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How do I handle scraping for real-time data that updates frequently?
Setting up a scheduler, like a cron job, lets me scrape at regular intervals, ensuring the data is as close to real-time as possible.
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7 Replies
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Using a WebSocket connection, if available, is a game-changer for real-time data. It’s faster than polling and updates instantly.
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For high-frequency scrapes, rotating IPs and adding randomized delays are critical to avoid detection. Real-time scrapers can get flagged quickly.
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I prioritize only the most essential data fields, which speeds up each request and allows for more frequent updates.
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Running the scraper on a server with high bandwidth ensures that updates are handled smoothly without lags.
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I cache recent data locally and compare it with new scrapes to identify meaningful changes instead of saving duplicate data.
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Using a message queue like RabbitMQ or Kafka helps organize and process real-time data efficiently without overloading resources.
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I sometimes subscribe to the site’s updates if available, then only scrape when notified of changes. This minimizes unnecessary scraping.
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