Whatnot All-in-One Scraper ⭐

From $1.00 / 1,000 items — The most complete scraper for Whatnot.com, the #1 live shopping marketplace for collectibles, trading cards, sneakers, and more. Search listings, extract seller profiles with reviews and shows, analyze category trends, browse leaderboards, and explore the entire marketplace — all in a single Apify Actor with no login, no API key, and no authentication required.

Search by keyword, URL, seller, user ID, or category. Returns listings, live streams, products, seller profiles, reviews, shop items, show schedules, category analytics, and ranked leaderboards. Up to 10,000,000 items per run. Built on Whatnot's native GraphQL API for speed and reliability.

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🚀 Features

• 🔍 Search by keyword or URL — Search Whatnot by text query or paste a full Whatnot search URL (query params parsed automatically). Supports multiple queries and URLs in a single run. Filter results by vertical: products, live streams, users, or categories.
• 👤 Seller intelligence — Extract seller profiles with bio, follower count, sold count, average ship days, seller rating, and verification status. Pull live and upcoming shows, buyer reviews with rating distribution, and shop listings (buy-it-now and auctions).
• 🗂️ Category analytics — Browse all Whatnot categories with viewer counts, discover trending categories ranked by popularity, deep-dive into any category for subcategories, filter/sort options, live shows, and seller leaderboards.
• 🏆 Seller leaderboards — Extract ranked seller leaderboards per category for daily, weekly, or live intervals. See top sellers, their follower counts, sold counts, ratings, and active livestream viewers.
• 🔬 Category explore pipeline — Automatically discover all categories, fetch detailed analytics and subcategories for each, then retrieve live shows — all in one run. Perfect for market research and competitive analysis.
• 📦 Bulk seller extraction — Process hundreds of sellers in a single execution. Each seller gets profile metrics, shows, reviews, and listings — all in parallel for maximum speed.
• 🔄 Auto-pagination — Handles multi-page pagination across all data types automatically. Set your result limits and the actor does the rest.
• 🔗 URL search with full param parsing — Paste any Whatnot search URL and the actor extracts the query, vertical, sort, and referring source. What you see in your browser is what you get in your data.
• 🔒 No authentication required — All data fetched from Whatnot's public GraphQL API. No login, cookies, or API keys needed. Optional cookie support for personalized results.
• 🌐 Apify proxy integration — Built-in proxy support for reliable large-scale runs.

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📋 What You Get

Every search result returns up to 10+ types of structured data depending on the mode. Here's a breakdown of the key output shapes:

Search Results (listings, live streams, products, users)

Field	Description	Example
type	Record type identifier	"listing"
id	Unique Whatnot identifier	"TGlzdGluZ05vZGU6MTQxNzQ4Njk4MQ=="
title	Listing or stream title	"Pokemon - Mimikyu - #1013"
searchQuery	Search term that produced this result	"pokemon cards"
vertical	Search vertical used	"PRODUCT"
scrapedAt	ISO timestamp of extraction	"2026-06-23T12:00:00.000Z"

Listing-specific fields

Field	Description	Example
price	Price with amount and currency	{"amountSafe": 9.00, "currency": "USD"}
currentBid	Current auction bid amount	{"amountSafe": 15.50, "currency": "USD"}
currentBidCount	Number of bids placed	3
transactionType	Buy-it-now or auction	"BUY_NOW"
quantity	Available quantity	1
isLive	Related to an active stream	false
user	Seller profile snapshot	{"id": "...", "username": "tagteamtrading"}
images	Product image URLs	[{"id": "...", "url": "https://..."}]

Livestream-specific fields

Field	Description	Example
status	Stream status	"PLAYING"
activeViewers	Current viewer count	450
startTime	Stream start time	"2026-02-13T10:00:00Z"
thumbnail	Stream thumbnail images	{"smallImage": "https://...", "biggerImage": "https://..."}
tags	Category tags for the stream	[{"id": "...", "name": "Pokémon Cards"}]
streamToken	Stream access token	"abc123..."

