# Walmart Products Scraper for Prices & Availability (`fetch_cat/walmart-products-scraper`) Actor Scrape Walmart search results with product titles, prices, ratings, reviews, sellers, availability, images, sponsored flags, and URLs for retail monitoring. - **URL**: https://apify.com/fetch\_cat/walmart-products-scraper.md - **Developed by:** [Hanna Nosova](https://apify.com/fetch_cat) (community) - **Categories:** E-commerce, Automation, Integrations - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.30 / 1,000 result extracteds This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 ## Walmart Products Scraper Scrape Walmart search results for product intelligence, price monitoring, assortment analysis, and marketplace research. Enter Walmart search terms or public Walmart search URLs and get clean product rows with titles, prices, ratings, review counts, sellers, availability, images, and product links. ### What does Walmart Products Scraper do? Walmart Products Scraper collects product listing data from public Walmart search pages. It is designed for quick search-result monitoring rather than account-only workflows. - 🔎 Search Walmart by keyword - 🛒 Collect product titles and URLs - 💵 Capture current price and comparison price when visible - ⭐ Save rating and review counts - 🚚 Include availability and fulfillment labels - 🏷️ Track sellers, brands, item IDs, and sponsored flags ### Who is it for? - Ecommerce teams tracking competitor prices - Marketplace sellers monitoring assortment and seller names - Retail analysts comparing product visibility across queries - Growth teams building price intelligence dashboards - Data teams feeding product catalogs into warehouses - Agencies reporting Walmart search visibility for clients ### Why use this Walmart scraper? Walmart search pages contain many useful product signals, but copying them by hand is slow and error-prone. This actor turns public listing pages into structured JSON, CSV, Excel, or API-ready dataset rows. ### What Walmart data can you extract? | Field | Description | | --- | --- | | `query` | Search term or URL query | | `position` | Result position in the run | | `title` | Product listing title | | `productUrl` | Full Walmart product URL | | `productId` | Walmart internal product ID when available | | `usItemId` | Walmart US item ID | | `price` | Current visible price | | `currency` | USD | | `wasPrice` | Previous/comparison price when shown | | `rating` | Average product rating | | `reviewCount` | Number of reviews | | `availability` | In-stock or availability text | | `sellerName` | Seller shown by Walmart | | `brand` | Brand or manufacturer when available | | `imageUrl` | Product thumbnail image | | `isSponsored` | Whether Walmart marks the item as sponsored | | `fulfillment` | Delivery, pickup, or shipping labels | | `scrapedAt` | Timestamp for the scrape | ### How much does it cost to scrape Walmart products? The actor uses pay-per-event pricing: a small start event plus a per-product result event. You only pay for products saved to the dataset. Use a low `maxResults` value for your first run, then increase after checking output quality. ### How to scrape Walmart search results 1. Open the actor on Apify. 2. Add one or more search queries, such as `iphone`, `coffee maker`, or `lego`. 3. Set `maxResults` to the number of products you need. 4. Keep `pageLimit` low for test runs. 5. Run the actor. 6. Download results as JSON, CSV, Excel, XML, RSS, or HTML. ### Input options #### Search queries Use `searchQueries` when you want the actor to build Walmart search URLs for you. #### Walmart search URLs Use `searchUrls` when you already have public Walmart search pages or category-like search links. #### Maximum products `maxResults` limits the total number of products saved across all queries and URLs. #### Pages per query `pageLimit` controls pagination for keyword searches. More pages can return more products but may increase runtime. #### Sort order Choose best match, price low to high, price high to low, best sellers, highest rating, or new arrivals. #### Sponsored products Set `includeSponsored` to `false` when you only want organic-looking product rows. #### Proxy settings The default input runs without Apify Proxy for a cheaper first test. If Walmart blocks your environment, enable Apify Proxy with US targeting. ### Example input ```json { "searchQueries": ["iphone", "coffee maker"], "maxResults": 50, "pageLimit": 1, "includeSponsored": true, "proxyConfiguration": { "useApifyProxy": false } } ```` ### Example output ```json { "query": "iphone", "position": 1, "title": "Straight Talk Apple iPhone 13, 128GB, Midnight - Prepaid Smartphone", "productUrl": "https://www.walmart.com/ip/example/454408250", "productId": "6M2CBPL4MQ1X", "usItemId": "454408250", "price": 199, "currency": "USD", "wasPrice": null, "rating": 