            pass
-
-    def render_maze(self, amazing: AMazeIng):
-        try:
-            next(self.generator)
-            self.update_maze(amazing.maze.get_maze())
-            # time.sleep(0.01)
-        except StopIteration:
-            # self.color_ft(amazing)
-            if self.path_printer is not None:
-                self.render_path()
-            else:
-                self.color_ft(amazing.maze.get_maze())
-
 
 def main() -> None:
+    """Run the maze application."""
     mlx = None
     try:
         mlx = MazeMLX(1000, 1000)

config.txt

@@ -1,8 +1,8 @@
-WIDTH=50
-HEIGHT=50
+WIDTH=10
+HEIGHT=10
 ENTRY=1,1
-EXIT=11,11
+EXIT=10,10
 OUTPUT_FILE=maze.txt
-PERFECT=False
-GENERATOR=DFS
-SOLVER=DFS
+PERFECT=True
+GENERATOR=Kruskal
+SOLVER=AStar

src/AMazeIng.py

@@ -6,6 +6,8 @@ from src.amaz_lib import Maze, MazeGenerator, MazeSolver
 
 
 class AMazeIng(BaseModel):
+    """Represent a complete maze configuration, generation, and solving setup."""
+
     model_config = ConfigDict(arbitrary_types_allowed=True)
 
     width: int = Field(ge=4)
@@ -20,6 +22,14 @@ class AMazeIng(BaseModel):
 
     @model_validator(mode="after")
     def check_entry_exit(self) -> Self:
+        """Validate that entry and exit coordinates fit within maze bounds.
+
+        Returns:
+            The validated model instance.
+
+        Raises:
+            ValueError: If entry or exit coordinates exceed maze dimensions.
+        """
         if self.entry[0] > self.width or self.entry[1] > self.height:
             raise ValueError("Entry coordinates exceed the maze size")
         if self.exit[0] > self.width or self.exit[1] > self.height:
@@ -27,15 +37,35 @@ class AMazeIng(BaseModel):
         return self
 
     def generate(self) -> Generator[Maze, None, None]:
+        """Generate the maze step by step.
+
+        The internal maze state is updated at each generation step.
+
+        Yields:
+            The current maze state after each generation step.
+        """
         for array in self.generator.generator(self.height, self.width):
             self.maze.set_maze(array)
             yield self.maze
         return
 
     def solve_path(self) -> str:
+        """Solve the current maze and return the path string.
+
+        Returns:
+            A string of direction letters representing the solution path.
+        """
         return self.solver.solve(self.maze, self.height, self.width)
 
     def __str__(self) -> str:
+        """Return a string representation of the maze and its solution.
+
+        The output includes the maze, entry coordinates, exit coordinates, and
+        the computed solution path.
+
+        Returns:
+            A formatted string representation of the maze data.
+        """
         res = self.maze.__str__()
         res += "\n"
         res += f"{self.entry[0]},{self.entry[1]}\n"

src/amaz_lib/Cell.py

@@ -3,50 +3,122 @@ from dataclasses import dataclass
 
 @dataclass
 class Cell:
+    """Represent a maze cell encoded as a bitmask of surrounding walls.
+
+    The cell value is stored as an integer where each bit represents the
+    presence of a wall in one cardinal direction:
+
+    - bit 0 (1): north wall
+    - bit 1 (2): east wall
+    - bit 2 (4): south wall
+    - bit 3 (8): west wall
+    """
+
     def __init__(self, value: int) -> None:
+        """Initialize a cell with its encoded wall value.
+
+        Args:
+            value: Integer bitmask representing the cell walls.
+        """
         self.value = value
 
     def __str__(self) -> str:
+        """Return the hexadecimal representation of the cell value.
+
+        Returns:
+            The uppercase hexadecimal form of the cell value without the
+            ``0x`` prefix.
+        """
         return hex(self.value).removeprefix("0x").upper()
 
     def set_value(self, value: int) -> None:
+        """Set the encoded value of the cell.
+
+        Args:
+            value: Integer bitmask representing the cell walls.
+        """
         self.value = value
 
     def get_value(self) -> int:
+        """Return the encoded value of the cell.
+
+        Returns:
+            The integer bitmask representing the cell walls.
+        """
         return self.value
 
     def set_north(self, is_wall: bool) -> None:
+        """Set or clear the north wall.
+
+        Args:
+            is_wall: ``True`` to add the north wall, ``False`` to remove it.
+        """
         if (not is_wall and self.value | 14 == 15) or (
             is_wall and self.value | 14 != 15
         ):
             self.value = self.value ^ (1)
 
     def get_north(self) -> bool:
+        """Return whether the north wall is present.
+
+        Returns:
+            ``True`` if the north wall is set, otherwise ``False``.
+        """
         return self.value & 1 == 1
 
