# 🛒 Walmart Data Extractor (`scraper-engine/walmart-data-extractor`) Actor 🛒 Walmart Data Extractor pulls product details, pricing, ratings & availability from Walmart for fast market research. 📊 Automate leads, monitor competitors & track trends with reliable data. 🚀 Great for B2B insights & analytics. - **URL**: https://apify.com/scraper-engine/walmart-data-extractor.md - **Developed by:** [Scraper Engine](https://apify.com/scraper-engine) (community) - **Categories:** E-commerce, Lead generation, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $4.99 / 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 ## 🛒 Walmart Data Extractor Extract rich, structured product data from **Walmart.com** at scale. Feed it category pages, search pages, or product (`/ip/`) URLs — or just a keyword — and get back prices, images, brand, full specifications, ratings, seller info, and much more. Built for reliability with automatic **proxy escalation**, anti-bot browser impersonation, retries, and **real-time** dataset saving. ### ✨ Why Choose This Actor? - 🔗 **Bulk URLs** — mix category, search and product URLs in a single run. - 🛡️ **Smart proxy escalation** — starts direct, falls back to datacenter, then residential automatically, and sticks with residential once it has to. - 🧰 **Anti-bot by design** — uses `impit` browser impersonation (real TLS/HTTP fingerprints) instead of heavy headless browsers. - 💾 **Live results** — products stream into the output table as they're scraped, grouped by source section, so a mid-run stop never loses data. - ⭐ **Reviews & specs** — opt into reviews and get full `idml` specifications. - 🧩 **Customizable output** — reshape every record with your own Python hooks. ### 🔑 Key Features | Feature | Description | |--------|-------------| | Category scraping | Auto-paginates browse/category pages | | Search scraping | Search pages or a raw keyword | | Product detail | Direct `/ip/` URL extraction | | Reviews | `includeReviews` / `onlyReviews` | | Limits | `maxItems` (global) and `endPage` | | Location | Best-effort `zipCode` targeting | | Proxy | direct → datacenter → residential (sticky) | ### 📥 Input ```json { "startUrls": [ { "url": "https://www.walmart.com/browse/auto-tires/brake-pads/91083_1074765_9038935_4670095_4582920" } ], "search": "laptop", "maxItems": 10, "endPage": null, "zipCode": "10001", "includeReviews": false, "onlyReviews": false, "proxy": { "useApifyProxy": false } } ```` | Field | Type | Description | |-------|------|-------------| | `startUrls` | array | Walmart category / search / product URLs (bulk). **Required.** | | `search` | string | Keyword → converted to a search URL. | | `maxItems` | integer | Cap on total products. Empty = no limit. | | `endPage` | integer | Last category/search page to read. | | `zipCode` | string | US ZIP for localized pricing/availability. | | `postalCode` | integer | ⚠️ Deprecated — use `zipCode`. | | `includeReviews` | boolean | Attach reviews to each product. | | `onlyReviews` | boolean | Keep only reviews + identifiers. | | `extendOutputFunction` | string | Python `def extendOutputFunction(product)` → dict merged in. | | `outputFilterFunction` | string | Python `def outputFilterFunction(product)` → reshape/drop. | | `proxy` | object | Proxy config. Default: no proxy (auto-escalates on block). | ### 📤 Output Each product is pushed as one dataset row with the **full** Walmart product object plus convenience columns for the table view: ```json { "name": "MAX Advanced Brakes - Brake Kit ...", "brand": "Max Advanced Brakes", "priceString": "$194.99", "price": 194.99, "availabilityStatus": "IN_STOCK", "usItemId": "1902495893", "productUrl": "https://www.walmart.com/ip/.../1902495893", "imageUrl": "https://i5.walmartimages.com/seo/...jpeg", "sourceSection": "browse_auto_tires", "sourceUrl": "https://www.walmart.com/browse/...", "priceInfo": { "currentPrice": { "price": 194.99, "priceString": "$194.99" } }, "idml": { "specifications": { }, "longDescription": "..." }, "reviews": null } ``` A structured, per-section summary (mirroring `results_by_url`) is also written to the key-value store as **`OUTPUT`**. ### 🚀 How to Use (Apify Console) 1. Log in at → **Actors**. 