# Whatnot Product Extractor (`kawsar/whatnot-product-extractor`) Actor Whatnot product extractor that pulls live listings by keyword, returning titles, sellers, prices, stock, images, and direct links, so resellers, sourcing teams, and market researchers can track pricing, monitor inventory, and feed clean product data into their own tools. - **URL**: https://apify.com/kawsar/whatnot-product-extractor.md - **Developed by:** [Kawsar](https://apify.com/kawsar) (community) - **Categories:** E-commerce, Automation, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $3.99 / 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. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 ## Whatnot Product Extractor Pull live Whatnot product listings into a clean, structured dataset. Type a keyword, get every matching product card the search page shows: title, seller handle, price, stock quantity, image, and direct listing link. Run it once for a quick lookup or queue a list of keywords for a bulk pull. Built for resellers, sourcing teams, market researchers, and SEO analysts who track what is selling, who is selling it, and at what price across the Whatnot marketplace. ### What you can do with it - Track competitor pricing and stock levels for the products you care about - Build a daily catalog feed of new arrivals in a niche - Discover which sellers dominate a category and how their inventory moves - Feed product data into a Google Sheet, BigQuery, or your own internal tool - Power SEO and keyword research with real marketplace demand signals ### Input Give the actor a list of keywords. Everything else is optional. | Field | Type | Default | What it does | |-------|------|---------|--------------| | `searchQueries` | array of strings | required | One keyword per entry, each runs as its own search | | `locale` | enum | `en-GB` | Region segment in the URL, `en-US` or `en-GB` | | `maxItems` | integer | 20 | Maximum listings per keyword, capped at 1000 | | `requestTimeoutSecs` | integer | 30 | Per request timeout | Duplicate keywords are removed automatically. #### Example input ```json { "searchQueries": ["t shirts", "pokemon cards", "vintage denim"], "locale": "en-GB", "maxItems": 100 } ```` With this input the actor runs three searches and pushes up to 100 listings per keyword, so up to 300 rows total. ### Output Each listing is pushed to the dataset as a single row. ```json { "searchQuery": "t shirts", "productTitle": "Righteous Worth White Tee", "sellerHandle": "nwahype", "sellerUrl": "https://www.whatnot.com/user/nwahype", "priceText": "US$75", "priceAmount": 75.0, "currency": "USD", "quantityText": "Qty. 20", "quantityAvailable": 20, "imageUrl": "https://images.whatnot.com/fit-in/3840x0/filters:format(webp)/listings/1951995711-0-...", "listingUrl": "https://www.whatnot.com/listing/TGlzdGluZ05vZGU6MTk1MTk5NTcxMQ==", "listingId": "TGlzdGluZ05vZGU6MTk1MTk5NTcxMQ==", "scrapedAt": "2026-06-27T14:21:09.482113+00:00" } ``` #### Field reference | Field | Description | |-------|-------------| | `searchQuery` | The keyword that produced this row | | `productTitle` | Listing title as shown on the card | | `sellerHandle` | Seller username, the part after `/user/` in the URL | | `sellerUrl` | Full seller profile URL | | `priceText` | Raw price string as displayed, e.g. `US$75` | | `priceAmount` | Parsed numeric amount | | `currency` | ISO 4217 code inferred from the symbol | | `quantityText` | Raw stock string as displayed, e.g. `Qty. 20` | | `quantityAvailable` | Parsed integer count | | `imageUrl` | Product image, high resolution variant | | `listingUrl` | Direct link to the Whatnot product page | | `listingId` | Whatnot listing identifier | | `scrapedAt` | UTC timestamp of the fetch | ### How it works 1. The actor builds the Whatnot search URL for each keyword you submit. 2. It loads the page through built-in bypass infrastructure so blocks and rate limits stay out of your way. 3. To maximize coverage per keyword, the actor rotates through price-range and sort variations, deduplicates by listing ID across every variation, and pushes one dataset row per unique listing. 4. It keeps requesting variations until your `maxItems` cap is hit or fresh listings stop appearing. 5. If a single keyword fails, the actor records the error and continues with the rest of the batch. ### Tips - Use specific keywords for cleaner results, `vintage levis 501` returns more useful data than `jeans`. - Combine the dataset with Apify Webhooks to refresh your sheet or warehouse on a schedule. - Schedule the actor daily to track price and stock movement over time. ### Limits - The actor stops when Whatnot stops returning fresh listings, so popular keywords pull more rows than niche ones. - For most keywords, expect roughly 70 to 120 unique listings per run. - Hard cap of 1000 listings per keyword via `maxItems`. ### Related This actor focuses on Whatnot product listings. For seller-level data, channel stats, or live show information, run companion actors and join on `sellerHandle`. # Actor input Schema ## `searchQueries` (type: `array`): One or more keywords to search for on Whatnot, for example 't shirts', 'pokemon cards', 'vintage denim'. Each entry runs as a separate search. ## `locale` (type: `string`): Language and region segment used in the Whatnot URL path. ## `maxItems` (type: `integer`): Maximum number of product listings to return per keyword. Each keyword fills up to this cap independently. ## `requestTimeoutSecs` (type: `integer`): Per-request timeout in seconds. ## Actor input object example ```json { "searchQueries": [ "t shirts", "vintage denim" ], "locale": "en-GB", "maxItems": 20, "requestTimeoutSecs": 30 } ``` # 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 = { "searchQueries": [ "t shirts", "vintage denim" ] }; // Run the Actor and wait for it to finish const run = await client.actor("kawsar/whatnot-product-extractor").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 = { "searchQueries": [ "t shirts", "vintage denim", ] } # Run the Actor and wait for it to finish run = client.actor("kawsar/whatnot-product-extractor").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 '{ "searchQueries": [ "t shirts", "vintage denim" ] }' | apify call kawsar/whatnot-product-extractor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=kawsar/whatnot-product-extractor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Whatnot Product Extractor", "description": "Whatnot product extractor that pulls live listings by keyword, returning titles, sellers, prices, stock, images, and direct links, so resellers, sourcing teams, and market researchers can track pricing, monitor inventory, and feed clean product data into their own tools.", "version": "0.0", "x-build-id": "FVTwcX93XFbXO35m4" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/kawsar~whatnot-product-extractor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-kawsar-whatnot-product-extractor", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/kawsar~whatnot-product-extractor/runs": { "post": { "operationId": "runs-sync-kawsar-whatnot-product-extractor", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/kawsar~whatnot-product-extractor/run-sync": { "post": { "operationId": "run-sync-kawsar-whatnot-product-extractor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "searchQueries": { "title": "Search keywords", "type": "array", "description": "One or more keywords to search for on Whatnot, for example 't shirts', 'pokemon cards', 'vintage denim'. Each entry runs as a separate search.", "items": { "type": "string" } }, "locale": { "title": "Locale", "enum": [ "en-US", "en-GB" ], "type": "string", "description": "Language and region segment used in the Whatnot URL path.", "default": "en-GB" }, "maxItems": { "title": "Max items per keyword", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum number of product listings to return per keyword. Each keyword fills up to this cap independently.", "default": 20 }, "requestTimeoutSecs": { "title": "Request timeout (seconds)", "minimum": 5, "maximum": 120, "type": "integer", "description": "Per-request timeout in seconds.", "default": 30 } } }, "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 } } } } } } } } } } ```