To improve the scraper, implement pagination handling to fetch tickets across multiple pages. StubHub often displays only a limited number of results per page, and using the “Next” button is crucial to scrape all ticket data. This can be automated in Selenium by identifying the pagination buttons and simulating clicks until all pages are scraped.

• Google Trends’ output includes related queries, so I scrape these as well to analyze secondary trends linked to primary keywords.

One of the challenges of scraping Ticketmaster is managing rate limits. Sending too many requests in a short time can result in IP blocking. To mitigate this, you can introduce delays between requests using Python’s time.sleep() function. Another strategy is to use proxy rotation, distributing requests across multiple IP addresses to mimic human…

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One of the ways to improve this scraper is by handling paginated reviews. OpenTable often has multiple pages of reviews for a single restaurant. You can identify the “Next” button on the page and automate navigation through all review pages. Adding a loop to fetch reviews from subsequent pages ensures comprehensive data collection. This…

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One of the key improvements you can make to the scraper is handling pagination. Craigslist listings often span multiple pages, and to scrape all listings in a category, you need to follow the “next page” links. This can be achieved by modifying the script to extract the URL of the “next page” button and recursively fetch subsequent pages. Adding…

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I extract featured snippets and “People Also Ask” results to understand common questions and valuable keywords in specific niches.

Grab’s API, when available, provides data on pricing and services for ride-hailing, food delivery, and more, making it easier to compare offers.

• Automating data checks for updates lets me track new arrivals or out-of-stock products without overloading the store’s server.

Schedule the scraper to run periodically, capturing review trends over time, which is useful for sentiment analysis.