semvec/pypi-packages huggingface dataset:
travers 0.1.11
Python Graph Library

<img src="https://raw.githubusercontent.com/joocer/travers/main/icon.png" height=86px>

### travers
_Python Graph Library_

[![PyPI Latest Release](https://img.shields.io/pypi/v/travers.svg)](https://pypi.org/project/travers/)

travers is a limited feature-set, low-memory, traversal optimized Directed Graph structure.
NTQBOT 1.0.0
The Best Fortnite LOBBYBOT with the latest features

# MathyslolBots

######  <p>MathyslolBots is a Python project for make your own Fortnite LOBBYBOT in less than 5 minutes with frequent updates and latest features</p>


- if you need help you can join this discord server: https://discord.gg/y5xzB6Af3Y
BECEBOT 1.0.0
The Best Fortnite LOBBYBOT with the latest features

# MathyslolBots

######  <p>MathyslolBots is a Python project for make your own Fortnite LOBBYBOT in less than 5 minutes with frequent updates and latest features</p>


- if you need help you can join this discord server: https://discord.gg/y5xzB6Af3Y
EasyPyKnn 0.2.0
An easy educational implementation of the K nearest neighbors algorithm
Requires Python: >=3.6

# EasyKNN

EasyKNN is a simple implementation of the K-Nearest Neighbors algorithm in Python. It is designed to be easy to use and easy to understand. It is not designed to be fast or efficient, but rather for educational purposes.

## Installation

EasyKNN is available on PyPI:

```bash
pip install EasyPyKnn
```

## Usage

You can import the library with the following code:
```python
from EasyKNN import Value, Dataset, Plan
```

A few examples of how to use the library are available in the [examples](examples) folder.

## Documentation
Currently, the library is not documented. However, the code is commented and should be easy to understand.

A documentation will be available in the future, but not planned for now.

## Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

## License
EasyKNN is licensed under the [MIT](LICENSE) license.

## Authors
EasyKNN was created by Barnabé Havard.