Python Selenium – Introduction

In this mini series, we will explore how to use Python and Selenium for web scraping and browser automation.
Before writing code, it is important to understand what web scraping is, when Selenium is useful, and what ethical rules we should keep in mind.


 

What is web scraping?
Web scraping is the process of extracting information from websites automatically.

Instead of manually copying data from a page, we can write a script that opens a website, reads the content, and collects the data we need.

Website page
    ↓
Python script
    ↓
Extracted data

For example, a scraper could collect:

Article titles
Product names
Prices
Links
Dates
Search results
Public tables

Web scraping is useful when data is visible on a website but not available through an official API.

 

What is Selenium?
Selenium is a tool that allows us to control a web browser using code.

With Selenium, Python can open a browser, visit a page, click buttons, fill forms, scroll, and read content from the page.

Python
  ↓
Selenium
  ↓
Browser
  ↓
Website

This makes Selenium useful when a website depends heavily on JavaScript or dynamic content.

For example, some pages only load data after the browser has opened the page, clicked a button, or waited a few seconds.

 

Web scraping vs browser automation
Selenium is not only used for scraping.

It can also be used for browser automation.

Open a website
Click buttons
Fill input fields
Submit forms
Navigate between pages
Take screenshots
Extract visible data

Web scraping focuses on collecting data.

Browser automation focuses on controlling the browser.

Web scraping       → Extract data
Browser automation → Interact with the browser

In this series, we will use Selenium mainly for web scraping, but we will also learn some browser automation techniques along the way.

 

When should we use Selenium?
Selenium is useful when the website needs a real browser to load or interact with the content.

Pages with JavaScript-rendered content
Pages that require clicking buttons
Pages with dynamic search results
Pages with infinite scroll
Pages where content appears after waiting
Pages where normal requests are not enough

However, Selenium is not always the best choice.

If a website has a simple static HTML page, other tools may be faster and lighter.

requests
BeautifulSoup
pandas read_html
official APIs

Selenium is powerful, but it is heavier because it runs a real browser.

 

Basic scraping flow
A simple Selenium scraping script usually follows this flow:

Open browser
Go to target page
Wait for content to load
Find elements
Extract text or attributes
Save the data
Close browser

In Python, this could look conceptually like this:

open_browser()
visit_page()
find_elements()
extract_data()
save_results()
close_browser()

In the next posts, we will turn this flow into real Python code.

 

What kind of data can Selenium extract?
Selenium can extract visible text and HTML attributes from a web page.

Text inside elements
Links from href attributes
Image URLs from src attributes
Button labels
Table data
Product card information
Search result titles

For example, from a product card, we might extract:

{
    "title": "Wireless Mouse",
    "price": "19.99",
    "link": "https://example.com/product/wireless-mouse"
}

This data can later be saved into files such as CSV or JSON.

 

Ethics and responsibility
Before scraping any website, we should think about ethics, legality, and respect for the website owner.

Just because data is visible in a browser does not always mean we should collect it automatically.

Respect the website terms of service
Check robots.txt when relevant
Avoid scraping private or sensitive data
Do not bypass logins or paywalls
Do not overload websites with too many requests
Avoid collecting personal data without permission
Prefer official APIs when available

Good scraping should be respectful and controlled.

A scraper should behave more like a careful user than an aggressive bot.

Use reasonable delays
Collect only the data you need
Avoid unnecessary repeated requests
Stop scraping if the website blocks or rejects your requests
Do not use scraped data in harmful or misleading ways

For this series, we will focus on safe and educational examples using public pages and simple demo scenarios.

 

What we will build in this series
Throughout this mini series, we will learn the basics of web scraping with Python and Selenium step by step.

1. Python Selenium: Introduction
2. Python Selenium: Project Setup
3. Python Selenium: Finding Elements and Extracting Data
4. Python Selenium: Waits, Clicks and Dynamic Pages
5. Python Selenium: Pagination and Multiple Pages
6. Python Selenium: Exporting Data to CSV
7. Python Selenium: Final Project

We will start with the setup, then learn how to find elements, extract data, handle dynamic pages, move through multiple pages, and finally save the scraped data.

 

Recommended mindset
When learning Selenium scraping, it is useful to think in small steps.

First open the page
Then inspect the HTML
Then find one element
Then extract one value
Then repeat for multiple elements
Then save the data

Do not try to build a complex scraper immediately.

Start with one page, one element, and one piece of data.

After that, it becomes easier to expand the script.

 

What comes next?
In the next post, we will set up our Python Selenium project.

We will install Selenium, prepare the browser driver, create a simple Python script, and open our first page automatically.

Python Selenium: Project Setup