     def set_est(self, is_wall: bool) -> None:
+        """Set or clear the east wall.
+
+        Args:
+            is_wall: ``True`` to add the east wall, ``False`` to remove it.
+        """
         if (not is_wall and self.value | 13 == 15) or (
             is_wall and self.value | 13 != 15
         ):
             self.value = self.value ^ (2)
 
     def get_est(self) -> bool:
+        """Return whether the east wall is present.
+
+        Returns:
+            ``True`` if the east wall is set, otherwise ``False``.
+        """
         return self.value & 2 == 2
 
     def set_south(self, is_wall: bool) -> None:
+        """Set or clear the south wall.
+
+        Args:
+            is_wall: ``True`` to add the south wall, ``False`` to remove it.
+        """
         if (not is_wall and self.value | 11 == 15) or (
             is_wall and self.value | 11 != 15
         ):
             self.value = self.value ^ (4)
 
     def get_south(self) -> bool:
+        """Return whether the south wall is present.
+
+        Returns:
+            ``True`` if the south wall is set, otherwise ``False``.
+        """
         return self.value & 4 == 4
 
     def set_west(self, is_wall: bool) -> None:
+        """Set or clear the west wall.
+
+        Args:
+            is_wall: ``True`` to add the west wall, ``False`` to remove it.
+        """
         if (not is_wall and self.value | 7 == 15) or (
             is_wall and self.value | 7 != 15
         ):
             self.value = self.value ^ (8)
 
     def get_west(self) -> bool:
+        """Return whether the west wall is present.
+
+        Returns:
+            ``True`` if the west wall is set, otherwise ``False``.
+        """
         return self.value & 8 == 8

src/amaz_lib/Maze.py

@@ -1,19 +1,41 @@
 from dataclasses import dataclass
-
-import numpy
+from numpy.typing import NDArray
+from typing import Optional, Any
 
 
 @dataclass
 class Maze:
-    maze: numpy.ndarray
+    """Represent a maze as a two-dimensional array of cells."""
 
-    def get_maze(self) -> numpy.ndarray | None:
+    maze: Optional[NDArray[Any]] = None
+
+    def get_maze(self) -> Optional[NDArray[Any]]:
+        """Return the underlying maze array.
+
+        Returns:
+            The two-dimensional array representing the maze, or ``None`` if no
+            maze has been set.
+        """
         return self.maze
 
-    def set_maze(self, new_maze: numpy.ndarray) -> None:
+    def set_maze(self, new_maze: NDArray[Any]) -> None:
+        """Set the maze array.
+
+        Args:
+            new_maze: A two-dimensional array containing the maze cells.
+        """
         self.maze = new_maze
 
     def __str__(self) -> str:
+        """Return a string representation of the maze.
+
+        Each cell is converted to its string representation and concatenated
+        line by line.
+
+        Returns:
+            A multiline string representation of the maze, or ``"None"`` if the
+            maze is not set.
+        """
         if self.maze is None:
             return "None"
         res = ""
@@ -24,6 +46,14 @@ class Maze:
         return res
 
     def ascii_print(self) -> None:
+        """Print an ASCII representation of the maze.
+
+        The maze is rendered using underscores and vertical bars to show the
+        walls of each cell. If no maze is set, ``"None"`` is printed.
+        """
+        if self.maze is None:
+            print("None")
+            return
         for cell in self.maze[0]:
             print("_", end="")
             if cell.get_north():

src/amaz_lib/MazeGenerator.py

@@ -6,7 +6,16 @@ import math
 
 
 class MazeGenerator(ABC):
+    """Define the common interface and helpers for maze generators."""
+
     def __init__(self, start: tuple, end: tuple, perfect: bool) -> None:
+        """Initialize the maze generator.
+
+        Args:
+            start: Starting cell coordinates, using 1-based indexing.
+            end: Ending cell coordinates, using 1-based indexing.
+            perfect: Whether to generate a perfect maze with no loops.
+        """
         self.start = (start[0] - 1, start[1] - 1)
         self.end = (end[0] - 1, end[1] - 1)
         self.perfect = perfect
@@ -14,10 +23,33 @@ class MazeGenerator(ABC):
     @abstractmethod
     def generator(
         self, height: int, width: int, seed: int | None = None
-    ) -> Generator[np.ndarray, None, np.ndarray]: ...
+    ) -> Generator[np.ndarray, None, np.ndarray]:
+        """Generate a maze step by step.
+
+        Args:
+            height: Number of rows in the maze.
+            width: Number of columns in the maze.
+            seed: Optional random seed for reproducibility.
+
+        Yields:
+            Intermediate maze states during generation.
+
+        Returns:
+            The final generated maze.
+        """
+        ...
 
