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Error handling ensures the scraper remains reliable even if Blue Apron updates its site structure. For example, missing elements like meal prices or ingredients should not cause the scraper to fail. Adding conditional checks for null values ensures that the script continues functioning smoothly. Regularly testing the scraper helps adapt it…

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If you’re combining the two, Puppeteer can grab dynamic content while Scrapy processes the rest. It’s an efficient workflow.

Dynamic pagination is trickier. I use Selenium for sites with “Load More” buttons, but it’s slower than working directly with requests.

For dynamic tables, Puppeteer is my go-to tool. It renders the page completely, so you don’t miss any hidden data.

Adding delays between requests helps. I use random intervals to make my traffic look more human-like.

Another feature to consider is comparing Lidl’s promotional data with other supermarket chains. Scraping similar data from competitor websites allows for direct comparisons, giving insights into pricing strategies and trends. Adding functionality to store historical data can further enhance this analysis, enabling trend predictions and future…

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A key consideration when scraping Decathlon.fr is managing multilingual content effectively. Decathlon operates in multiple countries with different languages, and detecting the language dynamically can help improve the scraper’s accuracy. Another improvement is to categorize products into their respective sports or activities, which can help in…

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Another useful feature is incorporating sentiment analysis for product reviews. By analyzing customer reviews alongside product data, you can gain insights into customer satisfaction and product quality. Adding this layer of analysis helps in identifying top-rated products or understanding common complaints. This feature adds significant value…

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