# Bidspotter Auctions category Spider (`getdataforme/bidspotter-auctions-category-spider`) Actor The Bidspotter Auctions Category Spider efficiently scrapes auction data from Bidspotter, allowing users to extract detailed information on lots based on keywords, categories, and locations.... - **URL**: https://apify.com/getdataforme/bidspotter-auctions-category-spider.md - **Developed by:** [GetDataForMe](https://apify.com/getdataforme) (community) - **Categories:** E-commerce - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $9.00 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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 --- ## Bidspotter Auctions Category Spider ### Introduction The Bidspotter Auctions Category Spider is designed to efficiently scrape auction data from the Bidspotter platform. It allows users to extract detailed information about various auction lots based on specified criteria such as keywords, categories, and locations. This tool is invaluable for conducting market research, competitive analysis, and price monitoring. ### Features - **Comprehensive Data Extraction**: Scrape detailed auction lot information including titles, descriptions, images, and bid details. - **Customizable Search Parameters**: Configure searches using keywords, category codes, search terms, and more to tailor data extraction. - **High-Quality Data Output**: Ensure reliable and accurate data for analysis with structured JSON output. - **Scalable Performance**: Set item limits to manage large datasets efficiently during each run. - **User-Friendly Configuration**: Easy setup with intuitive input parameters for seamless operation. ### Input Parameters | Parameter | Type | Required | Description | Example | |-------------------|----------|----------|-----------------------------------------------------------------------------|-----------------------------| | Keywords | array | No | The keywords for the spider. | `["fan"]` | | Categorycode | array | No | The category code for the spider. | `["1234", "5678"]` | | Searchterm | string | No | The search term for the spider. | `"air compressor"` | | Type | string | No | The type for the spider. | `"equipment"` | | Distancelocation | integer | No | The distance location for the spider. | `50` | | Postcodelocation | integer | No | The postal code location for the spider. | `90210` | | Countrylocation | string | No | The country location for the spider. | `"USA"` | | Sortterm | string | No | The sort term for the spider. | `"date"` | | Item limit | integer | No | Maximum items to scrape per actor run. Set to 0 for no limit. | `10` | ### Example Usage #### Input JSON ```json { "Keywords": ["fan"], "Categorycode": ["1234"], "Searchterm": "air compressor", "Type": "equipment", "Distancelocation": 50, "Postcodelocation": 90210, "Countrylocation": "USA", "Sortterm": "date", "item_limit": 10 } ```` #### Output JSON ```json [ { "lot_number": "aaf9d35d-f04e-4130-aec8-b460011d4699", "title": "Walk in Cold Storage Rooms- Overall Dims Approx 12'4\" L X 8'3\" W X 8'6\" tall, Inside Dims Approx", "url": "https://www.bidspotter.com/en-us/auction-catalogues/new-mill-capital/catalogue-id-bscnew10514/lot-aaf9d35d-f04e-4130-aec8-b460011d4699", "image": "https://cdn.globalauctionplatform.com/auctions-2026/bscnew10514/images/51aa3b51-4a07-49a5-925d-b460011e370a.jpg?h=175", "company": "New Mill Capital", "description": "Walk in Cold Storage Rooms- Overall Dims Approx 12'4\" L X 8'3\" W X 8'6\" tall, Inside Dims Approx 11'2\" L X 7'2\" W X 8' Tall, Krack Model KR26B-089...", "bid_ending_date": "2026-07-14T17:28:00+00:00", "location": "Denver, Colorado", "featured": true, "page": 1, "keyword": "fan", "opening_bid": 0, "current_bid": 0, "next_minimum_bid": 5, "is_closed": false, "actor_id": "4FcHeVWSuSUMuCBS5", "run_id": "DXwUrmb7JMnmWawZF" }, { "lot_number": "e31e84bc-367b-432c-bce9-b45e00fdfce9", "title": "Atlas Copco GA18FF Air Compressor", "url": "https://www.bidspotter.com/en-us/auction-catalogues/assetbuilt/catalogue-id-assetbuilt10012/lot-e31e84bc-367b-432c-bce9-b45e00fdfce9", "image": "https://cdn.globalauctionplatform.com/auctions-2026/assetbuilt10012/images/aca76a56-8697-434c-a93e-b45f00f7fafe.jpg?h=175", "company": "AssetBuilt", "description": " - Horsepower: 25 HP (18.5 kW) - Capacity: (CFM)~122.3 CFM @ 125 PSI - Max Working Pressure: 125 PSI (9.1 bar) - Voltage Options: Tri-voltage (208...", "bid_ending_date": null, "location": "Bowling Green, Kentucky", "featured": true, "page": 1, "keyword": "fan", "opening_bid": 2.5, "current_bid": 625, "next_minimum_bid": 750, "is_closed": false, "actor_id": "4FcHeVWSuSUMuCBS5", "run_id": "DXwUrmb7JMnmWawZF" } ] ``` ### Use Cases - **Market Research and Analysis**: Gather data on auction trends, pricing, and availability. - **Competitive Intelligence**: Monitor competitors' auction activities and strategies. - **Price Monitoring**: Track price changes and bidding patterns over time. - **Content Aggregation**: Compile auction listings for content creation or reporting. - **Academic Research**: Use auction data for studies in economics, business, or technology. - **Business Automation**: Integrate with systems to automate procurement processes. ### Installation and Usage 1. Search for "Bidspotter Auctions Category Spider" in the Apify Store. 