semvec/pypi-packages huggingface dataset:
esnapshot 0.0.1
Esnapshot let's you capture esnapshot of websites
Keywords: python,esnapshot,captures,sources

Esnapshot take snapshot of target provided to it . You can pass a single web address or a file
containing multiple web address to take screenshot for.

Installation :

              pip install esnapshot 

Usage :

              from esnapshot import click

For single web address :

              from esnapshot import click

              click.singleurl( <web addr> <path for geckodriver>)

For multiple web address :

              from esnapshot import click

              click.multipleurl( <file containing multiple web addr> < path for geckodriver> )

For geckodriver :

Link :  https://github.com/mozilla/geckodriver/releases
creditprice 0.0.8
Credit price tool

#Introduction
This package is used to create a suitable plan of credit price for 
different borrowers.As historical borrowers'
credit score and loan interests are given, you can train a credit price model 
through this package, and this model will allow you to calculate a different, recommended
loan interest for any borrower only based on his or her credit score.

---
#Example:
```
import creditprice as cp
#生成数据
import numpy as np
import pandas as pd
np.random.seed(123)
score = 650 + 100 * np.random.randn(1000)
price = 0.2 + 0.1 * np.random.randn(1000)
flag = np.random.randint(2, size=1000)
flagy = np.random.binomial(1, 0.2, size=flag[flag == 1].shape[0])
data = pd.DataFrame(columns=['score', 'r', 'accept', 'flagy'])
data['score'] = score
data['r'] = price
data['accept'] = flag
data.loc[data.accept == 1, 'flagy'] = flagy
#生成模型
cl = cp.calc(ld=0.5, d = 1, rl = 0.05, rf = 0.04, score='score', interest='r', flag='accept', y = 'flagy')
#计算利率表
r_table = cl.calc_r_table(data = data)
#根据data计算单利率
r = cl.calc_r(p=0.2, data=data)
```