README

add clean and fclean method to Makefile

.gitignore

@@ -216,3 +216,4 @@ __marimo__/
 .streamlit/secrets.toml
 test.txt
 
+mazegen-1.0.0-py3-none-any.whl

Makefile

@@ -1,3 +1,7 @@
+build:
+	uv build --clear --wheel
+	cp dist/*.whl mazegen-1.0.0-py3-none-any.whl
+
 install:
 	uv sync
 	uv pip install mlx-2.2-py3-none-any.whl
@@ -12,15 +16,26 @@ debug:
 	uv pdb python3 a_maze_ing.py config.txt
 
 clean:
-	rm -rf __pycache__ .mypy_cache .venv
+	rm -rf */**/__pycache__ */__pycache__ __pycache__ .mypy_cache .venv dist build */**/*.egg-info */*.egg-info *.egg-info test.txt
+
+fclean: clean
+	rm mazegen-1.0.0-py3-none-any.whl 
 
 lint:
 	uv run flake8 . --exclude=.venv
-	uv run mypy . --warn-return-any --warn-unused-ignores --ignore-missing-imports --disallow-untyped-defs --check-untyped-defs
+	uv run env PYTHONPATH=src python3 -m mypy --warn-return-any --warn-unused-ignores --ignore-missing-imports --disallow-untyped-defs --check-untyped-defs -p mazegen
+	uv run env PYTHONPATH=src python3 -m mypy --warn-return-any --warn-unused-ignores --ignore-missing-imports --disallow-untyped-defs --check-untyped-defs -p parsing
+	uv run env PYTHONPATH=src python3 -m mypy --warn-return-any --warn-unused-ignores --ignore-missing-imports --disallow-untyped-defs --check-untyped-defs src/AMazeIng.py
+	uv run env PYTHONPATH=src python3 -m mypy --warn-return-any --warn-unused-ignores --ignore-missing-imports --disallow-untyped-defs --check-untyped-defs tests
+	uv run env PYTHONPATH=src python3 -m mypy --warn-return-any --warn-unused-ignores --ignore-missing-imports --disallow-untyped-defs --check-untyped-defs a_maze_ing.py
 
 lint-strict:
-	uv run flake8 .
-	uv run mypy . --strict
+	uv run flake8 . --exclude=.venv
+	uv run env PYTHONPATH=src python3 -m mypy --strict -p mazegen
+	uv run env PYTHONPATH=src python3 -m mypy --strict src/AMazeIng.py
+	uv run env PYTHONPATH=src python3 -m mypy --strict -p parsing
+	uv run env PYTHONPATH=src python3 -m mypy --strict tests
+	uv run env PYTHONPATH=src python3 -m mypy --strict a_maze_ing.py
 
 run_test_parsing:
 	PYTHONPATH=src uv run pytest tests/test_parsing.py
@@ -34,3 +49,5 @@ run_test:
 	uv run pytest
 mlx:
 	uv run python3 test.py
+
+.PHONY: build install run debug clean fclean lint lint-strict run_test

README.md

@@ -1,3 +1,615 @@
-The Randomized Kruskal's Algorithm
+This project has been created as part of the 42 curriculum by *mteriier*, *dgaillet*
 
