# Vinted Scraper (`silentflow/vinted-scraper`) Actor Scrape Vinted marketplace data. Extract product listings, prices, seller info, images & stats. Search by keywords, brand, size, price range. Works with all Vinted countries (FR, DE, UK, ES, IT, PL, NL, BE, AT, CZ, LT). Fast & reliable API for e-commerce analysis. - **URL**: https://apify.com/silentflow/vinted-scraper.md - **Developed by:** [SilentFlow](https://apify.com/silentflow) (community) - **Categories:** E-commerce - **Stats:** 10 total users, 0 monthly users, 100.0% runs succeeded, 1 bookmarks - **User rating**: No ratings yet ## Pricing $16.00/month + usage To use this Actor, you pay a monthly rental fee to the developer. The rent is subtracted from your prepaid usage every month after the free trial period.You also pay for the Apify platform usage, which gets cheaper the higher Apify subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#rental-actors ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## 👗 Vinted Scraper **🇬🇧 English** | [🇫🇷 Français](#-vinted-scraper-français) --- ### What is Vinted Scraper? Vinted Scraper allows you to **extract product listings from Vinted** - Europe's largest second-hand fashion marketplace. Whether you're looking for clothes, shoes, bags, or accessories, this tool helps you collect all the information you need. Perfect for: - 🛍️ **Resellers** - Find the best deals to resell - 📊 **Market research** - Analyze prices and trends - 🔔 **Price monitoring** - Track specific items or brands - 📈 **Data analysis** - Build datasets for your projects --- ### What can you search for? | Search option | Examples | |--------------|----------| | **Keywords** | "Nike Air Max", "Chanel bag", "Levi's jeans" | | **Brands** | Nike, Adidas, Zara, H&M, Louis Vuitton, Gucci | | **Categories** | Women, Men, Kids, Home, Accessories | | **Price range** | From 5€ to 50€, From 100€ to 500€ | | **Condition** | New with tags, New, Very good, Good, Satisfactory | | **Size** | XS, S, M, L, XL, 38, 40, 42... | | **Colors** | Black, White, Blue, Red, etc. | --- ### What information do you get? For each product found, you receive: | Information | Description | |-------------|-------------| | 📝 **Title** | Product name | | 💰 **Price** | Current price in euros | | 🏷️ **Brand** | Brand name (Nike, Zara, etc.) | | 📏 **Size** | Size of the item | | ✨ **Condition** | New, Very good, Good, etc. | | 🎨 **Color** | Main color | | 📍 **Location** | Seller's city and country | | 🖼️ **Photos** | All product images | | ❤️ **Favorites** | Number of users who saved this item | | 👤 **Seller info** | Name, rating, number of reviews | | 🔗 **Link** | Direct URL to the product | | 📅 **Date** | When the item was listed | --- ### Supported countries | Country | Website | |---------|---------| | 🇫🇷 France | vinted.fr | | 🇩🇪 Germany | vinted.de | | 🇧🇪 Belgium | vinted.be | | 🇳🇱 Netherlands | vinted.nl | | 🇪🇸 Spain | vinted.es | | 🇮🇹 Italy | vinted.it | | 🇵🇱 Poland | vinted.pl | | 🇵🇹 Portugal | vinted.pt | | 🇱🇹 Lithuania | vinted.lt | | 🇨🇿 Czech Republic | vinted.cz | | 🇦🇹 Austria | vinted.at | | 🇬🇧 United Kingdom | vinted.co.uk | | 🇺🇸 USA | vinted.com | --- ### Two modes available #### 🚀 Fast Mode (Default) Quick extraction of basic information from search results. Perfect for large-scale data collection. #### 🔍 Details Mode (Browse Mode) Enable "Browse Mode" to get **complete information** for each product: - ✅ Full description - ✅ Exact price - ✅ Product condition - ✅ Category - ✅ High-quality images > 💡 Details Mode is slower but provides much more data. Use it when you need complete product information. --- ### How to use? #### Option 1: Search with keywords Simply enter what you're looking for: - **Search text**: `nike air max` - **Country**: France - **Pages**: 3 The scraper will find all matching products. #### Option 2: Use a Vinted URL 1. Go to Vinted and make your search 2. Apply