# Walmart Product Detail Scraper (`good-apis/walmart-product`) Actor - **URL**: https://apify.com/good-apis/walmart-product.md - **Developed by:** [Danny](https://apify.com/good-apis) (community) - **Categories:** E-commerce - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $2.00 / 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 web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows. 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 ## Walmart Product Detail Scraper Give it a Walmart item id (or product URL) and get back the **full product detail** — title, brand, model, price (and was-price), currency, availability, seller, category path, average rating, review count, the full image gallery, and the complete specifications table — as one dataset row. No login, no proxies to configure, no browser to manage. Leave the id blank and it details the top live result of a seed search, so a scheduled run never breaks on a delisted item. **Pricing: $3.50 per 1,000 products** (pay per result). You are only charged for a product actually returned — no monthly rental. ### What you get | Field | Description | |---|---| | `id` | Walmart item id (usItemId) | | `title` | Product title | | `brand` | Brand | | `type` | Product type | | `model_number` | Manufacturer model number, when present | | `price` / `price_value` | Current price as shown / as a number | | `was_price` | Strike-through / previous price, when on offer | | `currency` | Currency code (e.g. `USD`) | | `availability` | Availability (e.g. `IN_STOCK`) | | `seller_name` / `seller_id` | Seller name and id | | `category` | Full category path (e.g. `Electronics > TV & Home Theater > All TVs`) | | `rating` / `review_count` | Average star rating / number of reviews | | `num_images` / `images` | Image count and the gallery URLs | | `num_specs` / `specifications` | Spec count and the full `{name: value}` specifications table | | `description` / `long_description` | Short and long product descriptions | | `url` | Canonical Walmart product URL | ### Input | Field | Required | Description | |---|---|---| | `item_id` | ✓* | Walmart item id (e.g. `470905078`). | | `url` | ✓* | Alternatively, a full Walmart product URL. | | `seed_search` | | Used only when id/url are blank: details the top live result for this keyword. | *Provide `item_id`, `url`, or leave both blank to use `seed_search`. ```json { "item_id": "470905078" } ```` ### Notes & limits - Reflects the **US** Walmart catalog (residential US proxying is handled server-side). - This is an unofficial scraper and is not affiliated with Walmart. # Actor input Schema ## `item_id` (type: `string`): The Walmart item id — the number at the end of an /ip/ URL, e.g. '470905078'. Leave blank to auto-pick the top result of the seed search. ## `url` (type: `string`): Optional: a full Walmart product URL (e.g. 'https://www.walmart.com/ip/.../470905078') to use instead of an item id. ## `seed_search` (type: `string`): Used only when item ID and URL are both blank: returns the detail of the TOP live result for this Walmart search keyword. ## Actor input object example ```json { "seed_search": "coffee maker" } ``` # Actor output Schema ## `results` (type: `string`): All scraped items in the default 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 = { "seed_search": "coffee maker" }; // Run the Actor and wait for it to finish const run = await client.actor("good-apis/walmart-product").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 = { "seed_search": "coffee maker" } # Run the Actor and wait for it to finish run = client.actor("good-apis/walmart-product").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 '{ "seed_search": "coffee maker" }' | apify call good-apis/walmart-product --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=good-apis/walmart-product", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Walmart Product Detail Scraper", "version": "0.1", "x-build-id": "QZEWj1coj8RbpUrvL" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/good-apis~walmart-product/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-good-apis-walmart-product", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/good-apis~walmart-product/runs": { "post": { "operationId": "runs-sync-good-apis-walmart-product", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/good-apis~walmart-product/run-sync": { "post": { "operationId": "run-sync-good-apis-walmart-product", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "item_id": { "title": "Walmart item ID", "type": "string", "description": "The Walmart item id — the number at the end of an /ip/ URL, e.g. '470905078'. Leave blank to auto-pick the top result of the seed search." }, "url": { "title": "Walmart product URL", "type": "string", "description": "Optional: a full Walmart product URL (e.g. 'https://www.walmart.com/ip/.../470905078') to use instead of an item id." }, "seed_search": { "title": "Seed search (fallback)", "type": "string", "description": "Used only when item ID and URL are both blank: returns the detail of the TOP live result for this Walmart search keyword." } } }, "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 } } } } } } } } } } ```