Seller Profile

Field	Description	Example
seller.username	Whatnot username	"tagteamtrading"
seller.displayName	Display name	"Tag Team Trading"
seller.userId	Numeric user ID	"18249573"
profileMetrics.followerCount	Number of followers	1500
profileMetrics.soldCount	Total items sold	5000
profileMetrics.averageShipDays	Average shipping days	3
profileMetrics.rating	Overall seller rating (0–5)	4.9
profileMetrics.numReviews	Number of seller reviews	1200
profileMetrics.isVerifiedSeller	Whatnot verified status	true
profileMetrics.isLive	Currently streaming	true
profileMetrics.canGoLive	Eligible to go live	true
shows	Live and upcoming shows	(see shows table)
reviews	Buyer reviews with distribution	(see reviews table)
listings	Shop listings (buy-it-now + auction)	(see listings table)

Buyer Reviews

Field	Description	Example
reviews[].averageRating	Overall rating for this review	5.0
reviews[].overallReview	Review text	"Fast shipping, well packed!"
reviews[].reviewedOn	Date of review	"2026-06-15"
reviews[].ratingOverall	Overall star rating	5
reviews[].ratingShipping	Shipping star rating	5
reviews[].reviewedBy	Reviewer's username	"jdoe"
reviews[].sellerResponse	Seller's reply	"Thanks for the kind words!"
ratingDistribution	Percentage per star level	{"5.0": "~80%", "4.0": "~12%", ...}

Shop Listings

Field	Description	Example
listings[].id	Listing identifier	"TGlzdGluZ05vZGU6MTQxNzQ4Njk4MQ=="
listings[].title	Listing title	"2024 NFL Prizm White Sparkle Pack"
listings[].price.amountSafe	Listing price	1499.0
listings[].price.currency	Currency	"USD"
listings[].transactionType	Buy-it-now or auction	"ASYNC_AUCTION"
listings[].quantity	Available quantity	10
listings[].totalBookmarks	Times bookmarked	42
listings[].listingStatus	Listing status	"ACTIVE"
listings[].auctionInfo	Auction details if applicable	{"currentPrice": {...,}, "bidCount": 5, "endTime": "..."}
listings[].updatedAt	Last update timestamp	"2026-06-20T15:30:00Z"

Category Data

Field	Description	Example
categories[].tagId	Base64 category tag ID	"TGl2ZXN0cmVhbVRhZ05vZGU6ODk5"
categories[].name	Category name	"Pokémon Cards"
categories[].label	Category label	"Pokémon Cards"
categories[].viewerCount	Current viewer count	18500
categories[].livestreamCount	Active livestream count	124
categories[].description	Category description	"Browse live auctions for Pokémon Cards"
categories[].subcategories	Subcategory refinements	[{"tagId": "...", "label": "Vintage", "viewerCount": 3200}]
categories[].topShows	Top live shows in category	(see shows table)

Trending Categories

Field	Description	Example
trendingCategories[].rank	Rank by viewer count	1
trendingCategories[].name	Category name	"Pokémon Cards"
trendingCategories[].viewerCount	Current viewer count	18500

Seller Leaderboard

Field	Description	Example
leaderboard.interval	Leaderboard time interval	"CURRENT_DAY"
leaderboard.totalSellers	Number of ranked sellers	50
leaderboard.sellers[].username	Seller's username	"top_seller_1"
leaderboard.sellers[].followerCount	Seller follower count	8500
leaderboard.sellers[].soldCount	Items sold (first page only)	15000
leaderboard.sellers[].sellerRating	Seller rating summary	{"overall": 4.9, "numReviews": 1200}
leaderboard.sellers[].currentActiveLivestream	Live stream info if active	{"id": "...", "activeViewers": 320}

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📥 Input

The actor accepts a rich input schema depending on the selected mode. Key inputs:

Input	Required	Default	Description
mode	✅ Yes	"search"	Scraping mode: "search", "seller", or "category"
searchUrls	No	—	Whatnot search URLs to scrape
searchQueries	No	—	Search terms (e.g. "pokemon cards")
vertical	No	"PRODUCT"	Search vertical: UNIVERSAL, LIVESTREAM, PRODUCT, USER, CATEGORY
usernames	No	—	Seller usernames for seller mode
userIds	No	—	Numeric user IDs for seller mode
categoryView	No	"list"	Category view: list, trending, deep-dive, explore
categoryTagId	No	—	Category names from the built-in dropdown
maxResults	No	100	Default result limit across all modes
cookies	No	—	Optional browser cookies for personalized results
proxyConfiguration	No	—	Apify proxy settings