all your filters (brand, size, price, etc.) 3. Copy the URL from your browser 4. Paste it in the "Search URL" field The scraper will use your exact search with all filters. --- ### Example results ```json { "title": "Nike Air Max 90 - Size 42", "price": 45.00, "currency": "EUR", "brand": "Nike", "size": "42", "status": "Very good condition", "color": "White", "city": "Paris", "country": "France", "favouriteCount": 12, "sellerName": "marie_fashion", "sellerRating": 4.8, "sellerFeedbacks": 42, "url": "https://www.vinted.fr/items/12345..." } ```` *** ### Tips for best results 1. ✅ **Be specific** - "Nike Air Max 90 white" works better than just "shoes" 2. ✅ **Use filters** - Set price range to avoid unwanted results 3. ✅ **Start small** - Test with 1-2 pages first 4. ✅ **Choose the right country** - Products are country-specific *** ### Need help? If you have questions or need assistance, feel free to contact us! *** *** ## 👗 Vinted Scraper (Français) [🇬🇧 English](#-vinted-scraper) | **🇫🇷 Français** *** ### Qu'est-ce que Vinted Scraper ? Vinted Scraper vous permet d'**extraire les annonces de produits sur Vinted** - la plus grande marketplace de mode de seconde main en Europe. Que vous cherchiez des vêtements, chaussures, sacs ou accessoires, cet outil vous aide à collecter toutes les informations dont vous avez besoin. Parfait pour : - 🛍️ **Revendeurs** - Trouvez les meilleures affaires à revendre - 📊 **Études de marché** - Analysez les prix et tendances - 🔔 **Surveillance des prix** - Suivez des articles ou marques spécifiques - 📈 **Analyse de données** - Créez des jeux de données pour vos projets *** ### Que pouvez-vous rechercher ? | Option de recherche | Exemples | |---------------------|----------| | **Mots-clés** | "Nike Air Max", "Sac Chanel", "Jean Levi's" | | **Marques** | Nike, Adidas, Zara, H\&M, Louis Vuitton, Gucci | | **Catégories** | Femme, Homme, Enfant, Maison, Accessoires | | **Fourchette de prix** | De 5€ à 50€, De 100€ à 500€ | | **État** | Neuf avec étiquettes, Neuf, Très bon, Bon, Satisfaisant | | **Taille** | XS, S, M, L, XL, 38, 40, 42... | | **Couleurs** | Noir, Blanc, Bleu, Rouge, etc. | *** ### Quelles informations obtenez-vous ? Pour chaque produit trouvé, vous recevez : | Information | Description | |-------------|-------------| | 📝 **Titre** | Nom du produit | | 💰 **Prix** | Prix actuel en euros | | 🏷️ **Marque** | Nom de la marque (Nike, Zara, etc.) | | 📏 **Taille** | Taille de l'article | | ✨ **État** | Neuf, Très bon, Bon, etc. | | 🎨 **Couleur** | Couleur principale | | 📍 **Localisation** | Ville et pays du vendeur | | 🖼️ **Photos** | Toutes les images du produit | | ❤️ **Favoris** | Nombre d'utilisateurs ayant sauvegardé l'article | | 👤 **Info vendeur** | Nom, note, nombre d'avis | | 🔗 **Lien** | URL directe vers le produit | | 📅 **Date** | Date de mise en ligne | *** ### Pays supportés | Pays | Site | |------|------| | 🇫🇷 France | vinted.fr | | 🇩🇪 Allemagne | vinted.de | | 🇧🇪 Belgique | vinted.be | | 🇳🇱 Pays-Bas | vinted.nl | | 🇪🇸 Espagne | vinted.es | | 🇮🇹 Italie | vinted.it | | 🇵🇱 Pologne | vinted.pl | | 🇵🇹 Portugal | vinted.pt | | 🇱🇹 Lituanie | vinted.lt | | 🇨🇿 République Tchèque | vinted.cz | | 🇦🇹 Autriche | vinted.at | | 🇬🇧 Royaume-Uni | vinted.co.uk | | 🇺🇸 États-Unis | vinted.com | *** ### Deux modes disponibles #### 🚀 Mode Rapide (Par défaut) Extraction rapide des informations de base depuis les résultats de recherche. Parfait pour la collecte de données à grande échelle. #### 🔍 Mode Détails (Browse Mode) Activez le "Browse Mode" pour obtenir les **informations complètes** de chaque produit : - ✅ Description complète - ✅ Prix exact - ✅ État du produit - ✅ Catégorie - ✅ Images haute qualité > 💡 Le Mode Détails est plus lent mais fournit beaucoup plus de données. Utilisez-le quand vous avez besoin des informations complètes du produit. *** ### Comment utiliser ? #### Option 1 : Recherche par