     @staticmethod
     def get_cell_ft(width: int, height: int) -> set:
+        """Return the coordinates used to reserve the '42' pattern.
+
+        Args:
+            width: Number of columns in the maze.
+            height: Number of rows in the maze.
+
+        Returns:
+            A set of cell coordinates belonging to the reserved pattern.
+        """
         forty_two = set()
         y, x = (int(height / 2), int(width / 2))
         forty_two.add((y, x - 1))
@@ -41,23 +73,35 @@ class MazeGenerator(ABC):
         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)
-        }
+    def unperfect_maze(
+        width: int,
+        height: int,
+        maze: np.ndarray,
+        forty_two: set | None,
+        prob: float = 0.1,
+    ) -> Generator[np.ndarray, None, np.ndarray]:
+        """Add extra openings to transform a perfect maze into an imperfect one.
 
-        reverse = {
-            "N": "S",
-            "S": "N",
-            "W": "E",
-            "E": "W"
-        }
+        Random walls are removed while optionally preserving the reserved
+        ``forty_two`` area.
+
+        Args:
+            width: Number of columns in the maze.
+            height: Number of rows in the maze.
+            maze: The maze to modify.
+            forty_two: Optional set of reserved coordinates that must not be
+                altered.
+            prob: Probability of breaking an eligible wall.
+
+        Yields:
+            Intermediate maze states after each wall removal.
+
+        Returns:
+            The modified maze.
+        """
+        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
@@ -68,8 +112,7 @@ class MazeGenerator(ABC):
                     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
+                            (y, x) in forty_two or (ny, nx) in forty_two
                         ):
                             continue
                         if not (0 <= nx < width and 0 < ny < height):
@@ -81,9 +124,10 @@ class MazeGenerator(ABC):
                             cell = maze[y][x]
                             cell_n = maze[ny][nx]
                             cell = DepthFirstSearch.broken_wall(cell, direc)
-                            cell_n = DepthFirstSearch.broken_wall(cell_n,
-                                                                  reverse[
-                                                                    direc])
+                            cell_n = DepthFirstSearch.broken_wall(
+                                cell_n,
+                                reverse[direc],
+                            )
                             maze[y][x] = cell
                             maze[ny][nx] = cell_n
                             yield maze
@@ -93,19 +137,45 @@ class MazeGenerator(ABC):
 
 
 class Kruskal(MazeGenerator):
+    """Generate a maze using a Kruskal-based algorithm."""
 
     class Set:
+        """Represent a connected component of maze cells."""
+
         def __init__(self, cells: list[int]) -> None:
+            """Initialize a set of connected cells.
+
+            Args:
+                cells: List of cell indices belonging to the set.
+            """
             self.cells: list[int] = cells
 
     class Sets:
+        """Store all connected components used during generation."""
+
         def __init__(self, sets: list[Set]) -> None:
+            """Initialize the collection of connected components.
+
+            Args:
+                sets: List of disjoint cell sets.
+            """
             self.sets = sets
 
     @staticmethod
     def walls_to_maze(
         walls: np.ndarray, height: int, width: int
     ) -> np.ndarray:
+        """Convert a list of remaining walls into a maze grid.
+
+        Args:
+            walls: Collection of wall pairs between adjacent cells.
+            height: Number of rows in the maze.
+            width: Number of columns in the maze.
+
+        Returns:
+            A two-dimensional array of :class:`Cell` instances representing the
+            maze.
+        """
         maze: np.ndarray = np.array(
             [[Cell(value=0) for _ in range(width)] for _ in range(height)]
         )
@@ -132,6 +202,15 @@ class Kruskal(MazeGenerator):
 
     @staticmethod
     def is_in_same_set(sets: Sets, wall: tuple[int, int]) -> bool:
+        """Check whether both cells connected by a wall are in the same set.
+
+        Args:
+            sets: Current collection of connected components.
+            wall: Pair of adjacent cell indices.
+
+        Returns:
+            ``True`` if both cells belong to the same set, otherwise ``False``.
+        """
         a, b = wall
         for set in sets.sets:
             if a in set.cells and b in set.cells:
@@ -142,6 +221,15 @@ class Kruskal(MazeGenerator):
 
