# Nellis Auction Scraper (`lulzasaur/nellisauction-scraper`) Actor Scrape Nellis Auction retail-returns & liquidation lots. Per-lot data: title, current bid, bid count, retail/MSRP price, condition, category, location (city/state/zip), close date, images, and lot URL. Search by keyword or browse all active lots. - **URL**: https://apify.com/lulzasaur/nellisauction-scraper.md - **Developed by:** [lulz bot](https://apify.com/lulzasaur) (community) - **Categories:** E-commerce - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $5.00 / 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 ## Nellis Auction Scraper Scrape **[Nellis Auction](https://www.nellisauction.com)** — one of the largest retail-returns and liquidation online auction marketplaces in the US (Las Vegas, Phoenix, Houston, Dallas, Atlanta and more). Find deeply discounted merchandise: electronics, tools, furniture, appliances, home goods and Amazon returns sold to the highest bidder. Search by keyword or browse **all active lots nationwide**, and get clean structured data per lot — including **live current bid**, **retail/MSRP price**, condition, category, location and close time. ### What you get per lot | Field | Description | |-------|-------------| | `lotId` | Nellis lot ID | | `title` | Item title / lead description | | `currentBid` | Live current highest bid (USD) | | `bidCount` | Number of bids placed | | `retailPrice` | Suggested retail / MSRP (USD) | | `condition` | Item condition / grade (New, Open Box, etc.) | | `category` | Category (Electronics, Tools, Furniture...) | | `brand` | Brand name | | `city`, `state`, `zipCode`, `address` | Pickup / warehouse location | | `locationName`, `shoppingLocation` | Warehouse name & shopping market | | `endDate` | Auction close time (ISO 8601) | | `openTime`, `initialCloseTime` | Auction open / original close time | | `marketStatus`, `isClosed` | Live status | | `imageUrl`, `images` | Primary image + full photo gallery | | `rating`, `ratingCount`, `starRating` | Product ratings | | `taxonomyLevel1`, `taxonomyLevel2` | Category taxonomy | | `inventoryNumber` | Internal inventory number | | `itemUrl` | Direct link to the lot | | `scrapedAt` | ISO timestamp of scrape | ### Input ```json { "searchQueries": ["macbook", "power tools"], "maxResults": 100, "scrapeDetails": true, "proxyConfiguration": { "useApifyProxy": true } } ```` - **searchQueries** — keywords to search. Leave empty (`[]`) to browse **all** active lots. - **maxResults** — cap on total records. Use `0` for ALL matching lots (tens of thousands — use with care). - **scrapeDetails** — `true` (default) fetches each lot's page for **live current bid**, exact location, full photo gallery and taxonomy. Set `false` for a faster run using just the search index (no live bid). - **proxyConfiguration** — defaults to Apify datacenter proxy. Switch to RESIDENTIAL if you hit rate limits on very large runs. ### Example output ```json { "lotId": "115920408", "title": "2020 Apple MacBook Pro with Apple M1 Chip (13-inch, 8GB RAM, 512GB SSD Storage)", "currentBid": 104, "bidCount": 28, "retailPrice": 1499, "condition": "Open Box", "category": "Electronics", "brand": "Apple", "city": "Las Vegas", "state": "NV", "zipCode": "89139", "locationName": "Dean Martin", "endDate": "2026-07-04T03:07:00.000Z", "marketStatus": "open", "imageUrl": "https://firebasestorage.googleapis.com/...", "itemUrl": "https://www.nellisauction.com/p/item/115920408", "scrapedAt": "2026-07-03T06:40:00.000Z" } ``` ### Use cases - **Resale arbitrage** — find lots selling far below retail (compare `currentBid` vs `retailPrice`). - **Deal hunting & sniping** — monitor closing lots by category and location. - **Market research** — track liquidation pricing and inventory trends. - **Dropshipping / inventory sourcing** — bulk-source returned goods. ### How it works The scraper uses Nellis Auction's own public search index for fast discovery, then reads each lot's server-rendered page for live bid, price and location data. No login required. Data is delivered to the Apify dataset and downloadable as JSON, CSV, Excel or via API. ### Notes - This is an unofficial scraper for publicly available data. Respect Nellis Auction's Terms of Service. - Auctions are live — `currentBid` and `endDate` reflect the moment of scraping. # Actor input Schema ## `searchQueries` (type: `array`): Keywords to search Nellis Auction lots, e.g. 'macbook', 'power tools', 'patio furniture'. Add multiple to search each. Leave EMPTY to browse ALL active lots. ## `maxResults` (type: `integer`): Maximum number of lot records to return (across all queries). Use 0 to fetch ALL matching lots via pagination (can be tens of thousands). Default 100. ## `scrapeDetails` (type: `boolean`): When ON (default), fetch each lot's product page for live current bid, bid count, exact location (city/state/zip), full photo gallery and taxonomy. When OFF, use only the fast search index (no live bid). ## `proxyConfiguration` (type: `object`): Proxy settings. Nellis has no hard anti-bot, so Apify datacenter proxy is sufficient. Switch to RESIDENTIAL if you hit rate limits on large runs. ## Actor input object example ```json { "searchQueries": [ "macbook" ], "maxResults": 100, "scrapeDetails": true, "proxyConfiguration": { "useApifyProxy": true } } ``` # Actor output Schema ## `results` (type: `string`): No description # 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": [ "macbook" ], "proxyConfiguration": { "useApifyProxy": true } }; // Run the Actor and wait for it to finish const run = await client.actor("lulzasaur/nellisauction-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 = { "searchQueries": ["macbook"], "proxyConfiguration": { "useApifyProxy": True }, } # Run the Actor and wait for it to finish run = client.actor("lulzasaur/nellisauction-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 '{ "searchQueries": [ "macbook" ], "proxyConfiguration": { "useApifyProxy": true } }' | apify call lulzasaur/nellisauction-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=lulzasaur/nellisauction-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Nellis Auction Scraper", "description": "Scrape Nellis Auction retail-returns & liquidation lots. Per-lot data: title, current bid, bid count, retail/MSRP price, condition, category, location (city/state/zip), close date, images, and lot URL. Search by keyword or browse all active lots.", "version": "1.0", "x-build-id": "lSCcLPrPyql85n74W" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/lulzasaur~nellisauction-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-lulzasaur-nellisauction-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/lulzasaur~nellisauction-scraper/runs": { "post": { "operationId": "runs-sync-lulzasaur-nellisauction-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/lulzasaur~nellisauction-scraper/run-sync": { "post": { "operationId": "run-sync-lulzasaur-nellisauction-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "searchQueries": { "title": "Search Queries", "type": "array", "description": "Keywords to search Nellis Auction lots, e.g. 'macbook', 'power tools', 'patio furniture'. Add multiple to search each. Leave EMPTY to browse ALL active lots.", "items": { "type": "string" } }, "maxResults": { "title": "Max Results", "minimum": 0, "type": "integer", "description": "Maximum number of lot records to return (across all queries). Use 0 to fetch ALL matching lots via pagination (can be tens of thousands). Default 100.", "default": 100 }, "scrapeDetails": { "title": "Scrape Live Detail (current bid, exact location, photos)", "type": "boolean", "description": "When ON (default), fetch each lot's product page for live current bid, bid count, exact location (city/state/zip), full photo gallery and taxonomy. When OFF, use only the fast search index (no live bid).", "default": true }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Proxy settings. Nellis has no hard anti-bot, so Apify datacenter proxy is sufficient. Switch to RESIDENTIAL if you hit rate limits on large runs.", "default": { "useApifyProxy": true } } } }, "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 } } } } } } } } } } ```