mots-clés Entrez simplement ce que vous cherchez : - **Texte de recherche** : `nike air max` - **Pays** : France - **Pages** : 3 Le scraper trouvera tous les produits correspondants. #### Option 2 : Utiliser une URL Vinted 1. Allez sur Vinted et faites votre recherche 2. Appliquez tous vos filtres (marque, taille, prix, etc.) 3. Copiez l'URL de votre navigateur 4. Collez-la dans le champ "URL de recherche" Le scraper utilisera votre recherche exacte avec tous les filtres. *** ### Exemple de résultats ```json { "title": "Nike Air Max 90 - Taille 42", "price": 45.00, "currency": "EUR", "brand": "Nike", "size": "42", "status": "Très bon état", "color": "Blanc", "city": "Paris", "country": "France", "favouriteCount": 12, "sellerName": "marie_fashion", "sellerRating": 4.8, "sellerFeedbacks": 42, "url": "https://www.vinted.fr/items/12345..." } ``` *** ### Conseils pour de meilleurs résultats 1. ✅ **Soyez précis** - "Nike Air Max 90 blanc" fonctionne mieux que simplement "chaussures" 2. ✅ **Utilisez les filtres** - Définissez une fourchette de prix pour éviter les résultats indésirables 3. ✅ **Commencez petit** - Testez avec 1-2 pages d'abord 4. ✅ **Choisissez le bon pays** - Les produits sont spécifiques à chaque pays *** ### Besoin d'aide ? Si vous avez des questions ou besoin d'assistance, n'hésitez pas à nous contacter ! # Actor input Schema ## `searchUrl` (type: `string`): Paste a Vinted search URL with all your filters already applied. Go to vinted.fr (or your country's Vinted), set your keywords, category, brand, size, color, price range, etc., then copy the URL from your browser. If provided, all search filters below are ignored. ## `searchText` (type: `string`): Keywords to search for (e.g., nike, chanel, robe...). ## `catalogIds` (type: `array`): Category IDs to filter (e.g., 1904=Women, 1906=Men, 1905=Kids). ## `brandIds` (type: `array`): Brand IDs to filter (e.g., 53=Nike, 14=Adidas, 12=Zara). ## `sizeIds` (type: `array`): Size IDs to filter. ## `colorIds` (type: `array`): Color IDs to filter. ## `statusIds` (type: `array`): Condition/status IDs (e.g., 6=New with tags, 1=New, 2=Very good). ## `order` (type: `string`): Sort results by. ## `priceFrom` (type: `number`): Minimum price filter. ## `priceTo` (type: `number`): Maximum price filter. ## `country` (type: `string`): Vinted country/domain. ## `maxItems` (type: `integer`): Maximum number of results to return. The scraper automatically paginates until this limit is reached. Set to 0 for default (1000). ## `browseMode` (type: `boolean`): Fetch detailed information for each item (slower, more data). ## `maxConcurrency` (type: `integer`): Number of parallel workers for browse mode (1-10, default: 3). ## Actor input object example ```json { "searchText": "nike", "catalogIds": [], "brandIds": [], "sizeIds": [], "colorIds": [], "statusIds": [], "order": "newest_first", "country": "fr", "maxItems": 50, "browseMode": false, "maxConcurrency": 3 } ``` # Actor output Schema ## `products` (type: `string`): Complete product data including: id, title, description, price (local currency), currency, originalPrice, brand, brandId, size, sizeId, status (condition: new/like\_new/good/satisfactory), category, categoryId, color, colorId, material, city, country, sellerName, sellerId, sellerRating, sellerReviews, sellerVerified, photos (image URLs), url, favoritesCount, viewsCount, createdAt, updatedAt. ## `productsCSV` (type: `string`): CSV format export of all products for spreadsheet analysis ## `productsExcel` (type: `string`): Excel format export of all products # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "searchUrl": "", "searchText": "nike", "catalogIds": [], "brandIds": [], "sizeIds": [], "colorIds": [], "statusIds": [], "maxItems": 50 }; // Run the Actor and wait for it to finish const run = await