     @staticmethod
     def merge_sets(sets: Sets, wall: tuple[int, int]) -> None:
+        """Merge the two sets connected by the given wall.
+
+        Args:
+            sets: Current collection of connected components.
+            wall: Pair of adjacent cell indices.
+
+        Raises:
+            Exception: If the two corresponding sets cannot be found.
+        """
         a, b = wall
         base_set = None
         for i in range(len(sets.sets)):
@@ -163,6 +251,17 @@ class Kruskal(MazeGenerator):
         wall: tuple[int, int],
         cells_ft: None | set[tuple[int, int]],
     ) -> bool:
+        """Check whether a wall touches the reserved '42' pattern.
+
+        Args:
+            width: Number of columns in the maze.
+            wall: Pair of adjacent cell indices.
+            cells_ft: Reserved coordinates, or ``None``.
+
+        Returns:
+            ``True`` if either endpoint of the wall belongs to the reserved
+            pattern, otherwise ``False``.
+        """
         if cells_ft is None:
             return False
         s1 = (math.trunc(wall[0] / width), wall[0] % width)
@@ -172,6 +271,19 @@ class Kruskal(MazeGenerator):
     def generator(
         self, height: int, width: int, seed: int | None = None
     ) -> Generator[np.ndarray, None, np.ndarray]:
+        """Generate a maze using a Kruskal-based approach.
+
+        Args:
+            height: Number of rows in the maze.
+            width: Number of columns in the maze.
+            seed: Optional random seed for reproducibility.
+
+        Yields:
+            Intermediate maze states during generation.
+
+        Returns:
+            The final generated maze.
+        """
         cells_ft = None
         if height > 10 and width > 10:
             cells_ft = self.get_cell_ft(width, height)
@@ -208,8 +320,7 @@ class Kruskal(MazeGenerator):
         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)
+            gen = Kruskal.unperfect_maze(width, height, maze, cells_ft)
             for res in gen:
                 maze = res
                 yield maze
@@ -217,7 +328,16 @@ class Kruskal(MazeGenerator):
 
 
 class DepthFirstSearch(MazeGenerator):
+    """Generate a maze using a depth-first search backtracking algorithm."""
+
     def __init__(self, start: bool, end: bool, perfect: bool) -> None:
+        """Initialize the depth-first search generator.
+
+        Args:
+            start: Starting cell coordinates, using 1-based indexing.
+            end: Ending cell coordinates, using 1-based indexing.
+            perfect: Whether to generate a perfect maze with no loops.
+        """
         self.start = (start[0] - 1, start[1] - 1)
         self.end = (end[0] - 1, end[1] - 1)
         self.perfect = perfect
@@ -226,6 +346,19 @@ class DepthFirstSearch(MazeGenerator):
     def generator(
         self, height: int, width: int, seed: int = None
     ) -> Generator[np.ndarray, None, np.ndarray]:
+        """Generate a maze using depth-first search.
+
+        Args:
+            height: Number of rows in the maze.
+            width: Number of columns in the maze.
+            seed: Optional random seed for reproducibility.
+
+        Yields:
+            Intermediate maze states during generation.
+
+        Returns:
+            The final generated maze.
+        """
         if seed is not None:
             np.random.seed(seed)
         maze = self.init_maze(width, height)
@@ -269,8 +402,12 @@ class DepthFirstSearch(MazeGenerator):
             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)
+            gen = DepthFirstSearch.unperfect_maze(
+                width,
+                height,
+                maze,
+                self.forty_two,
+            )
             for res in gen:
                 maze = res
                 yield maze
@@ -278,6 +415,15 @@ class DepthFirstSearch(MazeGenerator):
 
     @staticmethod
     def init_maze(width: int, height: int) -> np.ndarray:
+        """Create a fully walled maze grid.
+
+        Args:
+            width: Number of columns in the maze.
+            height: Number of rows in the maze.
+
+        Returns:
+            A two-dimensional array of cells initialized with all walls present.
+        """
         maze = np.array(
             [[Cell(value=15) for _ in range(width)] for _ in range(height)]
         )
@@ -285,11 +431,31 @@ class DepthFirstSearch(MazeGenerator):
 
     @staticmethod
     def add_cell_visited(coord: tuple, path: set) -> list:
+        """Append a visited coordinate to the current traversal path.
+
+        Args:
+            coord: Coordinate of the visited cell.
+            path: Current traversal path.
+
+        Returns:
+            The updated path.
+        """
         path.append(coord)
         return path
 
     @staticmethod
     def random_cells(visited: np.array, coord: tuple, w_h: tuple) -> list:
+        """Return the list of unvisited neighboring directions.
+
+        Args:
+            visited: Boolean array marking visited cells.
+            coord: Current cell coordinate.
+            w_h: Tuple containing maze width and height.
+
+        Returns:
+            A list of direction strings among ``"N"``, ``"S"``, ``"W"``, and
+            ``"E"``.
+        """
         rand_cell = []
         x, y = coord
         width, height = w_h
@@ -309,10 +475,27 @@ class DepthFirstSearch(MazeGenerator):
 
     @staticmethod
     def next_step(rand_cell: list) -> str:
+        """Select the next direction at random.
+
+        Args:
+            rand_cell: List of candidate directions.
+
+        Returns:
+            A randomly selected direction.
+        """
         return np.random.choice(rand_cell)
 