2. Click "Try for free" or "Run". 3. Configure input parameters as needed. 4. Click "Start" to begin extraction. 5. Monitor progress in the log. 6. Export results in your preferred format (JSON, CSV, Excel). ### Output Format The output is a JSON array containing objects with the following fields: - `lot_number`: Unique identifier for the auction lot. - `title`: Title of the auction item. - `url`: Link to the auction listing. - `image`: URL of the item's image. - `company`: Name of the company hosting the auction. - `description`: Detailed description of the item. - `bid_ending_date`: Date and time when bidding ends. - `location`: Location of the auction. - `featured`: Boolean indicating if the lot is featured. - `page`: Page number where the lot appears. - `keyword`: Keyword associated with the lot. - `opening_bid`: Starting bid amount. - `current_bid`: Current highest bid. - `next_minimum_bid`: Minimum next bid increment. - `is_closed`: Boolean indicating if bidding is closed. - `actor_id`: Identifier for the actor run. - `run_id`: Unique identifier for the run. ### Support For custom/simplified outputs or bug reports, please contact: - Email: support@getdataforme.com - Subject line: "custom support" - Contact form: [Get Data For Me](https://getdataforme.com/contact/) We're here to help you get the most out of this Actor! # Actor input Schema ## `Keywords` (type: `array`): The keywords for the spider.eg.fan no need to add other option ## `Categorycode` (type: `array`): The categorycode for the spider. ## `Searchterm` (type: `string`): The searchterm for the spider. ## `Type` (type: `string`): The type for the spider. ## `Distancelocation` (type: `integer`): The distancelocation for the spider. ## `Postcodelocation` (type: `integer`): The postcodelocation for the spider. ## `Countrylocation` (type: `string`): The countrylocation for the spider. ## `Sortterm` (type: `string`): The sortterm for the spider. ## `item_limit` (type: `integer`): Maximum items to scrape per actor run. Set to 0 for no limit. ## Actor input object example ```json { "item_limit": 10 } ``` # Actor output Schema ## `results` (type: `string`): Scraped data items from dataset # 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("getdataforme/bidspotter-auctions-category-spider").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 = {} # Run the Actor and wait for it to finish run = client.actor("getdataforme/bidspotter-auctions-category-spider").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 '{}' | apify call getdataforme/bidspotter-auctions-category-spider --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=getdataforme/bidspotter-auctions-category-spider", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Bidspotter Auctions category Spider", "description": "The Bidspotter Auctions Category Spider efficiently scrapes auction data from Bidspotter, allowing users to extract detailed information on lots based on keywords, categories, and locations....", "version": "1.0", "x-build-id": "4v8iHB5s9IgXA3Yr2" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/getdataforme~bidspotter-auctions-category-spider/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-getdataforme-bidspotter-auctions-category-spider", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/getdataforme~bidspotter-auctions-category-spider/runs": { "post": { "operationId": "runs-sync-getdataforme-bidspotter-auctions-category-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/getdataforme~bidspotter-auctions-category-spider/run-sync": { "post": { "operationId": "run-sync-getdataforme-bidspotter-auctions-category-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "Keywords": { "title": "Keywords [direct search]", "type": "array", "description": "The keywords for the spider.eg.fan no need to add other option", "items": { "type": "string" } }, "Categorycode": { "title": "Categorycode eg.TRL", "type": "array", "description": "The categorycode for the spider.", "items": { "type": "string" } }, "Searchterm": { "title": "Searchterm [optional]", "type": "string", "description": "The searchterm for the spider." }, "Type": { "title": "Type [optional] ", "type": "string", "description": "The type for the spider." }, "Distancelocation": { "title": "Distancelocation[eg.402]", "type": "integer", "description": "The distancelocation for the spider." }, "Postcodelocation": { "title": "Postcodelocation[eg.64110]", "type": "integer", "description": "The postcodelocation for the spider." }, "Countrylocation": { "title": "Countrylocation[eg.US]", "type": "string", "description": "The countrylocation for the spider." }, "Sortterm": { "title": "Sortterm[optional]", "type": "string", "description": "The sortterm for the spider." }, "item_limit": { "title": "Item limit", "minimum": 0, "type": "integer", "description": "Maximum items to scrape per actor run. Set to 0 for no limit.", "default": 10 } } }, "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 } } } } } } } } } } ```