Example Input — Search by Query

{
  "mode": "search",
  "searchQueries": ["pokemon cards", "sneakers"],
  "vertical": "UNIVERSAL",
  "includeListings": true,
  "includeLivestreams": true,
  "includeProducts": true,
  "includeUsers": false,
  "maxResults": 200,
  "maxResultsPerQuery": 100
}

Example Input — Seller Profile with All Data

{
  "mode": "seller",
  "usernames": ["ah_sneakers", "tagteamtrading"],
  "includeProfile": true,
  "includeShows": true,
  "includeReviews": true,
  "includeShop": true,
  "maxShows": 25,
  "maxReviews": 50,
  "maxListings": 50
}

Example Input — Category Deep Dive

{
  "mode": "category",
  "categoryView": "deep-dive",
  "categoryTagId": ["Trading Card Games > Pokémon Cards", "Sneakers & Shoes > Sneakers"],
  "fetchDetails": true,
  "fetchShows": true,
  "fetchRankings": true,
  "showStatus": "live",
  "maxShows": 25,
  "interval": "CURRENT_DAY"
}

Example Output — Search Results

[
  {
    "type": "listing",
    "id": "TGlzdGluZ05vZGU6MTQxNzQ4Njk4MQ==",
    "title": "Pokemon - Mimikyu - #1013 - Fusion Strike",
    "description": "NM-Mint condition, sleeved and shipped in top loader",
    "price": { "amountSafe": 9.00, "currency": "USD" },
    "transactionType": "BUY_NOW",
    "quantity": 1,
    "currentBid": null,
    "currentBidCount": null,
    "isLive": false,
    "images": [{ "id": "SW1hZ2U6MTIzNDU2", "url": "https://images.whatnot.com/...", "label": "FRONT" }],
    "user": { "id": "UHVibGljVXNlck5vZGU6MTgyNDk1NzM=", "username": "tagteamtrading" },
    "publicStatus": "PUBLISHED",
    "searchQuery": "pokemon cards",
    "vertical": "PRODUCT",
    "scrapedAt": "2026-06-23T12:00:00.000Z"
  },
  {
    "type": "livestream",
    "id": "TGl2ZVN0cmVhbToxMjM0NTY3OA==",
    "title": "LIVE Pokemon Card Breaks & Mystery Packs!",
    "status": "PLAYING",
    "activeViewers": 320,
    "startTime": "2026-06-23T11:30:00Z",
    "thumbnail": {
      "smallImage": "https://images.whatnot.com/w:414/...",
      "biggerImage": "https://images.whatnot.com/w:642/..."
    },
    "tags": [{ "id": "TGl2ZXN0cmVhbVRhZ05vZGU6ODk5", "name": "Pokémon Cards", "label": "Pokémon Cards" }],
    "user": { "id": "UHVibGljVXNlck5vZGU6MTgyNDk1NzM=", "username": "card_breaker" },
    "searchQuery": "pokemon cards",
    "vertical": "LIVESTREAM",
    "scrapedAt": "2026-06-23T12:00:00.000Z"
  },
  {
    "type": "product",
    "id": "UHJvZHVjdE5vZGU6NTY3ODkw",
    "name": "Pokémon Trading Card Game: Scarlet & Violet Booster Box",
    "listingPrice": { "amountSafe": 159.99, "currency": "USD" },
    "lastSalePrice": { "amountSafe": 144.50, "currency": "USD" },
    "numListings": 47,
    "image": { "id": "SW1hZ2U6NTY3ODkw", "url": "https://images.whatnot.com/..." },
    "searchQuery": "pokemon cards",
    "vertical": "PRODUCT",
    "scrapedAt": "2026-06-23T12:00:00.000Z"
  }
]