     @staticmethod
     def broken_wall(cell: Cell, wall: str) -> Cell:
+        """Remove the specified wall from a cell.
+
+        Args:
+            cell: The cell to modify.
+            wall: Direction of the wall to remove.
+
+        Returns:
+            The modified cell.
+        """
         if wall == "N":
             cell.set_north(False)
         elif wall == "S":
@@ -325,16 +508,44 @@ class DepthFirstSearch(MazeGenerator):
 
     @staticmethod
     def next_cell(x: int, y: int, next: str) -> tuple:
+        """Return the coordinates of the adjacent cell in the given direction.
+
+        Args:
+            x: Current column index.
+            y: Current row index.
+            next: Direction to move.
+
+        Returns:
+            The coordinates of the next cell.
+        """
         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 the opposite cardinal direction.
+
+        Args:
+            direction: Input direction.
+
+        Returns:
+            The opposite direction.
+        """
         return {"N": "S", "S": "N", "W": "E", "E": "W"}[direction]
 
     @staticmethod
     def back_on_step(path: list, w_h: tuple, visited: np.ndarray) -> list:
+        """Backtrack through the path until a cell with unvisited neighbors is found.
+
+        Args:
+            path: Current traversal path.
+            w_h: Tuple containing maze width and height.
+            visited: Boolean array marking visited cells.
+
+        Returns:
+            The truncated path after backtracking.
+        """
         while path:
             last = path[-1]
             if DepthFirstSearch.random_cells(visited, last, w_h):
@@ -346,6 +557,15 @@ class DepthFirstSearch(MazeGenerator):
     def lock_cell_ft(
         visited: np.ndarray, forty_two: set[tuple[int]]
     ) -> np.ndarray:
+        """Mark the reserved '42' pattern cells as already visited.
+
+        Args:
+            visited: Boolean array marking visited cells.
+            forty_two: Set of reserved cell coordinates.
+
+        Returns:
+            The updated visited array.
+        """
         tab = [cell for cell in forty_two]
         for cell in tab:
             visited[cell] = True

src/amaz_lib/MazeSolver.py

@@ -1,178 +1,300 @@
 from abc import ABC, abstractmethod
 from .Maze import Maze
+from typing import Any
 import numpy as np
 
 
 class MazeSolver(ABC):
+    """Define the common interface for maze-solving algorithms."""
+
     def __init__(self, start: tuple[int, int], end: tuple[int, int]) -> None:
+        """Initialize the maze solver.
+
+        Args:
+            start: Start coordinates using 1-based indexing.
+            end: End coordinates using 1-based indexing.
+        """
         self.start = (start[1] - 1, start[0] - 1)
         self.end = (end[1] - 1, end[0] - 1)
 
     @abstractmethod
-    def solve(self, maze: Maze, height: int = None,
-              width: int = None) -> str: ...
+    def solve(
+        self, maze: Maze, height: int | None = None, width: int | None = None
+    ) -> str:
+        """Solve the maze and return the path as direction letters.
+
+        Args:
+            maze: The maze to solve.
+            height: Optional maze height.
+            width: Optional maze width.
+
+        Returns:
+            A string representing the path using cardinal directions.
+        """
+        ...
 
 
 class AStar(MazeSolver):
+    """Solve a maze using the A* pathfinding algorithm."""
+
+    class Node:
+        """Represent a node used during A* exploration."""
+
+        def __init__(
+            self,
+            coordinate: tuple[int, int],
+            g: int,
+            h: int,
+            f: int,
+            parent: Any,
+        ) -> None:
+            """Initialize a search node.
+
+            Args:
+                coordinate: Coordinates of the node.
+                g: Cost from the start node.
+                h: Heuristic cost to the goal.
+                f: Total estimated cost.
+                parent: Parent node in the reconstructed path.
+            """
+            self.coordinate = coordinate
+            self.g = g
+            self.h = h
+            self.f = f
+            self.parent = parent
+
+        def __eq__(self, value: object, /) -> bool:
+            """Compare a node to a coordinate.
+
+            Args:
+                value: Object to compare with.
+
+            Returns:
+                ``True`` if the value equals the node coordinate, otherwise
+                ``False``.
+            """
+            return value == self.coordinate
 
     def __init__(self, start: tuple[int, int], end: tuple[int, int]) -> None:
+        """Initialize the A* solver.
+
+        Args:
+            start: Start coordinates using 1-based indexing.
+            end: End coordinates using 1-based indexing.
+        """
         super().__init__(start, end)
+        self.path = []
 
-    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(self, n: tuple[int, int]) -> int:
+        """Compute the Manhattan distance heuristic to the goal.
 
-        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
+        Args:
+            n: Coordinates of the current node.
 
