google-search-aj 1.0.6

Fast, lightweight Google search scraper with stealth mode

Google Search Scraper

A fast, lightweight, and easy-to-use Python package for scraping Google search results with built-in stealth mode to avoid detection.

✨ Features

• 🚀 Fast: Optimized for speed with minimal overhead
• 🥷 Stealth Mode: Built-in anti-detection features
• 🎯 Simple API: Easy to use for both beginners and experts
• 📦 Zero Config: Playwright browser auto-installs on package installation
• 🔧 Flexible: Highly configurable with sensible defaults
• 💻 CLI Support: Use from command line or as a Python module
• 🎨 Multiple Output Formats: JSON and text output supported
• 📄 Content Extraction: Extract and analyze full page content from search results
• 💾 Auto-Save: Automatically save results to file with full content
• 🧹 Clean Text: Intelligent HTML parsing and text extraction

📦 Installation

pip install google-search-aj

The package will automatically install Playwright and download the Chromium browser during installation.

If automatic installation fails, manually install Playwright browsers:

playwright install chromium

🚀 Quick Start

Python API

from google_search_scraper import search

# Simple search
results = search("python tutorial")
print(results.urls)
# ['https://docs.python.org/3/tutorial/', 'https://www.w3schools.com/python/', ...]

# Access the direct answer (if available)
print(results.answer)
# 'Python is a high-level, general-purpose programming language...'

# Get more details
print(f"Found {results.total_results} results in {results.search_time:.2f} seconds")

# Extract full page content
results = search("machine learning", max_results=3, extract_content=True)
for content in results.contents:
    print(f"{content.title}: {content.word_count} words")
    print(f"Preview: {content.content[:200]}...")

# Auto-save to file with content extraction
results = search(
    "python tutorial", 
    extract_content=True, 
    save_to_file=True,  # Auto-save enabled
    output_file="search_results.txt"  # Custom filename
)
# Results automatically saved with full content!

Command Line

# Simple search
google-search "python tutorial"

# Limit results
google-search "best restaurants" --max-results 20

# Save to file
google-search "machine learning" --output results.txt

# JSON output
google-search "data science" --format json

# Run with visible browser (debugging)
google-search "web scraping" --visible

📖 Usage Examples

Basic Usage

from google_search_scraper import search

# Default: 10 results with answer extraction
results = search("artificial intelligence")

for i, url in enumerate(results.urls, 1):
    print(f"{i}. {url}")

Advanced Usage

from google_search_scraper import GoogleSearchScraper

# Create a scraper with custom settings
scraper = GoogleSearchScraper(
    max_results=20,          # Get more results
    timeout=60000,           # Increase timeout
    headless=False,          # Show browser (for debugging)
    stealth_mode=True,       # Enable anti-detection (default)
    extract_content=True     # Extract page content
)

# Perform search
results = scraper.search("python web scraping", extract_answer=True)

# Access results
print(f"Query: {results.query}")
print(f"Time: {results.search_time:.2f}s")
print(f"Answer: {results.answer}")
print(f"URLs: {len(results.urls)}")
print(f"Content extracted: {len(results.contents)} pages")

# Convert to dictionary
data = results.to_dict()

Content Extraction

from google_search_scraper import search

# Extract content from search results
results = search("machine learning tutorial", max_results=5, extract_content=True)

# Access extracted content
for content in results.contents:
    if not content.error:
        print(f"\nTitle: {content.title}")
        print(f"URL: {content.url}")
        print(f"Word Count: {content.word_count:,}")
        print(f"Content Preview: {content.content[:200]}...")
    else:
        print(f"Failed to extract: {content.url} - {content.error}")

# Auto-save to file
results = search(
    "python web scraping",
    extract_content=True,
    save_to_file=True,  # Auto-save enabled
    output_file="my_search.txt"
)
print(f"✓ Results saved with full content!")

# Or save manually
results = search("AI tutorial", extract_content=True)
results.save_to_file("ai_results.txt")

Multiple Searches

from google_search_scraper import search

queries = ["python", "javascript", "rust"]

for query in queries:
    results = search(query, max_results=5)
    print(f"\n{query}: {len(results.urls)} results")
    print(results.urls[0] if results.urls else "No results")

Error Handling

from google_search_scraper import search
from google_search_scraper.exceptions import (
    GoogleSearchError,
    RateLimitError,
    BrowserError,
    SearchTimeoutError
)

try:
    results = search("test query", timeout=10000)
except RateLimitError:
    print("Being rate limited by Google. Try again later.")
except SearchTimeoutError:
    print("Search timed out. Try increasing the timeout.")
except BrowserError:
    print("Browser failed to launch.")
except GoogleSearchError as e:
    print(f"Search failed: {e}")

