[Rita Lari]

A helpful enhancement to the scraper would be to integrate sorting logic directly in the script. By automating the selection of specific filters on the website, such as “low-to-high price” or “customer favorites,” you can target a specific dataset more efficiently. Another useful addition is the ability to monitor price changes over time. Regularly running the scraper on the same product categories can provide valuable insights into pricing strategies. These features make the scraper more targeted and insightful for market analysis.

[Rita Lari]

Integrating product image URLs into the dataset enhances the scraper’s output, especially for e-commerce analysis. For instance, collecting images alongside product details provides a richer dataset that can be used for visual comparisons. Another improvement could involve identifying and categorizing items based on specific tags, such as “best-seller” or “new arrival.” These features add value to the scraper by enabling targeted insights into product popularity and trends. Combining these capabilities makes the scraper more versatile and effective.

[Rita Lari]

Handling pagination ensures the scraper collects data from all available products on Petco. Products are often distributed across multiple pages, and automating navigation through “Next” buttons allows for a complete dataset. Random delays between page requests mimic real user behavior and reduce the likelihood of detection. Pagination handling ensures comprehensive data collection for better analysis.

[Rita Lari]

Pagination handling is an important improvement for scraping meal data from HelloFresh. Meal plans and options are often distributed across multiple pages or sections, and automating navigation ensures a more complete dataset. Random delays between requests mimic human browsing behavior, reducing the risk of detection. This functionality enhances the scraper’s ability to collect detailed information about all available meal kits. Proper pagination handling makes the scraper more efficient and comprehensive.

[Rita Lari]

Error handling improves the reliability of the DoorDash scraper by addressing missing elements or page structure changes. For example, if some restaurants lack menu prices, the scraper should skip those entries without crashing. Logging skipped entries helps refine the scraper and identify patterns. Regular updates to the script ensure that it remains functional despite website changes. These practices make the scraper robust and dependable over time.