Metadata-Version: 2.1
Name: natureAlgo
Version: 0.1.0
Summary: Nature Based Algorithm Library
Home-page: https://natureAlgo.readthedocs.io/
Author: OpenAI's ChatGPT, Shirish Kumar
Author-email: shirishk222@gmail.com
License: MIT
Platform: UNKNOWN
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
License-File: LICENSE

# 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.

