How to Scrape Vinted in 2026 (API & Python)

The fastest way to scrape Vinted in 2026 is to call a structured marketplace API that returns normalized JSON — catalog search, item detail, member profiles, brands, and categories — instead of parsing Vinted's HTML yourself. You can build a DIY scraper in Python, but per-country domains, anti-bot defenses, and price formatting make it expensive to keep working.

Vinted does not offer a general public API for third-party read access. It does run Vinted Pro Integrations, but that's an allowlisted API for Pro sellers to manage their own inventory and orders — not a way for outside teams to search or research the catalog. A structured scraping API is the practical route for resale-price research, brand tracking, and cross-market comparisons.

Why scrape Vinted data?

• Resale-price research — track what specific brands, sizes, and conditions actually sell for versus list for.
• Brand and category trend tracking — watch which brands and categories gain listing and favourite volume over time.
• Cross-country market research — Vinted runs separate locale domains (vinted.fr, vinted.de, vinted.co.uk, vinted.it, and more), so the same brand can price differently by market.
• Seller monitoring — track a specific closet's listings, ratings, and follower growth.
• AI and data pipelines — feed normalized secondhand-fashion listings into pricing models, sourcing tools, or arbitrage research.

Is it legal to scrape Vinted?

Vinted's Terms and Conditions restrict automated access to the site, so scraping is a contract question with Vinted, not automatically a criminal one. In the US, courts have repeatedly held that scraping publicly accessible pages does not violate the Computer Fraud and Abuse Act, even when a site's terms forbid it (see hiQ Labs v. LinkedIn, cited below) — but a terms-of-service breach can still get an account or IP banned, and EU users are additionally covered by GDPR when personal data (like a member's name or location) is involved.

Practically:

• Collect only public catalog, item, brand, category, and member pages — no login-gated data.
• Respect robots.txt and rate limits; Vinted's robots file explicitly blocks AI-training crawlers (ai-train=no) while allowing search indexing.
• Vinted operates per-country domains — check whether your use case needs consent or disclosure requirements that vary by jurisdiction.
• Don't reuse listing photos or descriptions beyond what your use case and copyright law allow; prices, brands, and conditions are facts, but item photos and write-ups are the seller's content.

Option 1: DIY in Python (and why it breaks)

The naive approach fetches a catalog search page and parses item cards:

import csv, requests
from bs4 import BeautifulSoup

resp = requests.get(
    "https://www.vinted.com/catalog",
    params={"search_text": "leather jacket"},
    headers={"User-Agent": "Mozilla/5.0", "Accept-Language": "en-US,en;q=0.9"},
)
soup = BeautifulSoup(resp.text, "html.parser")

rows = []
for card in soup.select("[data-testid='grid-item']"):
    title = card.select_one("[data-testid='item-title']")
    price = card.select_one("[data-testid='item-price']")
    rows.append({"title": title.get_text(strip=True) if title else None,
                 "price": price.get_text(strip=True) if price else None})

with open("vinted.csv", "w", newline="") as f:
    w = csv.DictWriter(f, fieldnames=["title", "price"]); w.writeheader(); w.writerows(rows)
# ...then keep these selectors alive, handle the SPA's client-rendered content, and paginate

It works once, then the maintenance starts:

• Client-side rendering. Vinted's catalog and item pages hydrate via JavaScript, so a plain requests.get() often returns a shell — you need a headless browser to get the real DOM.
• Anti-bot defenses. Datacenter IPs get blocked or rate-limited, so you need rotating residential proxies and realistic headers.
• Per-country domains and currency. vinted.com, vinted.fr, vinted.de, vinted.co.uk, and other locale sites use different currencies and layouts for the same underlying catalog.
• Price fields. The visible price is the item price; a separate "buyer protection" fee is added at checkout — parsing "the price" means picking the right field for your use case.
• Selector churn. Vinted redesigns its grid and item pages periodically, breaking hand-written CSS selectors without notice.

Option 2: No-code / ready-made tools

Browser extensions and point-and-click scrapers can export a page of search results, but resale-price and brand-trend research means re-running the same searches on a schedule and storing history across countries. That's a recurring pipeline job, better served by an API you can call from a script or cron job than a manual export tool.

