Python Tutorial: HTML Tags and Attributes

DataCamp · Beginner ·🧠 Large Language Models ·6y ago

Key Takeaways

This video tutorial covers HTML tags and attributes, focusing on the general abstract structure of HTML tags, including tag names and attributes, with a special emphasis on ID, class, and href attributes, using Python for web scraping.

Full Transcript

in the last lesson we became familiar with the tree-like structure of HTML and learned how to navigate the tree to access specific elements we did not pay much attention to the actual HTML tags nor the specifics of HTML syntax beyond this tree like structure in this lesson we delve deeper into some of the HTML specific syntax you may ask why we want to get more specific here it turns out that sometimes we want to access information that is held within the HTML tags themselves we often want to access this info in order to find the URL pointed to by a specific link on the site or because it can potentially give us another method to select specific HTML elements with a more friendly syntax than traversing the entire HTML tree to start let's look at an abstract tag formatting there are many HTML tag types that follow the same formatting we have already seen 3 tag names the HTML div and P tags these tags can also contain attributes which provide special instructions for the contents contained within that tag specific HTML attribute names are followed by an equal sign followed by information which is being passed to that attribute within the tag in well formatted HTML the information is in quotes sound confusing don't worry to look at a specific example let's consider a div tag with two attributes ID and class we chose these two attributes here because they arise frequently in practice in well form HTML the ID attribute can be used as a unique identifier for the tag element in this case the ID unique ID should only belong to this specific develoment giving us a quick way to identify it the class attribute some class can also help us identify this div element but even in well formatted HTML it doesn't need to be unique note tag needs to have an ID nor a class attribute but all tags can be given an ID and a class a point that will find its way into a future lesson is that a tag can belong to multiple classes and this is done when the class attribute that is the quoted text assigned for that class has multiple class names separated by spaces in fact this div tag would belong to both classes sum and class let's look at another example the a tag name here is the specific tag for hyperlinks the links we click on within a website to redirect somewhere the most important attribute within these hyperlink tags is the href attribute this attribute is used to identify the URL where the hyperlink redirects - it turns out that there are many allowable tag types in HTML and many allowable attributes which sometimes depend on those tag types we will not be able to nor want to go through each and every one of these in this course rather we're going to learn techniques that will be applicable regardless of the tag with a special focus on ID class and href attributes we saw in this lesson building up methods that can easily apply to other attributes as you encounter them and don't worry even with only those three attributes we will get a lot of traction so what did we learn in this lesson we focused on HTML specific syntax learning the general abstract structure of HTML tags we saw how to identify the tag naman attributes within those tags now let

Original Description

Want to learn more? Take the full course at https://campus.datacamp.com/courses/web-scraping-with-python/ at your own pace. More than a video, you'll learn hands-on coding & quickly apply skills to your daily work. -- In the last lesson, we became familiar with the tree-like structure of HTML, and learned how to navigate the tree to access specific elements. We did not pay much attention to the actual HTML tags, nor the specifics of HTML syntax beyond this tree-like structure. In this lesson, we delve deeper into some of the HTML-specific syntax. You may ask why we want to get more specific here? It turns out that sometimes we want to access information that is held within the HTML tags themselves -- we often want access this info in order to find the URL pointed to by a specific link on the site, or because it can potentially give us another method to select specific HTML elements with a more friendly syntax than traversing the entire HTML tree. To start, let's look at an abstract tag formatting. There are many HTML tag types that follow the same formatting; we have already seen three tag names: the html, div, and p tags. These tags can also contain attributes which provide special instructions for the contents contained within that tag. Specific html attribute names are followed by an equals sign, followed by information which is being passed to that attribute within the tag; in well-formatted HTML the information is in quotes. Sound confusing? Don't worry! To look at a specific example, let's consider a div tag with two attributes: id and class. We chose these two attributes here because they arise frequently in practice. In well-formatted HTML, the id attribute can be used as a unique identifier for the tag element; in this case, the id "unique-id" should only belong to this specific div element, giving us a quick way to identify it. The class attribute "some class" can also help us identify this div element, but even in well-formatted HTML, it doesn't nee
Watch on YouTube ↗ (saves to browser)
Sign in to unlock AI tutor explanation · ⚡30

