Walmart API Overview

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Overview

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Features

• Product search — keywords with sort, price band and facet filters. ~40–60 organic products per page. Sponsored ad tiles are dropped; sponsored products are returned and flagged is_sponsored.
• Category browse — any walmart.com/browse/... or /cp/... path, same result shape as search.
• Deals feed — Walmart’s live rollbacks and clearance as a paginated product feed, not a boolean on a product row.
• Full product detail — upc/gtin, model, grouped specification_groups[], variants[], condition_offers[] (new vs pre-owned on the same item), fulfillment_summary[] with promised delivery dates per method, return_policy, nutrition_facts for grocery, plus a reviews sample so shallow use cases need only one call.
• Full review histogram — distribution carries per-star counts and percentages (five_star, five_star_percent, …), recommended_percentage and total_media_count, alongside paginated review text.
• Marketplace sellers — profile (contact, address, rating, policies) and a searchable catalogue of that seller’s inventory.
• Physical stores — a store’s address, geo, phone, opening hours, per-department services each with their own hours and phone, fuel prices where present, and ~30 nearby stores in the same response.
• Walmart’s generative-AI product content — ai_description_html and ai_highlights[], surfaced rather than trimmed.

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Coverage

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Credits

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Quickstart

curl "https://scrapebadger.com/v1/walmart/search?query=laptop&sort=price_low&max_price=500" \
  -H "X-API-Key: YOUR_API_KEY"

const res = await fetch(
  "https://scrapebadger.com/v1/walmart/search?" +
    new URLSearchParams({
      query: "laptop",
      sort: "price_low",
      max_price: "500",
    }),
  { headers: { "X-API-Key": process.env.SCRAPEBADGER_API_KEY } },
);
const data = await res.json();
console.log(data.items.length, "products");

import requests

res = requests.get(
    "https://scrapebadger.com/v1/walmart/search",
    headers={"X-API-Key": "YOUR_API_KEY"},
    params={
        "query": "laptop",
        "sort": "price_low",
        "max_price": 500,
    },
)
print(len(res.json()["items"]), "products")

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Pagination limits

• Always page on has_more_pages, never on total_results_reported.
• max_page in every result set is the measured ceiling for that surface.
• To go deeper than 500, segment the query: repeat it per brand facet (facet=brand:HP) or across price bands (min_price / max_price).

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Store-specific prices

"location": {
  "postal_code": "95519",
  "city": "Mckinleyville",
  "state": "CA",
  "store_id": "5629",
  "intent": "SHIPPING"
}

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Other measured limits

• /category has no sort. Walmart’s browse pages ignore it (34/38 identical ids with and without it, and the param is not echoed back). Sort on /search instead.
• Facets can be applied but not enumerated. Pass facet=brand:HP and it filters; there is no endpoint listing available facets, because Walmart renders the filter rail client-side.
• The seller id is the numeric catalog_seller_id found on a product — not the 32-char hex seller_id, which 404s as a storefront URL.
• /sellers/{id} returns no product list. The storefront grid is rendered client-side. Use /sellers/{id}/products, which goes through search and therefore requires a query.
• Searching by UPC does not work. Walmart returns zero results for a bare UPC — resolve UPCs by keyword and read upc off the product detail instead.
• Reviews are 10 per page. That is Walmart’s page size and is not adjustable.

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Errors