Example Output — Seller Profile

{
  "seller": {
    "username": "ah_sneakers",
    "displayName": "AH Sneakers",
    "userId": "18249573"
  },
  "profileMetrics": {
    "followerCount": 23400,
    "soldCount": 89700,
    "averageShipDays": 2,
    "rating": 4.8,
    "numReviews": 14200,
    "isVerifiedSeller": true,
    "isLive": true,
    "canGoLive": true
  },
  "shows": {
    "username": "ah_sneakers",
    "showStatus": "live",
    "totalShows": 2,
    "hasMore": false,
    "shows": [
      {
        "id": "TGl2ZVN0cmVhbToxMjM0NTY3OA==",
        "title": "LIVE: Rare Jordans & Yeezys Auction 🔥",
        "startTime": "2026-06-23T10:30:00Z",
        "activeViewers": 665,
        "status": "PLAYING",
        "categories": [{ "name": "Sneakers", "label": "Sneakers" }],
        "sellerRating": 4.8
      }
    ]
  },
  "reviews": {
    "userId": "18249573",
    "totalReviews": 5,
    "hasMore": true,
    "reviews": [
      {
        "averageRating": 5.0,
        "overallReview": "Fast shipping, great condition!",
        "reviewedOn": "2026-06-20",
        "ratingOverall": 5,
        "ratingShipping": 5,
        "reviewedBy": "jdoe",
        "sellerResponse": "Thanks for the support!"
      }
    ],
    "ratingDistribution": { "5.0": "~80%", "4.0": "~15%", "3.0": "~3%", "2.0": "~1%", "1.0": "~1%" }
  },
  "fetchedAt": "2026-06-23T12:00:00.000Z"
}

---

💡 Use Cases

📊 Market Research — Track Pricing Trends Across Categories

A trading card reseller wants to understand how Pokémon card prices vary across different sellers and conditions on Whatnot. Running the Search mode with queries like "charizard", "moonbreon", and "PSA 10" across the PRODUCT vertical returns every active listing with prices (price.amountSafe), condition-related labels (listingLabels), and seller ratings (user.sellerRating.overall). By analyzing the lastSalePrice from product catalog entries, the reseller can identify which cards are undervalued relative to market comps on other platforms.

The reseller then runs the Category Deep Dive for "Trading Card Games > Pokémon Cards" with fetchRankings: true to see the top sellers in that category, their follower counts, and sold volumes. Cross-referencing seller ratings (rating) against price data reveals which top sellers offer the best value. Exporting to CSV enables pivot tables by card name, price range, and seller rating tier.

Outcome: Data-driven buying decisions that identify arbitrage opportunities, saving thousands on inventory acquisition.

🏪 Competitive Intelligence — Monitor Seller Activity and Strategy

A sneaker boutique wants to monitor top competitors on Whatnot. Using Seller mode with a list of competitor usernames, the business extracts each seller's complete profile metrics (followerCount, soldCount, averageShipDays), active shows with viewer counts (shows[].activeViewers), and shop listings with prices (listings[].price). By scheduling the actor to run daily via Apify's scheduler, the boutique builds a time-series dataset of competitor activity.

Analyzing show schedules (shows[].startTime, shows[].status) reveals when competitors go live and how many viewers they attract. Shop listing changes (listings[].updatedAt) show which inventory moves fast and which sits unsold. The listingLabels field reveals promotional strategies like "BUNDLE_DEAL" or "FREE_SHIPPING" that competitors use to convert buyers.

Outcome: Real-time competitive intelligence that informs pricing, scheduling, and promotional strategy — without manual data collection.

🏆 Category Trend Discovery — Identify Emerging Markets Before They Peak

A collectibles investor wants to find the next hot category before it blows up on Whatnot. Running the Trending Categories view returns all categories ranked by viewerCount, showing which verticals are gaining live audience attention. The investor then runs the Explore pipeline, which automatically discovers all categories, fetches detailed analytics (livestreamCount, subcategories, description), and retrieves top live shows for each.

Sorting by viewerCount reveals that "Labubu & Blind Boxes" jumped from 2,000 to 28,000 viewers in a week. The subcategories array shows sub-niches like "Labubu Macarons" and "Labubu Have a Seat" emerging. The topShows data reveals which sellers are capitalizing on the trend and how many viewers they're pulling. The investor can then use Seller mode to analyze those early-mover sellers.

Outcome: Early identification of trending categories enables strategic inventory positioning before prices rise and competition intensifies.

📈 Seller Reputation Analysis — Evaluate Trustworthiness Before Bulk Purchases

A wholesale buyer wants to source inventory from Whatnot sellers but needs to verify seller reliability first. Using Seller mode, the buyer extracts seller profiles for 50+ candidate sellers, getting rating, numReviews, soldCount, averageShipDays, and isVerifiedSeller status. The ratingDistribution in the reviews output shows whether a seller's 5-star rating is genuine (e.g., "5.0": "~85%" with healthy distribution) or suspicious ("5.0": "~100%" with zero lower ratings).