4.3, "reviewCount": 19602, "availability": "In stock", "sellerName": "Walmart.com", "brand": null, "imageUrl": "https://i5.walmartimages.com/example.jpeg", "isSponsored": false, "fulfillment": ["DELIVERY", "PICKUP"], "scrapedAt": "2026-06-21T19:15:08.453Z" } ``` ### Tips for better Walmart scraping - Start with 10-20 products to validate your query. - Use specific queries when you want precise product sets. - Use broader queries when you want assortment discovery. - Save `usItemId` for matching products across repeated runs. - Use `scrapedAt` to track price changes over time. - Disable sponsored products when measuring organic placement. ### Common use cases #### Price monitoring Run the actor daily or weekly for important product queries and compare `price`, `wasPrice`, and `availability` over time. #### Assortment research Collect Walmart products for a category keyword and analyze brands, sellers, and item IDs. #### Search visibility tracking Track which products appear for strategic keywords and whether sponsored placements change. #### Seller monitoring Use `sellerName` to identify whether Walmart.com or third-party sellers are visible in search results. ### Integrations Use this actor with: - Google Sheets exports for lightweight price tracking - BigQuery or Snowflake pipelines for historical analysis - Make or Zapier workflows for alerts - Apify webhooks for scheduled monitoring - BI tools that consume CSV or JSON datasets ### API usage #### Node.js ```js import { ApifyClient } from 'apify-client'; const client = new ApifyClient({ token: process.env.APIFY_TOKEN }); const run = await client.actor('fetch_cat/walmart-products-scraper').call({ searchQueries: ['iphone'], maxResults: 25, }); console.log(run.defaultDatasetId); ``` #### Python ```python from apify_client import ApifyClient client = ApifyClient('MY-APIFY-TOKEN') run = client.actor('fetch_cat/walmart-products-scraper').call(run_input={ 'searchQueries': ['iphone'], 'maxResults': 25, }) print(run['defaultDatasetId']) ``` #### cURL ```bash curl -X POST 'https://api.apify.com/v2/acts/fetch_cat~walmart-products-scraper/runs?token=MY-APIFY-TOKEN' \ -H 'Content-Type: application/json' \ -d '{"searchQueries":["iphone"],"maxResults":25}' ``` ### MCP: use Walmart data from AI tools You can use this actor through Apify MCP from Claude Desktop, Claude Code, and other MCP-compatible tools. MCP URL: ```text https://mcp.apify.com/?tools=fetch_cat/walmart-products-scraper ``` Setup for Claude Code: ```bash claude mcp add --transport http apify "https://mcp.apify.com" ``` Setup for Claude Desktop, Cursor, or VS Code: ```json { "mcpServers": { "apify": { "url": "https://mcp.apify.com" } } } ``` Example prompts: - "Scrape the top 25 Walmart results for coffee maker and summarize price ranges." - "Find Walmart iPhone listings and list sellers with ratings." - "Compare sponsored and non-sponsored products for lego." ### Scheduling Schedule this actor in Apify to run every day, week, or month. Scheduled runs are useful for price history, stock monitoring, and search placement tracking. ### FAQ **How fast is the Walmart Products Scraper?** Small search runs usually finish in seconds. Larger keyword batches depend on `pageLimit`, query count, and Walmart response time. **How much will my run cost?** Costs scale mainly with the number of product rows saved. Start with `maxResults` set to 10-20, then increase after reviewing output. **Is this the same as a Walmart API?** No. This actor extracts public Walmart search result data and does not require an official Walmart API key. ### Troubleshooting #### Why did my run return no products? Try a broader query, reduce filters, or enable Apify Proxy with US country targeting if Walmart blocks your runtime environment. #### Why are some fields null? Walmart does not show every field for every product. Optional fields such as brand, was price, and availability can be missing on some rows. #### Why are fewer products returned than requested? The query may have fewer visible results, duplicates may be removed, or Walmart may return fewer products on a page. ### Limits This actor scrapes public Walmart search listing data. It does not sign in, use private accounts, purchase items, collect personal data, or bypass access controls. ### Legality This actor is intended for public web data collection and business analysis. You are responsible for ensuring your use complies with applicable laws, Walmart terms, and your internal policies. ### Related actors - https://apify.com/fetch\_cat/shopify-products-scraper - https://apify.com/fetch\_cat/google-shopping-scraper - https://apify.com/fetch\_cat/amazon-products-scraper ### Changelog #### 0.1 Initial version with Walmart search queries, search URLs, product prices, ratings, review counts, sellers, availability, image URLs, sponsored flags, and fulfillment