Learn a Python Skill in 7 Days from Scratch: Web Scraping

Discover how websites work by learning the roles of HTML, CSS, and JavaScript. Build a basic webpage structure, style it, and add interactivity.

Learn how HTML uses tags to mark elements and create headings and paragraphs. Open and close tags define each element, and you can inspect live sites to study their HTML.

Install Visual Studio Code on your OS, then add extensions—VS Code icons, Prettier, and Live Preview—to write HTML and CSS with formatted code and live previews.

Explore HTML headings from h1 to h6 and the paragraph tag, with proper opening and closing tags, and learn how br and hr break lines.

Build a practice web page listing my top three books with h1, h2, and paragraph elements, featuring The E-Myth, Show Your Work, and Rich Dad, Poor Dad.

Learn to write unordered and ordered lists using ul, ol, and li tags. Practice building lists in VS Code with h1 and h2 headings and a step-by-step birdhouse example.

Master the image element in HTML, using a self-closing image tag with the src attribute, an alt attribute for accessibility and SEO, and width and height for sizing.

Explore three methods to add CSS—inline, internal, and external—and see how each affects elements like p and h1 in practical HTML examples.

Learn how CSS selectors work, covering element, class, id, attribute, and universal selectors, with practical examples styling headings, lists, and other elements.

Set up your Python development environment with Anaconda, launch Jupyter Notebook, and write and run basic code in a new notebook.

Learn how variables store values in Python using Jupyter Notebook and Anaconda Navigator, with tips for descriptive names, lowercase with underscores, spaces around the equals sign, and automatic type inference.

Explore Python operators, including arithmetic, comparison, logical, and assignment operators, plus identity and membership operators, with examples in a Jupyter notebook.

Explore Python conditional statements, including if, else, elif, with nested cases, proper colons and four spaces indentation, and examples like grade logic and even/odd checks in a Jupyter notebook.

Learn how Python loops automate repeated tasks using for and while constructs, with nested loops and range usage, through exercises and practical examples.

Explore nested loops in Python, including a nested for loop over two lists to compute products and print messages, then use a nested while loop to create a multiplication table.

Explore Python functions, from predefined built‑ins like len and range to user defined ones using def, with arguments, docstrings, and returns. Examples include a greet function and calculating area.

Explore flexible function arguments in Python, using *args and **kwargs to handle varying inputs, examine local and global scopes, and learn return values and multiple returns.

Learn to handle files in Python by opening and closing files, reading with read mode, and writing or appending with write and append modes, including with open usage.

Learn how Python handles input and output, including typing inputs as strings, ints, or floats, and formatting outputs with format method or f-strings, plus basic input error handling with try-except.

Create a python guess number project using random to pick a number between 1 and 100, and loop until the guess is correct with too high or too low hints.

Open an html file in jupyter notebook, parse it with BeautifulSoup, and extract and store data from html elements like p, title, and h2.

Explore extracting data from html using beautiful soup by searching by tag name or attributes and by css selectors. Use find_all or find, and print text with get_text or text.

Navigate the HTML tree to extract data by identifying parents, children, and siblings with Beautiful Soup, using next_sibling and parent, and printing text in a Jupyter Notebook.

Explore how to find web page elements with CSS selectors using BeautifulSoup, covering tag name, class, and ID selectors, plus attribute selectors and the difference between select and select_one.

Learn to extract data from html with BeautifulSoup and save it to a csv file using Python's csv module, including creating headers and handling encoding.

Learn to handle requests errors in web scraping IMDb’s top 250 movies using Python, requests, and BeautifulSoup; mimic a user agent and export data to CSV or Excel.

Learn to extract IMDb movie data by scraping a website, using soup.find_all and class names to pull title, rank, year, and rating, then save to a csv file named movies_data.csv.

Learn to scrape multiple pages from an e-commerce site using Python, BeautifulSoup, and requests to extract mobile names, ratings, prices, and descriptions, then save to a csv.

Install selenium and Chrome Webdriver, create a new Python environment in Anaconda Navigator, and verify selenium in Jupyter Notebook for web scraping projects.

Configure Selenium 4 with chrome driver, upgrade Selenium, import webdriver and By, and locate elements on a page using basic locators like tag name, id, class name, and link text.

Learn to locate web elements with selenium using xpath and css selectors in a Jupyter notebook, print element text, and select unique selectors such as a login button.

Learn to click a button with selenium in a web scraping workflow. Set up the selenium environment in Anaconda and locate elements by XPath to click.

Learn how to take user input with selenium by automating search and form filling through xpath and send keys, including entering names and phone numbers.

Learn to take screenshots using selenium in web scraping, including full-page and element-specific captures with driver.save_screenshot, path handling, and XPath element selection.

Learn to scroll a web page with Selenium in Python by measuring the page height with document.body.scrollHeight and scrolling to the bottom with window.scrollTo to enable complete web scraping.

Learn to scrape LinkedIn job listings using Selenium and ChatGPT in a Jupyter Notebook, extracting job titles, addresses, and links, saving to a CSV and scrolling to load more results.

Learn to monetize web scraping by selling data to clients on Fiverr and Upwork, specializing in a niche like LinkedIn or real estate scraping to win more orders.

Explore how price comparison sites show prices from multiple booking platforms, while aggregators focus on reviews and user experience, with monetization through ads or commissions.