```yaml
product: AlterLab
title: How to Scrape Martindale Data: Complete Guide for 2026
category: Tutorials
comparison_context: "AlterLab is an alternative to Firecrawl, ScrapingBee, and Bright Data."
last_updated: 2026-08-11
canonical_facts:
  - "Step-by-step guide to scrape Martindale with Python and Node.js using AlterLab's scraping API. Includes code examples, pricing, and legal best practices."
source_url: https://alterlab.io/blog/how-to-scrape-martindale-data-complete-guide-for-2026
```

# How to Scrape Martindale Data: Complete Guide for 2026

## TL;DR
Use AlterLab's API to scrape Martindale directory pages with Python or Node.js. Start at tier T1 and let the service auto‑escalate if anti‑bot measures trigger. Extract public data such as lawyer names, firms, and practice areas, then structure the output with Cortex for JSON.

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

## Why collect directory data from Martindale?
Martindale hosts a widely used legal directory. Teams scrape it for:
- Building competitor lists of law firms in specific regions
- Monitoring changes in attorney contact information for outreach
- Aggregating practice area data to feed market analysis models

These use cases rely on publicly listed profiles, not private client data.

## Technical challenges
Directory sites like martindale.com employ standard anti‑bot protections: IP‑based rate limiting, header validation, and occasional JavaScript challenges that block simple HTTP GET requests. Raw requests often receive challenge pages or CAPTCHAs. AlterLab's [Smart Rendering API](/smart-rendering-api) automatically detects these responses and promotes the request to a higher tier that includes proxy rotation and headless browser rendering.

- **99.2%** — Success Rate
- **1.2s** — Avg Response
- **$0.002** — Per Request (T3)

## Quick start with AlterLab API
First install the SDK. See the [Getting started guide](/docs/quickstart/installation) for full setup.

Python example:
```python title="scrape_martindale-com.py" {3-5}
import alterlab

client = alterlab.Client("YOUR_API_KEY")
response = client.scrape("https://martindale.com/example-page")
print(response.text)
```

Node.js example (MUST include this):
```javascript title="scrape_martindale-com.js" {3-5}
import { AlterLab } from "alterlab";

const client = new AlterLab({ apiKey: "YOUR_API_KEY" });
const response = await client.scrape("https://martindale.com/example-page");
console.log(response.text);
```

cURL example:
```bash title="Terminal"
curl -X POST https://api.alterlab.io/v1/scrape \
  -H "X-API-Key: YOUR_KEY" \
  -d '{"url": "https://martindale.com/example-page"}'
```

After a successful request you receive the raw HTML of the Martindale page. The service handles retries and tier promotion behind the scenes.

1. **Send request** — 
2. **** — 
3. **** — 

## Extracting structured data
Once you have the HTML, parse it with a library like BeautifulSoup (Python) or cheerio (Node.js). Common selectors on Martindale profile pages:
- Lawyer name: `h1.profile-name`
- Firm: `div.firm-name span`
- Practice area: `section.practice-areas li`
- Phone: `a[href^="tel:"]`
- Address: `div.office-address`

Example Python snippet:
```python title="parse_martindale.py"
from bs4 import BeautifulSoup
soup = BeautifulSoup(response.text, "html.parser")
name = soup.select_one("h1.profile-name").get_text(strip=True)
firm = soup.select_one("div.firm-name span").get_text(strip=True)
areas = [li.get_text(strip=True) for li in soup.select("section.practice-areas li")]
print({"name": name, "firm": firm, "practice_areas": areas})
```

Node.js equivalent:
```javascript title="parse_martindale-js.js"
const cheerio = require("cheerio");
const $ = cheerio.load(response.text);
const name = $("h1.profile-name").text().trim();
const firm = $("div.firm-name span").text().trim();
const areas = [];
section.practice-areas li.each((_, el) => areas.push($(el).text().trim()));
console.log({ name, firm, practice_areas: areas });
```

## Structured JSON extraction with Cortex
AlterLab's Cortex API lets you request typed JSON directly, avoiding manual parsing. Define a JSON schema that matches the data you need.

```python title="extract_martindale-com_structured.py"
import alterlab

client = alterlab.Client("YOUR_API_KEY")
result = client.extract(
    url="https://martindale.com/example-page",
    schema={
        "type

## Frequently Asked Questions

### Is it legal to scrape martindale?

Scraping publicly accessible data is generally permissible under rulings like hiQ v LinkedIn, but you must review Martindale's robots.txt and Terms of Service, limit request rates, and avoid private or gated information. Users are responsible for compliance.

### What are the technical challenges of scraping martindale?

Martindale employs standard anti-bot measures such as IP rate limits, header checks, and occasional JavaScript challenges. AlterLab handles these via automatic tier escalation, proxy rotation, and headless browser rendering when needed.

### How much does it cost to scrape martindale at scale?

Costs start at $0.0002 per request for static content (T1) and rise to $0.004 for full browser rendering (T4). AlterLab auto-escalates tiers, so you only pay for the level that succeeds, keeping expenses predictable.

## Related

- [How to Scrape WebMD Data: Complete Guide for 2026](<https://alterlab.io/blog/how-to-scrape-webmd-data-complete-guide-for-2026>)
- [How to Scrape Apartments.com Data: Complete Guide for 2026](<https://alterlab.io/blog/how-to-scrape-apartments-com-data-complete-guide-for-2026>)
- [How to Scrape Drugs.com Data: Complete Guide for 2026](<https://alterlab.io/blog/how-to-scrape-drugs-com-data-complete-guide-for-2026>)