```yaml
product: AlterLab
title: Allegro Data API: Extract Structured JSON in 2026
category: Tutorials
comparison_context: "AlterLab is an alternative to Firecrawl, ScrapingBee, and Bright Data."
last_updated: 2026-08-04
canonical_facts:
  - "Learn how to get structured Allegro data via API using AlterLab’s Extract API for reliable JSON output—no parsing, no fragility."
source_url: https://alterlab.io/blog/allegro-data-api-extract-structured-json-in-2026
```

# Allegro Data API: Extract Structured JSON in 2026

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

## TL;DR
Use AlterLab’s Extract API to POST a URL and a JSON schema. The service returns typed JSON for fields like title, price, currency, SKU and availability from Allegro pages. No HTML parsing, no fragile selectors—just structured data ready for your pipeline.

## Why use Allegro data?
Allegro is one of Europe’s largest marketplaces, hosting millions of product listings. Engineers pull this data for:
- Training price‑prediction models that need recent, real‑world examples.
- Building analytics dashboards that track category trends over time.
- Enabling competitive intelligence pipelines that monitor SKU availability and promotions.

## What data can you extract?
From a typical Allegro product page you can request:
- **title** – the product name as displayed.
- **price** – the current sale price.
- **currency** – the three‑letter ISO code (PLN, EUR, etc.).
- **sku** – the seller’s stock‑keeping unit.
- **availability** – in‑stock, out‑of‑stock or pre‑order status.
- **rating** – average user rating when present.
All fields are returned as strings; you can cast them downstream if needed.

## The extraction approach
Raw HTTP requests followed by HTML parsing break whenever Allegro updates its markup. Selectors become stale, anti‑bot measures trigger CAPTCHAs, and you spend time maintaining fragile code. A data API abstracts those concerns:
- Automatic proxy rotation and JavaScript rendering handle anti‑bot challenges.
- The Extract API validates output against your schema, guaranteeing typed JSON.
- You focus on the data model, not on page‑specific scraping logic.

## Quick start with AlterLab Extract API
First, install the Python client from the [Getting started guide](/docs/quickstart/installation). Then call the extract endpoint with a URL and a schema.

```python title="extract_allegro-pl.py" {5-12}
import alterlab

client = alterlab.Client("YOUR_API_KEY")

schema = {
  "type": "object",
  "properties": {
    "title": {
      "type": "string",
      "description": "The product title"
    },
    "price": {
      "type": "string",
      "description": "The price value"
    },
    "currency": {
      "type": "string",
      "description": "The currency code (e.g. PLN)"
    },
    "sku": {
      "type": "string",
      "description": "The seller SKU"
    },
    "availability": {
      "type": "string",
      "description": "Stock status"
    },
    "rating": {
      "type": "string",
      "description": "Average rating"
    }
  }
}

result = client.extract(
    url="https://allegro.pl/oferta/przykładowy-produkt-123456789",
    schema=schema,
)
print(result.data)
```

The same request works with cURL:

```bash title="Terminal"
curl -X POST https://api.alterlab.io/v1/extract \
  -H "X-API-Key: YOUR_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "url": "https://allegro.pl/oferta/przykładowy-produkt-123456789",
    "schema": {
      "properties": {
        "title": {"type": "string"},
        "price": {"type": "string"},
        "currency": {"type": "string"},
        "sku": {"type": "string"},
        "availability": {"type": "string"},
        "rating": {"type": "string"}
      }
    }
  }'
```

Both examples return a JSON object matching the schema, ready for ingestion into your data warehouse or ML pipeline.

## Define your schema
The Extract API uses JSON Schema to describe the shape of the output. You declare each field’s type, format and optional constraints. AlterLab validates the extracted content against this schema before returning it, so you never receive a field with the wrong type or missing key. If a field cannot be found, the API returns `null` for that property, preserving the schema’s structure.

Example schema with constraints:

```json
{
  "type": "object",
  "properties": {
    "title": {"type": "string", "minLength": 1},
    "price": {"type": "string", "pattern": "^[0-9]+\\.[0-9]{2}$"},
    "currency": {"type": "string", "enum": ["PLN", "EUR", "USD"]},
    "sku": {"type": "string", "maxLength": 50},
    "availability": {"type": "string", "enum": ["in_stock", "out_of_stock", "preorder"]},
    "rating": {"type": "string", "pattern": "^[0-9](\\.[0-9])?$"}
  },
  "required": ["title", "price", "currency"]
}
```

Supplying such a schema ensures downstream consumers can rely on consistent data contracts.

## Handle pagination and scale
For bulk extraction you’ll often need to iterate over search results or category pages. AlterLab supports asynchronous jobs and batch endpoints to stay within rate limits.

```python title="batch_extract.py" {8-15}
import alterlab
import asyncio

client = alterlab.Client("YOUR_API_KEY")

urls = [
    f"https://allegro.pl/listing?string=laptop&p={i}"
    for i in range(1, 21)  # first 20 pages
]

async def extract_all():
    tasks = [
        client.extract_async(url=url, schema=schema)
        for url in urls
    ]
    results = await asyncio.gather(*tasks)
    for resp in results:
        print(resp.data)

asyncio.run(extract_all())
```

The asynchronous client fires requests in parallel while respecting the concurrency limits you set in your dashboard. For very high volume, consider using the batch endpoint which accepts an array of URLs and returns an array of results in a single HTTP call—see the [Extract API docs](/docs/api/extract) for payload details.

Cost scales linearly with the number of successful extractions. Check the [AlterLab pricing](/pricing) page for per‑call rates and volume discounts.

## Key takeaways
- AlterLab’s Extract API turns any public Allegro page into typed JSON with a single POST.
- Define a JSON schema once and receive validated data every time—no parsing, no selector maintenance.
- The service handles proxies, JavaScript rendering and anti‑bot challenges so your pipeline stays reliable.
- Start with a single URL, iterate to batches, and pay only for what you use.

- **99.2%** — Extraction Accuracy
- **1.4s** — Avg Response Time
- **100%** — Typed JSON Output

1. **Define Schema** — 
2. **Call Extract API** — 
3. **Receive Typed JSON** — 

<div data-infographic="try-it" data-url="https://allegro.pl" data-description="Extract structured e-commerce data from Allegro"></div>
```

## Frequently Asked Questions

### Is there an official Allegro data API?

Allegro offers limited partner APIs for sellers; there is no public API for arbitrary product listings. AlterLab provides a generic data API that returns structured JSON from publicly accessible pages while respecting robots.txt and rate limits.

### What Allegro data can I extract with AlterLab?

You can extract publicly available e-commerce fields such as title, price, currency, SKU, availability and rating. Define a JSON schema and AlterLab validates the output so you receive typed data without post‑processing.

### How much does Allegro data extraction cost?

AlterLab charges per successful extraction, with costs clamped between $0.001 and $0.50 per call. There are no minimums, no expiring credits, and you only pay for what you use—see pricing for details.

## Related

- [Flipkart Data API: Extract Structured JSON in 2026](<https://alterlab.io/blog/flipkart-data-api-extract-structured-json-in-2026>)
- [Otto Data API: Extract Structured JSON in 2026](<https://alterlab.io/blog/otto-data-api-extract-structured-json-in-2026>)
- [How to Scrape Etherscan Data: Complete Guide for 2026](<https://alterlab.io/blog/how-to-scrape-etherscan-data-complete-guide-for-2026>)