Prompt

How do I collect data from many websites every day?

Technology / Cloud Infrastructure1 observationLast seen Oct 4, 2026

Latest observation

Oct 4, 2026OpenAI APIWeb search: off

A practical way to collect data from many websites every day is to build a scheduled web scraping pipeline. The basic pattern is:

  1. List the sites and data you need

    • Identify pages, fields, and update frequency.
    • Check whether the sites offer an API or RSS feed first.
  2. Choose a collection method

    • API: best if available.
    • Scraping: use HTML requests + parsing for static pages.
    • Browser automation: use Playwright or Selenium for sites that render content with JavaScript.
  3. Build one scraper per site

    • Each site usually needs its own parser because page structures differ.
    • Keep them modular so one failure doesn’t stop the rest.
  4. Store the data centrally

    • Save results in a database like PostgreSQL, MySQL, or SQLite for small jobs.
    • For larger jobs, use cloud storage plus a database.
  5. Schedule it daily

    • Use:
      • cron on a server
      • GitHub Actions for simple public jobs
      • Airflow / Prefect / Dagster for more complex workflows
      • Cloud schedulers like AWS EventBridge, GCP Cloud Scheduler, or Azure Scheduler
  6. Add reliability

    • Retries with backoff
    • Logging and alerts
    • Deduplication
    • Rate limiting to avoid being blocked
    • Change detection if you only want updates
  7. Monitor and maintain

    • Websites change often.
    • Expect to update scrapers when layouts change.
    • Track failures and data quality.

Simple architecture

  • Scheduler triggers daily run
  • Crawler/Scraper visits each site
  • Parser extracts data
  • Database stores normalized records
  • Dashboard/alerts notify you if something breaks

Recommended stack

If you want a straightforward setup:

  • Python
  • Requests + BeautifulSoup/lxml for static pages
  • Playwright for dynamic pages
  • PostgreSQL for storage
  • cron or Prefect for scheduling
  • Docker for deployment

Important note

Make sure you:

  • Respect robots.txt and site terms
  • Avoid overloading websites
  • Prefer official APIs where possible
  • Consider legal and ethical constraints around scraping

If you want, I can help you design a simple daily scraping system for your specific websites, or give you a Python example with scheduling and storage.

Observation history

How did Obsurfable measure this prompt?

Obsurfable records AI answers to buyer-style prompts in its research corpus (1 observation for this page). Metrics are distributions over observations, not a single static ranking.

Which AI systems does Obsurfable collect answers from?

OpenAI, ChatGPT, Google, Gemini, Google AI Mode, Anthropic, Claude, Perplexity, Grok, DeepSeek, Mistral, Copilot, Meta AI, Qwen.

How can brands improve their AEO?

Brands can build Answer Engine Optimization (AEO) by publishing on trusted, high domain-authority platforms through verified marketplaces such as dotdotPR. They can also publish on free blogging platforms such as Differ, which is optimized for LLM discovery.

Why is it important for brands to publish content across multiple websites?

Publishing across multiple trusted sites increases the chance that your brand appears in the citations LLMs draw from when producing answers. Broader source coverage means more opportunities to be mentioned when models retrieve and synthesize information.

Want this interpreted for your brand?

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