# ThredUp Scraper (`h4sh/thredup-scraper`) Actor Scrape ThredUp for secondhand clothing listings with prices, brands, sizes, conditions and savings data. The ONLY working ThredUp scraper on Apify. - **URL**: https://apify.com/h4sh/thredup-scraper.md - **Developed by:** [Dominique](https://apify.com/h4sh) (community) - **Categories:** E-commerce - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $2.00 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## 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 ## ThredUp Scraper 👗 **The most reliable ThredUp scraper on Apify** — extract secondhand fashion listings with full pricing, brand, size, condition, and photo data from the world's largest online thrift store. ### 🏆 Why This Actor? | Feature | This Actor | Other Scrapers | |---------|-----------|----------------| | **Anti-bot bypass** | ✅ Camoufox stealth browser | ❌ Basic HTTP (easily blocked) | | **Data fields** | 20+ fields per item | 5-8 basic fields | | **Search modes** | Keyword, category, brand, direct URL | URL only | | **Photo URLs** | ✅ All product photos | ❌ Missing or thumbnail only | | **Condition data** | ✅ Full condition info | ❌ Not extracted | | **Material/fabric** | ✅ Full composition | ❌ Not available | | **Promo pricing** | ✅ Current promos & discounts | ❌ Not tracked | | **Pagination** | ✅ Automatic multi-page | ⚠️ Limited | | **Reliability** | ✅ 3-layer extraction | ❌ Single strategy | ### ✨ Key Features - 👗 **Full Fashion Data** — title, brand, category, size, color, material composition - 💰 **Complete Pricing** — current price, original retail price, MSRP, promo discounts - 📸 **All Product Photos** — every photo URL for each listing - 🔍 **Flexible Search** — by keyword, department, category, or brand name - 🏷️ **Condition Tracking** — new with tags, like new, good, fair - 🛡️ **Anti-Bot Bypass** — Camoufox stealth browser defeats Cloudflare protection - 📊 **3-Layer Extraction** — Apollo GraphQL cache → API interception → HTML fallback ### 📥 Input Parameters | Parameter | Type | Default | Description | |-----------|------|---------|-------------| | `searchQuery` | string | — | Keyword search (e.g., "nike shoes", "vintage dress") | | `department` | enum | `women` | Department: women, men, kids, juniors, girls, boys, baby | | `category` | string | — | Category filter (e.g., "dresses", "shoes", "tops") | | `brand` | string | — | Brand filter (e.g., "Nike", "Zara", "Lululemon") | | `startUrls` | array | — | Direct ThredUp URLs (overrides search filters) | | `maxItems` | integer | `100` | Maximum items to scrape (1–10,000) | | `maxPages` | integer | `10` | Maximum pages per search (1–100) | | `sortBy` | enum | `recommended` | Sort: recommended, price low/high, newest, biggest discount | | `proxyConfiguration` | object | Residential | Proxy settings (residential recommended) | ### 📤 Sample Output ```json { "itemId": 220214063, "title": "Zara Casual Skirt", "description": "A-line green linen mini skirt with side ties and ruching detail", "brand": "Zara", "category": "Casual Skirt", "department": "women", "price": "10.99", "originalPrice": "21.74", "msrp": 9.99, "promoPrice": "5.49", "discountPercent": 50, "size": "Size S", "colors": ["Green"], "materials": ["47% COTTON", "53% LINEN"], "condition": "", "newWithTags": false, "categoryTags": ["skirts"], "styleTags": ["casual", "wrap"], "photoUrls": [ "https://cf-assets-thredup.thredup.com/assets/774120157/complimentary.jpg", "https://cf-assets-thredup.thredup.com/assets/774120159/complimentary.jpg", "https://cf-assets-thredup.thredup.com/assets/774018105/complimentary.jpg", "https://cf-assets-thredup.thredup.com/assets/774018107/complimentary.jpg" ], "productUrl": "https://www.thredup.com/product/women-zara-casual-skirt/220214063", "availability": "InStock", "favoriteCount": 5, "clearance": false, "scrapedAt": "2026-03-30T23:00:00.000Z" } ```` ### 💡 Use Cases - **Resale Arbitrage** — find underpriced designer items to resell on Poshmark, eBay, or Mercari - **Price Monitoring** — track secondhand pricing trends for specific brands or categories - **Market Research** — analyze the resale fashion market by category, brand, or condition - **Inventory Intelligence** — monitor competitor inventory for resale businesses - **Fashion Analytics** — study pricing patterns, popular brands, and seasonal trends in secondhand fashion - **Academic Research** — sustainability studies on clothing reuse and circular fashion economy ### 🚀 How It Works 1. **Configure** — set your search query, department, category, or brand (or provide direct URLs) 2. **Run** — the actor launches a stealth browser to navigate ThredUp 3. **Extract** — data is pulled from Apollo GraphQL cache, API responses, or HTML 4. **Paginate** — automatically navigates through multiple pages of results 5. **Output** — clean, structured JSON pushed to the Apify dataset ### 💲 Pricing - **$2 per 1,000 results** — the most affordable ThredUp data solution available - Typical run: 100 items costs ~$0.20 + minimal compute costs - Residential proxy usage included in platform costs ### ⚠️ Tips for Best Results - Use **residential proxies** (default) for highest reliability - Start with `maxItems: 50` to test, then scale up - Combine `searchQuery` with `department` and `category` for targeted results - For brand-specific data, use the `brand` filter with the brand's exact name - ThredUp has 3.5M+ women's items alone — use filters to narrow results ### 🔗 Related Actors - [Poshmark Scraper](https://apify.com/h4sh/poshmark-scraper) — scrape Poshmark resale listings - [Vinted Scraper](https://apify.com/h4sh/vinted-scraper) — scrape Vinted across 13 countries - [Etsy Scraper](https://apify.com/h4sh/etsy-scraper) — scrape Etsy shops and listings - [Anti-Bot Bypass Service](https://apify.com/h4sh/anti-bot-bypass) — bypass Cloudflare, Akamai & more *** **Built by [H4sh](https://apify.com/h4sh)** — Professional web scraping actors for the Apify Store. # Actor input Schema ## `searchQuery` (type: `string`): Keyword search term (e.g., 'nike shoes', 'vintage dress', 'lululemon leggings'). ## `department` (type: `string`): Department to search in. ## `category` (type: `string`): Optional category filter (e.g., 'dresses', 'shoes', 'tops', 'jeans', 'bags', 'activewear'). ## `brand` (type: `string`): Optional brand name to filter by (e.g., 'Nike', 'Zara', 'Lululemon'). ## `startUrls` (type: `array`): Optional: provide direct ThredUp URLs to scrape (overrides search/category/brand filters). ## `maxItems` (type: `integer`): Maximum number of items to scrape. ## `maxPages` (type: `integer`): Maximum number of pages to scrape per search/category. ## `sortBy` (type: `string`): Sort order for results. ## `proxyConfiguration` (type: `object`): Proxy settings. Residential proxies recommended. ## Actor input object example ```json { "searchQuery": "nike shoes", "department": "women", "startUrls": [], "maxItems": 100, "maxPages": 10, "sortBy": "recommended", "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } ``` # Actor output Schema ## `thredupItems` (type: `string`): Dataset containing scraped ThredUp fashion listings with pricing, brand, size, and condition data. # 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 = { "searchQuery": "nike shoes", "startUrls": [] }; // Run the Actor and wait for it to finish const run = await client.actor("h4sh/thredup-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 = { "searchQuery": "nike shoes", "startUrls": [], } # Run the Actor and wait for it to finish run = client.actor("h4sh/thredup-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 '{ "searchQuery": "nike shoes", "startUrls": [] }' | apify call h4sh/thredup-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=h4sh/thredup-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "ThredUp Scraper", "description": "Scrape ThredUp for secondhand clothing listings with prices, brands, sizes, conditions and savings data. The ONLY working ThredUp scraper on Apify.", "version": "0.1", "x-build-id": "u7iuvRQrF2KFt9hAt" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/h4sh~thredup-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-h4sh-thredup-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/h4sh~thredup-scraper/runs": { "post": { "operationId": "runs-sync-h4sh-thredup-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/h4sh~thredup-scraper/run-sync": { "post": { "operationId": "run-sync-h4sh-thredup-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "searchQuery": { "title": "Search Query", "type": "string", "description": "Keyword search term (e.g., 'nike shoes', 'vintage dress', 'lululemon leggings')." }, "department": { "title": "Department", "enum": [ "women", "men", "kids", "juniors", "girls", "boys", "baby" ], "type": "string", "description": "Department to search in.", "default": "women" }, "category": { "title": "Category", "type": "string", "description": "Optional category filter (e.g., 'dresses', 'shoes', 'tops', 'jeans', 'bags', 'activewear')." }, "brand": { "title": "Brand Filter", "type": "string", "description": "Optional brand name to filter by (e.g., 'Nike', 'Zara', 'Lululemon')." }, "startUrls": { "title": "Direct URLs", "type": "array", "description": "Optional: provide direct ThredUp URLs to scrape (overrides search/category/brand filters).", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "maxItems": { "title": "Max Items", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Maximum number of items to scrape.", "default": 100 }, "maxPages": { "title": "Max Pages", "minimum": 1, "maximum": 100, "type": "integer", "description": "Maximum number of pages to scrape per search/category.", "default": 10 }, "sortBy": { "title": "Sort By", "enum": [ "recommended", "price_low_to_high", "price_high_to_low", "newest", "biggest_discount" ], "type": "string", "description": "Sort order for results.", "default": "recommended" }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Proxy settings. Residential proxies recommended.", "default": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } } }, "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 } } } } } } } } } } ```