DEV Community: Boon

Ne Jamais Rater une Bonne Affaire sur Vinted : Le Système Automatisé en 2026

Boon — Sat, 11 Apr 2026 20:42:15 +0000

🚫 Ne Jamais Rater une Bonne Affaire sur Vinted : Le Système Automatisé en 2026

Tl;dr : Si tu passes 30 minutes par jour à refresh Vinted pour trouver cette veste Carhartt en taille M à moins de 30€ — ton temps vaut plus que ça. Voici le système sans-code qui te notifie en temps réel, sans risque de ban, sans infrastructure, et sans rien payer en plus de ton Apify.

Le problème est simple, la solution est nulle part

Vinted, c'est le flea market de 85 millions d'utilisateurs en Europe. Le problème ? Les bonnes affaires disparaissent en moins de 15 minutes. Tu postes un message pour demander la taille, le vendeur a déjà conclu avec quelqu'un d'autre.

Tu as deux options :

Passer 3h/jour à scroller — c'est ce que font 95% des utilisateurs. Inefficace, chronophage, frustrant.
Automatiser — mais construire son propre scraper en 2026, c'est s'exposer à la protection Datadome de Vinted, aux blocs Cloudflare, aux bans IP, et aux headers qui changent chaque semaine.

J'ai testé la voie #2 pendant 3 mois. Mon script Python a tenu 11 jours avant le premier 403. Le script corrigé a tenu 6 jours. À chaque mise à jour de Vinted, je recommençais de zéro.

La solution : arrêter de construire l'infrastructure quand quelqu'un l'a déjà faite.

L'architecture sans-code qui fonctionne en 2026

Le système repose sur deux briques :

Apify Vinted Turbo Scraper → extraction fiable des listings avec les bons headers et le bypass Datadome intégré
Telegram Bot API → notification push en temps réel sur ton téléphone

Le flux :

[Marque + Prix Max + Taille] → [Apify Actor] → [JSON propre] → [Telegram Bot] → [Notification 🔔]

Pas de serveur. Pas de cron custom. Pas de maintenance.

Étape 1 : Configure le Turbo Scraper sur Apify

Le Turbo Scraper te permet de filtrer par :

{
  "searchTerms": ["Carhartt", "Arc'teryx", "Nike ACG"],
  "priceMin": 5,
  "priceMax": 35,
  "sizeIds": ["m", "38", "40"],
  "country": "fr",
  "sortBy": "created_desc"
}

L'actor renvoie un JSON structuré :

[
  {
    "title": "Veste Carhartt WIP Detroit",
    "price": 29,
    "size": "M",
    "url": "https://www.vinted.fr/items/12345678",
    "seller": "thriftking_92",
    "created": "2026-04-11T14:32:00Z",
    "photo": "https://images.vinted.com/..."
  }
]

Tu récupères ce JSON via le webhook de l'Actor ou via API endpoint.

Étape 2 : Envoie les résultats sur Telegram

2 options, selon ton niveau :

Option A : Zapier / Make (zéro code)

Connecte le webhook Apify → Zapier → Telegram Bot. 10 minutes chrono, fonctionne pour 95% des cas.

Option B : 20 lignes de Node.js (contrôle total)

const TelegramBot = require('node-telegram-bot-api');
const axios = require('axios');

const bot = new TelegramBot(process.env.TELEGRAM_TOKEN, { polling: true });

app.post('/webhook', async (req, res) => {
  const items = req.body;

  for (const item of items) {
    const msg = `
🔔 *Nouvelle trouvaille Vinted !*

*{item.title}*
💰 {item.price}€ — Taille {item.size}
👤 {item.seller}
🔗 {item.url}
    `;

    await bot.sendMessage(process.env.CHAT_ID, msg, {
      parse_mode: 'Markdown',
      disable_web_page_preview: false
    });
  }

  res.json({ status: 'ok', items_processed: items.length });
});

Déploie ça sur Railway, Render ou ton VPS. Coût : ~5€/mois max.