-The Randomized Prim's Algorithm
+# A-Maze-ing
+
+## Description
+
+A-Maze-ing is a Python project that generates, solves, exports, and displays mazes.
+
+The program:
+
+- reads a configuration file,
+- generates a maze according to the requested parameters,
+- optionally enforces a **perfect maze** property,
+- solves the maze from entry to exit,
+- writes the maze to an output file using the required hexadecimal wall encoding,
+- and displays the maze visually through an **MLX graphical window**.
+
+This project was designed with **code reusability** in mind.  
+The maze generation and solving logic is exposed through a reusable Python package named **`mazegen`**, which can be built and installed independently for use in future projects.
+
+---
+
+## Features
+
+- Maze generation from a config file
+- Multiple generation algorithms:
+  - `DFS` (depth-first search / recursive backtracking style)
+  - `Kruskal`
+- Multiple solving algorithms:
+  - `AStar`
+  - `DFS`
+- Perfect and imperfect maze support
+- Maze export using hexadecimal wall encoding
+- Graphical rendering with MLX
+- Animated generation
+- Animated solution path display
+- Wall color switching
+- Reserved visual **“42” pattern** using fully closed cells when the maze is large enough
+- Reusable `mazegen` package
+
+---
+
+## Project Structure
+
+```text
+.
+├── a_maze_ing.py          # Main executable script and MLX display
+├── config.txt             # Default configuration file
+├── Makefile
+├── README.md
+├── src/
+│   ├── AMazeIng.py
+│   ├── mazegen/
+│   │   ├── __init__.py
+│   │   ├── Cell.py
+│   │   ├── Maze.py
+│   │   ├── MazeGenerator.py
+│   │   └── MazeSolver.py
+│   └── parsing/
+│       └── Parsing.py
+└── tests/
+```
+
+---
+
+## Instructions
+
+### Requirements
+
+- Python **3.10+**
+- `uv`, `pip`
+- MLX Python binding used by the project
+
+### Installation
+
+Using the provided `Makefile`:
+
+```bash
+make install
+```
+
+This installs project dependencies and the MLX wheel used by the graphical display.
+
+---
+
+## Run
+
+```bash
+make run
+```
+
+---
+
+## Debug
+
+```bash
+make debug
+```
+
+---
+
+## Lint
+
+Mandatory lint target:
+
+```bash
+make lint
+```
+
+Strict lint target:
+
+```bash
+make lint-strict
+```
+
+---
+
+## Clean
+
+```bash
+make clean
+```
+
+Full cleanup:
+
+```bash
+make fclean
+```
+
+---
+
+## Configuration File Format
+
+The configuration file contains one `KEY=VALUE` pair per line.
+
+### Mandatory keys
+
+| Key | Description | Example |
+|---|---|---|
+| `WIDTH` | Maze width in cells | `WIDTH=20` |
+| `HEIGHT` | Maze height in cells | `HEIGHT=15` |
+| `ENTRY` | Entry coordinates `(x,y)` | `ENTRY=1,1` |
+| `EXIT` | Exit coordinates `(x,y)` | `EXIT=20,15` |
+| `OUTPUT_FILE` | Output filename | `OUTPUT_FILE=maze.txt` |
+| `PERFECT` | Perfect maze or not | `PERFECT=True` |
+| `GENERATOR` | Generation algorithm | `GENERATOR=DFS` |
+| `SOLVER` | Solving algorithm | `SOLVER=AStar` |
+
+### Supported values
+
+#### GENERATOR
+
+- `DFS`
+- `Kruskal`
+
+#### SOLVER
+
+- `AStar`
+- `DFS`
+
+#### PERFECT
+
+- `True`
+- `False`
+
+### Example config
+
+```ini
+WIDTH=20
+HEIGHT=15
+ENTRY=1,1
+EXIT=20,15
+OUTPUT_FILE=maze.txt
+PERFECT=True
+GENERATOR=DFS
+SOLVER=AStar
+SEED=31766516
+```
+
+### Notes
+
+- Coordinates are handled as tuples in the form `x,y`.
+- In the current implementation, coordinates are expected to be **inside maze bounds**.
+- Entry and exit must be valid cells.
+- The parser validates required keys and converts values to the correct Python types.
+- You can add a `SEED` value
+
+---
+
+## Output File Format
+
+The generated maze is written row by row using **one hexadecimal digit per cell**.
+
+Each cell stores wall information using this bitmask:
+
+| Bit | Direction |
+|---|---|
+| `1` | North |
+| `2` | East |
+| `4` | South |
+| `8` | West |
+
+A bit set to `1` means the wall is **closed**.
+
+### Example
+
+- `3` = `0011` → north and east closed
+- `A` = `1010` → east and west closed
+
+### Output layout
+
+```text
+<maze row 1>
+<maze row 2>
+...
+<maze row n>
+
+<entry coordinates>
+<exit coordinates>
+<solution path>
+```
+
+Example:
+
+```text
+FFFF
+9A63
+8C47
+FFFF
+
+1,1
+4,4
+EESSEN
+```
+
+---
+
+## Visual Representation
+
+This project provides a graphical rendering through **MLX**.
+
+The display shows:
+
+- maze walls,
+- entry cell,
+- exit cell,
+- optional shortest path,
+- reserved “42” pattern when present.
+
+### Controls
+
+In the MLX window:
+
+- `1` / mapped equivalent: regenerate maze
+- `2` / mapped equivalent: show/hide path
+- `3` / mapped equivalent: change wall color
+- `4` / mapped equivalent: quit
+
+The code includes two key mappings to handle platform/layout differences.
+
+### Visual Features
+
+- animated generation,
+- animated path display,
+- color cycling for walls,
+- separate color cycling for the “42” cells.
+
+---
+
+## Maze Generation Algorithm
+
+This project supports two generation algorithms.
+
+### 1. Depth-First Search (DFS)
+
+This algorithm starts from a cell and repeatedly visits an unvisited neighbour, removing walls as it advances. When it reaches a dead end, it backtracks until it finds a cell with an unvisited neighbour.
+
+#### Why this algorithm was chosen
+
+- simple to implement,
+- naturally produces connected mazes,
+- works well for animation,
+- produces visually interesting long corridors,
+- easy to adapt for perfect mazes.
+
+### 2. Kruskal
+
+This algorithm treats each cell as its own set and removes walls between cells only when it connects two different sets. This avoids cycles and guarantees connectivity.
+
+#### Why this algorithm was included
+
+- classic maze generation algorithm,
+- good complement to DFS,
+- demonstrates modularity and algorithm interchangeability,
+- naturally fits the reusable package requirement.
+
+---
+
+## Why These Algorithms Were Chosen
+
+We chose DFS and Kruskal because together they provide:
+
+- two well-known and complementary approaches,
+- good pedagogical value,
+- simple integration into a reusable class-based architecture,
+- deterministic structure when used with a seed,
+- compatibility with perfect maze generation.
+
+DFS is particularly suitable for progressive visual rendering.  
+Kruskal is useful to show a different construction logic based on set merging.
+
+---
+
+## Perfect and Imperfect Mazes
+
+When `PERFECT=True`:
+
+- the maze is generated as a **perfect maze**,
+- there is exactly one path between any two reachable cells,
+- in particular, entry and exit have a unique valid path.
+
+When `PERFECT=False`:
+
+- additional walls may be removed after initial generation,
+- loops can appear,
+- the maze remains connected,
+- the solver still computes a valid path.
+
+---
+
+## The “42” Pattern
+
+For sufficiently large mazes, the generator reserves a group of fully closed cells to draw a visible **“42”** pattern in the visual rendering.
+
+### Behaviour
+
+- the pattern is added only if the maze is large enough,
+- if the maze is too small, the pattern may be omitted,
+- this should be reported to the user with a console message.
+
+### Current implementation note
+
+The current code includes support for reserving and rendering the “42” pattern using cells with value `15` (all walls closed).  
+The pattern is drawn in the central area when dimensions are large enough.
+
+---
+
+## Error Handling
+
+The project is designed to fail gracefully and provide clear messages for common problems such as:
+
+- missing configuration file,
+- empty file,
+- missing or invalid keys,
+- invalid boolean values,
+- invalid coordinates,
+- invalid maze dimensions,
+- solving an uninitialized maze.
+
+The parser catches several common exceptions and prints user-friendly messages before exiting.
+
+---
+
+## Reusable Code
+
+The reusable part of the project is the **`mazegen`** package.
+
+It contains:
+
+- `Cell`: wall bitmask representation,
+- `Maze`: maze container and textual/ascii rendering,
+- `MazeGenerator`: abstract generator interface,
+- `DepthFirstSearch`: DFS-based maze generator,
+- `Kruskal`: Kruskal-based maze generator,
+- `MazeSolver`: abstract solver interface,
+- `AStar`: shortest-path solver,
+- `DepthFirstSearchSolver`: DFS-based path solver.
+
+This package can be built as a wheel and reused independently of the MLX application.
+
+---
+
+## How to Use the Reusable Module
+
+### Basic example
+
+```python
+from mazegen import Maze
+from mazegen import DepthFirstSearch, AStar
+
+generator = DepthFirstSearch(start=(1, 1), end=(10, 10), perfect=True)
+solver = AStar(start=(1, 1), end=(10, 10))
+
+maze = Maze()
+
+for grid in generator.generator(height=10, width=10, seed=42):
+    maze.set_maze(grid)
+
+path = solver.solve(maze, height=10, width=10)
+
+print(maze)
+print(path)
+```
+
+### With Kruskal
+
+```python
+from mazegen import Maze, Kruskal, AStar
+
+generator = Kruskal(start=(1, 1), end=(20, 15), perfect=True)
+solver = AStar(start=(1, 1), end=(20, 15))
+
+maze = Maze()
+
+for grid in generator.generator(height=15, width=20, seed=123):
+    maze.set_maze(grid)
+
+print(solver.solve(maze, height=15, width=20))
+```
+
+### Accessing the generated structure
+
+```python
+maze_array = maze.get_maze()
+```
+
+Each element of `maze_array` is a `Cell` object exposing:
+
+- `get_north()`
+- `get_est()`
+- `get_south()`
+- `get_west()`
+- `get_value()`
+
+### Accessing a solution
+
+```python
+solution = solver.solve(maze, height=15, width=20)
+print(solution)  # Example: "EESSWN..."
+```
+
+---
+
+## Packaging
+
+The reusable package is distributed as **`mazegen-*`**.
+
+Example expected artifact:
+
+```text
+mazegen-1.0.0-py3-none-any.whl
+```
+
+Build with:
+
+```bash
+make build
+```
+
+This produces a wheel suitable for later installation with `pip`/`uv`.
+
+---
+
+## Tests
+
+Unit tests are recommended and partially integrated through `pytest` targets in the Makefile.
+
+Start test with:
+
+```bash
+make run_test
+```
+
+These tests are useful to validate:
+
+- parsing,
+- generation,
+- solver behavior,
+- edge cases.
+
+---
+
+## Technical Choices
+
+### Language
+
+- Python 3.10+
+
+### Libraries
+
+- `numpy` for grid storage
+- `pydantic` for model validation
+- `mlx` for graphical rendering
+- `pytest` for tests
+- `mypy` for static typing
+- `flake8` for style checking
+
+### Architecture
+
+The project is separated into three main parts:
+
+1. **Main application**
+   - parsing,
+   - orchestration,
+   - MLX rendering,
+   - user interaction.
+
+2. **Domain model**
+   - `AMazeIng`,
+   - maze configuration and lifecycle.
+
+3. **Reusable package**
+   - generation,
+   - solving,
+   - maze structure.
+
+This separation makes the generation logic portable to other projects.
+
+---
+
+## Team and Project Management
+
+### Team roles
+
+- **mteriier**
+  - Parsing
+  - DFS generator / solver
+  - Makefile
+  - some pytest
+  - Fix of mazegen package generation
+  - MLX
+- **dgaillet**
+  - AMazeIng config class
+  - AStar solver
+  - Kruskal generator
+  - some pytest
+  - mazegen package generation
+  - MLX
+  - Cell / Maze class
+
+### Initial planning
+
+Our initial plan was:
+
+1. define the maze data model,
+2. implement one working generation algorithm,
+3. export the maze to the required format,
+4. implement solving,
+5. add graphical rendering,
+6. package reusable code,
+7. write tests and documentation.
+
+### How planning evolved
+
+In practice:
+
+- the reusable package structure had to be stabilized earlier than expected,
+- coordinate handling between parser, generator, solver, and renderer required extra work,
+- rendering and animation took longer than planned,
+- algorithm modularity made later integration easier.
+
+### What worked well
+
+- clean separation between generation and display,
+- abstract base classes for generator and solver,
+- Makefile automation,
+- packaging the reusable module.
+
+### What could be improved
+
+- stricter normalization of coordinate conventions,
+- seed support should be exposed directly from configuration,
+- more tests for edge cases and invalid inputs,
+
+### Tools used
+
+- Git
+- `uv`
+- `flake8`
+- `mypy`
+- `pytest`
+- MLX
+- optionally AI assistance for docstrings, README
+
+---
+
+## Resources
+
+### Documentation and references
+
+- [NumPy Documentation](https://numpy.org/doc/)
+- [Pydantic Documentation](https://docs.pydantic.dev/)
+- [A* Pathfinding explanation](https://matteo-tosato7.medium.com/exploring-the-depths-solving-mazes-with-a-search-algorithm-c15253104899)
+- [Kruskal generation](https://medium.com/@anushidesilva28/understanding-kruskals-algorithm-44886bf8ba8b)
+
+### How AI was used
+
+AI was used as an assistant for:
+
+- improving docstrings,
+- helping structure the README,
+
+---
+
+## Reusable Module Summary
+
+If you only want the reusable maze engine:
+
+1. build/install `mazegen`,
+2. import a generator and a solver,
+3. generate a maze,
+4. solve it,
+5. access the grid through `Maze.get_maze()`.
+
+This part is intended for reuse in future Python projects.

