How to scrape car listings from AutoScout24.com using Python?

Linda Ylva · 2024-12-21T07:31:44+00:00

Scraping car listings from AutoScout24.com using Python allows you to gather data such as car models, prices, and mileage, providing valuable insights into the automotive market. AutoScout24 is one of Europe’s largest online car marketplaces, making it a great source for analyzing pricing trends and car availability. By using Python’s HTTP libraries, you can fetch content from the website and extract relevant information by parsing the HTML structure. This involves identifying the tags or classes that contain data like car names, prices, and specifications, and automating the process to handle multiple listings efficiently.Pagination is essential when scraping AutoScout24, as car listings are distributed across multiple pages. Automating navigation through the “Next” button ensures that the scraper collects all available data. Adding random delays between requests can mimic human behavior and reduce detection risks. Once extracted, storing the data in structured formats like CSV or JSON allows for easier analysis and comparison. Below is an example script for extracting car data from AutoScout24.import requests from html.parser import HTMLParserclass AutoScoutParser(HTMLParser): def __init__(self): super().__init__() self.in_car_name False self.in_car_price False self.cars self.current_car {} def handle_starttag(self, tag, attrs): attrs dict(attrs) if tag "h2" and "class" in attrs and "car-name" in attrs: self.in_car_name True if tag "span" and "class" in attrs and "price" in attrs: self.in_car_price True def handle_endtag(self, tag): if self.in_car_name and tag "h2": self.in_car_name False if self.in_car_price and tag "span": self.in_car_price False def handle_data(self, data): if self.in_car_name: self.current_car data.strip() if self.in_car_price: self.current_car data.strip() self.cars.append(self.current_car) self.current_car {}url "https://www.autoscout24.com/"response requests.get(url)parser AutoScoutParser()parser.feed(response.text)for car in parser.cars: print(f"Car: {car}, Price: {car}")This script parses the HTML content from AutoScout24 to extract car names and prices. Pagination logic can be added to navigate through all pages, ensuring that all listings are captured. Adding random delays between requests can prevent detection and ensure smooth scraping sessions.

General Web Scraping

How to scrape car listings from AutoScout24.com using Python?

Posted by Linda Ylva on 12/21/2024 at 7:31 am
Scraping car listings from AutoScout24.com using Python allows you to gather data such as car models, prices, and mileage, providing valuable insights into the automotive market. AutoScout24 is one of Europe’s largest online car marketplaces, making it a great source for analyzing pricing trends and car availability. By using Python’s HTTP libraries, you can fetch content from the website and extract relevant information by parsing the HTML structure. This involves identifying the tags or classes that contain data like car names, prices, and specifications, and automating the process to handle multiple listings efficiently.
Pagination is essential when scraping AutoScout24, as car listings are distributed across multiple pages. Automating navigation through the “Next” button ensures that the scraper collects all available data. Adding random delays between requests can mimic human behavior and reduce detection risks. Once extracted, storing the data in structured formats like CSV or JSON allows for easier analysis and comparison. Below is an example script for extracting car data from AutoScout24.
```
import requests
from html.parser import HTMLParser
class AutoScoutParser(HTMLParser):
    def __init__(self):
        super().__init__()
        self.in_car_name = False
        self.in_car_price = False
        self.cars = []
        self.current_car = {}
    def handle_starttag(self, tag, attrs):
        attrs = dict(attrs)
        if tag == "h2" and "class" in attrs and "car-name" in attrs["class"]:
            self.in_car_name = True
        if tag == "span" and "class" in attrs and "price" in attrs["class"]:
            self.in_car_price = True
    def handle_endtag(self, tag):
        if self.in_car_name and tag == "h2":
            self.in_car_name = False
        if self.in_car_price and tag == "span":
            self.in_car_price = False
    def handle_data(self, data):
        if self.in_car_name:
            self.current_car["name"] = data.strip()
        if self.in_car_price:
            self.current_car["price"] = data.strip()
            self.cars.append(self.current_car)
            self.current_car = {}
url = "https://www.autoscout24.com/"
response = requests.get(url)
parser = AutoScoutParser()
parser.feed(response.text)
for car in parser.cars:
    print(f"Car: {car['name']}, Price: {car['price']}")
```
This script parses the HTML content from AutoScout24 to extract car names and prices. Pagination logic can be added to navigate through all pages, ensuring that all listings are captured. Adding random delays between requests can prevent detection and ensure smooth scraping sessions.
Linda Ylva replied 1 day, 6 hours ago 1 Member · 0 Replies
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