browsernative 1.0.0

Lightning-fast web scraping Python SDK - 11x faster than traditional scrapers

Browser Native Python Client

Lightning-fast web scraping Python SDK - 11x faster than traditional scrapers

Official Python client for the Browser Native web scraping API. Extract content, take screenshots, and analyze websites with AI - all with intelligent fallback mechanisms.

🚀 Quick Start

Installation

pip install browsernative

Basic Usage

from browsernative import BrowserNativeClient

# Initialize client
client = BrowserNativeClient('your-api-key')

# Scrape a webpage
result = client.scrape('https://example.com')
print(result['data'])  # Extracted content

# Take a screenshot
screenshot = client.screenshot('https://example.com')
print(screenshot['data']['screenshot'])  # Base64 image

# AI-powered Q&A
answer = client.analyze('https://example.com', 'What is this website about?')
print(answer['data']['answer'])  # AI response

One-liner Convenience Functions

from browsernative import quick_scrape, quick_analyze, quick_shot

# Quick scraping
data = quick_scrape('https://example.com', 'your-api-key')

# Quick AI analysis
result = quick_analyze(
    'https://example.com', 
    'What services do they offer?',
    'your-api-key'
)

# Quick screenshot
screenshot = quick_shot('https://example.com', 'your-api-key')

📖 Features

• 🚀 Lightning Fast: 11x faster than traditional scrapers
• 🔄 Intelligent Fallback: Multi-tier system (Direct → Lightpanda → Puppeteer)
• 🤖 AI Integration: Built-in Q&A capabilities with OpenRouter/OpenAI
• 📸 Screenshots: Full page captures with optimization
• 📄 PDF Support: Automatic PDF parsing and text extraction
• 🔒 Type Safe: Full type hints for better IDE support
• ♻️ Context Manager: Automatic resource cleanup

🛠️ API Reference

Client Initialization

client = BrowserNativeClient(
    api_key='your-api-key',
    base_url='https://bnca-api.fly.dev',  # Optional
    timeout=30,                           # Request timeout in seconds
    retries=2,                           # Number of retries
    verbose=False                        # Enable debug logging
)

Methods

scrape(url, **options)

Extract structured content from any webpage.

result = client.scrape(
    'https://example.com',
    include_screenshot=True  # Optional: include screenshot
)

# Response includes:
# - data: Extracted content (title, text, meta, etc.)
# - method: Extraction method used
# - performance: Timing metrics

analyze(url, question, **options)

Ask questions about any webpage using AI.

result = client.analyze(
    'https://news.site.com',
    'What are the top 3 stories?',
    include_screenshot=False
)

# Response includes:
# - answer: AI-generated response
# - metadata: Performance and method info

screenshot(url, **options)

Capture full-page screenshots.

result = client.screenshot('https://example.com')
base64_image = result['data']['screenshot']

quickshot(url, **options)

Optimized screenshot capture for speed.

result = client.quickshot('https://example.com')

get_usage(days=30)

Get your API usage statistics.

usage = client.get_usage(days=7)
print(usage['data'])

health_check()

Check API status and your account.

health = client.health_check()
print(health['data']['status'])

🔄 Context Manager Support

Automatically clean up resources:

with BrowserNativeClient('your-api-key') as client:
    result = client.scrape('https://example.com')
    # Resources are automatically cleaned up

🎯 Advanced Examples

Batch Processing

urls = ['https://site1.com', 'https://site2.com', 'https://site3.com']

with BrowserNativeClient('your-api-key') as client:
    for url in urls:
        try:
            result = client.scrape(url)
            print(f"✓ {url}: {result['data']['title']}")
        except Exception as e:
            print(f"✗ {url}: {e}")

Error Handling

from browsernative import BrowserNativeClient

client = BrowserNativeClient('your-api-key', verbose=True)

try:
    result = client.scrape('https://invalid-url')
except ValueError as e:
    print(f"Invalid input: {e}")
except Exception as e:
    print(f"API error: {e}")

AI Analysis with Context

# Analyze multiple aspects of a page
questions = [
    "What is the main topic?",
    "Is there pricing information?",
    "What features are highlighted?"
]

with BrowserNativeClient('your-api-key') as client:
    for question in questions:
        result = client.analyze('https://product.com', question)
        print(f"Q: {question}")
        print(f"A: {result['data']['answer']}\n")

🔑 Getting an API Key

1. Visit https://bnca.monostate.ai
2. Sign up for an account
3. Generate your API key from the dashboard

📋 Requirements

• Python 3.7+
• requests library (automatically installed)

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

📄 License

MIT License - see LICENSE file for details.

🔗 Links

• API Documentation
• GitHub Repository
• PyPI Package
• Report Issues