Metadata-Version: 2.1
Name: xscrapers
Version: 0.0.5
Summary: A simple webscraping framework.
Home-page: https://github.com/juliandwain/webscrapers
Author: Julian Dwain Stang
Author-email: julian.stang@web.de
License: MIT
Platform: UNKNOWN
Requires-Python: >=3.8
Description-Content-Type: text/markdown
Requires-Dist: autopep8 (==1.5.5)
Requires-Dist: beautifulsoup4 (==4.9.3)
Requires-Dist: certifi (==2020.12.5)
Requires-Dist: chardet (==4.0.0)
Requires-Dist: fake-useragent (==0.1.11)
Requires-Dist: idna (==2.10)
Requires-Dist: numpy (==1.20.1)
Requires-Dist: pandas (==1.2.3)
Requires-Dist: pycodestyle (==2.7.0)
Requires-Dist: python-dateutil (==2.8.1)
Requires-Dist: pytz (==2021.1)
Requires-Dist: requests (==2.25.1)
Requires-Dist: six (==1.15.0)
Requires-Dist: soupsieve (==2.2)
Requires-Dist: toml (==0.10.2)
Requires-Dist: urllib3 (==1.26.4)

# XSCRAPERS

The [XSCRAPERS](https://github.com/juliandwain/webscrapers) package provides an OOP interface to some simple webscraping techniques.

A base use case can be to load some pages to [Beautifulsoup Elements](https://www.crummy.com/software/BeautifulSoup/bs4/doc/).
This package allows to load the URLs concurrently using multiple threads, which allows to safe an enormous amount of time.

```python
import scraper.webscraper as ws

URLS = [
    "https://www.google.com/",
    "https://www.amazon.com/",
    "https://www.youtube.com/",
]
PARSER = "html.parser"
web_scraper = ws.Webscraper(PARSER, verbose=True)
web_scraper.load(URLS)
web_scraper.parse()

```

Note that herein, the data scraped is stored in the `data` attribute of the webscraper.
The URLs parsed are stored in the `url` attribute.


