semvec/pypi-packages huggingface dataset:
imgload 0.2.1
An image downloading library
Requires Python: >=3.7

# imgload
[![Build Status](https://travis-ci.org/frenos/imgload.svg?branch=master)](https://travis-ci.org/frenos/imgload)  [![Maintainability](https://api.codeclimate.com/v1/badges/d86a6992bc47e8e90d6f/maintainability)](https://codeclimate.com/github/frenos/imgload/maintainability)  [![Test Coverage](https://api.codeclimate.com/v1/badges/d86a6992bc47e8e90d6f/test_coverage)](https://codeclimate.com/github/frenos/imgload/test_coverage)  ![GitHub code size in bytes](https://img.shields.io/github/languages/code-size/frenos/imgload.svg)  ![GitHub](https://img.shields.io/github/license/frenos/imgload.svg) [![PyPI - Downloads](https://img.shields.io/pypi/dm/imgload)](https://pypi.org/project/imgload/)
---
**imgload** is a python library to download images from several different hosters.
It's an ideal companion for writing web-crawlers, just feed the urls to imgload and get the raw bytes or a finished PIL 'Image' back.

---
## Supported Hosters:
Currently the following image hosters are supported.
* http://imgur.com/
* http://www.imagevenue.com/
* https://fastpic.ru/
* http://www.imagebam.com/

Further planned hosts:
* https://www.turboimagehost.com/

If you know other hosts that should be supported, create an Issue with a test file or send a pull request.
model-arena 0.0.4
A model extension package

# Models Package

1- Ridge Regression: Extends SKLearns Ridge regression by adding p-values, featureSelection and alpha optimisation.

## Example Usage:

### Import
from model_arena.Regression import RidgeRegression

### Create a RidgeRegression object
rm = RidgeRegression()

### Run the feature selection method as above to limit to the most important variables. 
### Stores the order of variables to the object
rm.featureSelection(X,y)

### Find the value of alpha minimising MSE for these features
rm.findBestAlpha(X[rm.bestMeanCVModel],y)

### Print the alpha
print('Alpha = {}'.format(rm.alpha))

### Fit the model with the best features and the alpha
rm.fit(X[rm.bestMeanCVModel],y)

### Display a summary including p-values
rm.summary(X[rm.bestMeanCVModel],y)


## To Update PYPI

1- Clone from github

2- Make Changes

3- Update version number in setup.py

4- CD into the setup.py directory

5- Run the following in the CMD:
python3 -m pip install --user --upgrade setuptools wheel
python3 setup.py sdist bdist_wheel
or
python -m pip install --user --upgrade setuptools wheel
python setup.py sdist bdist_wheel

6- Then the following in the CMD:
python3 -m pip install --user --upgrade twine
python3 -m twine upload dist/*
or
python -m pip install --user --upgrade twine
python -m twine upload dist/*

7- Test by pip install and importing