Web Scraping Course

Lesson 1 • How the Web Delivers Data

Covers HTTP request-response cycles, status codes, and headers. Establishes the network layer knowledge required for every scraping technique in the course.

Lesson 2 • HTML and CSS Structure Essentials

Introduces DOM tree structure, HTML tags, and CSS selectors. Provides the markup literacy needed to locate and extract target data from any webpage.

Lesson 3 • Ethical and Legal Considerations

Examines robots.txt, terms of service, and responsible crawl rates. Frames ethical boundaries that guide every practical decision made throughout the course.

Lesson 1 • Working with Response Formats

Parses JSON, XML, and binary responses returned by servers. Prepares students to handle diverse content types beyond standard HTML pages.

Lesson 2 • Managing Headers and Sessions

Teaches custom headers, user-agent strings, and session objects for persistent connections. Enables scrapers to mimic browser behavior and maintain state across requests.

Lesson 3 • Handling Timeouts and Errors

Addresses timeout configuration, retry logic, and HTTP error handling. Builds resilient scrapers that recover gracefully from network failures.

Lesson 1 • Creating and Navigating the Parse Tree

Introduces BeautifulSoup object creation, parsers, and tree traversal methods. Establishes the foundational navigation skills used in every extraction task.

Lesson 2 • CSS Selector Queries

Applies select and select_one with CSS selector syntax for concise element targeting. Complements tag-based searches with a more expressive query style.

Lesson 3 • Finding Elements by Tag and Attribute

Covers find, find_all, and attribute-based searches. Enables precise targeting of elements regardless of page complexity.

Lesson 4 • Extracting Text, Links, and Attributes

Retrieves text content, href values, image sources, and other attributes from matched elements. Produces the raw data that feeds downstream storage and analysis.

Lesson 1 • Browser Automation with Selenium

Covers WebDriver setup, element interaction, and page navigation in Selenium. Provides a widely adopted automation baseline for dynamic scraping tasks.

Lesson 2 • Why Static Scrapers Fail on Dynamic Pages

Explains client-side rendering, single-page applications, and lazy loading. Motivates the shift to browser automation for JavaScript-heavy targets.

Lesson 3 • Modern Automation with Playwright

Introduces Playwright's async API, auto-waiting, and multi-browser support. Offers a faster, more reliable alternative to Selenium for modern web applications.

Lesson 4 • Interacting with Complex UI Elements

Handles dropdowns, modals, infinite scroll, and pagination in automated browsers. Extends automation skills to real-world page interaction patterns.

Lesson 1 • Using Regular Expressions for Data Cleanup

Applies regex patterns to clean, validate, and transform raw extracted strings. Bridges the gap between messy scraped text and structured, usable data.

Lesson 2 • Scraping Lists and Repeated Structures

Extracts data from ul, ol, and repeated div patterns common in product and article listings. Builds looping extraction logic applicable to any list-based layout.

Lesson 3 • Handling Missing and Inconsistent Data

Addresses optional fields, null values, and layout variations across pages. Produces extraction pipelines that remain stable when source pages differ.

Lesson 4 • Extracting Tabular Data

Parses HTML tables into structured rows and columns using BeautifulSoup and pandas. Produces clean DataFrames ready for analysis or export.

Lesson 1 • Using pandas for Data Transformation

Loads scraped data into DataFrames for cleaning, deduplication, and reshaping. Prepares datasets for downstream analysis or export to multiple formats.

Lesson 2 • Saving Data to CSV and JSON Files

Writes scraped records to flat files using Python's csv module and json library. Establishes the simplest, most portable storage format for scraped datasets.

Lesson 3 • Storing Data in SQLite Databases

Creates SQLite schemas, inserts records, and queries stored data with Python's sqlite3 module. Introduces relational storage for structured, queryable datasets.

Lesson 1 • Understanding Anti-Scraping Mechanisms

Surveys bot detection techniques including fingerprinting, honeypots, and behavioral analysis. Provides a threat model that informs every countermeasure in the chapter.

Lesson 2 • Solving and Avoiding CAPTCHAs

Covers CAPTCHA types, third-party solving services, and avoidance strategies. Provides practical options for maintaining scraper access when CAPTCHAs are encountered.

Lesson 3 • Rotating Proxies and IP Management

Configures proxy pools, rotates IPs per request, and handles proxy failures gracefully. Prevents IP-based blocks on high-volume scraping tasks.

Lesson 4 • Handling Login and Session Authentication

Automates form-based login, OAuth flows, and cookie-based session maintenance. Unlocks access to authenticated content behind login walls.

Lesson 1 • Scheduling and Automating Scraper Runs

Schedules scrapers with cron, task queues, and cloud functions for recurring execution. Removes manual intervention from data collection workflows.

Lesson 2 • Maintaining Scrapers Against Site Changes

Detects layout changes, automates regression tests, and documents selectors for fast updates. Reduces maintenance cost when target sites redesign their pages.

Lesson 3 • Monitoring, Logging, and Alerting

Implements structured logging, error alerting, and scraper health dashboards. Ensures production scrapers surface failures before they affect downstream data consumers.

Lesson 4 • Building Scrapers with Scrapy Framework

Introduces Scrapy spiders, items, pipelines, and middleware. Provides a production-grade framework that handles concurrency, retries, and storage automatically.