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Scrape delivery options from Dunelm UK using Go
Scraping delivery options from Dunelm UK involves setting up a Go application using the Colly library to efficiently parse and extract HTML content. Delivery options are typically displayed on product pages, often under a dedicated section that highlights shipping methods, costs, and estimated delivery times. This information is crucial for customers and can include options such as standard delivery, next-day delivery, or click-and-collect services.
To begin, you inspect the webpage using browser developer tools to identify the specific tags and classes that house delivery-related information. Once identified, you can use Colly’s OnHTML method to target these elements and extract their content. Handling edge cases, such as products without delivery details or location-specific options, ensures the scraper functions reliably across different pages.
Below is a complete Go implementation for scraping delivery options from Dunelm UK:package main import ( "fmt" "log" "github.com/gocolly/colly" ) func main() { // Create a new collector c := colly.NewCollector() // Scrape delivery options c.OnHTML(".delivery-options", func(e *colly.HTMLElement) { deliveryOptions := e.Text fmt.Println("Delivery Options:") fmt.Println(deliveryOptions) }) // Handle errors c.OnError(func(_ *colly.Response, err error) { log.Println("Error occurred:", err) }) // Visit the Dunelm product page err := c.Visit("https://www.dunelm.com/product-page") if err != nil { log.Fatalf("Failed to visit website: %v", err) } } -
3 Replies
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The script could be improved by adding error handling for pages where the delivery options section might not exist. A simple check could be added to log cases where no delivery information is found.
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Adding functionality to store the scraped delivery options in a database or exporting them to a CSV file would make the script more versatile. This would allow for better data management and further analysis.
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The script could be extended to handle pagination or extract delivery information for multiple products by dynamically following links from a category page. This would enable the collection of a more comprehensive dataset.
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