Étape 3 : Automatise le scheduling

Tu n'as pas besoin de tourner ton script 24/7. Configure un run Apify planifié :

Schedule : toutes les 30 minutes
Coût : ~0.02€ par run (actor compute)
Résultat : notifications en temps réel sans server costs

Le coût mensuel réel : 1-3€ pour 1 440 runs/mois. Ton café coûte plus cher.

Ce que j'ai découvert après 6 mois d'usage

Les meilleures deals (marques streetwear, vêtements de sport) postés le matin sont souvent pris avant 10h. Schedule à 6h30, 7h30 et 8h30.
Filtrer par created_desc uniquement te donne les listings des 30 dernières minutes. Plus large = plus de bruit.
Le paramètre sizeIds est clé : Vinted ne filtre pas toujours correctement côté client. Ton actor doit le faire en post-processing.

Le piège à éviter en 2026

Ne construis pas ton propre parser HTTP. Vinted a déployé en 2025-2026 une couche Datadome de 4ème génération qui détecte les headers Selenium, les patterns de navigation automatisés et les IPs de data centers en moins de 3 requêtes.

Le Vinted Turbo Scraper sur Apify utilise des IPs résidentielles rotatives et des fingerprints browsers réels. C'est la différence entre 1h de dev + 2 jours de maintenance versus 10 minutes de config + 0 maintenance.

Tu veux tester en 2 minutes ?

Voici le lien direct vers l'actor Apify :

👉 Vinted Turbo Scraper — Apify Store

Premiers 3€ de compute offerts pour les nouveaux comptes. C'est suffisant pour tester le système complet.

Si tu veux une config Telegram clé-en-main avec le scheduling automatique, contacte-moi en commentaire — je partage le repo GitHub avec la stack complète (Node.js + Railway + Telegram).

Les deals n'attendent pas. Automatise ou regarde-les partir.

[Cet article est écrit à titre informatif. Vérifie les Conditions d'Utilisation de Vinted et la législation locale avant d'automatiser la récupération de données.]

Why building a Vinted scraper from scratch is a trap in 2026

Boon — Wed, 08 Apr 2026 09:23:29 +0000

If you're a data extraction developer or just someone trying to build a Vinted new listings alert system, you've probably noticed something over the past few months: Vinted's anti-bot protection has become completely paranoid.

I tried building my own Vinted scraper in Python last week to monitor some specific vintage deals. Total disaster.

Here is what happens if you try the DIY route right now:

Pure HTTP requests (Requests, HTTPX): Instant 403 Forbidden. Their Cloudflare/Datadome setup immediately flags the TLS fingerprint of standard libraries.
Headless Browsers (Playwright/Puppeteer): It works briefly, but it's incredibly slow and consumes massive amounts of RAM. Plus, Vinted will eventually flag your residential proxy IP if you don't rotate perfectly.

After burning through two different proxy providers and getting blocked anyway, I gave up on maintaining my own infrastructure for this.

While looking for an alternative, I stumbled upon an Apify Vinted actor called Vinted Turbo Scraper.

It essentially acts as a hybrid engine—it bypasses the Datadome checks natively and just returns clean JSON.

Instead of fighting with headers and proxies, this is literally all the code I run now:

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")

run = client.actor("IV3WPdQlMFG1cwXuK").call(run_input={
    "searchUrl": "https://www.vinted.com/catalog?search_text=carhartt",
    "maxItems": 50
})

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item["title"], item["price"])

It’s significantly cheaper than running my own headless cluster and I don't have to deal with WAF bypasses anymore. If you need to scrape Vinted listings efficiently, don't reinvent the wheel.

How to monitor Vinted automatically for new listings (Without getting IP banned)

Boon — Tue, 07 Apr 2026 22:09:34 +0000

If you're into flipping clothes or just trying to snag the best vintage deals, you already know that speed is everything. A good deal on Vinted is gone in literally seconds.