The buyer can filter for sellers with averageShipDays <= 3, rating >= 4.8, and soldCount >= 1000 — the sweet spot for reliable volume sellers. The sellerResponse field in individual reviews reveals how sellers handle complaints, a key trust signal. Exporting to JSON enables integration with internal vendor management systems.

Outcome: A vetted, ranked list of trustworthy sellers for wholesale partnerships, reducing fraud risk and shipping delays.

🎯 Lead Generation — Identify High-Performing Sellers for Partnership Outreach

A platform that provides seller tools and services wants to identify top Whatnot sellers for partnership outreach. Running the Seller Leaderboard via Category Deep Dive with intervals set to "CURRENT_WEEK" returns the top-performing sellers per category with followerCount, soldCount, and sellerRating. The leaderboard covers categories from "Trading Card Games" to "Sneakers" to "Jewelry & Watches" — every vertical where sellers compete.

Each leaderboard entry includes the seller's username and currentActiveLivestream viewer count, enabling outreach teams to prioritize sellers who are actively engaged. Running Seller mode on targeted usernames enriches the lead with full profile data (bio, premierShopStatus, shippingSourceCountryCode) for personalized outreach. The isVerifiedSeller flag helps qualify leads as established businesses.

Outcome: A prioritized, enriched pipeline of top seller leads across every Whatnot category — built in minutes, not days.

🔬 Live Commerce Research — Understand Viewer Engagement Patterns

A market analyst researching the live commerce space needs to quantify viewer engagement patterns on Whatnot. Using the Explore pipeline, the analyst collects data on every category: viewerCount, livestreamCount, and topShows[].activeViewers. Cross-referencing category viewer counts against show counts reveals engagement density — categories with few shows but high viewer counts indicate high-demand, low-supply opportunities.

The analyst then runs Search mode with vertical: "LIVESTREAM" across multiple queries to collect a broad sample of live streams with activeViewers, startTime, and seller ratings (user.sellerRating.overall). Time-series analysis of startTime and activeViewers reveals peak live shopping hours. The seller leaderboard data, combined with follower counts and rating distributions, provides a comprehensive picture of the platform's seller economy.

Outcome: A research-grade dataset on live commerce engagement, suitable for reports, investor decks, or published market analysis.

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🔗 Related Actors

Explore more scrapers from the same developer:

Actor	Description
Whatnot Seller Review Scraper	Extract seller reviews, ratings, and reviewer data from any Whatnot seller — fast and focused.
Whatnot Search Scraper — Listings, Streams & Seller Data	Search Whatnot by keyword or URL for listings, live streams, and seller profiles.
Vinted Scraper + Monitor	Monitor and extract product listings, prices, and seller data from Vinted.
Chrono24 Scraper	Scrape watch listings from Chrono24 with prices, images, and seller details.
DripShop Scraper	Extract trading cards, box breaks, and live stream data from DripShop.live.
Flippa Listings Scraper	Scrape online business and website listings from Flippa.com.

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❓ Frequently Asked Questions

How do I search Whatnot with this scraper?

You can search in two ways: by keyword (enter text queries like "pokemon cards" or "vintage sneakers") or by URL (paste a full Whatnot search URL like https://www.whatnot.com/search?query=pokemon&searchVertical=PRODUCT). Both methods support multiple entries in a single run. When searching by keyword, you can also filter by vertical (products only, live streams only, users, categories, or all) using the vertical input field.

How many results can I get in one run?

You can set maxResults up to 10,000,000 items. Each mode has its own practical limits: search (millions of results), seller (per-seller limits configurable), and category (capped by categories). The maxResultsPerQuery input overrides the default budget, allowing each query or URL to get its own full allocation. For bulk seller extraction, you can pass hundreds of usernames in a single run and each seller is processed independently.

Do I need a Whatnot account or API key?

No. All data is fetched from Whatnot's public GraphQL API — no login, cookies, or API keys required. The scraper mimics a standard browser session with realistic headers. If you want personalized or region-specific results, you can optionally provide browser cookies via the cookies input field (marked as secret for security).

