semvec/pypi-packages huggingface dataset:
hololive 0.1.4
Gets hololive streams
Requires Python: >=3.6

# hololive-python-api

Gets stream info from holodex(no longer limited to only hololive)
## Installation
```bash
pip install hololive
```

## Usage

```python
from hololive import hololive
streams = await hololive.get_live(limit=5)

for stream in streams:
  print(stream.title)
# -----------------
# 【APEX】カスタム3日目【#あの伝WIN】
# 【APEX】 casual & arena rank?
# 【APEX】V最協決定戦カスタム4 #KGSWIN 【ぶいすぽ / 花芽すみれ】
# 【APEX】最協カスタム4日目→ソロランク修行【ふぇありす/弦月藤士郎/パカエル】
# 【Portal 2】 😈마왕적 포탈! 👾 魔王的ポータル😈 【NIJISANJI KR】
  ```
image-fabio 0.0.4
Pacote para tratar imagens
Requires Python: >=3.0

# package_name

Description. 
The package image_fabio is used to:
	Processing:
		- Histogram matching
		- Structural similarity
		- Resize image
	Utils:
		- Read image
		- Save image
		- Plot image
		- Plot result
		- Plot histogram

## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install package_name

```bash
pip install image_fabio
```

## Changes

0.0.1 first commit
0.0.2 to correct error on io.py
0.0.3 to correct error on tranformation.py
0.0.4 to correct tranformation.py to transformation.py

## Author
Fabio_Tolentino

## License
[MIT](https://choosealicense.com/licenses/mit/)
flaremodel 1.0.3
A simple one zone code that can do many different flavours of flares

# flaremodel

## Overview

*flaremodel* is a `Python` package designed for one-zone modeling of astrophysical synchrotron sources.

The code aims to provide modular interface for the modeling of synchrotron sources with efficient low level utility functions written in `C` - the `cfuncs` module.
These functions constitute the core of the *flaremodel*. The `Python` interface is built on top of these functions for convenience and guidance to formulate new models.
Multithreading support is implemented with `OpenMP` at a lower level in the `cfuncs` module where it is found useful.
At the same time, these low level functions bypass the infamous *Global Interpreter Lock (GIL)* of `Python`.
In simple words, users can implement efficient high level `multithreading` on python side when low level C functions are used and avoid the costly overheads of `multiprocessing`.  

Our [documentation](https://ydallilar.github.io/flaremodel/) covers the installation, module references and examples.

The documentation mostly covers the usage of the code. The detailed methodology/physics are covered in our [paper](https://arxiv.org/abs/2111.15273). 
The examples introduced in the paper are provided as jupyter notebooks in `notebooks/` directory of the tarball and can also serve as a test of the compiled code.

Please cite the paper when the code is used in academical studies. Note that the paper refers to [our first stable release](https://github.com/ydallilar/flaremodel/releases/tag/v1.0.0).