labels. ### Support If a query stops working or output looks incomplete, open an issue from the Apify actor page with the run ID and input you used. ### Data freshness Each row includes `scrapedAt`, so repeated runs can be compared and stored as time-series product intelligence. ### Export formats Apify datasets support JSON, CSV, Excel, XML, RSS, HTML table views, and direct API access. ### Recommended first run Use this small input first: ```json { "searchQueries": ["iphone"], "maxResults": 10, "pageLimit": 1 } ``` ### Production run pattern For recurring monitoring, use one actor task per product category or keyword group. This keeps results easier to compare over time and avoids mixing unrelated categories in one dataset. # Actor input Schema ## `searchQueries` (type: `array`): Walmart product search phrases to scrape, such as iphone, coffee maker, or lego. ## `searchUrls` (type: `array`): Optional public Walmart search result URLs to scrape. Use this when you already have category/search URLs. ## `maxResults` (type: `integer`): Total number of Walmart products to save across all queries and URLs. ## `pageLimit` (type: `integer`): How many Walmart search pages to request for each query. Keep this low for quick test runs. ## `sort` (type: `string`): Optional Walmart search sorting preference. ## `includeSponsored` (type: `boolean`): Turn off to exclude products Walmart marks as sponsored. ## `proxyConfiguration` (type: `object`): Apify Proxy settings. Datacenter proxy is recommended first; use residential only if Walmart blocks your run. ## Actor input object example ```json { "searchQueries": [ "iphone" ], "searchUrls": [], "maxResults": 20, "pageLimit": 1, "sort": "best_match", "includeSponsored": true, "proxyConfiguration": { "useApifyProxy": false } } ``` # Actor output Schema ## `overview` (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": [ "iphone" ], "searchUrls": [], "proxyConfiguration": { "useApifyProxy": false } }; // Run the Actor and wait for it to finish const run = await client.actor("fetch_cat/walmart-products-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": ["iphone"], "searchUrls": [], "proxyConfiguration": { "useApifyProxy": False }, } # Run the Actor and wait for it to finish run = client.actor("fetch_cat/walmart-products-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": [ "iphone" ], "searchUrls": [], "proxyConfiguration": { "useApifyProxy": false } }' | apify call fetch_cat/walmart-products-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=fetch_cat/walmart-products-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Walmart Products Scraper for Prices & Availability", "description": "Scrape Walmart search results with product titles, prices, ratings, reviews, sellers, availability, images, sponsored flags, and URLs for retail monitoring.", "version": "0.1", "x-build-id": "UMOfKUUIe7ze7fRgL" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/fetch_cat~walmart-products-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-fetch_cat-walmart-products-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/fetch_cat~walmart-products-scraper/runs": { "post": { "operationId": "runs-sync-fetch_cat-walmart-products-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/fetch_cat~walmart-products-scraper/run-sync": { "post": { "operationId": "run-sync-fetch_cat-walmart-products-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": "Walmart product search phrases to scrape, such as iphone, coffee maker, or lego.", "items": { "type": "string" } }, "searchUrls": { "title": "Walmart search URLs", "type": "array", "description": "Optional public Walmart search result URLs to scrape. Use this when you already have category/search URLs.", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "maxResults": { "title": "Maximum products", "minimum": 1, "maximum": 5000, "type": "integer", "description": "Total number of Walmart products to save across all queries and URLs.", "default": 20 }, "pageLimit": { "title": "Pages per query", "minimum": 1, "maximum": 25, "type": "integer", "description": "How many Walmart search pages to request for each query. Keep this low for quick test runs.", "default": 1 }, "sort": { "title": "Sort order", "enum": [ "best_match", "price_low", "price_high", "best_seller", "rating_high", "new" ], "type": "string", "description": "Optional Walmart search sorting preference.", "default": "best_match" }, "includeSponsored": { "title": "Include sponsored products", "type": "boolean", "description": "Turn off to exclude products Walmart marks as sponsored.", "default": true }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Apify Proxy settings. Datacenter proxy is recommended first; use residential only if Walmart blocks your run." } } }, "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 } } } } } } } } } } ```