client.actor("silentflow/vinted-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "searchUrl": "", "searchText": "nike", "catalogIds": [], "brandIds": [], "sizeIds": [], "colorIds": [], "statusIds": [], "maxItems": 50, } # Run the Actor and wait for it to finish run = client.actor("silentflow/vinted-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "searchUrl": "", "searchText": "nike", "catalogIds": [], "brandIds": [], "sizeIds": [], "colorIds": [], "statusIds": [], "maxItems": 50 }' | apify call silentflow/vinted-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=silentflow/vinted-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Vinted Scraper", "description": "Scrape Vinted marketplace data. Extract product listings, prices, seller info, images & stats. Search by keywords, brand, size, price range. Works with all Vinted countries (FR, DE, UK, ES, IT, PL, NL, BE, AT, CZ, LT). Fast & reliable API for e-commerce analysis.", "version": "1.0", "x-build-id": "I2eEVoPq2ZUWr0h9d" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/silentflow~vinted-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-silentflow-vinted-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/silentflow~vinted-scraper/runs": { "post": { "operationId": "runs-sync-silentflow-vinted-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/silentflow~vinted-scraper/run-sync": { "post": { "operationId": "run-sync-silentflow-vinted-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "searchUrl": { "title": "Search URL", "type": "string", "description": "Paste a Vinted search URL with all your filters already applied. Go to vinted.fr (or your country's Vinted), set your keywords, category, brand, size, color, price range, etc., then copy the URL from your browser. If provided, all search filters below are ignored." }, "searchText": { "title": "Search Text", "type": "string", "description": "Keywords to search for (e.g., nike, chanel, robe...)." }, "catalogIds": { "title": "Category IDs", "type": "array", "description": "Category IDs to filter (e.g., 1904=Women, 1906=Men, 1905=Kids).", "items": { "type": "string" } }, "brandIds": { "title": "Brand IDs", "type": "array", "description": "Brand IDs to filter (e.g., 53=Nike, 14=Adidas, 12=Zara).", "items": { "type": "string" } }, "sizeIds": { "title": "Size IDs", "type": "array", "description": "Size IDs to filter.", "items": { "type": "string" } }, "colorIds": { "title": "Color IDs", "type": "array", "description": "Color IDs to filter.", "items": { "type": "string" } }, "statusIds": { "title": "Condition IDs", "type": "array", "description": "Condition/status IDs (e.g., 6=New with tags, 1=New, 2=Very good).", "items": { "type": "string" } }, "order": { "title": "Sort By", "enum": [ "relevance", "newest_first", "price_high_to_low", "price_low_to_high" ], "type": "string", "description": "Sort results by.", "default": "newest_first" }, "priceFrom": { "title": "Minimum Price", "type": "number", "description": "Minimum price filter." }, "priceTo": { "title": "Maximum Price", "type": "number", "description": "Maximum price filter." }, "country": { "title": "Country", "enum": [ "fr", "de", "be", "nl", "es", "it", "pl", "pt", "lt", "cz", "at", "co.uk", "com" ], "type": "string", "description": "Vinted country/domain.", "default": "fr" }, "maxItems": { "title": "Max Results", "minimum": 0, "maximum": 10000, "type": "integer", "description": "Maximum number of results to return. The scraper automatically paginates until this limit is reached. Set to 0 for default (1000).", "default": 1000 }, "browseMode": { "title": "Browse Mode", "type": "boolean", "description": "Fetch detailed information for each item (slower, more data).", "default": false }, "maxConcurrency": { "title": "Max Concurrency", "minimum": 1, "maximum": 10, "type": "integer", "description": "Number of parallel workers for browse mode (1-10, default: 3).", "default": 3 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```