Zalando Data API: Extract Structured JSON in 2026

Disclaimer

This guide covers extracting publicly accessible data. Always review a site’s robots.txt and Terms of Service before scraping.

TL;DR

You can retrieve typed JSON from any public Zalando page using AlterLab’s Extract API. Define a schema, call the endpoint, and receive validated data. Cost starts at $0.001 per request.

Why use Zalando data?

• Build AI training datasets from product listings.
• Feed competitive intelligence dashboards with price trends.
• Power inventory forecasting models with availability signals.

What data can you extract?

Publicly listed e‑commerce fields include:

• title: product name
• price: numeric string
• currency: ISO code
• sku: stock keeping unit
• availability: in stock or out of stock
• rating: customer score

These fields are present in the page’s visible HTML and are safe to query.

The extraction approach

Scraping raw HTML with CSS selectors is fragile. Page layout changes break parsers. A data API removes that risk. AlterLab wraps the extraction pipeline in a stable interface. It handles anti‑bot bypass, rotates proxies, and returns typed JSON. You focus on schema, not on selectors.

Quick start with AlterLab Extract API

The Extract API estimates cost before execution. Use the preview to display pricing in your UI. The endpoint is POST /v1/extract.

Python example

from alterlab import AlterLabSync

client = AlterLabSync("YOUR_API_KEY")

schema = {
  "type": "object",
  "properties": {
    "title": {"type": "string", "description": "The title field"},
    "price": {"type": "string", "description": "The price field"},
    "currency": {"type": "string", "description": "The currency field"},
    "sku": {"type": "string", "description": "The sku field"},
    "availability": {"type": "string", "description": "The availability field"},
    "rating": {"type": "string", "description": "The rating field"}
  }
}

result = client.scrape(
    url="https://www.zalando.com/mens-shoes.html",
    extraction_schema=schema,
)
print(result["filtered_content"])

cURL example

curl -X POST https://api.alterlab.io/v1/extract \
  -H "X-API-Key: YOUR_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "url": "https://www.zalando.com/mens-shoes.html",
    "schema": {"properties": {"title": {"type": "string"}, "price": {"type": "string"}, "currency": {"type": "string"}}}
  }'

The response contains a data object that matches the schema exactly. No post‑processing is required.

Batch and async usage

from alterlab import AlterLab
import asyncio

client = AlterLab("YOUR_API_KEY")

urls = [
    "https://www.zalando.com/mens-shirts.html",
    "https://www.zalando.com/women-dresses.html",
    "https://www.zalando.com/kids-socks.html"
]

async def extract_one(url):
    schema = {"properties": {"title": {"type": "string"}, "price": {"type": "string"}, "availability": {"type": "string"}}}
    resp = client.scrape(url=url, extraction_schema=schema)
    return resp["filtered_content"]

async def main():
    tasks = [extract_one(u) for u in urls]
    results = await asyncio.gather(*tasks)
    print(results)

asyncio.run(main())

The batch example shows how to process many URLs in parallel. Rate limits apply; see the scaling section below.

Define your schema

AlterLab validates output against the schema you provide. If a field is missing, the API returns null for that key. This guarantees a predictable JSON structure. Example schema for rating:

{
  "type": "object",
  "properties": {
    "rating": {
      "type": "string",
      "description": "The rating field"
    }
  }
}

Typed output simplifies downstream AI pipelines.

Handle pagination and scale

High‑volume pipelines need batching and async execution. Follow these steps:

1. Chunk URLs into batches of 10–20 to stay within rate limits.
2. Respect the 1 request per second limit. Use a queue with back‑off.
3. Store results in your own bucket; do not rely on temporary API storage.
4. Monitor costs via the pricing page. Costs are clamped between $0.001 and $0.50 per call.

Link to pricing: /pricing.

Key takeaways

• Use AlterLab’s Extract API for reliable, typed JSON from Zalando.
• Define a schema to lock down the output structure.
• Preview costs before committing; balance never expires.
• Scale with async batches while respecting rate limits.

Infographics

Getting started guide

New to AlterLab? Follow the getting started guide to install the SDK and generate an API key.