stara-cpp 0.1.2

A* pathfinding algorithm implementation in C++

Stara C++

A C++ implementation of the A* pathfinding algorithm with Python bindings using pybind11.

Installation

pip install stara-cpp

Requirements

• Python 3.12 or higher
• CMake 3.15 or higher
• C++17 compatible compiler
• Poetry (for Python dependency management)
• numpy

Development

1. Clone the repository:

git clone https://github.com/valerius21/stara-cpp.git
cd stara-cpp

2. Create and activate a Poetry environment:

poetry install
poetry shell

3. Build and install the package:

pip install -e .

Usage

Python

import numpy as np
from stara_cpp import load_maze, AStar

# Create a maze (0 = wall, ≥1 = passage)
maze = np.array([
    [1, 0, 1, 1, 1],
    [1, 1, 1, 0, 1],
    [0, 0, 1, 0, 1],
    [1, 1, 1, 0, 1],
    [1, 0, 1, 1, 1],
], dtype=np.int32)

# Load maze and create pathfinder
maze_ptr = load_maze(maze)
pathfinder = AStar(maze_ptr)

# Find path from (0,0) to (4,4)
start = (0, 0)
goal = (4, 4)

try:
    path = pathfinder.find_path(start, goal)
    if path is not None:
        print("Path found:", path)
    else:
        print("No path found!")
except RuntimeError as e:
    print("Error:", str(e))

API Reference

Python API

load_maze(array: np.ndarray) -> Maze

Loads a numpy array into a C++ Maze object.

• array: 2D numpy array where 0 represents walls and ≥1 represents passages
• Returns: Maze object

class AStar

A* pathfinding implementation.

Methods:

• __init__(maze: Maze): Initialize with a maze
• find_path(start: Tuple[int, int], goal: Tuple[int, int]) -> Optional[List[Tuple[int, int]]]: Find path from start to goal
• manhattan_distance(pos1: Tuple[int, int], pos2: Tuple[int, int]) -> int: Calculate Manhattan distance

C++ API

class Maze

Represents the maze grid.

Methods:

• isValid(int x, int y) -> bool: Check if coordinates are within bounds
• isWalkable(int x, int y) -> bool: Check if position is walkable
• getCellNeighbours(int x, int y) -> vector<tuple<int, int, int>>: Get neighboring cells

class AStar

A* pathfinding implementation.

Methods:

• findPath(pair<int, int> start, pair<int, int> goal) -> optional<vector<pair<int, int>>>: Find path
• manhattanDistance(pair<int, int> pos1, pair<int, int> pos2) -> int: Calculate heuristic

Development

Building from Source

1. Install development dependencies:

poetry install

2. Build in development mode:

poetry shell
pip install -e .

Running Tests

Run the example script:

python example.py