Playlist

Uploads from DataCamp · DataCamp · 0 of 60

← Previous Next →
1 SQL Server Tutorial: Date manipulation
SQL Server Tutorial: Date manipulation
DataCamp
2 R Tutorial: Intermediate Interactive Data Visualization with plotly in R
R Tutorial: Intermediate Interactive Data Visualization with plotly in R
DataCamp
3 R Tutorial: Adding aesthetics to represent a variable
R Tutorial: Adding aesthetics to represent a variable
DataCamp
4 R Tutorial: Moving Beyond Simple Interactivity
R Tutorial: Moving Beyond Simple Interactivity
DataCamp
5 Python Tutorial: Why use ML for marketing? Strategies and use cases
Python Tutorial: Why use ML for marketing? Strategies and use cases
DataCamp
6 Python Tutorial: Preparation for modeling
Python Tutorial: Preparation for modeling
DataCamp
7 Python Tutorial: Machine Learning modeling steps
Python Tutorial: Machine Learning modeling steps
DataCamp
8 R Tutorial: The prior model
R Tutorial: The prior model
DataCamp
9 R Tutorial: Data & the likelihood
R Tutorial: Data & the likelihood
DataCamp
10 R Tutorial: The posterior model
R Tutorial: The posterior model
DataCamp
11 R Tutorial: An Introduction to plotly
R Tutorial: An Introduction to plotly
DataCamp
12 R Tutorial: Plotting a single variable
R Tutorial: Plotting a single variable
DataCamp
13 R Tutorial: Bivariate graphics
R Tutorial: Bivariate graphics
DataCamp
14 Python Tutorial: Customer Segmentation in Python
Python Tutorial: Customer Segmentation in Python
DataCamp
15 Python Tutorial: Time cohorts
Python Tutorial: Time cohorts
DataCamp
16 Python Tutorial: Calculate cohort metrics
Python Tutorial: Calculate cohort metrics
DataCamp
17 Python Tutorial: Cohort analysis visualization
Python Tutorial: Cohort analysis visualization
DataCamp
18 R Tutorial: Building Dashboards with flexdashboard
R Tutorial: Building Dashboards with flexdashboard
DataCamp
19 R Tutorial: Anatomy of a flexdashboard
R Tutorial: Anatomy of a flexdashboard
DataCamp
20 R Tutorial: Layout basics
R Tutorial: Layout basics
DataCamp
21 R Tutorial: Advanced layouts
R Tutorial: Advanced layouts
DataCamp
22 Python Tutorial: Time Series Analysis in Python
Python Tutorial: Time Series Analysis in Python
DataCamp
23 Python Tutorial: Correlation of Two Time Series
Python Tutorial: Correlation of Two Time Series
DataCamp
24 Python Tutorial: Simple Linear Regressions
Python Tutorial: Simple Linear Regressions
DataCamp
25 Python Tutorial: Autocorrelation
Python Tutorial: Autocorrelation
DataCamp
26 R Tutorial: The gapminder dataset
R Tutorial: The gapminder dataset
DataCamp
27 R Tutorial: The filter verb
R Tutorial: The filter verb
DataCamp
28 R Tutorial: The arrange verb
R Tutorial: The arrange verb
DataCamp
29 R Tutorial: The mutate verb
R Tutorial: The mutate verb
DataCamp
30 R Tutorial: What is cluster analysis?
R Tutorial: What is cluster analysis?
DataCamp
31 R Tutorial: Distance between two observations
R Tutorial: Distance between two observations
DataCamp
32 R Tutorial: The importance of scale
R Tutorial: The importance of scale
DataCamp
33 R Tutorial: Measuring distance for categorical data
R Tutorial: Measuring distance for categorical data
DataCamp
34 Python Tutorial: Plotting multiple graphs
Python Tutorial: Plotting multiple graphs
DataCamp
35 Python Tutorial: Customizing axes
Python Tutorial: Customizing axes
DataCamp
36 Python Tutorial: Legends, annotations, & styles
Python Tutorial: Legends, annotations, & styles
DataCamp
37 Python Tutorial: Introduction to iterators
Python Tutorial: Introduction to iterators
DataCamp
38 Python Tutorial: Playing with iterators
Python Tutorial: Playing with iterators
DataCamp
39 Python Tutorial: Using iterators to load large files into memory
Python Tutorial: Using iterators to load large files into memory
DataCamp
40 SQL Tutorial: Introduction to Relational Databases in SQL
SQL Tutorial: Introduction to Relational Databases in SQL
DataCamp
41 SQL Tutorial: Tables: At the core of every database
SQL Tutorial: Tables: At the core of every database
DataCamp
42 SQL Tutorial: Update your database as the structure changes
SQL Tutorial: Update your database as the structure changes
DataCamp
43 Python Tutorial: Classification-Tree Learning
Python Tutorial: Classification-Tree Learning
DataCamp
44 Python Tutorial: Decision-Tree for Classification
Python Tutorial: Decision-Tree for Classification
DataCamp
45 Python Tutorial: Decision-Tree for Regression
Python Tutorial: Decision-Tree for Regression
DataCamp
46 Python Tutorial: Census Subject Tables
Python Tutorial: Census Subject Tables
DataCamp
47 Python Tutorial: Census Geography
Python Tutorial: Census Geography
DataCamp
48 Python Tutorial: Using the Census API
Python Tutorial: Using the Census API
DataCamp
49 R Tutorial: A/B Testing in R
R Tutorial: A/B Testing in R
DataCamp
50 R Tutorial: Baseline Conversion Rates
R Tutorial: Baseline Conversion Rates
DataCamp
51 R Tutorial: Designing an Experiment - Power Analysis
R Tutorial: Designing an Experiment - Power Analysis
DataCamp
52 R Tutorial: Introduction to qualitative data
R Tutorial: Introduction to qualitative data
DataCamp
53 R Tutorial: Understanding your qualitative variables
R Tutorial: Understanding your qualitative variables
DataCamp
54 R Tutorial: Making Better Plots
R Tutorial: Making Better Plots
DataCamp
55 SQL Tutorial: OLTP and OLAP
SQL Tutorial: OLTP and OLAP
DataCamp
56 SQL Tutorial: Storing data
SQL Tutorial: Storing data
DataCamp
57 SQL Tutorial: Database design
SQL Tutorial: Database design
DataCamp
58 Python Tutorial: Introduction to spaCy
Python Tutorial: Introduction to spaCy
DataCamp
59 Python Tutorial: Statistical Models
Python Tutorial: Statistical Models
DataCamp
60 Python Tutorial: Rule-based Matching
Python Tutorial: Rule-based Matching
DataCamp

