Lecture 40

Parsing and scraping HTML

MCS 275 Spring 2022
David Dumas

Lecture 40: Parsing and scraping HTML

Course bulletins:

  • Project 4 is due 6pm CDT Friday 29 April.
  • Please install beautifulsoup4 with
                python3 -m pip install beautifulsoup4

Getting data from the web

HTML is a language for making documents, meant to be displayed to humans. Avoid having programs read HTML if at all possible.

e.g. look for an API that serves the same data in a structured format (CSV, JSON, ...)


We discuss what you can do if there is no API, and you need to extract information from an HTML document.

Some of these ideas generalize to exploring and extracting data from other file formats.

HTML parsing

Level 0: Treat the HTML document as a string and use search operations (str.find or regexes) to locate something you care about, like <title>.

HTML is complicated, and this approach is very error-prone.

HTML parsing

Level 1: Use a parser that knows how to recognize start/end tags, attributes, etc., and tell it what to do when it finds them (e.g. call this function...)

html.parser is in the standard library.

This approach is event-based. You specify functions to handle things when they are found, but you don't get an overall picture of the entire document.

HTML parsing

Level 2: Use a higher-level HTML data extraction framework like Beautiful Soup, Scrapy, or Selenium.

These frameworks create a data structure that represents the entire document, supporting various kinds of searching, traversal, and extraction.


The Document Object Model or DOM is a language-independent model for representing a HTML document as a tree of nodes.

Each node represents part of the document, such as a tag, an attribute, or text appearing inside a tag.

The formal specification has rules for for naming, accessing, and modifying parts of a document. JavaScript fully implements this specification.

<html><head><title>My title</title></head><body><h1>A heading</h1>
<a href="https://example.com">Link text</a></body></html>
Adapted from DOM illustration by Birger Eriksson (CC-BY-SA).
<p>I <strong>really</strong>like Python.</p>
Adapted from DOM illustration by Birger Eriksson (CC-BY-SA).

Beautiful Soup

This package provides a module called bs4 for turning HTML into a DOM-like data structure.

Widely used, e.g. at one point Reddit's backend software used it to select a representative image from a web page when a URL appeared in a post*.

Requires an HTML parser. We'll use html.parser from the standard library (slow but always available).

* As of 2014. Perhaps they still use it?

Minimal soup

Parse HTML file into DOM:

        from bs4 import BeautifulSoup

        with open("lecture40.html") as fobj:
            soup = BeautifulSoup(fobj,"html.parser")

Minimal soup

Parse web page into DOM:

        from urllib.request import urlopen
        from bs4 import BeautifulSoup

        with urlopen("https://example.com/") as response:
            soup = BeautifulSoup(response,"html.parser")

Be careful about the ethics of connecting to web servers from programs.

Scraping and spiders

A program that extracts data from HTML is a scraper

A program that visits all pages on a site is a spider.

All forms of automated access should:

  • Allow the site to prioritize human users.
  • Limit frequency of requests.
  • Respect a site's Terms of Service (TOS).
  • Respect the site's robots.txt automated access exclusion file, if they have one.

Minimal soup

Parse string into DOM:

        from bs4 import BeautifulSoup

        soup = BeautifulSoup(

That was durian?!

", "html.parser" )

BS4 basics

        str(soup) # show as HTML
        soup.prettify() # prettier HTML
        soup.title # first (and only) title tag
        soup.p  # first p tag
        soup.find("p") # first p tag (alternative)
        soup.p.strong  # first strong tag within the first p tag
        soup.find_all("a") # list of all a tags

Working with tags

        str(tag) # HTML for this tag and everything inside it
        tag.name # name of the tag, e.g. "a" or "ul"
        tag.attrs # dict of tag's attributes
        tag["href"] # get a single attribute
        tag.text # All the text nodes inside tag, concatenated
        tag.string # If tag has only text inside it, returns that text
                   # But if it has other tags as well, returns None
        tag.parent # enclosing tag
        tag.contents # list of the children of this tag
        tag.children # iterable of children of this tag
        tag.banana # first descendant banana tag (sub actual tag name!)
        tag.find(...) # first descendant meeting criteria
        tag.find_all(...) # descendants meeting criteria
        tag.find_next_sibling(...) # next sibling tag meeting criteria


Arguments supported by all the find* methods:

        tag.find_all(True) # all descendants
        tag.find_all("tagname") # descendants by tag name
        tag.find_all(href="https://example.com/") # by attribute
        tag.find_all(class_="post") # by class
        tag.find_all(re.compile("^fig")) # tag name regex match
        tag.find_all("a",limit=15) # first 15 a tags
        tag.find_all("a",recursive=False) # all a *children*

Also work with find(), find_next_sibling(), ...

Simulating CSS

soup.select(SELECTOR) returns a list of tags that match a CSS selector, e.g.

        soup.select(".wide") # all tags of class "wide"
        # ul tags within divs of class messagebox
        soup.select("div.messagebox ul")

There are many CSS selectors and functions we haven't discussed, so this gives a powerful alternative search syntax.

        # all third elements of unordered lists
        soup.select("ul > li:nth-of-type(3)")


Revision history

  • 2022-04-20 Initial publication