2. Open **Walmart Data Extractor**. 3. Paste your Walmart URLs (or a keyword), set `maxItems`, and configure proxy. 4. Click **Start**. 5. Watch products stream into the run log and **Output** tab in real time. 6. Export to JSON / CSV / XLSX when done. ### 🤖 Use via API ```bash curl -X POST "https://api.apify.com/v2/acts//run-sync-get-dataset-items?token=$APIFY_TOKEN" \ -H "Content-Type: application/json" \ -d '{"startUrls":[{"url":"https://www.walmart.com/search?q=laptop"}],"maxItems":10}' ``` ### 🎯 Best Use Cases - 💰 Price monitoring & repricing - 📊 Catalog & assortment analysis - 🔎 Competitor & market research - 🏷️ Brand / seller tracking ### 💳 Pricing This actor uses the **pay-per-event** model. The primary event is `row_result`, charged once per product saved to the dataset. Platform startup is covered by the synthetic `apify-actor-start` event. You only pay for the products you actually receive. ### ❓ FAQ **Which URLs are supported?** Category/browse pages, search pages, and product (`/ip/`) pages. **Do I need a proxy?** No. The actor runs direct by default and only escalates to datacenter then residential proxies if Walmart blocks the request. **Can I limit the run?** Yes — use `maxItems` for a global cap and `endPage` to stop pagination early. **Why are some fields null?** Walmart omits fields per product; reviews are only attached when `includeReviews`/`onlyReviews` is enabled. ### ⚖️ Cautions / Legal - Data is collected only from **publicly available** Walmart pages. - You are responsible for compliance with Walmart's ToS and applicable laws (GDPR, CCPA, etc.). Use reasonable rate limits and scrape responsibly. ### 🛟 Support & Feedback Open an issue on the Actor's **Issues** tab with your run ID and input, and we'll take a look. # Actor input Schema ## `startUrls` (type: `array`): One or more Walmart URLs. ✅ Supported: category/browse pages, search pages, and product-detail (/ip/) pages. Add as many as you like — they run in bulk. ## `maxItems` (type: `integer`): Maximum number of products to scrape across the whole run. Leave empty for no limit. ## `endPage` (type: `integer`): Stop paginating category/search results at this page number. Leave empty for no limit. ## `search` (type: `string`): Optional. A keyword to search on Walmart (e.g. "laptop"). It's turned into a search URL automatically and added to the URLs above. ## `zipCode` (type: `string`): US ZIP code used to localize delivery/pickup pricing & availability (best-effort). ## `postalCode` (type: `integer`): ⚠️ Deprecated — please use ZIP code instead. Kept for backwards compatibility. ## `includeReviews` (type: `boolean`): Attach the reviews block to each scraped product. ## `onlyReviews` (type: `boolean`): Discard product data and keep only the reviews (plus identifiers). ## `extendOutputFunction` (type: `string`): Optional Python function `def extendOutputFunction(product): ...` returning a dict that is merged into every result. ## `outputFilterFunction` (type: `string`): Optional Python function `def outputFilterFunction(product): ...` to reshape each item. Return None to drop an item. ## `proxy` (type: `object`): Proxy settings. By default the actor connects directly (no proxy). If Walmart blocks the request, it automatically escalates: direct → datacenter → residential. 🛡️ ## Actor input object example ```json { "startUrls": [ "https://www.walmart.com/browse/auto-tires/brake-pads/91083_1074765_9038935_4670095_4582920" ], "maxItems": 10, "includeReviews": false, "onlyReviews": false, "proxy": { "useApifyProxy": false } } ``` # 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 = { "startUrls": [ "https://www.walmart.com/browse/auto-tires/brake-pads/91083_1074765_9038935_4670095_4582920" ], "maxItems": 10, "search": "", "extendOutputFunction": "", "outputFilterFunction": "", "proxy": { "useApifyProxy": false } }; // Run the Actor and wait for it to finish const run = await client.actor("scraper-engine/walmart-data-extractor").