semvec/pypi-packages huggingface dataset:
prettypo 0.0.5
Pretty Page Object Generator
Requires Python: >=3.4

# Pretty Page Object Generator
A simple tool to make your page objects pretty and save some time for standard methods implementation.
```python
class BasePage(PrettyPageObject):
    def __init__(self, driver):
        super(BasePage, self).__init__(driver)
        self.button('ok', By.ID, 'ok')
        self.text_field('login', By.XPATH, '//login')
        self.label('welcome_message', locator='welcome_message')
        self.elements('custom_parameters', locator='locator')
        self.element('parent', locator='xxx')
        self.button('button_that_difficult_to_find', By.XPATH, '/a', parent_getter=self.parent_element)

def test_page(driver):
    page = BasePage(driver)
    page.login = 'SuperUser'
    page.ok()
    wait_for_element(page.welcome_message_element())
    assert page.welcome_message == "Welcom SuperUser"
```


## Usage
Just inherit your Base Page class from PrettyPageObject and that's all!

## Features
Prettypo generates several methods for the requested element depending on the type of the element

* self.button('name', by, locator, parent_getter) will generate next methods:
  * **name**() - to call click()
  * **name_element**() - to get full access to WebElement object
* self.text_field('name', by, locator, parent_getter)
  * **name** property to get element's _.text()_
  * **name**=string - setter is reassigned to _.send_keys(string)_
  * **name_element**() - to get full access to WebElement object
* self.elements('name', by, locator, parent_getter)
  * **name_elements**() - get list of WebElement objects
* self.label('name', by, locator, parent_getter)
  * **name** property to get element's _.text()_
  * **name_element**() - to get full access to WebElement object
caireCovid 0.1.8
system for covid-19.
Requires Python: >=3.6

# caireCovid system
<img src="img/tensorflow.png" width="12%"> [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

<img align="right" src="img/HKUST.jpg" width="15%">
Kaggle system for covid 19

## requirements
<pre>
tensorflow(-gpu)==1.13.1
</pre>

## Install
You can use our package by install with ```pip```
```
pip install caireCovid
```
## Question Answering System
In this system, we build QA modules by a ensemble of two QA models, which are [BioBERT](https://github.com/dmis-lab/bioasq-biobert) model which fine-tuned on SQuAD, and MRQA model which is our submission to MRQA@EMNLP 2019. 

The MRQA model and the exported BioBERT model that are utilized in this project can bo downloaded by this [link](https://drive.google.com/drive/folders/1yjzYN_KCz8uLobqaUddftBGPAZ6uSDDj?usp=sharing).

If you want to use our MRQA model in your work, please cite the following paper. The bibtex is listed below:
<pre>
@inproceedings{su2019generalizing,
  title={Generalizing Question Answering System with Pre-trained Language Model Fine-tuning},
  author={Su, Dan and Xu, Yan and Winata, Genta Indra and Xu, Peng and Kim, Hyeondey and Liu, Zihan and Fung, Pascale},
  booktitle={Proceedings of the 2nd Workshop on Machine Reading for Question Answering},
  pages={203--211},
  year={2019}
}
</pre>