a_maze_ing.py

@@ -1,8 +1,8 @@
 from typing import Any
-from src.AMazeIng import AMazeIng
-from src.parsing import Parsing
+from numpy.typing import NDArray
+from AMazeIng import AMazeIng
+from parsing.Parsing import DataMaze as Parsing
 from mlx import Mlx
-import numpy as np
 import time
 
 
@@ -29,14 +29,12 @@ class MazeMLX:
         self.buf, self.bpp, self.size_line, self.format = (
             self.mlx.mlx_get_data_addr(self.img_ptr)
         )
-        self.path_printer = None
-        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):
+    def close_loop(self, _: Any) -> None:
         """Stop the MLX event loop.
 
         Args:
@@ -63,7 +61,9 @@ class MazeMLX:
             "1: regen; 2: path; 3: color; 4: quit;",
         )
 
-    def put_pixel(self, x, y, color: list | None = None) -> None:
+    def put_pixel(
+        self, x: int, y: int, color: list[Any] | None = None
+    ) -> None:
         """Draw a single pixel into the image buffer.
 
         Args:
@@ -93,7 +93,7 @@ class MazeMLX:
         self,
         start: tuple[int, int],
         end: tuple[int, int],
-        color: list | None = None,
+        color: list[Any] | None = None,
     ) -> None:
         """Draw a horizontal or vertical line.
 
@@ -115,7 +115,7 @@ class MazeMLX:
         self,
         ul: tuple[int, int],
         dr: tuple[int, int],
-        color: list | None = None,
+        color: list[Any] | None = None,
     ) -> None:
         """Draw a filled rectangular block.
 
@@ -165,7 +165,7 @@ class MazeMLX:
             for color in colors:
                 yield color
 
-    def get_margin_line_len(self, maze: np.ndarray) -> tuple[int, int, int]:
+    def get_margin_line_len(self, maze: NDArray[Any]) -> tuple[int, int, int]:
         """Compute the cell size and margins for centering the maze.
 