A few weeks ago, I decided to build a simple Python script to send a Discord notification whenever a specific brand was uploaded in my size. I thought it would take an hour. I was wrong.

The Datadome Nightmare

If you've ever tried to build a vinted scraper, you've probably hit a wall of 403 Forbidden errors. Vinted uses heavy anti-bot protections to block automated traffic.

I tried everything:

Rotating free proxies (instantly blocked)
Premium residential proxies (worked for a bit, then got flagged)
Playwright/Puppeteer (way too slow and resource-heavy to run 24/7 on my small VPS)

To truly monitor vinted automatically, you need something that handles TLS fingerprinting natively. I was about to give up on my vinted new listings alert project when I stumbled across a pre-built solution.

The Discovery

Instead of reinventing the wheel and fighting anti-bot systems daily, I found an apify vinted actor that handles the heavy lifting. It's called Vinted Turbo Scraper.

Here is the tool I use now: Vinted Turbo Scraper

It uses a hybrid approach: it uses a real browser context to bypass the WAF, grabs the session tokens, and then uses fast HTTP requests to extract the data at scale.

How I set up my Discord Alert

Using this actor, my code went from a 300-line messy Puppeteer script to a simple API call.

I just set up a webhook in Discord, and use a simple cron job that hits the Apify API every 5 minutes. The actor returns clean JSON with all the new items matching my search URL.

// Simple example of how clean the data is
const items = data.items.map(item => ({
    title: item.title,
    price: item.price,
    brand: item.brand,
    url: item.url
}));

If you're a developer trying to build a vinted vintage deals automation pipeline, save yourself the headache. Stop fighting WAFs and use the right tools for the job.

Scraping Vinted in 2026: Why your Python script keeps getting 403 Errors

Boon — Mon, 06 Apr 2026 22:19:08 +0000

If you've tried to build a vinted scraper recently using requests or BeautifulSoup in Python, you probably hit a brick wall. Specifically, a 403 Forbidden wall.

I spent the weekend trying to scrape vinted to get notifications for some vintage jackets I was hunting. My IP got banned within 10 requests. Vinted uses Datadome and Cloudflare to aggressively block basic scraping attempts.

The problem with DIY Vinted Automation

When you try to monitor new listings automatically, Vinted's WAF checks your TLS fingerprint. Standard HTTP libraries (like Python's requests or Node's axios) leak signatures that scream "I am a bot".

You can try rotating proxies or using Playwright/Puppeteer, but Playwright is too heavy to run a fast loop (you want alerts in seconds, not minutes). I was basically out of memory running 5 browser tabs just for one search query.

The bypass I found

After getting tired of dealing with TLS fingerprinting and headless browser crashes, I looked for managed solutions. I stumbled upon this vinted turbo scraper actor on Apify:
Vinted Turbo Scraper on Apify

It handles the Datadome bypass natively. It uses a hybrid approach:

It uses a real browser to fetch the initial tokens and solve challenges.
It switches to lightweight HTTP requests for the actual data extraction.

This means you get the bypass rate of a real browser but the speed and low cost of an API. It literally returns JSON data from any Vinted search URL instantly.

If you are a vinted data extraction developer or just trying to set up a vinted new listings alert, stop wasting your time fighting Datadome. Just use the Apify actor and plug the JSON into your Discord webhook or database.

It completely saved my weekend project. If you've found other ways to bypass the 403s without spending hundreds on residential proxies, let me know below!

How to Track Vinted Price Drops for Reselling (Automation)

Boon — Sun, 05 Apr 2026 22:26:45 +0000

When reselling on Vinted, finding underpriced items is only half the battle. The other half is tracking when a seller drops their price so you can instantly send an offer.

If you try to monitor multiple closets or search queries manually, you'll lose out to faster buyers.

