# natureAlgo: Nature-Inspired Optimization Library

natureAlgo is a Python library for nature-inspired optimization algorithms. It provides implementations of optimization algorithms inspired by the behavior of natural systems, such as bees. It was created as a demo library to understand how to publish libraries to pypi.

## Features

- Implementation of the Artificial Bee Colony (ABC) algorithm.
- Easily extendable for adding more nature-inspired optimization algorithms.

## Installation

You can install natureAlgo via pip:

```bash
pip install natureAlgo
```

## Usage

```Python
import pandas as pd
import numpy as np
from natureAlgo import bee_colony

# Create a sample DataFrame for optimization
data = pd.DataFrame(np.random.rand(10, 2), columns=['Feature1', 'Feature2'])

# Define the objective function
def objective_function(x):
    return sum([x_i ** 2 for x_i in x])

# Initialize the ABC algorithm
abc = bee_colony.ArtificialBeeColony(data, objective_function, max_iterations=100, num_employed=10, num_onlookers=10)

# Run the ABC algorithm
abc.run()

# Get the best solution and its fitness
best_solution = abc.best_solution
best_fitness = abc.best_fitness

print("Best solution:", best_solution)
print("Best fitness:", best_fitness)
```

## Contributing
Contributions are welcome! If you have ideas for new features, improvements, or bug fixes, feel free to open an issue or submit a pull request.

## License
This project is licensed under the MIT License - see the LICENSE file for details.

## Credits
The ABC algorithm implementation and README.md template were provided by OpenAI's ChatGPT.