semvec/pypi-packages huggingface dataset:
python-saber 0.1.1
A Beat Saber framework written in Python.
Requires Python: >=3.9

# PySaber
A Beat Saber framework written in Python.

## Features
### Compression
Significantly reduce your wall/geo count without losing quality when generating text!
### TTF Font Support
Load TTF files to use any font you want. Arial? Comic Sans? Ghostly Panic? If it's a TTF file, it should work!
### Customizable Text Generation
Generate text with customizable parameters including color, position, scale, depth, and track.
### Geometric Text Generation
Generate text using Chroma Geometry with customizable materials and shaders.
### Difficulty Management
Easily manage and modify beatmaps using the `Beatmap` and `Difficulty` classes.
### Multi-Language Support
Generate text in multiple languages with Unicode support.
### Custom Data Modification & Preservation
PySaber preserves your CustomData, and allows modification.

## Installation
To install PySaber, use pip:

```sh
pip install python-saber
```

Alternatively, you can install PySaber by cloning the repository and using `setup.py`:

```sh
git clone https://github.com/CodeSoftGit/pysaber.git
cd pysaber
python setup.py install
```
Passenger-flow-OD-chart-RunningTrainsPlot 2024.0.5
An open-source library for visualizing transportation data
Requires Python: >=3.8

# Example Package

Given this background and current research and development status, we believe that it is necessary to develop an open-source library for visualizing data in rail transit organization, covering the vast majority of operational data visualization functions in the field of rail transit organization. This will further address the growing volume of transportation data and information, improve transportation research efficiency, and meet standardization requirements This open-source library will not only provide data based drawing functions for rail transit researchers, but also provide more comprehensive and convenient scheduling and planning visualization support for railway industry practitioners based on the needs and application scenarios of the rail transit transportation sector, promoting the digital transformation and innovative development of the rail transit fieldYou can use
[GitHub-flavored Markdown](https://guides.github.com/features/mastering-markdown/)
to write your content.