I used to run a custom Python script to track my favorite items, but Vinted's Cloudflare protection (and Datadome) made it a nightmare to maintain. You get a 403 Forbidden error unless your proxy and TLS fingerprint are perfect.

Instead of maintaining my own scraper and rotating proxies, I found a tool that handles the bypassing for me: the Vinted Turbo Scraper on Apify.

Why it works

It runs a hybrid architecture. It grabs valid CSRF tokens with a real browser session in the background, then uses raw HTTP requests to fetch the data at crazy speeds. You never have to worry about getting blocked.

How I track price drops:

I pass my target Vinted search URLs into the scraper.
I set the Apify actor to run on a schedule (e.g., every 10 minutes).
I push the clean JSON output to a Google Sheet using Make.com (formerly Integromat).
A simple formula compares the new price field with the previous data. If it drops below my target threshold, it sends me a Discord ping.

If you're building any kind of vinted automation, price monitor, or alert system, don't waste time fighting WAFs. Just use a maintained data extraction tool.

How to Build a Vinted to Telegram Alert Bot in 2026 (Zero Code)

Boon — Sun, 05 Apr 2026 05:21:03 +0000

If you're flipping vintage clothes or reselling items from Vinted, you already know that good deals disappear in seconds. Refreshing the app manually is a waste of time.

I wanted to build a simple Telegram bot to send me a notification the exact second a specific brand (like Carhartt or Nike) was posted in my size.

I initially tried coding a Python scraper using requests and BeautifulSoup, but Vinted's Cloudflare and Datadome protection blocked me with 403 Forbidden errors immediately. Playwright worked, but it was incredibly slow and heavy to run 24/7 on a cheap VPS.

Instead of building from scratch, I found the Vinted Turbo Scraper on Apify.

How it works

This tool handles all the proxy rotation and TLS fingerprinting for you. You just give it a standard Vinted search URL, and it returns clean JSON data.

To connect it to Telegram without coding:

Go to Make.com or Zapier.
Set up a trigger: Apify -> Watch for Actor Run.
Add an action: Telegram -> Send a Message.
Map the fields (Title, Price, URL, Image) from the Apify JSON output to your Telegram message format.

That's it. You can schedule the Apify actor to run every 5 minutes. Whenever it finds new items matching your search URL, your Telegram bot instantly pings your phone.

It's by far the easiest vinted automation setup I've tested, and it completely bypasses the anti-bot headache.

Never miss a Vinted deal: How to monitor listings automatically (2026)

Boon — Sun, 05 Apr 2026 04:20:07 +0000

If you are flipping clothes, you already know that the best vintage deals on Vinted are gone in seconds.

I used to refresh the app manually like a maniac. Then I tried building a Python script to scrape Vinted listings, but my IP got instantly banned by Datadome. Vinted's security is no joke right now.

After looking around for a workaround, I stumbled upon the Vinted Turbo Scraper on Apify.

It’s honestly a game changer. You just paste your Vinted search URL (e.g., filtered for Nike, size L, under 20€), and it extracts all the new listings into clean JSON.

Since it handles all the proxy rotation and bypasses Cloudflare automatically, you never get blocked. I hooked it up to a simple Discord webhook, so now I get pinged the second a new item drops.

If you need to monitor vinted automatically and want a reliable apify vinted actor, save yourself the headache of building it from scratch.

How to Bypass Vinted 403 Errors & Cloudflare (2026 Fix)

Boon — Sat, 04 Apr 2026 13:06:46 +0000

If you've tried to scrape Vinted recently using Python (requests) or Node.js (axios), you've probably hit a wall of 403 Forbidden errors or Cloudflare/Datadome blocks.

Vinted's anti-bot system is extremely aggressive. If you try to pull data from their internal API, you need the right x-csrf-token and flawless TLS fingerprinting. A standard headless Playwright setup will get flagged almost instantly unless you're heavily patching the browser.

