How do I choose the right web scraping tech stack?
Choosing the right stack depends on your specific requirements and constraints.
Key decision factors:
- JavaScript requirement
- Project scale
- Team experience
- Deployment environment
- Data processing needs
- Budget and performance requirements
Decision tree:
If site requires JavaScript rendering:
- Python → Selenium or Playwright (via playwright-python)
- Node.js → Playwright or Puppeteer
- Go → Rod or Chromedp
If site is static HTML:
- Python → Requests + BeautifulSoup (simple) or Scrapy (large-scale)
- Node.js → Axios + Cheerio
- Go → Colly
- Rust → reqwest + scraper (for max performance)
Scale considerations:
Small (< 1,000 pages):
- Any stack works
- Prefer simplicity and team knowledge
Medium (1,000 - 100,000 pages):
- Python: Scrapy with Redis queue
- Node.js: Custom crawler with Cheerio
- Concurrent requests and queuing needed
Large (100,000+ pages):
- Python: Scrapy + ScrapyRT + Redis/Kafka
- Distributed architecture required
- Consider managed services (ScrapingHub, Apify)
Performance requirements:
Speed-critical:
- Go with Colly (fastest)
- Node.js with Cheerio (good balance)
- Rust for extreme performance
Moderate performance:
- Python with async (asyncio + aiohttp)
- Python with threading
Data processing needs:
Heavy analysis after scraping:
- Python (best data science ecosystem)
- Built-in pandas, numpy, scikit-learn integration
Real-time processing:
- Node.js or Go
- Stream processing as you scrape
Common stacks by use case:
E-commerce monitoring:
- Scrapy + Playwright (when needed) + PostgreSQL + Celery
News aggregation:
- Requests + BeautifulSoup + MongoDB
Price comparison:
- Node.js + Cheerio + Redis + Puppeteer (fallback)
SEO tools:
- Scrapy + Splash + Elasticsearch
Recommendation:
Start simple and evolve:
- Begin with HTTP + parser (Requests/BeautifulSoup or Axios/Cheerio)
- Add headless browser only if needed
- Scale up to framework (Scrapy) when complexity grows
- Add distribution/queuing (Redis/RabbitMQ) at large scale
Choose based on team expertise first, then optimize later if needed.