# Walmart Scraper - Products, Prices & Reviews (`scrapercompany/walmart-scraper`) Actor

Scrape Walmart search results (item id, name, brand, price, rating, ratings count, sponsored flag, image, link) with sorting and paging, or product reviews with the rating summary by item id. Batch many searches or products. No proxies needed.

- **URL**: https://apify.com/scrapercompany/walmart-scraper.md
- **Developed by:** [ScraperCompany](https://apify.com/scrapercompany) (community)
- **Categories:** E-commerce, Lead generation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $6.00 / 1,000 search results pages

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/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## Walmart Scraper - Products, Prices & Reviews

**Walmart Scraper** collects walmart.com data in two modes. **Product search** returns each product with its **item id, name, brand, price, rating, ratings count, sponsored flag, image and link**, with Walmart's sort orders and paging over up to 50 pages. **Product reviews** returns the product's **rating summary** (average, counts per star, recommended %) and reviews page by page. Use it for price monitoring, assortment analysis and review mining. Pricing is pay-per-event: **$0.006 per search page** and **$0.003 per review page**; failed requests are not charged.

Proxies, retries and anti-bot handling are built in, so you don't need your own proxies or an API key. Start a run, get structured JSON.

### What can this Walmart scraper do?

- **Product search**: item id, name, brand, price, rating, ratings count, sponsored flag, image, URL.
- Walmart **sort orders** (best match, price, best sellers, rating, new) and up to 50 pages.
- **Product reviews** with the rating summary and per-review details, up to 100 pages.
- Batch many searches or item ids; empty pages are free.

#### Modes

| Mode | What it returns | Price per request |
| --- | --- | --- |
| `search` | Products for a search: item id, name, brand, price, rating, ratings count, sponsored flag, image, link | $0.006 |
| `reviews` | Rating summary and a page of reviews for an item id | $0.003 |

### Use cases for Walmart data

- **E-commerce sellers**: Track Walmart prices and sponsored placements in your category.
- **Retail analysts**: Study assortment and brand coverage on walmart.com.
- **Brands**: Mine Walmart reviews and rating summaries for your products.

### What Walmart data can you extract?

| Field | Description |
| --- | --- |
| `products[].item_id / name / brand / url` | Product identity |
| `products[].price / currency` | Price |
| `products[].rating / ratings_count` | Rating and number of ratings |
| `products[].sponsored / image` | Sponsored flag and image |
| `aggregated_count / next_page` | Total matching products and paging |
| `summary (Reviews)` | Average rating, counts and percentages per star, recommended % |
| `reviews[].rating / title / text / date` | Review content (Reviews) |

Every dataset item also carries `input` (the exact request that was sent), `request_id` (quote it to support), `billed` and `scraped_at`.

### How to scrape Walmart products and reviews

1. Open Walmart Scraper in Apify Console and go to the **Input** tab.
2. Enter search queries, or switch **Mode** to Product reviews and paste Walmart item ids.
3. Adjust the options if needed. Dates accept an exact date (`2026-12-01`) or a relative one (`30 days` from today), so saved tasks and schedules never go stale.
4. Click **Start** and wait for the run to finish.
5. Download the results from the **Output** tab as JSON, CSV, Excel or HTML, or fetch them with the Apify API.

### Input example

This is the default input; running the Actor without changes uses it.

```json
{
  "mode": "search",
  "queries": [
    "bathrobe"
  ],
  "maxPages": 1,
  "itemIds": [
    "5255687930"
  ],
  "includeErrors": true,
  "maxConcurrency": 3,
  "maxRetries": 2
}
```

### Output example

One dataset item per request (trimmed here; real items contain every field the API returns):

```json
{
  "mode": "search",
  "endpoint": "/v1/walmart/search",
  "input": {
    "q": "bathrobe"
  },
  "aggregated_count": 387,
  "meta": {
    "elapsed_s": 1.344,
    "source": "walmart_search"
  },
  "next_page": null,
  "products": [
    {
      "brand": "Pavilia",
      "currency": "USD",
      "image": "https://i5.walmartimages.com/seo/PAVILIA-Black-Women-Robe_482875EB",
      "item_id": "5255687930",
      "name": "Black Womens Robe, Fleece Plush Soft Fluffy Bathrobe, S/M",
      "price": 19.99,
      "rating": 4.4,
      "ratings_count": 2484,
      "sponsored": false,
      "url": "https://www.walmart.com/ip/PAVILIA-Black-Women-Robe-5255687930"
    },
    {
      "brand": "Mainstays",
      "currency": "USD",
      "image": null,
      "item_id": "17299362344",
      "name": "Mainstays Fleece Bathrobe, Unisex, Adult",
      "price": 16.98,
      "rating": 4.5,
      "ratings_count": 1290,
      "sponsored": true,
      "url": "https://www.walmart.com/ip/Mainstays-Fleece-Bathrobe-17299362344"
    }
  ],
  "search_parameters": {
    "engine": "walmart_search",
    "q": "bathrobe"
  },
  "total": 2,
  "request_id": "req_3f9c0d6e2b8a4c1f9e7d5b3a1c0e8f6d",
  "billed": true,
  "scraped_at": "2026-10-01T14:03:27.512Z"
}
```

A request that fails is saved with an `error` message instead (turn off **Include failed requests** to skip those). Failed requests are never charged.

