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Scrapy is my go-to tool for large-scale projects. Its built-in features like middlewares and pipelines make it very efficient.

Handling pagination in the StockX scraper allows for collecting data from all available sneakers. Automating navigation through “Next” buttons ensures you capture the entire dataset, which can include rare or popular listings. Random delays between requests help mimic human behavior, reducing the chances of being flagged. With pagination…

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To collect data from all product pages on Newegg, pagination handling is essential. Automating navigation through the “Next” button ensures that you don’t miss products listed on subsequent pages. Random delays between requests make the scraper appear more like a human user, reducing the chances of being flagged. Proper pagination handling…

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Adding pagination handling allows the scraper to collect hotel data across all available pages. EconoLodge typically lists hotels over multiple pages, so automating navigation through “Next” buttons ensures a complete dataset. Introducing random delays between requests mimics human behavior and reduces the risk of being flagged. With…

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Pagination handling is critical for scraping all available stock data from Robinhood. Stocks are often distributed across dynamically loaded sections, so automating scrolling or pagination ensures a comprehensive dataset. Tools like Selenium can help simulate user interactions to load additional stocks. Random delays between interactions…

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For dynamically loaded content, chromedp is an excellent Go library. It allows JavaScript rendering and interaction with elements like dropdowns and buttons.

Using Puppeteer to interact with dropdowns and filters ensures I capture all menu items, even those hidden behind dynamic elements.

To handle anti-scraping measures, I rotate proxies and add delays between requests. This reduces the likelihood of my scraper being flagged or blocked.