Supacrawler vs Selenium

Performance Benchmarks

Single Page Performance

Supacrawler is 3.0x faster despite identical JavaScript rendering.

Multi-Page Crawling

Technical Architecture

Selenium Sequential Processing

# One URL at a time - sequential bottleneck
for url in urls:
    driver.get(url)      # Block until complete
    extract_data()       # Process sequentially

Supacrawler Go Streaming

// Concurrent worker pool with goroutines
maxWorkers := 10
for i := 0; i < maxWorkers; i++ {
    go worker()  // Parallel processing
}

Performance Advantages:

• Go Concurrency vs Python sequential execution
• Streaming Architecture vs batch processing
• Memory Efficiency vs Python/Chrome overhead
• Managed cloud browsers vs local browser management

Content Quality

Selenium Raw Output

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Supacrawler LLM-Ready Output

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Supacrawler removes navigation, ads, and boilerplate while preserving structured content.

Use Cases

Code Comparison

from supacrawler import SupacrawlerClient

client = SupacrawlerClient(api_key="your-api-key")
result = client.scrape("https://example.com", render_js=True)
print(result.markdown)

from selenium import webdriver
from selenium.webdriver.chrome.options import Options

options = Options()
options.add_argument('--headless')
driver = webdriver.Chrome(options=options)

try:
    driver.get("https://example.com")
    content = driver.page_source
    # Need additional parsing...
finally:
    driver.quit()

Why Choose Supacrawler?

1. 3-20x Faster: Go concurrent architecture vs Python sequential
2. Zero Setup: No browser installation or management
3. LLM-Ready: Clean markdown output out of the box
4. Auto-Scaling: Cloud infrastructure handles load
5. Lower Resource Usage: No local browser overhead

When to Use Selenium

• UI/Browser automation testing
• Complex form interactions
• Need full browser control
• Budget allows for infrastructure costs