semvec/pypi-packages huggingface dataset:
you-are-gay 0.2.0
A package that displays a name with 'IS GAY' in a fancy way in the terminal
Requires Python: >=3.6

# You Are Gay

A fun Python package that displays any name with "IS GAY" in a colorful, animated way in your terminal.

## Installation

```bash
pip install you-are-gay
```

## Usage

Simply run with a name:

```bash
you-are-gay John
```

Or run without a name to get the default "YOU IS GAY":

```bash
you-are-gay
```

Multiple words work too:

```bash
you-are-gay "John Smith"
# or
you-are-gay John Smith
```

You can also use it in your Python code:

```python
from fancy_text import display_text

# Display with your custom message
display_text("JOHN IS GAY")

# Use the underlying animation function directly
from fancy_text import animate_text
animate_text("ANY TEXT YOU WANT")
```

## Features

- Colorful, animated terminal display
- Gradient text effects
- Sparkle animations
- Auto-sizing to fit your terminal
- Large ASCII art characters

## Requirements

- Python 3.6+
- Works on Linux, macOS, and Windows

## License

MIT
energyStats 0.1
A python statistical library for energy statistics methods.
Requires Python: >=3.7

# Estats
Estats is a python statistical package containing a set of method based upon energy statistics.

Energy statistics are a set of distribition-free non-parametrics methods first expounded by GÃ¡bor J. SzÃ©kely and later on expanded by several others. They are of particular interest because they very little about the data generating distribution, merely that either its first or second moment is defined.

As well as being non-parametrc, energy statistics are valuable because its methods take no notice of the size of the data matrix $X$, since all its methods are functions of the distance matrix of $X$ not of $X$ itself, therefore there is no trouble in analysing multi-dimensional data.
py-estats 0.1
A python statistical library for energy statistics methods.
Requires Python: >=3.7

# Estats
Estats is a python statistical package containing a set of method based upon energy statistics.

Energy statistics are a set of distribition-free non-parametrics methods first expounded by GÃ¡bor J. SzÃ©kely and later on expanded by several others. They are of particular interest because they very little about the data generating distribution, merely that either its first or second moment is defined.

As well as being non-parametrc, energy statistics are valuable because its methods take no notice of the size of the data matrix $X$, since all its methods are functions of the distance matrix of $X$ not of $X$ itself, therefore there is no trouble in analysing multi-dimensional data