-        try:
-            return g(n) + h(n)
-        except Exception:
-            return 1000
+        Returns:
+            The heuristic distance to the end coordinate.
+        """
+        return (
+            max(n[0], self.end[0])
+            - min(n[0], self.end[0])
+            + max(n[1], self.end[1])
+            - min(n[1], self.end[1])
+        )
 
-    def best_path(
+    def get_paths(
         self,
         maze: np.ndarray,
         actual: tuple[int, int],
-        last: str | None,
-    ) -> dict[str, int]:
-        path = {
-            "N": (
-                self.f((actual[0], actual[1] - 1))
-                if not maze[actual[1]][actual[0]].get_north() and actual[1] > 0
+        close: list,
+    ) -> list[tuple[int, int]]:
+        """Return all reachable neighboring coordinates.
+
+        Args:
+            maze: Maze grid to inspect.
+            actual: Current coordinate.
+            close: List of already explored nodes.
+
+        Returns:
+            A list of reachable adjacent coordinates not yet closed.
+        """
+        path = [
+            (
+                (actual[0], actual[1] - 1)
+                if not maze[actual[1]][actual[0]].get_north()
+                and actual[1] > 0
+                and (actual[0], actual[1] - 1)
+                not in [n.coordinate for n in close]
                 else None
             ),
-            "E": (
-                self.f((actual[0] + 1, actual[1]))
+            (
+                (actual[0] + 1, actual[1])
                 if not maze[actual[1]][actual[0]].get_est()
                 and actual[0] < len(maze[0]) - 1
+                and (actual[0] + 1, actual[1])
+                not in [n.coordinate for n in close]
                 else None
             ),
-            "S": (
-                self.f((actual[0], actual[1] + 1))
+            (
+                (actual[0], actual[1] + 1)
                 if not maze[actual[1]][actual[0]].get_south()
                 and actual[1] < len(maze) - 1
+                and (actual[0], actual[1] + 1)
+                not in [n.coordinate for n in close]
                 else None
             ),
-            "W": (
-                self.f((actual[0] - 1, actual[1]))
-                if not maze[actual[1]][actual[0]].get_west() and actual[0] > 0
+            (
+                (actual[0] - 1, actual[1])
+                if not maze[actual[1]][actual[0]].get_west()
+                and actual[0] > 0
+                and (actual[0] - 1, actual[1])
+                not in [n.coordinate for n in close]
                 else None
             ),
-        }
-        return {
-            k: v
-            for k, v in sorted(path.items(), key=lambda item: item[0])
-            if v is not None and k != last
-        }
+        ]
+        return [p for p in path if p is not None]
 
-    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_path(self, maze: np.ndarray) -> list:
+        """Perform A* exploration until the destination is reached.
 
-    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
+        Args:
+            maze: Maze grid to solve.
 
-    def get_path(self, maze: np.ndarray) -> str | None:
-        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
+        Returns:
+            The closed list ending with the goal node.
 
-            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
+        Raises:
+            Exception: If no path can be found.
+        """
+        open: list[AStar.Node] = []
+        close: list[AStar.Node] = []
 
-            pre = self.get_opposit(list(path[-1][1].keys())[0])
-            path.append(
-                (
-                    next_pos,
-                    self.best_path(maze, next_pos, pre),
-                )
+        open.append(
+            AStar.Node(
+                self.start,
+                0,
+                self.h(self.start),
+                self.h(self.start),
+                None,
             )
-            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, height: int = None,
-              width: int = None) -> str:
-        res = self.get_path(maze.get_maze())
-        if res is None:
-            raise Exception("Path not found")
+        while len(open) > 0:
+            to_check = sorted(open, key=lambda x: x.f)[0]
+            open.remove(to_check)
+            close.append(to_check)
+            if to_check.coordinate == self.end:
+                return close
+            paths = self.get_paths(maze, to_check.coordinate, close)
+            for path in paths:
+                open.append(
+                    self.Node(
+                        path,
+                        to_check.g + 1,
+                        self.h(path),
+                        self.h(path) + to_check.g + 1,
+                        to_check,
+                    )
+                )
+        raise Exception("Path not found")
+
+    def get_rev_dir(self, current: Node) -> str:
+        """Determine the direction taken from the parent to the current node.
+
+        Args:
+            current: Current node in the reconstructed path.
+
+        Returns:
+            A cardinal direction letter.
+
+        Raises:
+            Exception: If the parent-child relationship cannot be translated.
+        """
+        if current.parent.coordinate == (
+            current.coordinate[0],
+            current.coordinate[1] - 1,
+        ):
+            return "S"
+        elif current.parent.coordinate == (
+            current.coordinate[0] + 1,
+            current.coordinate[1],
+        ):
+            return "W"
+        elif current.parent.coordinate == (
+            current.coordinate[0],
+            current.coordinate[1] + 1,
+        ):
+            return "N"
+        elif current.parent.coordinate == (
+            current.coordinate[0] - 1,
+            current.coordinate[1],
+        ):
+            return "E"
+        else:
+            raise Exception("Translate error: AStar path not found")
+
+    def translate(self, close: list) -> str:
+        """Translate a node chain into a path string.
+
+        Args:
+            close: Closed list ending with the goal node.
+
+        Returns:
+            A string of direction letters from start to end.
+        """
+        current = close[-1]
+        res = ""
+        while True:
+            res = self.get_rev_dir(current) + res
+            current = current.parent
+            if current.coordinate == self.start:
+                break
         return res
 