After spending days trying to rotate residential proxies and tweak headers, I found a much cleaner solution that bypasses the headache entirely.

Instead of fighting the WAF yourself, you can just use the Vinted Turbo Scraper on Apify.

Why it works

It uses a hybrid asymmetric architecture: it runs a real browser session in the background just to harvest the valid CSRF tokens and cookies, and then uses fast HTTP requests to do the actual data extraction.

This means you get the speed of HTTP scraping without getting blocked by Datadome.

How to use it

You just feed it a Vinted search URL (like https://www.vinted.com/catalog?search_text=vintage+nike), and it outputs clean JSON.

{
  "id": 123456789,
  "title": "Vintage Nike Hoodie",
  "price": "25.00",
  "currency": "EUR",
  "brand_title": "Nike",
  "url": "https://www.vinted.com/items/123456789-vintage-nike-hoodie"
}

It's highly optimized for speed, so you can poll it frequently if you're building a Discord sniper bot or an alert system. It handles all the proxy rotation, TLS spoofing, and token refresh logic under the hood.

If you are tired of debugging 403 Forbidden responses, give this vinted automation tool a try. It completely saved my current project.

Extracting Vinted Data to CSV for Market Analysis (Easiest Way)

Boon — Fri, 03 Apr 2026 10:15:17 +0000

If you're a vinted data extraction developer or just someone trying to analyze market trends, you know how painful it is to scrape vinted right now. Cloudflare, Datadome, IP bans... it's a mess.

I used to run my own Puppeteer scripts to get Vinted data into CSV files, but I spent more time maintaining the proxies than actually looking at the data.

Recently, I found a tool on Apify that handles all the WAF bypasses natively. It's called vinted turbo scraper and it's honestly the most reliable vinted automation I've tested so far.

Here's how I use it for market analysis:

I plug in the search URLs for the brands I'm tracking (e.g., Ralph Lauren, Carhartt).
I set it to run every morning via the Apify scheduler.
I download the results directly as a CSV or JSON.

The best part is you don't need to write any proxy rotation logic. If you want to monitor vinted automatically without fighting 403 errors all day, give this vinted scraper a try. It saves me about 5 hours a week of debugging.

Has anyone else found a better way to scrape vinted listings at scale? Let me know below.

How to turn any Vinted search URL into a dataset

Boon — Fri, 03 Apr 2026 10:01:08 +0000

How to turn any Vinted search URL into a dataset

Have you ever looked at a perfectly filtered page on Vinted and thought, "I wish I could just download this as a CSV?"

Whether you're building a reselling bot, analyzing pricing trends for specific brands, or curating a vintage fashion database, extracting clean data from Vinted is notoriously difficult. The platform's anti-bot measures—like Cloudflare and Datadome—make it almost impossible to scrape reliably with simple scripts.

But there's a powerful shortcut. Let's look at how you can take literally any search URL from Vinted, complete with all your complex filters, and instantly convert it into a structured dataset.

The Challenge

Vinted has advanced rate limits. Even if you manage to bypass the initial captcha using Playwright or Puppeteer with residential proxies, extracting large volumes of listings quickly leads to IP bans.

Instead of reinventing the wheel and managing a proxy pool yourself, we're going to use a managed scraper that handles all the anti-bot friction for you: the Vinted Turbo Scrapper on Apify.

Step 1: Craft the Perfect Search URL

The beauty of this method is that you don't need to write complex query parameters in code. You just use Vinted like a normal user.

Head to Vinted and apply your exact filters. Let's say you're looking for:

Brand: Ralph Lauren
Category: Men's Sweaters
Condition: Very Good or New without tags
Price: Under 40€

Your browser URL will look something like this:
https://www.vinted.com/vetements?search_text=ralph+lauren&status[]=2&status[]=1&price_to=40

This URL is the only input you need.

