Check the sample data
Download free sample products of a website before you pay for a scrape.
The training of a website extracts a random sample of its products. The sample is free. Use it to make sure that the data has the fields you need before you approve a paid scrape.
Get the sample
When the setup job is in the QUALITY_CHECK phase or COMPLETED, send GET /samples/{website_id} with the project_id. The API returns a temporary download URL.
curl "https://api.deepscout.ai/v1/samples/example-shop.cz?project_id=$PROJECT_ID" \
-H "Authorization: Bearer $SCOUT_API_KEY"{ "url": "https://...amazonaws.com/example-shop.cz.json?X-Amz-Signature=..." }The URL is valid for 1 hour. Do not send the Authorization header to this URL. It is a presigned storage URL that needs no key.
If the sample is not ready yet, the API answers 404 with the code SAMPLE_NOT_FOUND. Try again after a few minutes.
The file
- The file is in JSON Lines format: one JSON object for each product, one product on each line. It is not compressed.
- It has 20% of the products of the website, but not more than 1,000.
- After each full scrape of the website, a new random sample replaces the file.
{
"name": "Bio kokosový olej 500 ml",
"price": 189,
"price_standard": 229,
"price_discounted": 189,
"currency": "CZK",
"ean": "8594173461123",
"sku": "SKU-1000",
"brand": "Country Life",
"category": "Potraviny __ Oleje",
"category_extracted": ["Potraviny", "Oleje"],
"availability": "Skladem",
"availability_extracted": "IN_STOCK",
"product_url": "https://www.example-shop.cz/p/bio-kokosovy-olej-500-ml",
"image_url": "https://www.example-shop.cz/img/1000.jpg",
"specification": { "Hmotnost": "500 g" }
}Fields
Each line has all these fields. A field that the website does not show is null. The example above leaves out the null fields.
| Group | Fields |
|---|---|
| Product | name, brand, brand_extracted, description, specification, variant, variants, condition, condition_extracted |
| Identifiers | ean, sku, product_url, image_url, images_gallery |
| Category | category, category_extracted |
| Price | price, currency, price_standard, price_discounted, price_coupon, price_club, price_recommended, and the five detailed prices without VAT, with the suffix _no_vat (for example price_standard_no_vat) |
| Availability | availability, availability_extracted |
| History | history |
The fields have the same meaning as in the Products dataset. After a scrape, the export files have all the fields of this dataset.
What to look for
- Prices. Compare some prices with the website. The price fields show which price types the website has, for example a discounted price or a club price.
- Identifiers. If you plan to match products, EAN codes make the matching more accurate.
- Categories and specifications. Make sure that the fields that your analysis needs are present.
If the data is not correct, do not approve a scrape. Write to support@deepscout.ai with the website ID.