This video tutorial teaches the basics of HTML tags and attributes, with a focus on ID, class, and href attributes, and how to apply this knowledge using Python for web scraping. The lesson covers the general abstract structure of HTML tags and provides techniques for identifying and accessing HTML elements. By the end of the lesson, learners will be able to understand and work with HTML tags and attributes, and apply this knowledge to real-world web scraping tasks.

Key Takeaways
  1. Learn the general abstract structure of HTML tags
  2. Understand the purpose and usage of ID, class, and href attributes
  3. Apply Python for web scraping
  4. Identify and access HTML elements using tag names and attributes
  5. Practice using the techniques learned in the lesson
💡 The key insight from this lesson is that understanding HTML tags and attributes is crucial for web scraping, and that Python can be used to easily access and manipulate HTML elements.

Related AI Lessons

Claude AI vs ChatGPT: Which One Is Actually Better in 2026?
Compare Claude AI and ChatGPT based on real-world usage and benchmarking to determine which one is better in 2026
Medium · AI
Claude AI vs ChatGPT: Which One Is Actually Better in 2026?
Compare Claude AI and ChatGPT to determine which AI model is better for your needs in 2026
Medium · Programming
IntelliBooks: Classic RAG vs Graph RAG vs Agentic RAG – Choosing the Right AI Retrieval Architecture for Enterprise AI
Learn to choose the right AI retrieval architecture for enterprise AI between Classic RAG, Graph RAG, and Agentic RAG
Dev.to AI
Fluid, natural voice translation with Gemini 3.5 Live Translate
Learn about Gemini 3.5 Live Translate, a new voice translation technology that enables fluid and natural conversations across languages
Dev.to AI
Up next
5 Levels of AI Agents - From Simple LLM Calls to Multi-Agent Systems
Dave Ebbelaar (LLM Eng)
Watch →