### How much does it cost to scrape Walmart products and reviews?

This Actor uses **pay-per-event** pricing: you pay for successful API requests, not for compute time.

| Event | Charged when | Price | Per 1,000 |
| --- | --- | --- | --- |
| `search-page` | One page of Walmart search results. Empty pages are free. | $0.006 | $6.00 |
| `review-page` | One page of a product's reviews with the rating summary. Empty pages are free. | $0.003 | $3.00 |

For example, 1,000 requests in the default mode cost **$6.00**.

- Failed requests (errors, invalid input, blocked upstream after retries) are **free**.
- Requests where the source returns nothing at all (no results, nothing priced) are saved but **not charged**.
- Set **Maximum cost per run** when you start a run and the Actor stops cleanly before going over it.

### FAQ

#### Do I need proxies or an API key?

No. Proxy rotation, retries and anti-bot handling are built in, and the Actor is ready to run as is. You only pay the per-event prices above.

#### Which Walmart site is used?

walmart.com (US).

#### Is it legal to scrape Walmart products and reviews?

The Actor collects publicly available information that anyone can see without logging in. You are responsible for how you use the results: respect the source site's terms, copyright and privacy law (such as GDPR) and do not collect personal data without a lawful basis. If in doubt, ask a lawyer.

#### What happens when a request is blocked or rate-limited?

Rate limits (HTTP 429) and temporary errors (5xx) are retried automatically with exponential backoff, respecting `Retry-After`. If a request still fails it is saved with the error message and not charged, and the rest of the batch keeps going. A run only fails when every request failed.

#### Why did a request return an error?

Read the `error` field: validation problems (for example a malformed date or an unknown id) are reported exactly as the API sees them. Fix the input and run again; failed requests cost nothing.

#### How many requests can I run at once?

Any number per run. The Actor sends up to 3 requests in parallel by default (change it under **Run options**); larger batches simply take longer.

### Use it from your code

Call the Actor from any language through the [Apify API](https://docs.apify.com/api/v2). With the JavaScript client (`npm install apify-client`):

```javascript
import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('scrapercompany/walmart-scraper').call({
    "mode": "search",
    "queries": [
        "bathrobe"
    ]
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);
```

With Python (`pip install apify-client`):

```python
import os
from apify_client import ApifyClient

client = ApifyClient(os.environ["APIFY_TOKEN"])
run = client.actor("scrapercompany/walmart-scraper").call(run_input={
    "mode": "search",
    "queries": ["bathrobe"],
})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)
```

You can also schedule runs, chain them with webhooks, or connect them to Make, Zapier, n8n, Google Sheets and other integrations from the **Integrations** tab.

### Related scrapers

- [Amazon Scraper](https://apify.com/scrapercompany/amazon-scraper): the same products on Amazon
- [Google Shopping Scraper](https://apify.com/scrapercompany/google-shopping-scraper): prices across merchants on Google Shopping

### Support

Questions, a field you need, or a site that stopped working? Open an issue on the **Issues** tab. Include the `request_id` from the dataset item so we can trace the request.

# Changelog

This Actor's version history is a separate document: https://apify.com/scrapercompany/walmart-scraper/changelog.md

# Actor input Schema

## `mode` (type: `string`):

Search products by keyword, or read reviews for known Walmart item ids.

## `queries` (type: `array`):

One Walmart search per line.

## `maxPages` (type: `integer`):

How many result pages to fetch for each query (1-50). Each page is a separate request and is charged separately; paging stops early when a page comes back empty.

## `searchSort` (type: `string`):

Walmart search sort order.

## `page` (type: `integer`):

Page to start from (search 1-50, reviews 1-100).

## `itemIds` (type: `array`):

Numeric Walmart item ids, e.g. <code>5255687930</code> from <code>walmart.com/ip/.../5255687930</code> or from search results.

## `reviewSort` (type: `string`):

Walmart review sort order.

## `customRequests` (type: `array`):

Optional list of JSON objects, one request each, using the API field names shown above. Each object is merged over the options above, so you only need to give what differs. Example: <code>{"q":"air fryer","sort":"rating"}</code>

## `includeErrors` (type: `boolean`):

When on, a request that fails (for example an unknown property id) is saved as a dataset item with an <code>error</code> message so you can see what went wrong. Failed requests are never charged.

## `maxConcurrency` (type: `integer`):

How many API requests run at the same time (1-8). Parallel runs share one limit, so extra requests wait for a free slot instead of failing.

## `maxRetries` (type: `integer`):

Retries for rate limits (HTTP 429), temporary server errors (5xx) and network errors, with exponential backoff. Validation errors are never retried.

## Actor input object example

```json
{
  "mode": "search",
  "queries": [
    "bathrobe"
  ],
  "maxPages": 1,
  "page": 1,
  "itemIds": [
    "5255687930"
  ],
  "reviewSort": "relevancy",
  "includeErrors": true,
  "maxConcurrency": 3,
  "maxRetries": 2
}
```

# Actor output Schema

## `results` (type: `string`):

One dataset item per request.

## `summary` (type: `string`):

Counts of succeeded, failed, skipped and charged requests.

# 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 '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "queries": [
        "bathrobe"
    ],
    "itemIds": [
        "5255687930"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("scrapercompany/walmart-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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "queries": ["bathrobe"],
    "itemIds": ["5255687930"],
}

# Run the Actor and wait for it to finish
run = client.actor("scrapercompany/walmart-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "queries": [
    "bathrobe"
  ],
  "itemIds": [
    "5255687930"
  ]
}' |
apify call scrapercompany/walmart-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,scrapercompany/walmart-scraper"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/AU3qAwbHSQYfNvOJm/builds/432kLUKptUGTYtBLg/openapi.json