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https://github.com/thomasthaddeus/algorithmselector
Explore our extensive Algorithms Repository, featuring a diverse range of algorithms from computational methods to data structures, cryptographic techniques, and AI. Ideal for education, research, and practical application, each algorithm is well-documented, tested, and optimized for performance and readability.
https://github.com/thomasthaddeus/algorithmselector
ai algorithms computational-algorithms computer-science cryptography data-compression data-structures educational-resource game-theory graph-theory machine-learning network-flow open-source optimization python
Last synced: 2 months ago
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Explore our extensive Algorithms Repository, featuring a diverse range of algorithms from computational methods to data structures, cryptographic techniques, and AI. Ideal for education, research, and practical application, each algorithm is well-documented, tested, and optimized for performance and readability.
- Host: GitHub
- URL: https://github.com/thomasthaddeus/algorithmselector
- Owner: thomasthaddeus
- License: mit
- Created: 2023-12-24T19:43:55.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2024-06-19T06:19:08.000Z (7 months ago)
- Last Synced: 2024-10-20T05:39:30.194Z (2 months ago)
- Topics: ai, algorithms, computational-algorithms, computer-science, cryptography, data-compression, data-structures, educational-resource, game-theory, graph-theory, machine-learning, network-flow, open-source, optimization, python
- Language: Python
- Homepage:
- Size: 141 KB
- Stars: 2
- Watchers: 2
- Forks: 0
- Open Issues: 4
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Algorithm Selector
[![Publish to PyPI][shield1]](https://github.com/thomasthaddeus/AlgorithmSelector/actions/workflows/workflow.yml) [![PyPI][shield2]](https://pypi.org/project/AlgorithmSelector/) ![License][shield3] ![Python Version][shield4] ![Code Size][shield5] ![Last Commit][shield6] ![Issues][shield7] ![Pull Requests][shield8] ![Build Status][shield10] ![Coverage][shield9]
## Overview
This repository contains a comprehensive collection of algorithms across various domains including computational algorithms, data structures, machine learning, cryptographic methods, and more. Each algorithm is implemented with a focus on clarity, efficiency, and adherence to best practices.
## Table of Contents
- [Algorithm Repository](#algorithm-repository)
- [Overview](#overview)
- [Table of Contents](#table-of-contents)
- [Installation](#installation)
- [Usage](#usage)
- [Directory Structure](#directory-structure)
- [Testing](#testing)
- [Contributing](#contributing)
- [License](#license)
## Installation
To get started with this repository, clone it to your local machine using:
```bash
git clone https://github.com/thomasthaddeus/AlgorithmSelector.git
cd algorithm-repository
```
Install the required dependencies:
```bash
pip install -r requirements.txt
```
## Usage
Each algorithm is encapsulated in its own class and can be used independently. Here's an example of how to use an algorithm from the repository:
```python
from src.data_structures.binary_search_tree import BinarySearchTree
# Example usage
bst = BinarySearchTree()
bst.insert(3)
bst.insert(1)
bst.insert(4)
print(bst.search(1)) # Output: True or False
```
## Directory Structure
The repository is organized as follows:
- `src/`: Contains the source code for all algorithms.
- `computational/`: Computational algorithms like FFT, Monte Carlo, etc.
- `data_structures/`: Common data structures like AVL Tree, Heap, etc.
- `ml/`: Machine learning algorithms like k-means, linear regression, etc.
- `...` (other directories following a similar structure)
- `tests/`: Contains unit tests for each algorithm.
- `docs/`: Documentation related to the algorithms.
- `scripts/`: Useful scripts like setup or build scripts.
- `requirements.txt`: List of dependencies for the project.
- `pyproject.toml`: Project metadata and configuration.
## Testing
To run the tests, navigate to the root directory of the project and run:
```bash
python -m unittest discover -s tests
```
## Contributing
Contributions to the repository are welcome! Here's how you can contribute:
1. Fork the repository and create your branch from `main`.
2. Write your algorithm or improvement.
3. Ensure your code passes all existing tests and add new tests if necessary.
4. Submit a pull request.
Please ensure your code adheres to the existing style conventions and add relevant documentation.
## License
This project is licensed under the [MIT License](LICENSE).
[shield1]: "Publish to PyPi Status Shield"
[shield2]: "Version of package on PyPI"
[shield3]: "LICENSE Type"
[shield4]: "Python versions supported"
[shield5]: "Size of the package on PyPI"
[shield6]: "Time of last commit to the repository"
[shield7]: "Open issues"
[shield8]: "Open pull requests"
[shield9]: "Codecov status"
[shield10]: "TravisCI status"