> ## Documentation Index
> Fetch the complete documentation index at: https://docs.scrapebadger.com/llms.txt
> Use this file to discover all available pages before exploring further.
# Search Products
> Search walmart.com by keyword with sort, price band and facet filters.
Search `walmart.com` for products. Returns \~40–60 organic products per page.
Sponsored ad tiles are dropped; sponsored *products* are returned and flagged
`is_sponsored`.
**Credits:** 5
## Authorization
Your ScrapeBadger API key.
## Query Parameters
Search keywords, e.g. `laptop`.
Result page, `1`–`10`. Results dry up after page 10 — see
[Pagination](#pagination).
Result ordering. One of `best_match`, `best_seller`, `price_low`,
`price_high`, `rating_high`, `new`.
Minimum price in USD.
Maximum price in USD.
Walmart facet filter, e.g. `brand:HP`. Facets can be **applied but not
enumerated** — Walmart renders the filter rail client-side, so there is no
endpoint that lists them.
## Response
Echo of the requested query.
The walmart.com URL that was fetched.
The page returned.
**Walmart's own claim**, not a reachable count — it reports \~14,700 for a
query that stops returning products after page 10. It moves correctly when a
filter is applied, so it is a useful *relative* signal only.
Measured page ceiling for this surface (`10` for search).
Products on this page.
Page on this, not on `total_results_reported`.
The sort that was applied.
Walmart's result heading, e.g. `Results for "laptop"`.
`name`, `url`.
Walmart's related query suggestions.
Set when Walmart corrected the query.
Product cards.
Walmart's item id — use it for `/products/{item_id}` and to deduplicate.
Full price block — `current_price`, `was_price`, `price_range`, `savings_amount`.
e.g. `IN_STOCK`, `OUT_OF_STOCK`.
e.g. `FC`, `MARKETPLACE`.
`id`, `text`, `type`, `key`.
## Example
```bash cURL theme={null}
curl "https://scrapebadger.com/v1/walmart/search?query=laptop&sort=price_low&max_price=500" \
-H "X-API-Key: YOUR_API_KEY"
```
```javascript Node.js theme={null}
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();
```
```python Python theme={null}
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,
},
)
data = res.json()
```
```json Response theme={null}
{
"query": "laptop",
"url": "https://www.walmart.com/search?q=laptop",
"page": 1,
"total_results_reported": 14714,
"max_page": 10,
"result_count": 52,
"has_more_pages": true,
"sort": null,
"title": "Results for \"laptop\"",
"breadcrumbs": [{ "name": "laptop", "url": null }],
"related_searches": ["hp laptop", "macbook", "gaming laptop", "chromebook"],
"spelling_correction": null,
"items": [
{
"us_item_id": "20353606354",
"item_id": "20353606354",
"product_id": "4W9K25QVD1IR",
"offer_id": "CFD877430F6D3E37B5678F4880EC10C8",
"name": "HP Essential 14\" Laptop, Intel N150, 8GB RAM, 128GB eMMC, Windows 11 Home, Pink",
"brand": "HP",
"url": "https://www.walmart.com/ip/HP-Essential-14-Laptop.../20353606354",
"image_url": "https://i5.walmartimages.com/seo/HP-Essential-14-Laptop....jpeg",
"price": 298.96,
"price_string": "$298.96",
"price_info": {
"current_price": { "price": 298.96, "price_string": "$298.96", "price_display": "$298.96" },
"price_range": { "min_price": 269.0, "price_string": "Options from $269.00" },
"savings_amount": 0.0
},
"rating": 4.0,
"review_count": 4,
"in_stock": true,
"is_out_of_stock": false,
"availability_status": "IN_STOCK",
"fulfillment_type": "FC",
"fulfillment_badges": ["Free shipping, arrives in 3+ days"],
"seller_id": "E3AC3CCD80E94D77A876ADE3B17D7B89",
"seller_name": "PCOnline US",
"is_sponsored": true,
"is_two_day_shipping": false,
"badges": [{ "id": "L1600", "text": "Best seller", "type": "flag", "key": "BEST_SELLER" }],
"position": 1
}
]
}
```
## Pagination
`total_results_reported` is not reachable. Search dries up after **page 10** —
roughly **500 products per query**. Page on `has_more_pages`; page 11 returns
HTTP 200 with `result_count: 0`.
Consecutive pages **overlap by roughly 20%** — Walmart re-ranks between
requests. **Deduplicate on `us_item_id`.**
To collect more than \~500 products for a term, segment the query rather than
paging deeper: repeat it per brand (`facet=brand:HP`) or across price bands
(`min_price` / `max_price`).
**Searching by UPC does not work** — Walmart returns zero results for a bare
UPC. Search by keyword and read `upc` off
[`/products/{item_id}`](/api-reference/endpoint/walmart/get-product) instead.
Prices and availability are **store-specific**, resolved from the request IP
and not pinnable by parameter. Fetch a product to see which store answered
(its `location` block).