Hybrid SSR + CSR data extraction
A scraper that decides per page whether it needs a browser at all. Static pages go through plain HTTP; JavaScript-rendered ones fall back to headless automation. I built it after too many runs silently returned empty markup on client-rendered sites.
1 / 4Impact
- 01Reduced scrape failures from 40% to <5% on JS-heavy sites
- 02Supports recursive crawling up to 10 depth levels
- 03Extracts 6 content types: titles, headings, paragraphs, links, images, forms
What I built
Engineered a hybrid scraping architecture that intelligently switches between lightweight HTTP requests for SSR pages and headless Chrome automation for JavaScript-rendered SPAs, reducing scrape failures by 90% compared to static-only approaches.
Implemented anti-bot countermeasures including random User-Agent rotation via fake-useragent, configurable request delays, and Chrome automation flag bypasses—enabling successful extraction from protected sites with 85%+ success rate.
Built a real-time dashboard with WebSocket-powered live log streaming, interactive JSON tree viewer with copy functionality, and an image gallery for visual content discovery—providing complete visibility into the extraction pipeline.
Inspiration
Traditional scrapers fail silently on JavaScript-heavy pages, leaving users with incomplete or empty data.
Features
- Hybrid static/dynamic scraping engine
- Automatic JavaScript detection and fallback
- Real-time WebSocket log streaming
- Recursive BFS-based crawling with depth control
- Anti-bot detection bypass mechanisms
- Interactive JSON data viewer with image gallery
Challenges
- Detecting when JavaScript rendering is required
- Handling lazy-loaded content and infinite scroll
SnapshotAt a glance
Full-Stack Developer & System Architect
2 months
Reduced scrape failures from 40% to <5% on JS-heavy sites
Supports recursive crawling up to 10 depth levels
Extracts 6 content types: titles, headings, paragraphs, links, images, forms
Technologies Used
10 Technologies Integrated
Impact
Key Features
Feature Implementation
Project Vision
Create a scraping tool that never gives up—automatically adapting to any website architecture.
Core Process
The process of Developing it.
Built a BFS crawler with heuristic JS detection, triggering Selenium fallback when content indicators suggest client-side rendering.
