Need to crawl thousands of URLs daily

To crawl thousands of URLs daily, you’ll want a setup that is polite, fast, fault-tolerant, and easy to scale.

Recommended approach

1. Use a crawler framework

Good options:

• Scrapy (best for large-scale crawling in Python)
• Playwright / Selenium only if pages require JavaScript rendering
• httpx / aiohttp + asyncio for custom lightweight crawlers

For thousands of URLs/day, Scrapy is usually the best starting point.

2. Build in concurrency

You’ll want to fetch multiple URLs in parallel:

• Use async requests or a crawler framework with concurrency support
• Limit concurrency per domain to avoid getting blocked
• Add timeouts and retries

3. Respect robots.txt and rate limits

• Check robots.txt
• Use delays between requests
• Rotate user agents only if appropriate and compliant
• Don’t hammer the same host too hard

4. Handle failures gracefully

• Retry transient failures
• Track status codes
• Log timeouts, redirects, and parsing errors
• Store crawl state so you can resume after crashes

5. Queue the URLs

If you have thousands daily, use a queue:

• Redis, RabbitMQ, Kafka, or even a DB table
• Workers pull URLs from the queue and process them
• This makes scaling easier

6. Store results cleanly

Save:

• URL
• status code
• fetch timestamp
• response headers
• parsed content / extracted fields
• error details if failed

Use a database like:

• PostgreSQL for structured data
• S3/object storage for raw HTML if needed

7. Monitor performance

Track:

• requests/min
• success rate
• average latency
• error rate by domain
• blocked/banned responses

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Example architecture

Scheduler → URL queue → Crawler workers → Parser → Storage/DB

This can run on:

• a single VM for moderate scale
• Docker containers
• Kubernetes if you need horizontal scaling

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Practical recommendation

If your goal is just “thousands of URLs per day,” start with:

• Scrapy
• PostgreSQL
• Redis queue
• Docker
• one or more worker instances

This is usually enough unless pages are heavily JavaScript-driven, in which case add Playwright for those specific sites only.

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If you want, I can help you with one of these next:

1. A Scrapy project template for daily crawling
2. A Python async crawler example
3. A production architecture for crawling at scale
4. A database schema for storing crawl results