The Dynamic Web Scraper is a Selenium-based browser automation system designed to scrape data from modern JavaScript-rendered websites.
Unlike static HTML scraping, this project focuses on handling:
- infinite scrolling
- dynamic DOM rendering
- asynchronous page loading
- load-more pagination
- search-driven navigation workflows
The system demonstrates real-world scraping patterns commonly used in modern data engineering and automation workflows.
Modern websites increasingly rely on:
- JavaScript rendering
- lazy loading
- client-side DOM updates
- asynchronous APIs
Traditional scraping tools often fail on such platforms.
This project was built to demonstrate how browser automation systems can simulate real user behavior to extract dynamically generated content.
This repository demonstrates practical understanding of:
- Selenium browser automation
- JavaScript-rendered website scraping
- dynamic DOM interaction
- infinite scroll automation
- XPath-based element handling
- scraping workflow engineering
- extraction pipeline foundations
- downstream HTML processing preparation
Automatically:
- scrolls continuously
- waits for lazy-loaded content
- detects end-of-page conditions
Implemented in:
ajio_infinite_scroll.py
Automates:
- repeated button clicking
- content expansion
- dynamic pagination workflows
Implemented in:
smartprix_load_more.py
Simulates:
- Google search workflows
- result navigation
- target page interaction
Implemented in:
google_search_navigation.py
Handles:
- dynamically generated DOMs
- delayed rendering
- AJAX-driven page updates
Exports:
- rendered HTML pages
- dynamically loaded content
for downstream:
- BeautifulSoup processing
- Pandas transformation
- ETL workflows
- structured dataset generation
Target Website
(Dynamic / JavaScript-based)
↓
Selenium WebDriver
↓
User Interaction Simulation
(scroll / click / search)
↓
Rendered DOM Extraction
↓
Local HTML Storage
↓
Downstream Data Processing
Built using:
- Selenium WebDriver
- ChromeDriver
Responsibilities:
- browser control
- page interaction
- event simulation
- DOM rendering
Simulates:
- scrolling
- button clicks
- search queries
- navigation events
This allows the scraper to behave similarly to a real human user.
Extracts:
- rendered HTML
- lazy-loaded elements
- dynamically inserted content
after JavaScript execution completes.
Stores:
- raw HTML snapshots
for:
- downstream parsing
- data engineering workflows
- dataset generation
DYNAMIC_WEB_SCRAPER/
│
├── ajio_infinite_scroll.py
├── smartprix_load_more.py
├── google_search_navigation.py
│
├── ajio.html
├── smartprix.html
│
├── requirements.txt
└── README.md
Open Website
↓
Scroll Down
↓
Wait For New Content
↓
Detect Page Height Change
↓
Repeat Until End
- lazy loading
- asynchronous content rendering
- dynamic page growth
ajio_infinite_scroll.py
Open Website
↓
Locate "Load More" Button
↓
Click Button
↓
Wait For New Content
↓
Repeat Until Button Disappears
- dynamic pagination
- DOM mutation handling
- repeated content expansion
smartprix_load_more.py
Google Search
↓
Search Query Submission
↓
Result Selection
↓
Target Website Navigation
↓
Data Extraction
- multi-page workflows
- browser navigation automation
- search-driven scraping pipelines
google_search_navigation.py
git clone https://github.com/your-username/dynamic-web-scraper.git
cd dynamic-web-scraperpip install -r requirements.txtRun any scraper independently:
python ajio_infinite_scroll.pypython smartprix_load_more.pypython google_search_navigation.pyUpdate the ChromeDriver path inside scripts:
Service("path/to/chromedriver")Ensure:
- ChromeDriver version matches Chrome browser version
Generated outputs include:
ajio.html
smartprix.html
These contain:
- fully rendered HTML
- dynamically loaded content
- browser-rendered DOM snapshots
The extracted HTML can later be processed using:
| Tool | Purpose |
|---|---|
| BeautifulSoup | HTML parsing |
| Pandas | Data transformation |
| Regex | Pattern extraction |
| ETL Pipelines | Structured data workflows |
| Technology | Purpose |
|---|---|
| Python | Core programming |
| Selenium | Browser automation |
| ChromeDriver | Browser control |
| XPath | DOM interaction |
| HTML | Raw extracted content |
- Dynamic website scraping
- Infinite scroll automation
- Browser interaction simulation
- DOM extraction workflows
- Selenium automation engineering
- Modular scraping patterns
- Real-world scraping problem handling
- JavaScript-rendered page support
Current constraints include:
- hardcoded XPath selectors
- no proxy rotation
- no CAPTCHA bypass support
- HTML-only extraction
- limited retry/error handling
- not optimized for large-scale distributed scraping
Planned enhancements include:
- modular scraping framework (
src/) - headless browser support
- stealth scraping
- proxy rotation
- user-agent spoofing
- retry and resilience systems
- structured data export
- JSON / CSV pipeline generation
- distributed scraping architecture
- AWS-integrated ETL workflows
Target Websites
↓
Selenium Workers
↓
Extraction Queue
↓
S3 HTML Storage
↓
ETL Processing Pipeline
↓
Structured Dataset
Possible future technologies:
- AWS Lambda
- AWS S3
- SQS
- ECS
- Airflow
This project helped build understanding of:
- Selenium automation
- dynamic content scraping
- asynchronous page interaction
- DOM navigation
- infinite scroll workflows
- scraping architecture design
- browser automation engineering
This project demonstrates stronger engineering depth than basic BeautifulSoup scraping projects because it handles:
- JavaScript-rendered websites
- browser interaction automation
- dynamic page rendering
- real-world scraping workflows
- user simulation systems
Add screenshots for stronger recruiter impact:
- ML Systems
- MLOps
- AI Infrastructure
- Automation Engineering
- Data Engineering Foundations
This repository demonstrates:
- browser automation engineering
- Selenium-based scraping systems
- handling dynamic web architectures
- extraction workflow design
- foundational data pipeline thinking
If you found this project useful, consider giving it a ⭐ on GitHub.