How to Scrape Walmart with TypeScript

Walmart contains valuable data — product listings, prices, ratings, review counts, and more. Scraping this data directly means dealing with anti-bot detection, CAPTCHAs, IP rotation, and constantly breaking selectors. The Scavio API handles all of that and returns clean, structured JSON from a single POST request.

This tutorial shows you how to scrape Walmart using TypeScript and the Scavio API. By the end, you will have a working TypeScript script that fetches real-time Walmart data and parses the results.

Prerequisites

• TypeScript installed on your machine
• A Scavio API key (free tier includes 500 credits/month — no credit card required)

Step 1: Install Dependencies

Install fetch to make HTTP requests:

npm install typescript tsx

Step 2: Make Your First Walmart Search

Send a POST request to the Scavio Walmart API endpoint with your query. The API returns structured JSON with product listings, prices, ratings, and more.

const API_KEY = "your_scavio_api_key";

interface WalmartResult {
  search_metadata: { status: string };
  products: Array<{ position: number; title: string; price: string; rating: number; reviews_count: number }>;
}

const response = await fetch("https://api.scavio.dev/api/v1/walmart/search", {
  method: "POST",
  headers: {
    "x-api-key": API_KEY,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({ query }),
});

const data: WalmartResult = await response.json();
for (const product of data.products?.slice(0, 5) ?? []) {
  console.log(`${product.title} — ${product.price} (${product.rating}⭐)`);
}

Step 3: Example Response

The API returns structured JSON. Here is an example response for a Walmart search:

{
  "search_metadata": { "status": "success" },
  "products": [
    {
      "position": 1,
      "title": "FlexiSpot E7 Standing Desk",
      "product_id": "1234567890",
      "price": "$349.99",
      "rating": 4.5,
      "reviews_count": 1823,
      "fulfillment": "Free delivery",
      "pickup": "Available for pickup"
    }
  ]
}

Every field is structured and typed — no HTML parsing, no CSS selectors, no regex extraction. Your TypeScript code can access any field directly.

Step 4: Full Working Example

Here is a complete, runnable TypeScript script that searches Walmart and prints the results:

/**
 * Scrape Walmart search results with full type safety.
 * Run with: npx tsx walmart-search.ts
 */

const API_KEY = process.env.SCAVIO_API_KEY!;

interface WalmartResult {
  search_metadata: { status: string };
  products: Array<{ position: number; title: string; price: string; rating: number; reviews_count: number }>;
}

async function searchWalmart(query: string): Promise<WalmartResult> {
  const response = await fetch("https://api.scavio.dev/api/v1/walmart/search", {
    method: "POST",
    headers: {
      "x-api-key": API_KEY,
      "Content-Type": "application/json",
    },
    body: JSON.stringify({ query }),
  });

  if (!response.ok) {
    throw new Error(`Scavio API error: ${response.status}`);
  }

  return response.json();
}

const results = await searchWalmart("standing desk");
console.log(JSON.stringify(results, null, 2));

Why Use Scavio Instead of Scraping Walmart Directly?

• No proxy management. Direct scraping requires rotating proxies to avoid IP bans. Scavio handles all of this server-side.
• No CAPTCHA solving. Walmart aggressively blocks automated requests. Scavio returns clean data every time.
• Structured JSON output. No HTML parsing or CSS selector maintenance. Get typed, consistent data from every request.
• Multi-platform in one API. Search Google, Amazon, YouTube, and Walmart from the same API key with the same authentication pattern.
• Free tier included. 500 credits/month with no credit card required. Each search costs 1 credit.