I am working on a project where I am crawling thousands of websites to extract text data, the end use case is natural language processing.
EDIT * since I am crawling 100's of thousands of websites I cannot tailor a scraping code for each one, which means I cannot search for specific element id's, the solution I am looking for is a general one *
I am aware of solutions such as the .get_text() function from beautiful soup. The issue with this method is that it gets all the text from the website, much of it being irrelevant to the main topic on that particular page. for the most part a website page will be dedicated to a single main topic, however on the sides and top and bottom there may be links or text about other subjects or promotions or other content.
With the .get_text() function it return all the text on the site page in one go. the problem is that it combines it all (the relevant parts with the irrelevant ones. is there another function similar to .get_text() that returns all text but as a list and every list object is a specific section of the text, that way it can be know where new subjects start and end.
As a bonus, is there a way to identify the main body of text on a web page?