Option 3: A structured Vinted API

Crawlora's Vinted API wraps request handling, rendering, proxies, and parsing behind documented endpoints for catalog search, item detail, member profiles, brands, and categories.

curl "https://api.crawlora.net/api/v1/vinted/catalog?search_text=jacket&page=1" \
  -H "x-api-key: $CRAWLORA_API_KEY"

import requests

resp = requests.get(
    "https://api.crawlora.net/api/v1/vinted/catalog",
    headers={"x-api-key": "YOUR_API_KEY"},
    params={"search_text": "jacket", "page": 1},
)
for item in resp.json()["data"]["items"]:
    print(item["title"], item["price_raw"], item["brand"])

A response is normalized JSON (confirm the exact fields in the docs):

{
  "code": 200,
  "msg": "OK",
  "data": {
    "search_text": "jacket",
    "page": 1,
    "source_url": "https://www.vinted.com/catalog?search_text=jacket",
    "items": [
      {
        "id": "9595406652",
        "title": "Vintage leather Cabelas Women's jacket",
        "url": "https://www.vinted.com/items/9595406652-vintage-leather-cabelas-womens-jacket",
        "brand": "Cabela's",
        "size": "L / US 12-14",
        "condition": "Good",
        "price_raw": "$20.00",
        "total_price_raw": "$21.70",
        "favourite_count": 9,
        "image_url": "https://images1.vinted.net/t/01_00ebe_Runxp7FBSGM86vRdXFhYhM4A/310x430/3e52418b.webp"
      }
    ]
  }
}

Note price_raw (item price) versus total_price_raw (item price plus buyer protection) — pick the field your use case actually needs. From a search result, pull item detail, a member's profile, or browse by brand and category:

h = {"x-api-key": "YOUR_API_KEY"}
base = "https://api.crawlora.net/api/v1/vinted"

item = requests.get(f"{base}/item", headers=h, params={"id": "9595406652"}).json()["data"]
member = requests.get(f"{base}/member", headers=h, params={"id": "3159465141"}).json()["data"]
brand_items = requests.get(f"{base}/brand", headers=h, params={"id": "386688", "price_from": "10", "price_to": "50"}).json()["data"]
categories = requests.get(f"{base}/categories", headers=h).json()["data"]["categories"]

catalog, brand, and category all accept price_from, price_to, order, and page, so you can filter and paginate a search, a brand's listings, or a category browse the same way.

What you can collect

• Catalog search results: title, brand, size, condition, price and total price, favourite count, and image
• Item detail: description, material, color, categories, and photos for a specific listing
• Member profiles: username, location, rating, and follower/following counts
• Brand and category browsing, each with the same price and pagination filters as catalog search
• The full brand list and category tree for building your own taxonomy

Limitations

• No third-party read API. Vinted Pro Integrations exists for allowlisted Pro sellers managing their own inventory — it isn't a research or bulk-read API, so full catalog access still means scraping.
• Locale fragmentation. Prices and currency are per-country domain; comparing markets means querying each locale separately and normalizing currency yourself.
• Price ambiguity. Item price and buyer-protection total are separate fields — decide which one your analysis needs before you aggregate.
• Anti-bot and rendering. Client-side rendering plus IP-based blocking make plain HTTP requests unreliable; a structured API handles headers, rendering, and retries behind one key.
• Media is copyrighted. Prices, brands, and conditions are facts you can collect; listing photos and descriptions carry copyright — don't republish beyond what your use case and law allow.

Where this gets used

• Resale and arbitrage research comparing list price to typical sold price by brand and category
• Secondhand-fashion market reports segmented by country or locale domain
• Seller and closet monitoring for competitive research
• Enrichment pipelines feeding brand and category catalogs into pricing or sourcing tools

Sources

Start collecting

Try it first, free: run any public URL through the Free Web Scraper, or check whether a site blocks bots with the Anti-Bot Checker — no signup.

Vinted data pairs well with other resale-marketplace APIs for cross-platform price comparisons — see how to scrape StockX for sneaker and streetwear resale, how to scrape eBay for general secondhand and auction listings, how to scrape Etsy for handmade and vintage goods, how to scrape Mercari for the general secondhand-marketplace equivalent, how to scrape Poshmark for the social-selling side of the same closet-fashion market, and how to scrape Zalando for the retail-fashion counterpart across Vinted's European markets. Get started by testing the endpoint in the Playground, reading the request and response schema in the API docs, and reviewing credit costs on the pricing page. Not sure this is legal for your use case? Read Is web scraping legal in 2026? first.

Part of our how-to-scrape guide series — every platform we cover, in one index.