semvec/pypi-packages huggingface dataset:
mcglm 0.2.4
Multivariate Covariance Generalized Linear Models
Requires Python: >=3.9

### Multivariate Covariance Generalized Linear Models

https://pypi.org/project/mcglm/

The mcglm package brings to python language one of the most powerful extensions to GLMs(Nelder, Wedderburn; 1972), the Multivariate Covariance Generalized Linear Models(Bonat, Jørgensen; 2016).

The GLMs have consolidated as a unified statistical model for analyzing non-gaussian independent data throughout the years. Notwithstanding enhancements to Linear Regression Models(Gauss), some key assumptions, such as the independence of components in the response, each element of the target belonging to an exponential dispersion family maintains.

MCGLM aims to expand the GLMs by allowing fitting on a wide variety of inner-dependent datasets, such as spatial and longitudinal, and supplant the exponential dispersion family output by second-moment assumptions(Wedderburn; 1974)

https://jeancmaia.github.io/posts/tutorial-mcglm/tutorial_mcglm.html

-----

The mcglm python package follows the standard pattern of the statsmodels library and aims to be another API on the package. Therefore, Python machine learning practitioners will be very familiar with this new statistical model. 


To install this package, use 

```bash
pip install mcglm
```

Tutorial MCGLM instills on the library usage by a wide-variety of examples(https://jeancmaia.github.io/posts/tutorial-mcglm/tutorial_mcglm.html). The following code snippet shows the model fitting for a Gaussian regression analysis.

```python
modelresults = MCGLM(endog=y, exog=X).fit()

modelresults.summary()
```
aiconfig-extension-gemini 0.0.5
An extension for using Gemini with aiconfig
Requires Python: >=3.10

# Using Gemini with AIConfig

We are prioritizing the Python library Usage

1. Install `pip install aiconfig-extension-gemini`
2. Import the extension `import aiconfig_extension_gemini`

And you're all good to go! This extension automatically updates the model parser registry with the model "gemini-pro". Check out the Gemini Cookbook in the aiconfig repo for a full example.
youtube-livechat-scraper-ohn0 1.0.5
Livechat scraper for Youtube video streams
Requires Python: >=3.10

# youtube-livechat-scraper
A tool to scrape youtube livechat data I came up with while watching vtubers. It rips almost all data from a VOD's livechat including the following:
- Chat messages
- Superchats
- Memberships joined
- Memberships gifted and received
- Purchased Stickers

All of the data can be wrapped up in a large raw JSON object that also contains lots of metadata from the responses, like the author, the time the message got sent, etc.

## USAGE:

Requires the following python3 packages:
  - NOTE: These packages will be installed via pip when installing the scraper.
  - BeautifulSoup
  - Requests

How to use:
  - Import the LiveChatScraper from scrapers.liveChatScraper to wherever you want to make the scraping call.
  - Find a VOD URL and copy it
  - Create a LiveChatScraper object and pass in the VOD's URL.
  - Call the scrape() method on the created scraper object and the scrape will run.
  - Once the scrape is completed, you can call ouputMessages() to get a dictionary with all the scraped data.
  - You can all save the scraped data as a JSON to a fill by calling the writeToFile method passing the OUTPUT_JSON constant

* example.py has a working example which saves the data to different formats
py-jutil 0.0.3
JUtil is a collection of useful functions, values, and classes for Python.


# JUtil

## Description:
JUtil is a collection of useful functions, values, and classes for Python.

## Dependencies:
- None yet

## Note:
- This module is a work in progress.

## Recent Changes:
- Added `jutil.styling`, for styling text in the console.
- Added `jutil.inp`, for quick and easy input functions.
- Added `jutil.logs`, for quick and easy logging functions.


___
v0.0.3, developed by Noah Wilhoite
Last updated: Dec 21th, 2023