What is the ideal number of concurrent requests to Vestiaire Collective to avoid being detected?

When scraping websites such as Vestiaire Collective, it's important to be respectful and cautious because web scraping can impose a heavy load on the website's servers and can also be against the website's terms of service (ToS). Many websites have measures in place to detect and block scrapers, including rate-limiting, IP bans, and more sophisticated detection systems.

There is no one-size-fits-all answer to the "ideal number of concurrent requests" that will avoid detection, as it highly depends on the website's infrastructure, traffic management, and anti-scraping measures. Here are some general guidelines to follow when scraping to minimize the risk of being detected:

  1. Read the ToS and Robots.txt: Always check the website's terms of service and robots.txt file first. The robots.txt file can provide information on areas of the site the administrators prefer bots to avoid. If scraping is against the ToS, you should not scrape the site.

  2. Rate Limiting: Start with a low number of concurrent requests and gradually increase while monitoring the server's response. If you notice any issues (e.g., slower response times, 429 Too Many Requests errors), scale back immediately.

  3. Randomize Requests: Avoid making requests at regular intervals. Instead, introduce randomness in the timing of your requests to mimic human behavior more closely.

  4. Use Headers: Set realistic user-agent strings and consider rotating them, along with other headers, to reduce the chance of being flagged as a bot.

  5. IP Rotation: Use a pool of IP addresses and switch between them to avoid IP-based rate-limiting or bans.

  6. Be Ethical: Only scrape public data, do not attempt to bypass authentication, and avoid scraping personal data without consent.

  7. Caching: Cache responses when possible to avoid unnecessary additional requests to the same endpoints.

  8. Respect the Server: If the server sends an error response or a message asking you to slow down, comply with the request.

As a starting point, you might want to begin with a single thread (one request at a time) and slowly ramp up to a few concurrent requests, observing how the server responds. A typical conservative setup might involve 1-5 concurrent requests with a delay of 5-10 seconds between each request. However, the actual number you can use without encountering issues will depend on the factors mentioned above and will require some experimentation.

Please note that web scraping can be a legal gray area, and you should always seek legal advice before proceeding with a scraping project, especially if you plan to use the scraped data for commercial purposes.

As for code examples, here are some high-level concepts in Python using the requests library and in JavaScript using axios with Promise.all for concurrency, but keep in mind these are just examples and not Vestiaire Collective specific:

Python Example (with the requests library):

import requests
import time
from random import uniform

headers = {
    'User-Agent': 'Your User-Agent Here',

def make_request(url):
        response = requests.get(url, headers=headers)
        # Handle the response
    except requests.exceptions.RequestException as e:

urls = ['https://www.vestiairecollective.com/some-page',]  # Add more URLs as needed

for url in urls:
    time.sleep(uniform(5, 10))  # Random delay between requests

JavaScript Example (with axios and Promise.all):

const axios = require('axios');

const headers = {
    'User-Agent': 'Your User-Agent Here',

const makeRequest = async (url) => {
    try {
        const response = await axios.get(url, { headers });
        // Handle the response
    } catch (error) {

const urls = ['https://www.vestiairecollective.com/some-page',]; // Add more URLs as needed

// Example of making 3 concurrent requests
Promise.all(urls.slice(0, 3).map(url => makeRequest(url)))
    .then(() => {
        console.log('All requests completed');

Always test your scraper to ensure it works correctly and adjust the concurrency and delay settings as needed to avoid placing too much load on the server or getting detected.

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