semvec/pypi-packages huggingface dataset:
flask-error-templating 1.1.1
Create Flask HTTP error handlers that use template rendering.
Requires Python: >=3.7

# flask-error-templating

Create Flask HTTP error handlers that use template rendering. This is a very small and simple idea but I couldn't find anything like it so I made it myself.

## Installation

Install with `pip install flask-error-templating`.

## Usage

```python
create_http_error_handlers(app, error_pages, page_template_file, **kwargs)
```

#### Parameters

###### app
`app` is a handle to your `Flask` object. Need I write more?

###### error_pages

`error_pages` is a list of `ErrorPage` objects. It accepts three arguments: `error_code`, `message` and `long_message`. `error_code` and `message` are required; `long_message` is optional and if it is not present then it will not be rendered into the template. Note that it's possible to have some `ErrorPage` objects with `long_message` set and others without.

Example of `error_pages`:
```python
error_pages = [
    ErrorPage(400, 'Bad request'),
    ErrorPage(400, 'Access is denied to this page.'),
    ErrorPage(403, 'You are forbidden to view this page.',
        'A very long message that we also want to display in the long_message field'),
    ErrorPage(404, 'The page you are looking for does not exist'),
    ErrorPage(418, 'I\'m a teapot!')
]
```

###### page_template_file

`page_template_file` is the filename of a HTML file in your projects `templates` folder. Parameters supplied to the file for template rendering are `error_code`, `message` and `long_message`. See the above paragraph for information on these parameters. If `long_message` is not present then an empty string will be rendered in its place - this allows the same template to serve pages with long message and also without.

Example of `page_template_file`:
```html
<!DOCTYPE html>
<html>
    <body>
        <h1>{{ error_code }}</h1>
        <h2>{{ message }}</h2>
        <br>
        <p>{{ long_message }}</p>
    </body>
</html>
```

###### keyword arguments

Often, you will want to pass things like the name of your app to the template when it is being rendered. To allow passing this value, all keyword arguments after `page_template_file` will be passed to Flask's `render_template()` function.

#### Complete basic example:
```python
from flask import *
from flask_error_templating import ErrorPage, create_http_error_handlers

app = Flask(__name__)

@app.route('/')
def homepage():
    return '<h1>Homepage</h1>'

error_pages = [
    ErrorPage(400, 'Bad request'),
    ErrorPage(400, 'Access is denied to this page.'),
    ErrorPage(403, 'You are forbidden to view this page.',
        'A very long message that we also want to display in the long_message field'),
    ErrorPage(404, 'The page you are looking for does not exist'),
    ErrorPage(418, 'I\'m a teapot!')
]
create_http_error_handlers(app, error_pages, 'http_error.html', app_name='Some testing app')

if __name__ == '__main__':
    app.run()
```
webplucker 0.0.8
webplucker Is A Fast And Handy Package For Web Scraping
Requires Python: >=3.1

# WebPlucker
<p align="center">
<img title="WebPlucker"  alt="WebPlucker" src="https://raw.githubusercontent.com/shivjeetbhullar/webplucker/main/ic_launcher.png"> 
</p>
WebPlucker is a handy and fast python package for website scraping. It also supports javascript rendering in HTML pages.
Websites built in react, angular, etc is also possible to scrape using webplucker.
pytorch-aman 1.0.10
A wrapper of pytorch and utils to facilitate ml.
Requires Python: ~=3.7

# Aman

A wrapper of PyTorch, especially for cv tasks. Inspired by PyTorch Lightning, Aman provides an elegant way to organize machine learning code. PyTorch is an excellent deep learning framework, but insufficient for the high-level wrapper. PyTorch Lightning does great works on it, if you want to seek a more universal framework for PyTorch wrapper, please go to PyTorch Lightning. Aman is a sampler but more personal library which contains some custom functions fitting our CV requirements.

[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/pytorch-aman)](https://pypi.org/project/pytorch-aman/) [![PyPI Status](https://badge.fury.io/py/pytorch-aman.svg)](https://badge.fury.io/py/pytorch-aman) [![license](https://img.shields.io/badge/License-GPLv3-blue.svg)](https://github.com/daijian217/Aman/blob/main/LICENSE)

## Install
- Install through pypi
```
pip install pytorch-aman
```
- Install through source code
```
python setup.py sdist
pip install dist/pytorch_aman-x.x.x.tar.gz
```
## Key features of Aman
- Powerful context management for training.
- More organizable coding style.
- Balanced weighed and grid sampler(**python 3.9 is required**).
- Useful API for medical image segmentation.
- Visualization log assembling.

## [Quick Start](https://github.com/daijian217/Aman/wiki/How-to-use)
A simple demo is available [here](https://colab.research.google.com/drive/1mouwdctoMYHIvE0vF1DNEbAhFWWCTag9?usp=sharing).
#### [Define your dataset](https://github.com/daijian217/Aman/wiki/How-to-use#1-define-your-dataset)
#### [Define your training process](https://github.com/daijian217/Aman/wiki/How-to-use#2-define-your-training-process)
#### [Define a Trainer and Run](https://github.com/daijian217/Aman/wiki/How-to-use#3-define-a-trainer-and-run)

See [Aman wiki](https://github.com/daijian217/Aman/wiki) for more.

## Balanced weighed and grid sampler

Due to the limitation of GPU memory, huge 3D medical images like CT, MRI are difficult to be feed into networks entirely. Balanced weighted sampling strategy is a more reasonable sampling way than random sampling, axial direction sampling.
See [Weighted Balanced Sampler](https://github.com/daijian217/Aman/wiki/Weighted-Balanced-Sampler) and [Grid Sampler](https://github.com/daijian217/Aman/wiki/Grid-Sampler) for more.
tepezza 1.0.6
Scrape doctor data from www.tepezza.com

# TepezzaScraper

## Motivation/use case
Get a list of doctors and their metadata from www.tepezza.com/ted-specialist-finder, which is unfortunately ReCaptcha-protected.

## Mechanism of action
A user enters zip codes and the program uses tshark to monitor the JSON sent back.

## Requirements
* All third-party python packages that pip requires for the package download
* tshark
* Python 3.8+

## Configuration
See [default_config.ini](tepezza/data/default_config.ini) for the default; otherwise pass custom args to the constructor of `TepezzaApi`. Available fields are in `TepezzaApi._SEARCH_FOR_KEYS`.