Step 2: Use the Vinted Turbo Scrapper

Instead of fighting Cloudflare, we'll feed that URL directly into the scraper.

Go to the Vinted Turbo Scrapper on Apify.
Click Start.
Under Input, paste your filtered URL into the "Start URLs" field.
Set the maximum number of items you want to extract.
Hit Run.

Step 3: Accessing Your Dataset Programmatically (Python)

If you're building a data pipeline or an alert system, you can completely automate this process using the Apify API. Here's a quick Python script to turn that URL into a dataset programmatically.

import pandas as pd
from apify_client import ApifyClient

# Initialize the ApifyClient with your API token
client = ApifyClient("YOUR_APIFY_TOKEN")

# Set the URL you want to scrape
run_input = {
    "startUrls": [
        {"url": "https://www.vinted.com/vetements?search_text=ralph+lauren&status[]=2&price_to=40"}
    ],
    "maxItems": 1000
}

# Run the Scraper
print("Starting the extraction. Bypassing protections...")
run = client.actor("IV3WPdQlMFG1cwXuK").call(run_input=run_input)

# Get the dataset ID
dataset_id = run["defaultDatasetId"]

# Fetch the items as a list of dictionaries
dataset_items = client.dataset(dataset_id).list_items().items
print(f"Successfully extracted {len(dataset_items)} listings.")

# Convert to a Pandas DataFrame for analysis
df = pd.DataFrame(dataset_items)

# Preview the data
print(df[['title', 'brand', 'price', 'url']].head())

# Export directly to CSV
df.to_csv("vinted_dataset.csv", index=False)

What's in the dataset?

The scraper returns incredibly detailed, structured data for every listing:

Core Info: Title, Brand, Description, Listing URL
Pricing: Base Price, Currency, Total Price (with buyer protection)
Media: High-res Image URLs
Metadata: Size, Condition, Upload time
Seller: Rating, last active timestamp

Why use this method?

No Infrastructure: You don't need to manage proxies, headless browsers, or captcha solvers.
Accuracy: By using the exact search URL from your browser, you get exactly the niche data you want.
Speed: It's lightning fast. Need 1,000 listings? It scales instantly.

Stop wasting time debugging broken DOM selectors and fighting anti-bot systems. Build your data pipeline today with the Vinted Turbo Scrapper.

The fastest way to export filtered Vinted listings

Boon — Thu, 02 Apr 2026 15:43:42 +0000

The fastest way to export filtered Vinted listings

If you've ever tried building an arbitrage bot, tracking competitor pricing, or curating a dataset of second-hand fashion, you've hit the same wall: how do you get Vinted data out quickly without getting blocked?

Vinted has notoriously strict rate limits and bot-protection measures (Cloudflare, Datadome). Trying to write a Python script with BeautifulSoup or even Selenium usually ends up with a blocked IP or endless captchas.

But there's a workaround that requires zero proxy management or infrastructure. Let's see how to export any filtered Vinted search into a clean dataset (CSV/JSON/Excel) in three simple steps.

Step 1: Set Your Exact Filters

The beauty of Vinted is its robust filtering system. Before writing any code, go to Vinted in your browser and dial in exactly what you want.

Let's say you're looking for:

Brand: Carhartt
Category: Men's Jackets
Condition: New with tags
Price: Under 60€

Once you apply these filters, the URL in your browser is all you need. It looks something like this:
https://www.vinted.com/vetements?search_text=carhartt&status[]=1&price_to=60

Step 2: Use the Vinted Turbo Scrapper

Instead of building a scraper from scratch, we're going to use a managed Apify actor called Vinted Turbo Scrapper. It handles all the anti-bot bypasses and IP rotation automatically.

You don't even need to code this part if you don't want to.

Go to the Vinted Turbo Scrapper on Apify.
Click Start.
Under Input, paste your filtered URL into the "Start URLs" field.
Set the maximum number of items you want to extract.
Hit Run.