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 = { "startUrls": ["https://www.walmart.com/browse/auto-tires/brake-pads/91083_1074765_9038935_4670095_4582920"], "maxItems": 10, "search": "", "extendOutputFunction": "", "outputFilterFunction": "", "proxy": { "useApifyProxy": False }, } # Run the Actor and wait for it to finish run = client.actor("scraper-engine/walmart-data-extractor").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 '{ "startUrls": [ "https://www.walmart.com/browse/auto-tires/brake-pads/91083_1074765_9038935_4670095_4582920" ], "maxItems": 10, "search": "", "extendOutputFunction": "", "outputFilterFunction": "", "proxy": { "useApifyProxy": false } }' | apify call scraper-engine/walmart-data-extractor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scraper-engine/walmart-data-extractor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "🛒 Walmart Data Extractor", "description": "🛒 Walmart Data Extractor pulls product details, pricing, ratings & availability from Walmart for fast market research. 📊 Automate leads, monitor competitors & track trends with reliable data. 🚀 Great for B2B insights & analytics.", "version": "0.1", "x-build-id": "lE2pl3rxDqc3nNmLA" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scraper-engine~walmart-data-extractor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scraper-engine-walmart-data-extractor", "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/scraper-engine~walmart-data-extractor/runs": { "post": { "operationId": "runs-sync-scraper-engine-walmart-data-extractor", "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/scraper-engine~walmart-data-extractor/run-sync": { "post": { "operationId": "run-sync-scraper-engine-walmart-data-extractor", "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": [ "startUrls" ], "properties": { "startUrls": { "title": "🔗 Walmart URLs (bulk)", "type": "array", "description": "One or more Walmart URLs. ✅ Supported: category/browse pages, search pages, and product-detail (/ip/) pages. Add as many as you like — they run in bulk.", "items": { "type": "string" } }, "maxItems": { "title": "🎯 Max items", "minimum": 1, "type": "integer", "description": "Maximum number of products to scrape across the whole run. Leave empty for no limit." }, "endPage": { "title": "📑 Category end page", "minimum": 1, "type": "integer", "description": "Stop paginating category/search results at this page number. Leave empty for no limit." }, "search": { "title": "🔍 Search keyword", "type": "string", "description": "Optional. A keyword to search on Walmart (e.g. \"laptop\"). It's turned into a search URL automatically and added to the URLs above." }, "zipCode": { "title": "📍 ZIP code", "type": "string", "description": "US ZIP code used to localize delivery/pickup pricing & availability (best-effort)." }, "postalCode": { "title": "📮 Postal code (deprecated)", "type": "integer", "description": "⚠️ Deprecated — please use ZIP code instead. Kept for backwards compatibility." }, "includeReviews": { "title": "⭐ Include reviews", "type": "boolean", "description": "Attach the reviews block to each scraped product.", "default": false }, "onlyReviews": { "title": "💬 Only reviews", "type": "boolean", "description": "Discard product data and keep only the reviews (plus identifiers).", "default": false }, "extendOutputFunction": { "title": "🧩 Extend output function (Python)", "type": "string", "description": "Optional Python function `def extendOutputFunction(product): ...` returning a dict that is merged into every result." }, "outputFilterFunction": { "title": "🔧 Output filter function (Python)", "type": "string", "description": "Optional Python function `def outputFilterFunction(product): ...` to reshape each item. Return None to drop an item." }, "proxy": { "title": "🌐 Proxy configuration", "type": "object", "description": "Proxy settings. By default the actor connects directly (no proxy). If Walmart blocks the request, it automatically escalates: direct → datacenter → residential. 🛡️", "default": { "useApifyProxy": false } } } }, "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 } } } } } } } } } } ```