# Used Laptop & GPU Resale Price Index (`kayhermes/152-used-laptop-gpu-resale-price-index`) Actor Build quality-adjusted used-laptop resale indexes by mobile GPU and estimate target laptops from verified sold records. - **URL**: https://apify.com/kayhermes/152-used-laptop-gpu-resale-price-index.md - **Developed by:** [Khoa Nguyen](https://apify.com/kayhermes) (community) - **Categories:** E-commerce - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 ## Used Laptop & GPU Resale Price Index Creates mobile-GPU price indexes and target-laptop estimates after normalizing major configuration differences. ### Inputs Provide verified laptop sales with GPU model, sale price/date, TGP, CPU tier, memory, storage, year, and condition. Desktop GPU records are rejected. ### Outputs Dataset rows contain one index series per GPU plus optional laptop estimates. ### Responsible-use notes This is a market index, not a device inspection. Records with unverified sales are downweighted; active asking prices should not be labeled as sold prices. ### Local validation ```bash npm ci npm test npm run check npm run sample ```` `npm run sample` runs the real Apify SDK entry point with local storage and writes Dataset, `OUTPUT`, and `REPORT.html`. # Actor input Schema ## `observations` (type: `array`): Verified laptop sales ## `targets` (type: `array`): Optional laptops to estimate ## `sourceUrls` (type: `array`): Public or authorized URLs returning records. No login bypass is attempted. ## `targetCurrency` (type: `string`): Target currency ## `fxRates` (type: `object`): Example: {"EUR\_USD": 1.08}. Required for non-target currencies. ## `halfLifeDays` (type: `integer`): Comparable recency half-life ## `cadence` (type: `string`): Index cadence ## `referenceYear` (type: `integer`): Reference year ## `baselinePeriod` (type: `string`): Example 2026-01 or 2026-Q1. ## Actor input object example ```json { "observations": [ { "id": "g1", "gpuModel": "RTX 4070 Laptop GPU", "formFactor": "laptop", "laptopModel": "ASUS ROG Zephyrus G16", "soldPrice": 1180, "currency": "USD", "soldAt": "2026-04-12", "condition": "good", "cpuTier": 4, "ramGb": 16, "storageGb": 1000, "tgpWatts": 105, "year": 2024, "saleVerified": true }, { "id": "g2", "gpuModel": "NVIDIA RTX 4070 Mobile", "formFactor": "laptop", "laptopModel": "Lenovo Legion Pro 5", "soldPrice": 1275, "currency": "USD", "soldAt": "2026-04-25", "condition": "excellent", "cpuTier": 4, "ramGb": 32, "storageGb": 1000, "tgpWatts": 140, "year": 2024, "saleVerified": true }, { "id": "g3", "gpuModel": "RTX 4070 Laptop", "formFactor": "laptop", "laptopModel": "MSI Vector", "soldPrice": 1090, "currency": "USD", "soldAt": "2026-05-19", "condition": "good", "cpuTier": 3, "ramGb": 16, "storageGb": 512, "tgpWatts": 105, "year": 2024, "saleVerified": true }, { "id": "g4", "gpuModel": "RTX 4070 Laptop GPU", "formFactor": "laptop", "laptopModel": "Alienware m16", "soldPrice": 1300, "currency": "USD", "soldAt": "2026-06-15", "condition": "excellent", "cpuTier": 4, "ramGb": 32, "storageGb": 1000, "tgpWatts": 140, "year": 2024, "saleVerified": true }, { "id": "g5", "gpuModel": "RTX 4060 Laptop GPU", "formFactor": "laptop", "laptopModel": "Acer Nitro 16", "soldPrice": 760, "currency": "USD", "soldAt": "2026-04-10", "condition": "good", "cpuTier": 3, "ramGb": 16, "storageGb": 512, "tgpWatts": 115, "year": 2024, "saleVerified": true }, { "id": "g6", "gpuModel": "RTX 4060 Mobile", "formFactor": "laptop", "laptopModel": "Lenovo LOQ", "soldPrice": 710, "currency": "USD", "soldAt": "2026-06-12", "condition": "good", "cpuTier": 3, "ramGb": 16, "storageGb": 512, "tgpWatts": 105, "year": 2024, "saleVerified": true } ], "targets": [ { "id": "my-laptop", "laptopModel": "ROG Zephyrus G16", "gpuModel": "RTX 4070 Laptop GPU", "condition": "excellent", "cpuTier": 4, "ramGb": 32, "storageGb": 1000, "tgpWatts": 105, "year": 2024 } ], "sourceUrls": [], "targetCurrency": "USD", "fxRates": {}, "halfLifeDays": 180, "cadence": "monthly", "referenceYear": 2026 } ``` # Actor output Schema ## `results` (type: `string`): No description ## `output` (type: `string`): No description ## `report` (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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("kayhermes/152-used-laptop-gpu-resale-price-index").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("kayhermes/152-used-laptop-gpu-resale-price-index").