+    def solve(
+        self, maze: Maze, height: int | None = None, width: int | None = None
+    ) -> str:
+        """Solve the maze using A*.
+
+        Args:
+            maze: The maze to solve.
+            height: Unused optional maze height.
+            width: Unused optional maze width.
+
+        Returns:
+            A string representing the path using cardinal directions.
+        """
+        path = self.get_path(maze.get_maze())
+        return self.translate(path)
+
 
 class DepthFirstSearchSolver(MazeSolver):
+    """Solve a maze using depth-first search with backtracking."""
+
     def __init__(self, start, end):
+        """Initialize the depth-first search solver.
+
+        Args:
+            start: Start coordinates using 1-based indexing.
+            end: End coordinates using 1-based indexing.
+        """
         super().__init__(start, end)
 
-    def solve(self, maze: Maze, height: int = None,
-              width: int = None) -> str:
-        res = list()
-        for _ in range(50):
-            res.append(self.get_path(maze, height, width))
-        return min(res, key=lambda x: len(x))
+    def solve(
+        self, maze: Maze, height: int | None = None, width: int | None = None
+    ) -> str:
+        """Solve the maze using depth-first search.
 
-    def get_path(self, maze: Maze, height: int = None,
-                 width: int = None) -> str:
+        Args:
+            maze: The maze to solve.
+            height: Maze height.
+            width: Maze width.
+
+        Returns:
+            A string representing the path using cardinal directions.
+
+        Raises:
+            Exception: If no path can be found.
+        """
         path_str = ""
         visited = np.zeros((height, width), dtype=bool)
         path = list()
@@ -186,8 +308,9 @@ class DepthFirstSearchSolver(MazeSolver):
             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)
+                path, move = self.back_on_step(
+                    path, visited, maze_s, h_w, move
+                )
                 if not path:
                     break
                 coord = path[-1]
@@ -202,8 +325,20 @@ class DepthFirstSearchSolver(MazeSolver):
         return path_str
 
     @staticmethod
-    def random_path(visited: np.ndarray, coord: tuple,
-                    maze: np.ndarray, h_w: tuple) -> list:
+    def random_path(
+        visited: np.ndarray, coord: tuple, maze: np.ndarray, h_w: tuple
+    ) -> list:
+        """Return all valid unvisited directions from the current cell.
+
+        Args:
+            visited: Boolean array marking visited cells.
+            coord: Current coordinate.
+            maze: Maze grid to inspect.
+            h_w: Tuple containing maze height and width.
+
+        Returns:
+            A list of valid direction letters.
+        """
         random_p = []
         h, w = h_w
         y, x = coord
@@ -223,11 +358,36 @@ class DepthFirstSearchSolver(MazeSolver):
 
     @staticmethod
     def next_path(rand_path: list) -> str:
+        """Select the next move at random.
+
+        Args:
+            rand_path: List of available directions.
+
+        Returns:
+            A randomly selected direction.
+        """
         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:
+    def back_on_step(
+        path: list,
+        visited: np.ndarray,
+        maze: np.ndarray,
+        h_w: tuple,
+        move: list,
+    ) -> list:
+        """Backtrack until a cell with an unexplored path is found.
+
+        Args:
+            path: Current path of visited coordinates.
+            visited: Boolean array marking visited cells.
+            maze: Maze grid to inspect.
+            h_w: Tuple containing maze height and width.
+            move: List of moves made so far.
+
+        Returns:
+            A tuple containing the updated path and move list.
+        """
         while path:
             last = path[-1]
             if DepthFirstSearchSolver.random_path(visited, last, maze, h_w):
@@ -238,6 +398,15 @@ class DepthFirstSearchSolver(MazeSolver):
 
     @staticmethod
     def next_cell(coord: tuple, next: str) -> tuple:
+        """Return the coordinates of the next cell in the given direction.
+
+        Args:
+            coord: Current coordinate.
+            next: Direction to move.
+
+        Returns:
+            The coordinates of the next cell.
+        """
         y, x = coord
         next_step = {"N": (-1, 0), "S": (1, 0), "W": (0, -1), "E": (0, 1)}
         add_y, add_x = next_step[next]

src/parsing/Parsing.py

@@ -3,9 +3,21 @@ from src.amaz_lib.MazeSolver import AStar, DepthFirstSearchSolver
 
 
 class DataMaze:
+    """Provide helper methods to load and validate maze configuration data."""
 
