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Adding pagination handling is crucial for collecting data from all restaurant listings on DoorDash. Restaurants are often distributed across multiple pages, and automating navigation ensures a complete dataset. Random delays between requests mimic human browsing behavior and reduce detection risks. Pagination functionality enhances the scraper’s…

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I use Go’s goroutines to scrape multiple endpoints simultaneously, ensuring high performance even for large datasets. Adding proper error handling ensures smooth operation.

Saving the scraped categories to a database or file, such as JSON or CSV, would make the data easier to analyze and integrate with other systems. This would be particularly useful for building a product classification system.

Adding advanced error logging to the scraper enhances its functionality. Detailed logs provide insights into issues encountered during scraping, such as failed requests or missing elements. This information helps in refining the script and ensuring reliable operation. Combining logs with automated retries for failed requests improves…

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For dynamic loading, I’ve used Puppeteer to click “Load More” buttons and scrape the additional reviews that appear. It’s slower than direct API requests but works reliably.

For sites with APIs, I prefer using those instead of scraping the page. APIs are faster, more reliable, and don’t require managing HTML or handling dynamic JavaScript.

Adding error handling ensures the scraper doesn’t break if elements are missing or Yelp updates its structure. For instance, some businesses might not display ratings or full addresses. Wrapping the extraction logic in conditional checks or try-catch blocks prevents the script from crashing. Logging skipped businesses helps refine the script for…

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Adding robust error handling improves the scraper’s reliability, especially when elements like job budgets or descriptions are missing. The script should skip such listings gracefully without breaking and log errors for debugging purposes. Conditional checks for null values prevent runtime errors and ensure smooth operation. Regularly testing…

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Error handling is critical for maintaining the reliability of the scraper as Vistaprint’s page structure evolves. Missing elements like product descriptions or prices can cause issues, but adding conditional checks ensures that problematic entries are skipped. Logging skipped items helps refine the scraper and provides insights into potential…

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Error handling ensures the scraper remains reliable even if Snapfish updates its page layout. Missing elements like prices or descriptions should not cause the scraper to crash. By adding conditional checks for null values, the scraper can skip problematic entries and log them for review. Regularly updating the script ensures compatibility…

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