Guide for scraping public profiles on Vinted

Here's a general guide for scraping public profiles on Vinted on the homepage :

  1. Define the information you want to extract: Before starting the scraping process, determine the specific information you want to extract from Vinted's public profiles, such as the username, location, reviews, etc.
  2. Identify the pages to scrape: Identify the Vinted pages that contain the profiles you want to extract. You can use tools like BeautifulSoup or Scrapy to parse web pages and extract data.
  3. Use Vinted APIs: If Vinted offers APIs to retrieve the data you want to extract, it's recommended to use them for legal and reliable data extraction. Be sure to follow the Vinted API instructions to retrieve the data and respect rate request limits to avoid being blocked.
  4. Use a scraping tool: If you don't have access to Vinted APIs, you can use a scraping tool to extract data from web pages. However, it's important to respect Vinted's usage policies and not abuse scraping to avoid being blocked.
  5. Store the data: Once you've extracted the data from Vinted's public profiles, you can store it in a database or CSV file for further analysis.
  6. Clean and process the data: Extracted data may contain errors or unnecessary data. Therefore, it's important to clean and process the data before using it for analysis.
  7. Finally, it's important to remember that scraping can be an effective method for retrieving large-scale data, but it can also be used in an abusive and illegal manner. Be sure to respect Vinted's usage policies and obtain the necessary permissions before scraping public profiles on Vinted.

Example of a simple scrapper

import requests
from bs4 import BeautifulSoup
 
# URL de la page contenant les profils
url = "https://www.vinted.fr"
 
# En-têtes de la demande pour imiter un navigateur Web
headers = {
    "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.36"
}
 
# Envoyer une demande GET à l'URL
response = requests.get(url, headers=headers)
 
# Analyser la réponse HTML avec BeautifulSoup
soup = BeautifulSoup(response.text, "html.parser")
 
# Trouver tous les éléments HTML contenant les noms d'utilisateur
usernames = soup.find_all("h4", class_="web_ui__Text__text web_ui__Text__caption web_ui__Text__left")
 
# Boucle à travers chaque élément et extraire le nom d'utilisateur
for username in usernames:
    print(username.text)
import requests
from bs4 import BeautifulSoup
 
# URL de la page contenant les profils
url = "https://www.vinted.fr"
 
# En-têtes de la demande pour imiter un navigateur Web
headers = {
    "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.36"
}
 
# Envoyer une demande GET à l'URL
response = requests.get(url, headers=headers)
 
# Analyser la réponse HTML avec BeautifulSoup
soup = BeautifulSoup(response.text, "html.parser")
 
# Trouver tous les éléments HTML contenant les noms d'utilisateur
usernames = soup.find_all("h4", class_="web_ui__Text__text web_ui__Text__caption web_ui__Text__left")
 
# Boucle à travers chaque élément et extraire le nom d'utilisateur
for username in usernames:
    print(username.text)