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Use Python to scrape product availability from Ruten Taiwan
How would you scrape product availability from Ruten, one of Taiwan’s largest online marketplaces? Is the availability clearly displayed on the product page, or is it part of a dynamic element that requires JavaScript to load? Would using Python with BeautifulSoup and requests be enough, or would additional tools like Selenium be necessary if the content is dynamically rendered? These questions arise when designing a scraper for availability information.
Product availability on Ruten is typically displayed near the “Add to Cart” button or as part of a product status label. These labels might include terms like “In Stock,” “Out of Stock,” or even estimated delivery times. To begin, the script sends an HTTP request to the product page using the requests library, and the HTML is parsed with BeautifulSoup. By identifying the correct tags and classes, the scraper targets the availability information. Below is a potential implementation:import requests
from bs4 import BeautifulSoup
# URL of the Ruten product page
url = "https://www.ruten.com.tw/item/show?product-id"
# Headers to mimic a browser request
headers = {
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36"
}
# Fetch the page content
response = requests.get(url, headers=headers)
if response.status_code == 200:
soup = BeautifulSoup(response.content, "html.parser")
# Extract product availability
availability = soup.find("div", class_="availability-status")
if availability:
print("Product Availability:", availability.text.strip())
else:
print("Availability information not found.")
else:
print(f"Failed to fetch the page. Status code: {response.status_code}") -
4 Replies
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If the product availability is dynamically loaded, using a headless browser like Selenium or Playwright might be necessary. These tools can render JavaScript content and ensure that the availability information is fully visible before scraping.
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Inspecting the network traffic in the browser’s developer tools could reveal API endpoints used by Ruten to fetch availability information. Querying these APIs directly might provide more reliable and efficient access to the data.
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The script could be improved by adding error handling for cases where the availability information is missing or the structure of the page changes. Logging these errors would make it easier to identify and resolve issues in future runs.
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Saving the scraped availability information into a structured format like CSV or JSON would allow for easier data management. Including additional metadata, such as product IDs or timestamps, would enhance the dataset for long-term analysis.
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