Web scraping automation with Python
by Open Weaver kits ✔ Updated: Jan 10, 2023
Build smart application to collect and scrap data from a variety of online sources using these open-source data scrapping libraries.
In today’s world, we are surrounded loads of data of different types and from diverse sources. And every business organisation wants to make the best use of this data. The ability to gather and utilise this data is a must-have skill for every data scientist.
Web scraping is the process of extracting structured and unstructured data from the web with the help of programs and exporting into a useful format. You can efficiently use the Python language to build application to harvest online data through these specific Python libraries.
The following list covers the top and trending libraries for web data scrapping. By clicking on each you can check out the overview, code examples, best applications and cases for each of them, and a lot more. Scroll through:
Working with HTTP to request a web page
Small, fast HTTP client library for Python. Features persistent connections, cache, and Google App Engine support. Originally written by Joe Gregorio, now supported by community.
Python 423 Version:Current License: Others (Non-SPDX)
Complete web scraping framework
Scrapy, a fast high-level web crawling & scraping framework for Python.
Python 46510 Version:2.8.0 License: Permissive (BSD-3-Clause)
Parsing HTML, XML
BeautifulSoup 4 for Python 3.3
Python 93 Version:Current License: No License