```yaml
product: AlterLab
title: Yelp Data API: Extract Structured JSON in 2026
category: Tutorials
comparison_context: "AlterLab is an alternative to Firecrawl, ScrapingBee, and Bright Data."
last_updated: 2026-06-24
canonical_facts:
  - "A practical guide to extracting structured JSON data from Yelp using AlterLab's Extract API — no HTML parsing needed, just define your schema and get typed output."
source_url: https://alterlab.io/blog/yelp-data-api-extract-structured-json-in-2026
```

# Yelp 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
To get structured Yelp data via API, use AlterLab's Extract API: define a JSON schema for the fields you need (e.g., business_name, rating, address), send a POST request to the extract endpoint with the Yelp URL and your schema, and receive validated JSON output. No HTML parsing or selector maintenance required.

## Why use Yelp data?
Yelp contains rich, structured local business information valuable for multiple engineering applications:
- **Training data for local search AI**: Restaurant attributes, service categories, and geographic patterns help build better recommendation models
- **Market analytics pipelines**: Competitive density analysis, price point correlation, and trend detection across business types
- **Lead enrichment for B2B platforms**: Verified business details improve sales territory mapping and partnership identification

## What data can you extract?
Yelp's public business pages consistently expose these fields through semantic markup:
- `business_name`: Official display name (e.g., "Joe's Pizza")
- `rating`: Aggregate score as string (e.g., "4.5") to preserve precision
- `address`: Full street address with neighborhood context
- `phone`: Primary contact number in E.164 format where available
- `hours`: Weekly schedule as structured string (e.g., "Mon-Thu: 11AM-10PM")
- `category`: Primary and secondary business classifications (e.g., "Pizza, Italian")

These fields appear in predictable locations across Yelp's site structure, making them ideal candidates for schema-based extraction.

## The extraction approach
Raw HTTP requests combined with HTML parsing create fragile pipelines for Yelp due to:
- Frequent frontend framework updates breaking CSS selectors
- JavaScript-rendered content requiring headless browser execution
- Anti-bot measures triggering CAPTCHAs or IP blocks during scaling

A data API approach solves these by abstracting the retrieval complexity. AlterLab handles:
- Automatic tier escalation (T1-T5) based on detected bot resistance
- Proxy rotation and session management
- Structured output generation via AI-powered semantic understanding
This transforms extraction from a maintenance burden into a reliable API call.

## Quick start with AlterLab Extract API
Begin by installing the SDK and making your first extraction request. See the [Getting started guide](/docs/quickstart/installation) for setup details.

Here's a Python example extracting core business fields from a Yelp page:
```python title="extract_yelp-com.py" {5-12}
import alterlab

client = alterlab.Client("YOUR_API_KEY")

schema = {
  "type": "object",
  "properties": {
    "business_name": {
      "type": "string",
      "description": "The business name field"
    },
    "rating": {
      "type": "string",
      "description": "The rating field"
    },
    "address": {
      "type": "string",
      "description": "The address field"
    },
    "phone": {
      "type": "string",
      "description": "The phone field"
    },
    "hours": {
      "type": "string",
      "description": "The hours field"
    },
    "category": {
      "type": "string",
      "description": "The category field"
The category field"
    }
  }
}

result = client.extract(
    url="https://www.yelp.com/biz/joes-pizza-new-york",
    schema=schema,
)
print(result.data)
```

For direct HTTP interaction, use this cURL equivalent:
```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://www.yelp.com/biz/joes-pizza-new-york",
    "schema": {
      "properties": {
        "business_name": {"type": "string"},
        "rating": {"type": "string"},
        "address": {"type": "string"}
      }
    }
  }'
```

## Define your schema
The Extract API validates output against your JSON Schema definition, ensuring type safety and field presence. Key considerations for Yelp data:
- Use `string` type for all fields since Yelp presents data as formatted text
- Add `description` to clarify field semantics for the extraction model
- Specify `required` array for critical fields (e.g., `["business_name", "rating"]`)
- Leverage `pattern` or `enum` where values follow known formats (e.g., phone numbers)

AlterLab returns strictly typed JSON matching your schema—no need for post-processing validation. This is fundamental to treating AlterLab as a data API rather than a scraper.

## Handle pagination and scale
For extracting multiple Yelp listings (e.g., search results or category pages):
1. **Batch processing**: Send 10-50 URLs per request using the `urls` array parameter
2. **Rate limiting**: AlterLab automatically enforces polite crawling; monitor `X-RateLimit-Remaining` headers
3. **Async workflows**: Use webhook notifications for large jobs instead of polling
4. **Cost optimization**: Set `min_tier=3` for JavaScript-heavy Yelp pages to avoid unnecessary T1/T2 attempts

See [AlterLab pricing](/pricing) for volume tiers—extraction costs scale linearly with successful requests, making high-volume pipelines predictable.

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

## Key takeaways
- Structured Yelp data extraction requires schema definition, not selector maintenance
- AlterLab's Extract API handles anti-bot measures and outputs validated JSON
- Publicly available fields like business_name, rating, and address are reliably accessible
- Always verify compliance with Yelp's robots.txt and Terms of Service
- Treat AlterLab as a data API: define your schema, call the endpoint, use the output

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

<div data-infographic="try-it" data-url="https://yelp.com" data-description="Extract structured local data from Yelp"></div>
```

## Frequently Asked Questions

### Is there an official Yelp data API?

Yelp offers an official API for certain business data access, but it has restrictions and approval processes. AlterLab provides a complementary solution for extracting publicly available Yelp data as structured JSON via a simple API call, ideal for developers needing flexible, schema-driven extraction without navigating official API limitations.

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

You can extract publicly available local business data such as business name, rating, address, phone number, hours, and categories. AlterLab's Extract API uses a JSON schema you define to return validated, typed output — ensuring you get exactly the fields you need in the correct format without manual parsing.

### How much does Yelp data extraction cost?

AlterLab operates on a pay-as-you-go model with no minimums or expiring credits. Costs are based on the number of successful extract requests and the complexity tier used (determined by the target site's anti-bot measures). See our pricing page for detailed rates and volume discounts.

## Related

- [Lowe's Data API: Extract Structured JSON in 2026](<https://alterlab.io/blog/lowe-s-data-api-extract-structured-json-in-2026>)
- [How to Migrate from Scrapfly to AlterLab: Step-by-Step Guide \(2026\)](<https://alterlab.io/blog/how-to-migrate-from-scrapfly-to-alterlab-step-by-step-guide-2026>)
- [Scaling Web Scraping Pipelines for High-Volume Data](<https://alterlab.io/blog/scaling-web-scraping-pipelines-for-high-volume-data>)