What geographic coverage does this scraper have?

Whatnot.com is a US-based platform, and the scraper accesses the global public marketplace. Results are in USD and English. The shippingSourceCountryCode field in seller profiles indicates the seller's shipping origin. For region-specific results, you can optionally provide cookies from a session logged into a specific regional version of Whatnot.

How fresh is the data?

Every run fetches live data in real-time from Whatnot's GraphQL API. Search results reflect current listings, active live streams, and up-to-date pricing. Seller profiles show current follower counts, ratings, and sold counts. Shows include both currently playing (PLAYING) and upcoming (CREATED) streams with real-time viewer counts. The scrapedAt and fetchedAt fields provide per-record timestamps.

What export formats are available?

Your data is available in JSON, CSV, XML, Excel (XLSX), HTML, and RSS — all directly from the Apify Console's Dataset tab. You can also access the data programmatically via the Apify REST API, webhooks, or integrations with Make, Zapier, Google Sheets, and Airbyte. Each dataset item is a structured JSON object with clearly labeled fields ready for analysis.

How is this different from other Whatnot scrapers on Apify?

This is the only Whatnot scraper that covers all three modes — search, seller, and category — in a single actor. Other scrapers focus on just one area (e.g., seller profiles only or search results only). This actor additionally offers category analytics (viewer counts, subcategories, filter/sort options), trending categories (ranked by popularity), seller leaderboards per category, and the Explore pipeline (auto-discover categories → fetch details → get shows). It supports search by URL with full param parsing, 70+ pre-mapped subcategories, and bulk seller extraction for hundreds of sellers.

Can I scrape auction data and live bids?

Yes. Search results include currentBid and currentBidCount for auction listings. Seller shop listings include full auctionInfo with currentPrice, bidCount, and endTime. The transactionType field distinguishes buy-it-now (BUY_NOW) from auction (ASYNC_AUCTION) listings. For live streams, activeViewers and totalWatchlistUsers provide real-time engagement metrics.

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📚 Technical Details

How It Works

The actor communicates directly with Whatnot's public GraphQL API, using the same endpoints the Whatnot web app uses. Each mode dispatches to a dedicated handler that constructs the appropriate GraphQL queries, handles cursor-based pagination, and normalizes the response into structured output. Search mode supports multi-vertical UNIVERSAL searches that run up to 4 vertical queries in parallel and interleave results. Seller mode resolves usernames to numeric user IDs, then fetches profile, shows, reviews, and listings in parallel for each seller. Category mode supports four views — list, trending, deep-dive (multi-category with parallel sub-fetches), and explore (pipeline that discovers → details → shows).

Error Handling

• GraphQL errors — Error messages from Whatnot's API are surfaced with context (operation name and message). Runs fail fast with clear error messages.
• Seller not found — Individual seller failures are caught and logged as warnings. Other sellers in the same run continue processing. The run only fails if all sellers fail.
• Category not found — Category deep-dive skips failed categories and reports success/failure counts. Failed categories receive an error flag in the output.
• Rate limiting — Built-in 300ms delay between pages and 2 retries on 408/429/500/502/503/504 status codes. Concurrency is handled by JavaScript's single-threaded event loop.
• Proxy failures — If the configured proxy URL is invalid, the actor falls back to direct requests with a warning.

Data Integrity

• Deduplication — Category tag IDs are deduplicated before processing. Seller inputs from duplicate usernames are processed independently.
• Timestamps — Every record includes an ISO 8601 scrapedAt or fetchedAt timestamp for time-series accuracy.
• Structured normalization — Each GraphQL response is normalized into a consistent output shape with predictable field names and types. Null fields are explicitly set to null (not omitted).
• Charge tracking — Each item is counted via Actor.charge() for accurate billing and usage tracking.
• Error isolation — In multi-seller and multi-category modes, failures are isolated to the individual entity — a bad seller or category never blocks valid ones.

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⚠️ Disclaimer

This Actor is an independent tool and is not affiliated with, endorsed by, or sponsored by Whatnot, Inc. or any of its subsidiaries. All trademarks are the property of their respective owners.

This Actor accesses only publicly available data on whatnot.com. You are solely responsible for ensuring your use complies with the site's Terms of Service and applicable laws.