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 kayhermes/152-used-laptop-gpu-resale-price-index --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=kayhermes/152-used-laptop-gpu-resale-price-index", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Used Laptop & GPU Resale Price Index", "description": "Build quality-adjusted used-laptop resale indexes by mobile GPU and estimate target laptops from verified sold records.", "version": "1.0", "x-build-id": "SsuCT15jiFI8EESqp" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/kayhermes~152-used-laptop-gpu-resale-price-index/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-kayhermes-152-used-laptop-gpu-resale-price-index", "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/kayhermes~152-used-laptop-gpu-resale-price-index/runs": { "post": { "operationId": "runs-sync-kayhermes-152-used-laptop-gpu-resale-price-index", "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/kayhermes~152-used-laptop-gpu-resale-price-index/run-sync": { "post": { "operationId": "run-sync-kayhermes-152-used-laptop-gpu-resale-price-index", "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", "required": [ "observations" ], "properties": { "observations": { "title": "Verified laptop sales", "type": "array", "description": "Verified laptop sales", "default": [ { "id": "g1", "gpuModel": "RTX 4070 Laptop GPU", "formFactor": "laptop", "laptopModel": "ASUS ROG Zephyrus G16", "soldPrice": 1180, "currency": "USD", "soldAt": "2026-04-12", "condition": "good", "cpuTier": 4, "ramGb": 16, "storageGb": 1000, "tgpWatts": 105, "year": 2024, "saleVerified": true }, { "id": "g2", "gpuModel": "NVIDIA RTX 4070 Mobile", "formFactor": "laptop", "laptopModel": "Lenovo Legion Pro 5", "soldPrice": 1275, "currency": "USD", "soldAt": "2026-04-25", "condition": "excellent", "cpuTier": 4, "ramGb": 32, "storageGb": 1000, "tgpWatts": 140, "year": 2024, "saleVerified": true }, { "id": "g3", "gpuModel": "RTX 4070 Laptop", "formFactor": "laptop", "laptopModel": "MSI Vector", "soldPrice": 1090, "currency": "USD", "soldAt": "2026-05-19", "condition": "good", "cpuTier": 3, "ramGb": 16, "storageGb": 512, "tgpWatts": 105, "year": 2024, "saleVerified": true }, { "id": "g4", "gpuModel": "RTX 4070 Laptop GPU", "formFactor": "laptop", "laptopModel": "Alienware m16", "soldPrice": 1300, "currency": "USD", "soldAt": "2026-06-15", "condition": "excellent", "cpuTier": 4, "ramGb": 32, "storageGb": 1000, "tgpWatts": 140, "year": 2024, "saleVerified": true }, { "id": "g5", "gpuModel": "RTX 4060 Laptop GPU", "formFactor": "laptop", "laptopModel": "Acer Nitro 16", "soldPrice": 760, "currency": "USD", "soldAt": "2026-04-10", "condition": "good", "cpuTier": 3, "ramGb": 16, "storageGb": 512, "tgpWatts": 115, "year": 2024, "saleVerified": true }, { "id": "g6", "gpuModel": "RTX 4060 Mobile", "formFactor": "laptop", "laptopModel": "Lenovo LOQ", "soldPrice": 710, "currency": "USD", "soldAt": "2026-06-12", "condition": "good", "cpuTier": 3, "ramGb": 16, "storageGb": 512, "tgpWatts": 105, "year": 2024, "saleVerified": true } ] }, "targets": { "title": "Optional laptops to estimate", "type": "array", "description": "Optional laptops to estimate", "default": [ { "id": "my-laptop", "laptopModel": "ROG Zephyrus G16", "gpuModel": "RTX 4070 Laptop GPU", "condition": "excellent", "cpuTier": 4, "ramGb": 32, "storageGb": 1000, "tgpWatts": 105, "year": 2024 } ] }, "sourceUrls": { "title": "Optional JSON/CSV source URLs", "type": "array", "description": "Public or authorized URLs returning records. No login bypass is attempted.", "default": [], "items": { "type": "string" } }, "targetCurrency": { "title": "Target currency", "type": "string", "description": "Target currency", "default": "USD" }, "fxRates": { "title": "Manual FX rates", "type": "object", "description": "Example: {\"EUR_USD\": 1.08}. Required for non-target currencies.", "default": {} }, "halfLifeDays": { "title": "Comparable recency half-life", "minimum": 30, "maximum": 1460, "type": "integer", "description": "Comparable recency half-life", "default": 180 }, "cadence": { "title": "Index cadence", "enum": [ "weekly", "monthly", "quarterly" ], "type": "string", "description": "Index cadence", "default": "monthly" }, "referenceYear": { "title": "Reference year", "minimum": 2015, "maximum": 2035, "type": "integer", "description": "Reference year", "default": 2026 }, "baselinePeriod": { "title": "Optional baseline period", "type": "string", "description": "Example 2026-01 or 2026-Q1." } } }, "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 } } } } } } } } } } ```