         Args:
@@ -188,7 +188,7 @@ class MazeMLX:
 
         return (line_len, margin_x, margin_y)
 
-    def update_maze(self, maze: np.ndarray) -> None:
+    def update_maze(self, maze: NDArray[Any]) -> None:
         """Render the maze walls into the image buffer.
 
         Args:
@@ -272,7 +272,7 @@ class MazeMLX:
         self.put_block(ul, dr)
         return
 
-    def put_start_end(self, amazing: AMazeIng):
+    def put_start_end(self, amazing: AMazeIng) -> None:
         """Draw highlighted blocks for the maze entry and exit.
 
         Args:
@@ -306,8 +306,11 @@ class MazeMLX:
         )
         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.
+    def draw_ft(
+        self, maze: NDArray[Any], color: list[Any] | None = None
+    ) -> None:
+        """Draw filled cells corresponding to the reserved fully
+            walled pattern.
 
         Args:
             maze: Maze grid to inspect.
@@ -325,33 +328,36 @@ class MazeMLX:
                     self.put_block((x0, y0), (x1, y1), color)
 
     def draw_image(self, amazing: AMazeIng) -> None:
+        maze = amazing.maze.get_maze()
         """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.print_path:
                 if self.render_path():
                     color = next(self.color_gen_ft)
-                    self.draw_ft(amazing.maze.get_maze(), color)
+                    if maze is not None:
+                        self.draw_ft(maze, color)
                     next(self.timer_gen)
             else:
                 self.time_gen()
-                self.update_maze(amazing.maze.get_maze())
-                self.draw_ft(amazing.maze.get_maze())
+                if maze is not None:
+                    self.update_maze(maze)
+                    self.draw_ft(maze)
             self.put_start_end(amazing)
         self.redraw_image()
 
-    def shift_color(self):
+    def shift_color(self) -> None:
         """Reset the maze color generator."""
         self.color_gen = self.random_color()
 
-    def shift_color_ft(self):
+    def shift_color_ft(self) -> None:
         """Reset the reserved-pattern color generator."""
         self.color_gen_ft = self.random_color_ft()
 
-    def time_gen(self):
+    def time_gen(self) -> None:
         """Reset the timing generator used for animation pacing."""
         self.timer_gen = self.time_generator()
 
@@ -406,8 +412,10 @@ class MazeMLX:
             ``True`` if maze generation is complete, otherwise ``False``.
         """
         try:
+            maze = amazing.maze.get_maze()
             next(self.generator)
-            self.update_maze(amazing.maze.get_maze())
+            if maze is not None:
+                self.update_maze(maze)
             return False
         except StopIteration:
             pass
@@ -466,7 +474,7 @@ class MazeMLX:
         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.win_ptr, 2, 1 << 0, self.handle_key_press_mteriier, amazing
         )
         self.mlx.mlx_loop(self.mlx_ptr)
 
@@ -476,7 +484,7 @@ def main() -> None:
     mlx = None
     try:
         mlx = MazeMLX(1000, 1000)
-        config = Parsing.DataMaze.get_data_maze("config.txt")
+        config = Parsing.get_data_maze("config.txt")
         amazing = AMazeIng(**config)
         mlx.start(amazing)
         with open("test.txt", "w") as output:

output_validator.py

@@ -1,25 +0,0 @@
-# This script does not check for errors or malformed files.
-# It only validates that neighbooring cells sharing a wall have
-#  both the correct encoding.
-# Usage: python3 output_validator.py output_maze.txt
-
-import sys
-
-if len(sys.argv) != 2:
-    print(f"Usage: python3 {sys.argv[0]} <output_file>")
-    sys.exit(1)
-
-g = []
-for line in open(sys.argv[1]):
-    if line.strip() == '':
-        break
-    g.append([int(c, 16) for c in line.strip(' \t\n\r')])
-
-for r in range(len(g)):
-    for c in range(len(g[0])):
-        v = g[r][c]
-        if not all([(r < 1 or v & 1 == (g[r-1][c] >> 2) & 1),
-                    (c >= len(g[0])-1 or (v >> 1) & 1 == (g[r][c+1] >> 3) & 1),
-                    (r >= len(g)-1 or (v >> 2) & 1 == g[r+1][c] & 1),
-                    (c < 1 or (v >> 3) & 1 == (g[r][c-1] >> 1) & 1)]):
-            print(f'Wrong encoding for ({c},{r})')

pyproject.toml

@@ -1,5 +1,5 @@
 [project]
-name = "A-Maze-ing"
+name = "mazegen"
 version = "0.1.0"
 description = "This is the way"
 readme = "README.md"
@@ -20,6 +20,18 @@ dev = [
 
 [tool.mypy]
 python_version = "3.10"
+explicit_package_bases = true
 
 [tool.pytest.ini_options]
 pythonpath = ["src"]
+
+[build-system]
+requires = ["setuptools>=78.1.0", "wheel>=0.45.1"]
+build-backend = "setuptools.build_meta"
+
+[tool.setuptools]
+package-dir = {"" = "src"}
+
+[tool.setuptools.packages.find]
+where = ["src"]
+

src/AMazeIng.py

@@ -2,11 +2,13 @@ from typing import Generator
 from typing_extensions import Self
 from pydantic import BaseModel, Field, model_validator, ConfigDict
 
-from src.amaz_lib import Maze, MazeGenerator, MazeSolver
+from mazegen import Maze, MazeGenerator, MazeSolver
 
 
 class AMazeIng(BaseModel):
-    """Represent a complete maze configuration, generation, and solving setup."""
+    """Represent a complete maze configuration, generation,
+    and solving setup.
+    """
 
     model_config = ConfigDict(arbitrary_types_allowed=True)
 

src/amaz_lib/__init__.py

@@ -1,10 +0,0 @@
-from .Cell import Cell
-from .Maze import Maze
-from .MazeGenerator import MazeGenerator, DepthFirstSearch
-from .MazeGenerator import Kruskal
-from .MazeSolver import MazeSolver, AStar, DepthFirstSearchSolver
-
-__version__ = "1.0.0"
-__author__ = "us"
-__all__ = ["Cell", "Maze", "MazeGenerator", "DepthFirstSearchSolver",
-           "MazeSolver", "AStar", "Kruskal", "DepthFirstSearch"]

src/mazegen/MazeGenerator.py

@@ -1,14 +1,18 @@
 from abc import ABC, abstractmethod
-from typing import Generator, Set
+from typing import Generator, Any
 import numpy as np
-from .Cell import Cell
+from numpy.typing import NDArray
+from mazegen.Cell import Cell
 import math
+import random
 
 
 class MazeGenerator(ABC):
     """Define the common interface and helpers for maze generators."""
 
