How to Scrape Idealista.com with Python

	import json
	from datetime import datetime
	import requests
	from bs4 import BeautifulSoup
	
	
	
	
	scraper_api_key = 'api_key'
	
	
	
	
	idealista_query = "https://www.idealista.com/en/venta-viviendas/barcelona-barcelona/"
	scraper_api_url = f'http://api.scraperapi.com/?api_key={scraper_api_key}&url={idealista_query}'
	
	
	
	
	response = requests.get(scraper_api_url)
	
	
	
	
	# Check if the request was successful (status code 200)
	if response.status_code == 200:
	   # Parse the HTML content using BeautifulSoup
	   soup = BeautifulSoup(response.text, 'html.parser')
	
	
	
	
	   # Extract each house listing post
	   house_listings = soup.find_all('article', class_='item')
	 
	   # Create a list to store extracted information
	   extracted_data = []
	 
	   # Loop through each house listing and extract information
	   for index, listing in enumerate(house_listings):
		   # Extracting relevant information
		   title = listing.find('a', class_='item-link').get('title')
		   price = listing.find('span', class_='item-price').text.strip()
	
	
	
	
		   # Find all div elements with class 'item-detail'
		   item_details = listing.find_all('span', class_='item-detail')
	
	
	
	
		   # Extracting bedrooms and area from the item_details
		   bedrooms = item_details[0].text.strip() if item_details and item_details[0] else "N/A"
		   area = item_details[1].text.strip() if len(item_details) > 1 and item_details[1] else "N/A"
	
	
	
	
		   description = listing.find('div', class_='item-description').text.strip() if listing.find('div', class_='item-description') else "N/A"
		   tags = listing.find('span', class_='listing-tags').text.strip() if listing.find('span', class_='listing-tags') else "N/A"
	
	
	
	
		   # Extracting images
		   image_elements = listing.find_all('img')
		   print(image_elements)
		   image_tags = [img.prettify() for img in image_elements] if image_elements else []
		   print(image_tags)
	
	
	
	
		   # Store extracted information in a dictionary
		   listing_data = {
			   "Title": title,
			   "Price": price,
			   "Bedrooms": bedrooms,
			   "Area": area,
			   "Description": description,
			   "Tags": tags,
			   "Image Tags": image_tags
		   }
	
	
	
	
		   # Append the dictionary to the list
		   extracted_data.append(listing_data)
	
	
	
	
		   # Print or save the extracted information (you can modify this part as needed)
		   print(f"Listing {index + 1}:")
		   print(f"Title: {title}")
		   print(f"Price: {price}")
		   print(f"Bedrooms: {bedrooms}")
		   print(f"Area: {area}")
		   print(f"Description: {description}")
		   print(f"Tags: {tags}")
		   print(f"Image Tags: {', '.join(image_tags)}")
		   print("=" * 50)
	
	
	
	
		 
	
	
	
	
	   # Save the extracted data to a JSON file
	   current_datetime = datetime.now().strftime("%Y%m%d%H%M%S")
	   json_filename = f"extracted_data_{current_datetime}.json"
	   with open(json_filename, "w", encoding="utf-8") as json_file:
		   json.dump(extracted_data, json_file, ensure_ascii=False, indent=2)
	
	
	
	
	   print(f"Extracted data saved to {json_filename}")
	
	
	
	
	else:
	   print(f"Error: Unable to retrieve HTML content. Status code: {response.status_code}")