The following seven topics will be covered in this Data Science and Machine Learning course:

Introducing Scrapy. Be able to explain the functionality and use cases of Scrapy in this first topic in the Data Science and Machine Learning Series. Scrapy is an open source web crawling framework written in Python for extracting the data you need from websites. It is built on top of Twisted, an asynchronous networking framework. Learn about the UrlLib2 and Requests modules for reading and opening web pages. Beautiful Soup is used for extracting data points and Selenium is a tool for writing automated tests for web applications.

Building your First Scrapy Spider. Install Scrapy and build your first scrapy spider in this second topic in the Data Science and Machine Learning Series.

Combining Xpath with Scrapy. Combine Xpath with Scrapy in this third topic in the Data Science and Machine Learning Series. Xpath is a handy tool for extracting html tags.

Building an Advanced Scrapy Spider. Build a more advanced Scrapy spider in this fourth topic in the Data Science and Machine Learning Series.

Scrapy Architecture. Be able to explain the Scrapy Architecture in this fifth topic in the Data Science and Machine Learning Series.

Deploying and Scheduling a Spider Through ScrapingHub. Deploy and schedule a spider through ScrapingHub in this sixth topic in the Data Science and Machine Learning Series.

Logging into Websites using Scrapy. Log in to websites using Scrapy in this seventh topic in the Data Science and Machine Learning Series.

HOMEPAGE

https://www.oreilly.com/library/view/data-science-and/9781634626590/