-    def __init__(self, start: tuple, end: tuple, perfect: bool) -> None:
+    def __init__(
+        self, start: tuple[int, int], end: tuple[int, int], perfect: bool
+    ) -> None:
         """Initialize the maze generator.
 
         Args:
@@ -23,7 +27,7 @@ class MazeGenerator(ABC):
     @abstractmethod
     def generator(
         self, height: int, width: int, seed: int | None = None
-    ) -> Generator[np.ndarray, None, np.ndarray]:
+    ) -> Generator[NDArray[Any], None, NDArray[Any]]:
         """Generate a maze step by step.
 
         Args:
@@ -40,7 +44,7 @@ class MazeGenerator(ABC):
         ...
 
     @staticmethod
-    def get_cell_ft(width: int, height: int) -> set:
+    def get_cell_ft(width: int, height: int) -> set[tuple[int, int]]:
         """Return the coordinates used to reserve the '42' pattern.
 
         Args:
@@ -76,11 +80,12 @@ class MazeGenerator(ABC):
     def unperfect_maze(
         width: int,
         height: int,
-        maze: np.ndarray,
-        forty_two: set | None,
+        maze: NDArray[Any],
+        forty_two: set[tuple[int, int]] | None,
         prob: float = 0.1,
-    ) -> Generator[np.ndarray, None, np.ndarray]:
-        """Add extra openings to transform a perfect maze into an imperfect one.
+    ) -> Generator[NDArray[Any], None, NDArray[Any]]:
+        """Add extra openings to transform a perfect maze into an imperfect
+        one.
 
         Random walls are removed while optionally preserving the reserved
             ``forty_two`` area.
@@ -99,6 +104,7 @@ class MazeGenerator(ABC):
         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"}
@@ -139,7 +145,7 @@ class MazeGenerator(ABC):
 class Kruskal(MazeGenerator):
     """Generate a maze using a Kruskal-based algorithm."""
 
-    class Set:
+    class KruskalSet:
         """Represent a connected component of maze cells."""
 
         def __init__(self, cells: list[int]) -> None:
@@ -153,7 +159,7 @@ class Kruskal(MazeGenerator):
     class Sets:
         """Store all connected components used during generation."""
 
-        def __init__(self, sets: list[Set]) -> None:
+        def __init__(self, sets: list["Kruskal.KruskalSet"]) -> None:
             """Initialize the collection of connected components.
 
             Args:
@@ -163,8 +169,8 @@ class Kruskal(MazeGenerator):
 
     @staticmethod
     def walls_to_maze(
-        walls: np.ndarray, height: int, width: int
-    ) -> np.ndarray:
+        walls: list[tuple[int, int]], height: int, width: int
+    ) -> NDArray[Any]:
         """Convert a list of remaining walls into a maze grid.
 
         Args:
@@ -176,7 +182,8 @@ class Kruskal(MazeGenerator):
             A two-dimensional array of :class:`Cell` instances representing the
             maze.
         """
-        maze: np.ndarray = np.array(
+
+        maze: NDArray[Any] = np.array(
             [[Cell(value=0) for _ in range(width)] for _ in range(height)]
         )
         for wall in walls:
@@ -270,7 +277,7 @@ class Kruskal(MazeGenerator):
 
     def generator(
         self, height: int, width: int, seed: int | None = None
-    ) -> Generator[np.ndarray, None, np.ndarray]:
+    ) -> Generator[NDArray[Any], None, NDArray[Any]]:
         """Generate a maze using a Kruskal-based approach.
 
         Args:
@@ -292,7 +299,7 @@ class Kruskal(MazeGenerator):
 
         if seed is not None:
             np.random.seed(seed)
-        sets = self.Sets([self.Set([i]) for i in range(height * width)])
+        sets = self.Sets([self.KruskalSet([i]) for i in range(height * width)])
         walls = []
         for h in range(height):
             for w in range(width - 1):
@@ -330,7 +337,9 @@ 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:
+    def __init__(
+        self, start: tuple[int, int], end: tuple[int, int], perfect: bool
+    ) -> None:
         """Initialize the depth-first search generator.
 
         Args:
@@ -341,11 +350,11 @@ class DepthFirstSearch(MazeGenerator):
         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
+        self.forty_two: set[tuple[int, int]] | None = None
 
     def generator(
-        self, height: int, width: int, seed: int = None
-    ) -> Generator[np.ndarray, None, np.ndarray]:
+        self, height: int, width: int, seed: int | None = None
+    ) -> Generator[NDArray[Any], None, NDArray[Any]]:
         """Generate a maze using depth-first search.
 
         Args:
@@ -364,14 +373,14 @@ class DepthFirstSearch(MazeGenerator):
         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)
+        visited: NDArray[np.object_] = 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()
+        path: list[tuple[int, int]] = list()
         w_h = (width, height)
         coord = (0, 0)
         x, y = coord
@@ -414,7 +423,7 @@ class DepthFirstSearch(MazeGenerator):
         return maze
 
     @staticmethod
-    def init_maze(width: int, height: int) -> np.ndarray:
+    def init_maze(width: int, height: int) -> NDArray[Any]:
         """Create a fully walled maze grid.
 
         Args:
@@ -422,7 +431,8 @@ class DepthFirstSearch(MazeGenerator):
             height: Number of rows in the maze.
 
         Returns:
-            A two-dimensional array of cells initialized with all walls present.
+            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)]
@@ -430,7 +440,9 @@ class DepthFirstSearch(MazeGenerator):
         return maze
 
     @staticmethod
-    def add_cell_visited(coord: tuple, path: set) -> list:
+    def add_cell_visited(
+        coord: tuple[int, int], path: list[tuple[int, int]]
+    ) -> list[tuple[int, int]]:
         """Append a visited coordinate to the current traversal path.
 
         Args:
@@ -444,7 +456,9 @@ class DepthFirstSearch(MazeGenerator):
         return path
 
     @staticmethod
-    def random_cells(visited: np.array, coord: tuple, w_h: tuple) -> list:
+    def random_cells(
+        visited: NDArray[Any], coord: tuple[int, int], w_h: tuple[int, int]
+    ) -> list[str]:
         """Return the list of unvisited neighboring directions.
 
         Args:
@@ -456,7 +470,7 @@ class DepthFirstSearch(MazeGenerator):
             A list of direction strings among ``"N"``, ``"S"``, ``"W"``, and
             ``"E"``.
         """
-        rand_cell = []
+        rand_cell: list[str] = []
         x, y = coord
         width, height = w_h
 
@@ -474,7 +488,7 @@ class DepthFirstSearch(MazeGenerator):
         return rand_cell
 
     @staticmethod
-    def next_step(rand_cell: list) -> str:
+    def next_step(rand_cell: list[str]) -> str:
         """Select the next direction at random.
 
         Args:
@@ -483,7 +497,7 @@ class DepthFirstSearch(MazeGenerator):
         Returns:
             A randomly selected direction.
         """
-        return np.random.choice(rand_cell)
+        return random.choice(rand_cell)
 
     @staticmethod
     def broken_wall(cell: Cell, wall: str) -> Cell:
@@ -507,7 +521,7 @@ class DepthFirstSearch(MazeGenerator):
         return cell
 
     @staticmethod
-    def next_cell(x: int, y: int, next: str) -> tuple:
+    def next_cell(x: int, y: int, next: str) -> tuple[int, int]:
         """Return the coordinates of the adjacent cell in the given direction.
 
         Args:
@@ -535,8 +549,13 @@ class DepthFirstSearch(MazeGenerator):
         return {"N": "S", "S": "N", "W": "E", "E": "W"}[direction]
 
     @staticmethod
-    def back_on_step(path: list, w_h: tuple, visited: np.ndarray) -> list:
-        """Backtrack through the path until a cell with unvisited neighbors is found.
+    def back_on_step(
+        path: list[tuple[int, int]],
+        w_h: tuple[int, int],
+        visited: NDArray[Any],
+    ) -> list[tuple[int, int]]:
+        """Backtrack through the path until a cell with unvisited neighbors
+        is found.
 
         Args:
             path: Current traversal path.
@@ -555,8 +574,8 @@ class DepthFirstSearch(MazeGenerator):
 
     @staticmethod
     def lock_cell_ft(
-        visited: np.ndarray, forty_two: set[tuple[int]]
-    ) -> np.ndarray:
+        visited: NDArray[Any], forty_two: set[tuple[int, int]]
+    ) -> NDArray[Any]:
         """Mark the reserved '42' pattern cells as already visited.
 
         Args:

src/mazegen/MazeSolver.py

@@ -2,6 +2,8 @@ from abc import ABC, abstractmethod
 from .Maze import Maze
 from typing import Any
 import numpy as np
+from numpy.typing import NDArray
+import random
 
 
 class MazeSolver(ABC):
@@ -83,7 +85,6 @@ class AStar(MazeSolver):
             end: End coordinates using 1-based indexing.
         """
         super().__init__(start, end)
-        self.path = []
 
     def h(self, n: tuple[int, int]) -> int:
         """Compute the Manhattan distance heuristic to the goal.
@@ -103,9 +104,9 @@ class AStar(MazeSolver):
 
     def get_paths(
         self,
-        maze: np.ndarray,
+        maze: NDArray[Any],
         actual: tuple[int, int],
-        close: list,
+        close: list["Node"],
     ) -> list[tuple[int, int]]:
         """Return all reachable neighboring coordinates.
 
@@ -153,7 +154,7 @@ class AStar(MazeSolver):
         ]
         return [p for p in path if p is not None]
 
-    def get_path(self, maze: np.ndarray) -> list:
+    def get_path(self, maze: NDArray[Any]) -> list["Node"]:
         """Perform A* exploration until the destination is reached.
 
         Args:
@@ -232,7 +233,7 @@ class AStar(MazeSolver):
         else:
             raise Exception("Translate error: AStar path not found")
 
-    def translate(self, close: list) -> str:
+    def translate(self, close: list["Node"]) -> str:
         """Translate a node chain into a path string.
 
         Args:
@@ -263,14 +264,18 @@ class AStar(MazeSolver):
         Returns:
             A string representing the path using cardinal directions.
         """
-        path = self.get_path(maze.get_maze())
+
+        maze_arr = maze.get_maze()
+        if maze_arr is None:
+            raise Exception("Maze is not initialized")
+        path: list[AStar.Node] = self.get_path(maze_arr)
         return self.translate(path)
 
 
 class DepthFirstSearchSolver(MazeSolver):
     """Solve a maze using depth-first search with backtracking."""
 
-    def __init__(self, start, end):
+    def __init__(self, start: tuple[int, int], end: tuple[int, int]):
         """Initialize the depth-first search solver.
 
         Args:
@@ -296,16 +301,20 @@ class DepthFirstSearchSolver(MazeSolver):
             Exception: If no path can be found.
         """
         path_str = ""
-        visited = np.zeros((height, width), dtype=bool)
-        path = list()
-        move = list()
+        if height is None or width is None:
+            raise Exception("We need Height and Width in the arg")
+        visited: NDArray[Any] = np.zeros((height, width), dtype=bool)
+        path: list[tuple[int, int]] = list()
+        move: list[str] = list()
         maze_s = maze.get_maze()
+        if maze_s is None:
+            raise Exception("Maze is not initializef")
         coord = self.start
-        h_w = (height, width)
+        h_w: tuple[int, int] = (height, width)
         while coord != self.end:
             visited[coord] = True
             path.append(coord)
-            rand_p = self.random_path(visited, coord, maze_s, h_w)
+            rand_p: list[str] = self.random_path(visited, coord, maze_s, h_w)
 
             if not rand_p:
                 path, move = self.back_on_step(
@@ -326,8 +335,11 @@ class DepthFirstSearchSolver(MazeSolver):
 
     @staticmethod
     def random_path(
-        visited: np.ndarray, coord: tuple, maze: np.ndarray, h_w: tuple
-    ) -> list:
+        visited: NDArray[Any],
+        coord: tuple[int, int],
+        maze: NDArray[Any],
+        h_w: tuple[int, int],
+    ) -> list[str]:
         """Return all valid unvisited directions from the current cell.
 
         Args:
@@ -357,7 +369,7 @@ class DepthFirstSearchSolver(MazeSolver):
         return random_p
 
     @staticmethod
-    def next_path(rand_path: list) -> str:
+    def next_path(rand_path: list[str]) -> str:
         """Select the next move at random.
 
         Args:
@@ -366,16 +378,17 @@ class DepthFirstSearchSolver(MazeSolver):
         Returns:
             A randomly selected direction.
         """
-        return np.random.choice(rand_path)
+
+        return random.choice(rand_path)
 
     @staticmethod
     def back_on_step(
-        path: list,
-        visited: np.ndarray,
-        maze: np.ndarray,
-        h_w: tuple,
-        move: list,
-    ) -> list:
+        path: list[tuple[int, int]],
+        visited: NDArray[Any],
+        maze: NDArray[Any],
+        h_w: tuple[int, int],
+        move: list[str],
+    ) -> tuple[list[Any], list[Any]]:
         """Backtrack until a cell with an unexplored path is found.
 
         Args:
@@ -388,6 +401,7 @@ class DepthFirstSearchSolver(MazeSolver):
         Returns:
             A tuple containing the updated path and move list.
         """
+
         while path:
             last = path[-1]
             if DepthFirstSearchSolver.random_path(visited, last, maze, h_w):
@@ -397,7 +411,7 @@ class DepthFirstSearchSolver(MazeSolver):
         return path, move
 
     @staticmethod
-    def next_cell(coord: tuple, next: str) -> tuple:
+    def next_cell(coord: tuple[int, int], next: str) -> tuple[int, int]:
         """Return the coordinates of the next cell in the given direction.
 
         Args:

src/mazegen/__init__.py

@@ -0,0 +1,18 @@
+from mazegen.Cell import Cell
+from mazegen.Maze import Maze
+from mazegen.MazeGenerator import MazeGenerator, DepthFirstSearch
+from mazegen.MazeGenerator import Kruskal
+from mazegen.MazeSolver import MazeSolver, AStar, DepthFirstSearchSolver
+
+__version__ = "1.0.0"
+__author__ = "us"
+__all__ = [
+    "Cell",
+    "Maze",
+    "MazeGenerator",
+    "DepthFirstSearchSolver",
+    "MazeSolver",
+    "AStar",
+    "Kruskal",
+    "DepthFirstSearch",
+]

src/parsing/Parsing.py

@@ -1,5 +1,6 @@
-from src.amaz_lib.MazeGenerator import DepthFirstSearch, Kruskal
-from src.amaz_lib.MazeSolver import AStar, DepthFirstSearchSolver
+from mazegen import DepthFirstSearch, Kruskal
+from mazegen import AStar, DepthFirstSearchSolver
+from typing import Any
 
 
 class DataMaze:
@@ -25,7 +26,7 @@ class DataMaze:
         return data
 
     @staticmethod
-    def transform_data(data: str) -> dict:
+    def transform_data(data: str) -> dict[str, str]:
         """Transform raw configuration text into a dictionary.
 
         Each non-empty line containing ``=`` is split into a key-value pair.
@@ -42,7 +43,7 @@ class DataMaze:
         return data_t
 
     @staticmethod
-    def verif_key_data(data: dict) -> None:
+    def verif_key_data(data: dict[str, str]) -> None:
         """Validate that the configuration contains the expected keys.
 
         Args:
@@ -71,20 +72,20 @@ class DataMaze:
             )
 
     @staticmethod
-    def convert_values(data: dict):
+    def convert_values(data: dict[str, str]) -> dict[str, Any]:
         """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.
+            A dictionary containing converted values and instantiated
+            solver and generator objects.
         """
         key_int = {"WIDTH", "HEIGHT"}
         key_tuple = {"ENTRY", "EXIT"}
         key_bool = {"PERFECT"}
-        res: dict = {}
+        res: dict[str, Any] = {}
         for key in key_int:
             res.update({key: int(data[key])})
         for key in key_tuple:
@@ -104,11 +105,11 @@ class DataMaze:
 
     @staticmethod
     def get_solver_generator(
-        data: dict,
-        entry: tuple,
-        exit: tuple,
+        data: dict[str, str],
+        entry: tuple[int, int],
+        exit: tuple[int, int],
         perfect: bool,
-    ) -> dict:
+    ) -> dict[str, Any]:
         """Instantiate the configured maze generator and solver.
 
         Args:
@@ -121,11 +122,14 @@ class DataMaze:
             A dictionary containing initialized ``GENERATOR`` and ``SOLVER``
             objects.
         """
-        available_generator = {
+        available_generator: dict[str, Any] = {
             "Kruskal": Kruskal,
             "DFS": DepthFirstSearch,
         }
-        available_solver = {"AStar": AStar, "DFS": DepthFirstSearchSolver}
+        available_solver: dict[str, Any] = {
+            "AStar": AStar,
+            "DFS": DepthFirstSearchSolver,
+        }
         res = {}
         res["GENERATOR"] = available_generator[data["GENERATOR"]](
             entry,
@@ -136,7 +140,7 @@ class DataMaze:
         return res
 
     @staticmethod
-    def convert_tuple(data: str) -> tuple:
+    def convert_tuple(data: str) -> tuple[int, int]:
         """Convert a comma-separated coordinate string into a tuple.
 
         Args:
@@ -178,7 +182,7 @@ class DataMaze:
         return False
 
     @staticmethod
-    def get_data_maze(name_file: str) -> dict:
+    def get_data_maze(name_file: str) -> dict[str, Any]:
         """Load, validate, and convert maze configuration data from a file.
 
         Args:

src/parsing/__init__.py

@@ -1,6 +0,0 @@
-__version__ = "1.0.0"
-__author__ = "mteriier, dgaillet"
-
-from .Parsing import DataMaze
-
-__all__ = ["DataMaze"]

tests/test_Cell.py

@@ -1,4 +1,4 @@
-from amaz_lib.Cell import Cell
+from mazegen import Cell
 
 
 def test_cell_setter_getter() -> None:

tests/test_Depth.py

@@ -1,5 +1,5 @@
-from amaz_lib.MazeGenerator import DepthFirstSearch
-from amaz_lib.Cell import Cell
+from mazegen import DepthFirstSearch
+from mazegen import Cell
 import numpy as np
 
 

tests/test_Maze.py

@@ -1,6 +1,6 @@
 import numpy
-from amaz_lib.Cell import Cell
-from amaz_lib.Maze import Maze
+from mazegen import Cell
+from mazegen import Maze
 
 
 def test_maze_setter_getter() -> None:
@@ -15,7 +15,9 @@ def test_maze_setter_getter() -> None:
     )
 
     maze.set_maze(test)
-    assert numpy.array_equal(maze.get_maze(), test) is True
+    m = maze.get_maze()
+    assert m is not None
+    assert numpy.array_equal(m, test) is True
 
 
 def test_maze_str() -> None:

tests/test_MazeGenerator.py

@@ -1,5 +1,5 @@
 import numpy
-from amaz_lib.MazeGenerator import DepthFirstSearch, MazeGenerator
+from mazegen import DepthFirstSearch
 
 
 class TestMazeGenerator:
@@ -12,7 +12,3 @@ class TestMazeGenerator:
             maze = output
 
         assert maze.shape == w_h
-
-    def test_gen_broken(self) -> None:
-        test = MazeGenerator.gen_broken_set(50, 50)
-        assert len(test) > 0

tests/test_MazeSolver.py

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

tests/test_parsing.py

@@ -4,71 +4,71 @@ import pytest
 
 class TestParsing:
 
