# Bonhams Carpets, Rugs & Tapestries Auction Results Scraper (`jungle_synthesizer/bonhams-carpets-rugs-tapestries-auction-results-scraper`) Actor Scrape sold lot results from the Bonhams Carpets, Rugs & Tapestries department. Extracts title, origin region, rug type, period, dimensions (imperial + metric), estimates, hammer price, sale date, location, provenance notes, and thumbnail URL. Supports full-department crawl or BYO lot URL list mode. - **URL**: https://apify.com/jungle\_synthesizer/bonhams-carpets-rugs-tapestries-auction-results-scraper.md - **Developed by:** [BowTiedRaccoon](https://apify.com/jungle_synthesizer) (community) - **Categories:** Business, Other - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per event 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 ## Bonhams Carpets, Rugs & Tapestries Auction Results Scraper Scrape sold lot results from the Bonhams Carpets, Rugs & Tapestries department. Extracts title, origin region, rug type, period, dimensions (imperial + metric), estimates, hammer price, sale date, location, provenance notes, and thumbnail URL. ### What it does The actor crawls the Bonhams auction platform using a three-level discovery architecture: 1. **Auction list** — scans `/auctions/results/` pages to discover past sales containing Rugs, Carpets & Tapestries lots 2. **Sale page** — processes each sale to enumerate lots; for dedicated RUG-department sales, all lots are crawled; for mixed-department sales, only RUG lots from the sale's server-rendered preview are included 3. **Lot detail** — fetches each individual lot page and extracts structured data from the Next.js server-side rendered JSON (`__NEXT_DATA__`) ### Supported input modes - **Default (auction list scan)** — scans up to 10 pages of auction results (240 past sales) for any that include the Carpets, Rugs & Tapestries department - **BYO sale IDs** — provide specific Bonhams sale IDs (e.g. `["32361"]`) to crawl directly, skipping the listing scan - **BYO lot URLs** — provide a list of Bonhams lot detail page URLs to scrape directly (fastest mode) ### Input | Field | Type | Description | Default | |-------|------|-------------|---------| | `maxItems` | integer | Maximum number of lot records to return | 100 | | `lotUrls` | array | Direct Bonhams lot page URLs to scrape | — | | `saleIds` | array | Bonhams auction sale IDs to crawl directly | — | | `auctionPages` | integer | Number of auction list pages to scan (max 10, 24 sales/page) | 10 | ### Output Each record represents a single auction lot: | Field | Type | Description | |-------|------|-------------| | `lot_id` | string | Unique Bonhams lot identifier | | `sale_id` | string | Bonhams auction sale ID | | `sale_title` | string | Name of the auction sale | | `sale_date` | string | Sale date (ISO format YYYY-MM-DD) | | `sale_location` | string | Sale venue and city | | `lot_number` | string | Lot number within the sale | | `title` | string | Full lot title as catalogued | | `origin_region` | string | Inferred geographic origin (Persia, Caucasus, Anatolia, etc.) | | `rug_type` | string | Textile type: carpet, rug, runner, kilim, tapestry, sumak, bag-face | | `design_pattern` | string | Dominant design vocabulary (medallion, herati, boteh, etc.) | | `period_circa` | string | Period as catalogued ("late 19th century", "circa 1880") | | `age_classification` | string | antique, semi-antique, or modern | | `dimensions_imperial` | string | Dimensions in feet and inches | | `dimensions_metric` | string | Dimensions in centimetres | | `low_estimate` | number | Lower pre-sale estimate | | `high_estimate` | number | Upper pre-sale estimate | | `estimate_currency` | string | ISO currency code for estimates | | `hammer_price` | number | Hammer price realised (null if unsold) | | `sold_currency` | string | ISO currency code for hammer price | | `is_sold` | boolean | True if the lot sold at hammer | | `provenance_notes` | string | Provenance and special notices | | `condition_notes` | string | Condition report text | | `thumbnail_url` | string | Primary lot image URL | | `lot_url` | string | Bonhams lot detail page URL | ### Example output record ```json { "lot_id": "2684312", "sale_id": "25946", "sale_title": "Fine Carpets and Rugs", "sale_date": "2019-10-30", "sale_location": "New Bond Street, London", "lot_number": "25", "title": "A very large Mahal carpet, North West Persia", "origin_region": "Persia", "rug_type": "carpet", "design_pattern": "medallion", "period_circa": "late 19th century", "age_classification": "antique", "dimensions_imperial": "", "dimensions_metric": "638cm x 533cm", "low_estimate": 3000, "high_estimate": 5000, "estimate_currency": "GBP", "hammer_price": 4500, "sold_currency": "GBP", "is_sold": true, "provenance_notes": "", "condition_notes": "", "thumbnail_url": "https://bonhams-assets.s3.amazonaws.com/...", "lot_url": "https://www.bonhams.com/auction/25946/lot/25/..." } ```` ### Notes - Results are limited to the Carpets, Rugs & Tapestries department (Bonhams department code `RUG`) - Mixed-department sales (e.g. Discovery Sales) include only the RUG lots visible in the sale's server-side rendered preview (up to 48 lots per mixed sale) - Dedicated Carpets & Rugs sales enumerate all lots - Hammer prices are only populated for sold lots; unsold lots have `hammer_price: null` - Dimensions are extracted from the lot description text using pattern matching and may be incomplete for some older catalogue entries # Actor input Schema ## `sp_intended_usage` (type: `string`): Please describe how you plan to use the data extracted by this crawler. ## `sp_improvement_suggestions` (type: `string`): Provide any feedback or suggestions for improvements. ## `sp_contact` (type: `string`): Provide your email address so we can get in touch with you. ## `maxItems` (type: `integer`): Maximum number of lot records to scrape. ## `lotUrls` (type: `array`): Optional list of Bonhams lot URLs to scrape directly. ## `saleIds` (type: `array`): Bonhams auction sale IDs to crawl directly (e.g. \["32361"]). Skips the auction-list scan. ## `auctionPages` (type: `integer`): Number of /auctions/results/ pages to scan (default 10, max 10). Each page contains 24 past auctions. ## Actor input object example ```json { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 10, "auctionPages": 10 } ``` # 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 = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 10 }; // Run the Actor and wait for it to finish const run = await client.actor("jungle_synthesizer/bonhams-carpets-rugs-tapestries-auction-results-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 = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 10, } # Run the Actor and wait for it to finish run = client.actor("jungle_synthesizer/bonhams-carpets-rugs-tapestries-auction-results-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 '{ "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 10 }' | apify call jungle_synthesizer/bonhams-carpets-rugs-tapestries-auction-results-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=jungle_synthesizer/bonhams-carpets-rugs-tapestries-auction-results-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Bonhams Carpets, Rugs & Tapestries Auction Results Scraper", "description": "Scrape sold lot results from the Bonhams Carpets, Rugs & Tapestries department. Extracts title, origin region, rug type, period, dimensions (imperial + metric), estimates, hammer price, sale date, location, provenance notes, and thumbnail URL. Supports full-department crawl or BYO lot URL list mode.", "version": "0.1", "x-build-id": "WHkoGfrmIMaEQwRnl" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/jungle_synthesizer~bonhams-carpets-rugs-tapestries-auction-results-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-jungle_synthesizer-bonhams-carpets-rugs-tapestries-auction-results-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/jungle_synthesizer~bonhams-carpets-rugs-tapestries-auction-results-scraper/runs": { "post": { "operationId": "runs-sync-jungle_synthesizer-bonhams-carpets-rugs-tapestries-auction-results-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/jungle_synthesizer~bonhams-carpets-rugs-tapestries-auction-results-scraper/run-sync": { "post": { "operationId": "run-sync-jungle_synthesizer-bonhams-carpets-rugs-tapestries-auction-results-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": { "sp_intended_usage": { "title": "What is the intended usage of this data?", "minLength": 1, "type": "string", "description": "Please describe how you plan to use the data extracted by this crawler." }, "sp_improvement_suggestions": { "title": "How can we improve this crawler for you?", "minLength": 1, "type": "string", "description": "Provide any feedback or suggestions for improvements." }, "sp_contact": { "title": "Contact Email", "minLength": 1, "type": "string", "description": "Provide your email address so we can get in touch with you." }, "maxItems": { "title": "Max Items", "type": "integer", "description": "Maximum number of lot records to scrape.", "default": 100 }, "lotUrls": { "title": "Lot URLs (optional)", "type": "array", "description": "Optional list of Bonhams lot URLs to scrape directly.", "items": { "type": "string" } }, "saleIds": { "title": "Sale IDs (optional)", "type": "array", "description": "Bonhams auction sale IDs to crawl directly (e.g. [\"32361\"]). Skips the auction-list scan.", "items": { "type": "string" } }, "auctionPages": { "title": "Auction Pages to Scan (optional)", "type": "integer", "description": "Number of /auctions/results/ pages to scan (default 10, max 10). Each page contains 24 past auctions.", "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 } } } } } } } } } } ```