Concurrent Web Crawler
High performance URL extraction powered by Go Concurrency and Vue 3.
Project Overview
In a digital landscape where information is massive and fragmented, speed and resource precision are the ultimate deciders. This project was born to conquer the limitations of traditional, sluggish crawling systems. By harnessing the raw power of Go's Goroutines and Channels, I engineered a high performance system capable of dissecting hundreds of web targets simultaneously without causing a surge in server memory. The architecture is a masterclass in decoupling: a relentless, concurrent backend paired with a reactive Vue 3 frontend. Through real time job status polling, the interface remains fluid and responsive, ensuring that even during the most intensive extraction tasks, the user experience is never compromised. It isn't just a crawler; it is a manifestation of data processing at scale.
Key Features
Concurrent Processing
Utilizes a Worker Pool (10 parallel workers) to process multiple URLs concurrently and efficiently.
Metadata Extraction
Automatic extraction of page Titles, Meta Descriptions (including OpenGraph), and Internal Link lists.
Real time Job Tracking
An integrated job queue system with real time status tracking (Pending, Processing, Completed).
Resilient HTTP Client
Equipped with custom User Agents and timeout mechanisms to handle slow websites and bypass basic bot protection.
Impact & Outcomes
- ✓Capable of processing 100 URLs in under 15 seconds using a worker pool.
- ✓Successfully implemented a cleanly decoupled backend frontend architecture.
- ✓Robust error handling system, ensuring that a single URL failure does not halt the entire job process.
Technical Challenges
Concurrency Management
Managing data synchronization across goroutines using RWMutex to prevent race conditions when writing crawling results.
Bot Detection Bypass
Customizing HTTP headers to prevent the crawler from being blocked by basic security systems on major websites.