Ich versuche, mehrere Werte von der Website (https://carone.com.uy/autos-usados-y-0km?p=21) zu extrahieren. Einige funktionieren gut, andere jedoch nicht. Ich kann beispielsweise den Namen, das Modell, den Preis und die Kraftstoffart extrahieren, kann aber die Felder „Jahr“ oder „Kilometer“ nicht korrekt extrahieren. Der Code gibt als Wert immer „N/A“ zurück.
Das ist der Code, den ich verwende:
import pandas as pd
from datetime import date
import os
import socket
import requests
from bs4 import BeautifulSoup
def scrape_product_data(url):
try:
headers = {
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.3"
}
product_data = []
# Make the request to get the HTML content
response = requests.get(url, headers=headers)
response.raise_for_status() # Check if the request was successful
soup = BeautifulSoup(response.text, 'html.parser')
product_elements = soup.find_all('div', class_='product-item-info')
for product_element in product_elements:
# Extract product name, price, model, and attributes as before (same code as previous version)
product_name_element = product_element.select_one('p.carone-car-info-data-brand.cursor-pointer')
product_name = product_name_element.text.strip() if product_name_element else "N/A"
product_price_element = product_element.find('span', class_='price')
product_price = product_price_element.text.strip() if product_price_element else "N/A"
product_model_element = product_element.select_one('p.carone-car-info-data-model')
product_model = product_model_element.get('title').strip() if product_model_element else "N/A"
# Extract product attributes
attributes_div = product_element.find('div', class_='carone-car-attributes')
year_element = attributes_div.find('p', class_='carone-car-attribute-title', text='Año')
year_value = year_element.find_previous_sibling('p', class_='carone-car-attribute-value').text if year_element else "N/A"
kilometers_element = attributes_div.find('p', class_='carone-car-attribute-title', text='Kilómetros')
kilometers_value = kilometers_element.find_previous_sibling('p', class_='carone-car-attribute-value').text if kilometers_element else "N/A"
fuel_element = attributes_div.find('p', class_='carone-car-attribute-title', text='Combustible')
fuel_value = fuel_element.find_previous_sibling('p', class_='carone-car-attribute-value').text if fuel_element else "N/A"
# Append product data as a tuple (name, price, model, year, kilometers, fuel) to the list
product_data.append((product_name, product_price, product_model, year_value, kilometers_value, fuel_value))
Das Ergebnis sieht so aus: Geben Sie hier eine Bildbeschreibung ein
Ich verstehe nicht, warum der genannte Wert immer „N/A“ erhält, während die anderen gut funktionieren, die Methode ist die gleiche.
问题是，该网站在元素的文本中使用的不是
Kilómetros，而是Kilómetros（年龄也是同样的情况）：def scrape_product_data(url): headers = { "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.3" } product_data = [] response = requests.get(url, headers=headers) response.raise_for_status() soup = BeautifulSoup(response.text, "html.parser") product_elements = soup.find_all("div", class_="product-item-info") for product_element in product_elements: product_name_element = product_element.select_one( "p.carone-car-info-data-brand.cursor-pointer" ) product_name = ( product_name_element.text.strip() if product_name_element else "N/A" ) product_price_element = product_element.find("span", class_="price") product_price = ( product_price_element.text.strip() if product_price_element else "N/A" ) product_model_element = product_element.select_one( "p.carone-car-info-data-model" ) product_model = ( product_model_element.get("title").strip() if product_model_element else "N/A" ) attributes_div = product_element.find("div", class_="carone-car-attributes") year_element = attributes_div.find( "p", class_="carone-car-attribute-title", string="Año" ) year_value = ( year_element.find_previous_sibling( "p", class_="carone-car-attribute-value" ).text if year_element else "N/A" ) kilometers_element = attributes_div.find( "p", class_="carone-car-attribute-title", string="Kilómetros" ) kilometers_value = ( kilometers_element.find_previous_sibling( "p", class_="carone-car-attribute-value" ).text if kilometers_element else "N/A" ) fuel_element = attributes_div.find( "p", class_="carone-car-attribute-title", string="Combustible" ) fuel_value = ( fuel_element.find_previous_sibling( "p", class_="carone-car-attribute-value" ).text if fuel_element else "N/A" ) product_data.append( ( product_name, product_price, product_model, year_value, kilometers_value, fuel_value, ) ) return pd.DataFrame( product_data, columns=["Name", "Price", "Model", "Year", "KM", "Fuel"] ) df = scrape_product_data("https://carone.com.uy/autos-usados-y-0km?p=2") print(df)打印结果：