     @staticmethod
     def get_file_data(name_file: str) -> str:
+        """Read and return the contents of a configuration file.
+
+        Args:
+            name_file: Path to the configuration file.
+
+        Returns:
+            The file contents as a string.
+
+        Raises:
+            ValueError: If the file is empty.
+        """
         with open(name_file, "r") as file:
             data = file.read()
         if data == "":
@@ -14,6 +26,16 @@ class DataMaze:
 
     @staticmethod
     def transform_data(data: str) -> dict:
+        """Transform raw configuration text into a dictionary.
+
+        Each non-empty line containing ``=`` is split into a key-value pair.
+
+        Args:
+            data: Raw configuration text.
+
+        Returns:
+            A dictionary mapping configuration keys to their string values.
+        """
         tmp = data.split("\n")
         tmp2 = [value.split("=", 1) for value in tmp if "=" in value]
         data_t = {value[0]: value[1] for value in tmp2}
@@ -21,6 +43,14 @@ class DataMaze:
 
     @staticmethod
     def verif_key_data(data: dict) -> None:
+        """Validate that the configuration contains the expected keys.
+
+        Args:
+            data: Configuration dictionary to validate.
+
+        Raises:
+            KeyError: If keys are missing or unexpected keys are present.
+        """
         key_test = {
             "WIDTH",
             "HEIGHT",
@@ -42,6 +72,15 @@ class DataMaze:
 
     @staticmethod
     def convert_values(data: dict):
+        """Convert configuration values to their appropriate Python types.
+
+        Args:
+            data: Raw configuration dictionary with string values.
+
+        Returns:
+            A dictionary containing converted values and instantiated solver and
+            generator objects.
+        """
         key_int = {"WIDTH", "HEIGHT"}
         key_tuple = {"ENTRY", "EXIT"}
         key_bool = {"PERFECT"}
@@ -54,30 +93,62 @@ class DataMaze:
             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"])
+            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:
+    def get_solver_generator(
+        data: dict,
+        entry: tuple,
+        exit: tuple,
+        perfect: bool,
+    ) -> dict:
+        """Instantiate the configured maze generator and solver.
+
+        Args:
+            data: Raw configuration dictionary.
+            entry: Entry coordinates.
+            exit: Exit coordinates.
+            perfect: Whether the maze must be perfect.
+
+        Returns:
+            A dictionary containing initialized ``GENERATOR`` and ``SOLVER``
+            objects.
+        """
         available_generator = {
             "Kruskal": Kruskal,
             "DFS": DepthFirstSearch,
         }
-        available_solver = {
-            "AStar": AStar,
-            "DFS": DepthFirstSearchSolver
-        }
+        available_solver = {"AStar": AStar, "DFS": DepthFirstSearchSolver}
         res = {}
-        res["GENERATOR"] = available_generator[data["GENERATOR"]](entry, exit,
-                                                                  perfect)
+        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:
+        """Convert a comma-separated coordinate string into a tuple.
+
+        Args:
+            data: Coordinate string in the form ``"x,y"``.
+
+        Returns:
+            A tuple of two integers.
+
+        Raises:
+            ValueError: If the coordinate string does not contain exactly two
+                values.
+        """
         data_t = data.split(",")
         if len(data_t) != 2:
             raise ValueError(
@@ -89,6 +160,17 @@ class DataMaze:
 
     @staticmethod
     def convert_bool(data: str) -> bool:
+        """Convert a string to a boolean value.
+
+        Args:
+            data: String representation of a boolean.
+
+        Returns:
+            ``True`` if the string is ``"True"``, otherwise ``False``.
+
+        Raises:
+            ValueError: If the string is neither ``"True"`` nor ``"False"``.
+        """
         if data != "True" and data != "False":
             raise ValueError("This is not True or False")
         if data == "True":
@@ -97,6 +179,14 @@ class DataMaze:
 
     @staticmethod
     def get_data_maze(name_file: str) -> dict:
+        """Load, validate, and convert maze configuration data from a file.
+
+        Args:
+            name_file: Path to the configuration file.
+
+        Returns:
+            A dictionary of validated configuration values with lowercase keys.
+        """
         try:
             data_str = DataMaze.get_file_data(name_file)
             data_dict = DataMaze.transform_data(data_str)

tests/test_Cell.py

@@ -1,4 +1,3 @@
-import pytest
 from amaz_lib.Cell import Cell
 
 

tests/test_MazeSolver.py

@@ -1,6 +1,6 @@
 from amaz_lib.Cell import Cell
 import numpy as np
-from amaz_lib import AStar, Maze, MazeSolver
+from amaz_lib import AStar, Maze
 
 
 def test_solver() -> None: