6 Commits

Author SHA1 Message Date
da7e b54e49122c README 2026-04-02 14:15:40 +02:00
maoake 53316f4e32 need to be merge 2026-04-02 12:36:10 +02:00
maoake 732cf25a57 trying a README 2026-04-01 23:20:11 +02:00
maoake 4c1955ace4 changing the import for mypy test 2026-04-01 23:00:08 +02:00
maoake 3e85cbe919 doing again the wheel 2026-04-01 22:41:11 +02:00
maoake 2edf61affa doing the wheel 2026-04-01 22:31:08 +02:00
19 changed files with 689 additions and 70 deletions
+7 -3
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@@ -16,20 +16,24 @@ debug:
uv pdb python3 a_maze_ing.py config.txt uv pdb python3 a_maze_ing.py config.txt
clean: clean:
rm -rf */**/__pycache__ __pycache__ .mypy_cache .venv dist build */**/*.egg-info *.egg-info test.txt rm -rf */**/__pycache__ */__pycache__ __pycache__ .mypy_cache .venv dist build */**/*.egg-info */*.egg-info *.egg-info test.txt
fclean: clean fclean: clean
rm mazegen-1.0.0-py3-none-any.whl rm mazegen-1.0.0-py3-none-any.whl
lint: lint:
uv run flake8 . --exclude=.venv uv run flake8 . --exclude=.venv
uv run env PYTHONPATH=src python3 -m mypy --warn-return-any --warn-unused-ignores --ignore-missing-imports --disallow-untyped-defs --check-untyped-defs src 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 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 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: lint-strict:
uv run flake8 . --exclude=.venv uv run flake8 . --exclude=.venv
uv run env PYTHONPATH=src python3 -m mypy --strict src 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 tests
uv run env PYTHONPATH=src python3 -m mypy --strict a_maze_ing.py uv run env PYTHONPATH=src python3 -m mypy --strict a_maze_ing.py
+614 -2
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@@ -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.
+3 -3
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@@ -1,7 +1,7 @@
from typing import Any from typing import Any
from numpy.typing import NDArray from numpy.typing import NDArray
from src.AMazeIng import AMazeIng from AMazeIng import AMazeIng
from src.parsing.Parsing import DataMaze as Parsing from parsing.Parsing import DataMaze as Parsing
from mlx import Mlx from mlx import Mlx
import time import time
@@ -474,7 +474,7 @@ class MazeMLX:
self.mlx.mlx_loop_hook(self.mlx_ptr, self.draw_image, amazing) 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, 33, 0, self.close_loop, None)
self.mlx.mlx_hook( 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) self.mlx.mlx_loop(self.mlx_ptr)
+5 -2
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@@ -1,5 +1,5 @@
[project] [project]
name = "A-Maze-ing" name = "mazegen"
version = "0.1.0" version = "0.1.0"
description = "This is the way" description = "This is the way"
readme = "README.md" readme = "README.md"
@@ -30,5 +30,8 @@ requires = ["setuptools>=78.1.0", "wheel>=0.45.1"]
build-backend = "setuptools.build_meta" build-backend = "setuptools.build_meta"
[tool.setuptools] [tool.setuptools]
package-dir = {"" = "src/amaz_lib"} package-dir = {"" = "src"}
[tool.setuptools.packages.find]
where = ["src"]
+1 -1
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@@ -2,7 +2,7 @@ from typing import Generator
from typing_extensions import Self from typing_extensions import Self
from pydantic import BaseModel, Field, model_validator, ConfigDict from pydantic import BaseModel, Field, model_validator, ConfigDict
from .amaz_lib import Maze, MazeGenerator, MazeSolver from mazegen import Maze, MazeGenerator, MazeSolver
class AMazeIng(BaseModel): class AMazeIng(BaseModel):
-18
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@@ -1,18 +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",
]
@@ -2,7 +2,7 @@ from abc import ABC, abstractmethod
from typing import Generator, Any from typing import Generator, Any
import numpy as np import numpy as np
from numpy.typing import NDArray from numpy.typing import NDArray
from .Cell import Cell from mazegen.Cell import Cell
import math import math
import random import random
+18
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@@ -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",
]
+2 -2
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@@ -1,5 +1,5 @@
from ..amaz_lib import DepthFirstSearch, Kruskal from mazegen import DepthFirstSearch, Kruskal
from ..amaz_lib import AStar, DepthFirstSearchSolver from mazegen import AStar, DepthFirstSearchSolver
from typing import Any from typing import Any
+1 -1
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@@ -1,4 +1,4 @@
from amaz_lib.Cell import Cell from mazegen import Cell
def test_cell_setter_getter() -> None: def test_cell_setter_getter() -> None:
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@@ -1,5 +1,5 @@
from amaz_lib.MazeGenerator import DepthFirstSearch from mazegen import DepthFirstSearch
from amaz_lib.Cell import Cell from mazegen import Cell
import numpy as np import numpy as np
+2 -2
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@@ -1,6 +1,6 @@
import numpy import numpy
from amaz_lib.Cell import Cell from mazegen import Cell
from amaz_lib.Maze import Maze from mazegen import Maze
def test_maze_setter_getter() -> None: def test_maze_setter_getter() -> None:
+1 -1
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@@ -1,5 +1,5 @@
import numpy import numpy
from amaz_lib.MazeGenerator import DepthFirstSearch from mazegen import DepthFirstSearch
class TestMazeGenerator: class TestMazeGenerator:
+2 -2
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@@ -1,6 +1,6 @@
from amaz_lib.Cell import Cell from mazegen import Cell
import numpy as np import numpy as np
from amaz_lib import AStar, Maze from mazegen import AStar, Maze
def test_solver() -> None: def test_solver() -> None:
Generated
+30 -30
View File
@@ -6,36 +6,6 @@ resolution-markers = [
"python_full_version < '3.11'", "python_full_version < '3.11'",
] ]
[[package]]
name = "a-maze-ing"
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]] [[package]]
name = "annotated-types" name = "annotated-types"
version = "0.7.0" 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" }, { 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]] [[package]]
name = "mccabe" name = "mccabe"
version = "0.7.0" version = "0.7.0"