Getting Started with FineData API

Getting Started with FineData API

Welcome. This guide will walk you through setting up your account and making your first web scraping request in under 5 minutes.

Prerequisites

Before you begin, make sure you have:

• An account (sign up free)
• Python 3.8+ or Node.js 18+
• Your API key from the dashboard

Step 1: Get Your API Key

After creating your account, navigate to the API Keys section in your dashboard. Click Create New Key and give it a descriptive name like “Development”.

Keep your API key secure. Never commit it to version control or share it publicly.

Step 2: Install the SDK

Python

pip install finedata

Node.js

npm install finedata

Step 3: Make Your First Request

Here’s a minimal example that scrapes a webpage and returns structured data. The same fields work over REST with the x-api-key header if you prefer curl or requests over the SDK:

Python

from finedata import FineData

client = FineData(api_key="your-api-key")

result = client.scrape(
    url="https://example.com",
    options={
        "use_js_render": True,
        "timeout": 30
    }
)

print(result.content)      # Page HTML content
print(result.status_code)  # HTTP status
print(result.metadata)     # Extracted metadata

Node.js

import { FineData } from 'finedata';

const client = new FineData({ apiKey: 'your-api-key' });

const result = await client.scrape({
  url: 'https://example.com',
  options: {
    use_js_render: true,
    timeout: 30,
  },
});

console.log(result.content);
console.log(result.statusCode);
console.log(result.metadata);

Step 4: Stronger Rendering Modes

For pages that gate content behind a challenge, enable full-browser rendering with a matching TLS profile and a residential exit. You only pay when the page renders:

result = client.scrape(
    url="https://example.com/catalog",
    options={
        "use_js_render": True,
        "stealth_antibot": True,
        "tls_profile": "chrome124",
        "use_residential": True,
        "solve_captcha": True
    }
)

stealth_antibot is the strongest managed rendering mode for most sites. For the hardest targets, try stealth_antibot_headful — and remember that a failed render is not billed.

Step 5: Parse Structured Data

Extract specific data points using CSS selectors:

result = client.scrape(
    url="https://example.com/products",
    extract={
        "title": "h1.product-title",
        "price": ".price-current",
        "description": ".product-description p",
        "images": ["img.product-image @src"]
    }
)

for item in result.extracted:
    print(f"{item['title']}: {item['price']}")

Understanding Token Usage

Each request consumes tokens based on the features used:

Feature	Token Cost
Base request	1 token
JavaScript rendering (use_js_render)	+5 tokens
Browser-grade TLS (use_antibot, on by default)	+2 tokens
Residential proxy (use_residential)	+3 tokens
Captcha solving (solve_captcha)	+10 tokens

Monitor your usage in the dashboard or via the API:

usage = client.get_usage()
print(f"Tokens used: {usage.tokens_used}/{usage.tokens_limit}")

What’s Next?

Now that you’ve made your first request, explore these resources:

• API Reference — Complete endpoint documentation
• Proxy Configuration — TLS profiles and proxy options
• Batch Scraping — Process multiple URLs efficiently
• Webhooks — Async scraping with callbacks
• Scraping API vs. DIY: a cost comparison — the math on when to keep building your own scraper and when to switch
• Starting a data business on scraped data — what changes once scraping is the product, not a side tool

Need help? Reach out to our support team or join the community on Discord.