-    def test_get_data_valid(self):
+    def test_get_data_valid(self) -> None:
         data = DataMaze.get_file_data("tests/test_txt/config_1.txt")
         assert isinstance(data, str) is True
 
-    def test_file_error(self):
+    def test_file_error(self) -> None:
         with pytest.raises(FileNotFoundError):
             DataMaze.get_file_data("tete")
 
-    # def test_permission_error(self):
+    # def test_permission_error(self) -> None:
     #     with pytest.raises(PermissionError):
     #         DataMaze.get_file_data("tests/test_txt/error_1.txt")
 
-    def test_empty_file_error(self):
+    def test_empty_file_error(self) -> None:
         with pytest.raises(ValueError):
             DataMaze.get_file_data("tests/test_txt/error_6.txt")
 
-    def test_transform_data_valid(self):
+    def test_transform_data_valid(self) -> None:
         data = DataMaze.get_file_data("tests/test_txt/config_1.txt")
         data_2 = DataMaze.transform_data(data)
         assert isinstance(data_2, dict)
 
-    def test_transform__index_error(self):
+    def test_transform__index_error(self) -> None:
         with pytest.raises(IndexError):
             DataMaze.transform_data("asdasdasdasdasdasda\nasdasdas=asdasd")
 
-    def test_key_data_error(self):
+    def test_key_data_error(self) -> None:
         with pytest.raises(KeyError):
             data = DataMaze.get_file_data("tests/test_txt/error_8.txt")
             data2 = DataMaze.transform_data(data)
             DataMaze.verif_key_data(data2)
 
-    def test_key_data_error_2(self):
+    def test_key_data_error_2(self) -> None:
         with pytest.raises(KeyError):
             data = DataMaze.get_file_data("tests/test_txt/error_9.txt")
             data2 = DataMaze.transform_data(data)
             DataMaze.verif_key_data(data2)
 
-    def test_convert_int(self):
+    def test_convert_int(self) -> None:
         with pytest.raises(ValueError):
             data = DataMaze.get_file_data("tests/test_txt/error_2.txt")
             data2 = DataMaze.transform_data(data)
             DataMaze.convert_values(data2)
 
-    def test_tuple_error(self):
+    def test_tuple_error(self) -> None:
         with pytest.raises(ValueError):
             DataMaze.convert_tuple("0,3,5,5")
 
-    def test_tuple_error1(self):
+    def test_tuple_error1(self) -> None:
         with pytest.raises(AttributeError):
-            DataMaze.convert_tuple(None)
+            DataMaze.convert_tuple("None")
 
-    def test_bool_error(self):
+    def test_bool_error(self) -> None:
         with pytest.raises(ValueError):
             DataMaze.convert_bool("Trueeee")
 
-    def test_valid_tuple(self):
+    def test_valid_tuple(self) -> None:
         assert DataMaze.convert_tuple("7534564654, 78") == (7534564654, 78)
 
-    def test_valid_bool(self):
+    def test_valid_bool(self) -> None:
         assert DataMaze.convert_bool("False") is False
 
-    def test_valid_bool1(self):
+    def test_valid_bool1(self) -> None:
         assert DataMaze.convert_bool("True") is True
 
-    def test_data_maze(self):
+    def test_data_maze(self) -> None:
         data = DataMaze.get_data_maze("tests/test_txt/config_1.txt")
         assert data["WIDTH"] == 200
         assert data["HEIGHT"] == 100

uv.lock

@@ -6,36 +6,6 @@ resolution-markers = [
     "python_full_version < '3.11'",
 ]
 
-[[package]]
-name = "a-maze-ing"
-version = "0.1.0"
-source = { virtual = "." }
-dependencies = [
-    { name = "numpy", version = "2.2.6", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.11'" },
-    { name = "numpy", version = "2.4.3", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.11'" },
-    { name = "pydantic" },
-]
-
-[package.dev-dependencies]
-dev = [
-    { name = "flake8" },
-    { name = "mypy" },
-    { name = "pytest" },
-]
-
-[package.metadata]
-requires-dist = [
-    { name = "numpy", specifier = ">=2.2.6" },
-    { name = "pydantic", specifier = ">=2.12.5" },
-]
-
-[package.metadata.requires-dev]
-dev = [
-    { name = "flake8", specifier = ">=7.3.0" },
-    { name = "mypy", specifier = ">=1.19.1" },
-    { name = "pytest", specifier = ">=9.0.2" },
-]
-
 [[package]]
 name = "annotated-types"
 version = "0.7.0"
@@ -174,6 +144,36 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/b2/c8/d148e041732d631fc76036f8b30fae4e77b027a1e95b7a84bb522481a940/librt-0.8.1-cp314-cp314t-win_arm64.whl", hash = "sha256:bf512a71a23504ed08103a13c941f763db13fb11177beb3d9244c98c29fb4a61", size = 48755, upload-time = "2026-02-17T16:12:47.943Z" },
 ]
 
+[[package]]
+name = "mazegen"
+version = "0.1.0"
+source = { editable = "." }
+dependencies = [
+    { name = "numpy", version = "2.2.6", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.11'" },
+    { name = "numpy", version = "2.4.3", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.11'" },
+    { name = "pydantic" },
+]
+
+[package.dev-dependencies]
+dev = [
+    { name = "flake8" },
+    { name = "mypy" },
+    { name = "pytest" },
+]
+
+[package.metadata]
+requires-dist = [
+    { name = "numpy", specifier = ">=2.2.6" },
+    { name = "pydantic", specifier = ">=2.12.5" },
+]
+
+[package.metadata.requires-dev]
+dev = [
+    { name = "flake8", specifier = ">=7.3.0" },
+    { name = "mypy", specifier = ">=1.19.1" },
+    { name = "pytest", specifier = ">=9.0.2" },
+]
+
 [[package]]
 name = "mccabe"
 version = "0.7.0"