Step 3: Export Your Data

Within seconds, the actor will navigate the pages, extract the listings, and compile them into a structured dataset.

Once the run is complete, head to the Dataset tab. You'll have the option to export your clean data in multiple formats:

JSON (Perfect for piping into your own app or database)
CSV / Excel (Great for data analysts or manual review)
XML

What data do you get?

You get everything you need for analysis or reselling:

Exact item title and brand
Listing URL
Price and Currency (including the total price with buyer protection)
High-res Image URLs
Upload time
Seller information (rating, last active)

Automating the Export (Python)

If you're building an automated pipeline, you can trigger this export programmatically using the Apify API.

from apify_client import ApifyClient

# Initialize the ApifyClient with your API token
client = ApifyClient("YOUR_APIFY_TOKEN")

# Set the URL you want to scrape
run_input = {
    "startUrls": [
        {"url": "https://www.vinted.com/vetements?search_text=carhartt&status[]=1&price_to=60"}
    ],
    "maxItems": 500
}

# Run the Scraper
print("Scraping in progress...")
run = client.actor("IV3WPdQlMFG1cwXuK").call(run_input=run_input)

# Get the dataset ID
dataset_id = run["defaultDatasetId"]

# Export the data (example: fetch all items as a list of dicts)
dataset_items = client.dataset(dataset_id).list_items().items
print(f"Extracted {len(dataset_items)} listings.")

# From here, you can save to CSV using pandas or insert to your database

Stop fighting Captchas

Building scrapers is fun, but maintaining them when sites change their layout or upgrade their security is a nightmare. By using the Vinted Turbo Scrapper, you offload the headache of bypasses and proxies.

Whether you're building a Vinted alert bot, analyzing fashion trends, or reselling, this is the most reliable way to get your data quickly.

Check out the tool here: Vinted Turbo Scrapper

How to get Discord alerts for Vinted vintage deals (Node.js)

Boon — Thu, 02 Apr 2026 09:32:18 +0000

I’ve been flipping clothes for a few months now, and trying to monitor vinted automatically has been an absolute nightmare.

If you're looking for a vinted new listings alert setup, you’ve probably hit the same wall I did: Datadome. Vinted’s anti-bot protection is ruthless right now. I tried building a custom vinted scraper using Axios and even Puppeteer, but my IPs got banned almost instantly. If you want to never miss a vinted deal, the DIY route is basically dead unless you want to spend hundreds on premium residential proxies.

I finally stopped trying to reinvent the wheel. I found an existing vinted apify actor that bypasses all the WAFs natively. It’s called vinted turbo scraper (link to the tool here).

Here is my exact setup for vinted vintage deals automation using Node.js and a Discord Webhook. It takes about 10 minutes to set up.

const { ApifyClient } = require('apify-client');
const axios = require('axios');

const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });
const DISCORD_WEBHOOK = 'YOUR_DISCORD_WEBHOOK_URL';

async function monitorVinted() {
    console.log('Fetching new listings...');

    // Call the Vinted Turbo Scraper actor
    const run = await client.actor('kazkn/vinted-turbo-scraper').call({
        searchUrl: "https://www.vinted.fr/vetements?search_text=carhartt+vintage&order=newest_first",
        maxItems: 10
    });

    const { items } = await client.dataset(run.defaultDatasetId).listItems();

    for (const item of items) {
        // Send alert to Discord
        await axios.post(DISCORD_WEBHOOK, {
            content: `🚨 **New Vintage Carhartt Deal!**\nPrice: ${item.price} €\nLink: ${item.url}`
        });
    }
}

monitorVinted();

If you are a vinted data extraction developer or just someone flipping clothes, stop wasting time fighting Cloudflare. Just use the Apify actor and plug the output into Discord or Telegram.

Has anyone figured out how to run this on a cheaper cron schedule (like AWS Lambda)? Let me know.