Batch Processing

from google_search_scraper import search
import time

queries = [
    "machine learning",
    "deep learning",
    "neural networks"
]

all_results = []

for query in queries:
    print(f"Searching: {query}")
    results = search(query, max_results=15)
    all_results.append(results)
    
    # Be respectful - add delay between searches
    time.sleep(5)

# Process results
for result in all_results:
    print(f"\n{result.query}:")
    print(f"  - Answer: {result.answer[:100] if result.answer else 'N/A'}")
    print(f"  - URLs: {len(result.urls)}")

🎯 API Reference

Main Functions

search(query, max_results=10, extract_answer=True, extract_content=False, headless=True, timeout=30000, save_to_file=False, output_file="search_results.txt")

Convenience function for quick searches.

Parameters:

• query (str): Search query string
• max_results (int): Maximum URLs to return (default: 10)
• extract_answer (bool): Extract Google's direct answer (default: True)
• extract_content (bool): Extract page content from URLs (default: False)
• headless (bool): Run browser in headless mode (default: True)
• timeout (int): Page load timeout in milliseconds (default: 30000)
• save_to_file (bool): Automatically save results to file (default: False)
• output_file (str): Name of the output file (default: search_results.txt)

Returns: SearchResult object

Classes

GoogleSearchScraper

Main scraper class with configurable options.

scraper = GoogleSearchScraper(
    max_results=10,
    timeout=30000,
    headless=True,
    stealth_mode=True,
    user_agent=None,
    extract_content=False
)

Methods:

• search(query, extract_answer=True): Perform a search

SearchResult

Container for search results.

Attributes:

• query (str): The search query
• answer (str | None): Google's direct answer if available
• urls (List[str]): List of result URLs
• total_results (int): Number of URLs returned
• search_time (float): Time taken for search in seconds
• timestamp (float): Unix timestamp of search
• contents (List[PageContent]): Extracted page content (if extract_content=True)

Methods:

• to_dict(): Convert to dictionary
• save_to_file(filename="search_results.txt"): Save results to text file with full content

PageContent

Container for extracted page content.

Attributes:

• url (str): The page URL
• title (str | None): Page title
• content (str): Extracted clean text content
• word_count (int): Number of words in content
• error (str | None): Error message if extraction failed

Exceptions

• GoogleSearchError: Base exception for all errors
• RateLimitError: Raised when rate limited by Google
• BrowserError: Raised when browser fails
• SearchTimeoutError: Raised when search times out
• NoResultsError: Raised when no results found

🎛️ CLI Reference

usage: google-search [-h] [-n N] [--no-answer] [--visible] [--timeout MS]
                     [-o FILE] [-f {text,json}] [-v] [-q]
                     [query]

positional arguments:
  query                 Search query (if not provided, enters interactive mode)

optional arguments:
  -h, --help            show this help message and exit
  -n N, --max-results N
                        Maximum number of results to return (default: 10)
  --no-answer           Skip extracting Google's direct answer
  --visible             Run browser in visible mode (for debugging)
  --timeout MS          Page load timeout in milliseconds (default: 30000)
  -o FILE, --output FILE
                        Save results to file
  -f {text,json}, --format {text,json}
                        Output format: text or json (default: text)
  -v, --version         show program's version number and exit
  -q, --quiet           Suppress all output except results

⚠️ Important Notes

Rate Limiting

Google may rate limit or block requests if you make too many searches too quickly. To avoid this:

1. Add delays between searches (5-10 seconds recommended)
2. Use residential proxies for large-scale scraping
3. Respect robots.txt and Google's Terms of Service

Legal Considerations

Web scraping may have legal implications. This tool is for educational and research purposes. Users are responsible for:

• Complying with Google's Terms of Service
• Respecting robots.txt
• Following applicable laws and regulations
• Not using for commercial purposes without permission

Detection

While this package includes stealth features, Google continuously updates their detection methods. If you're being blocked:

1. Increase delays between requests
2. Use headless=False to run in visible mode
3. Consider using residential proxies
4. Rotate user agents

🛠️ Development

Setup Development Environment

# Clone the repository
git clone https://github.com/Aaditya17032002/google-search.git
cd google-search

# Create virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install in development mode
pip install -e ".[dev]"

# Install Playwright browsers
playwright install chromium

Running Tests

pytest tests/

Code Formatting

black google_search_scraper/
flake8 google_search_scraper/

🤝 Contributing

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

1. Fork the repository
2. Create your feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

📝 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

• Built with Playwright
• Inspired by the need for a simple, reliable Google search scraper

📧 Support

If you encounter any issues or have questions:

• Open an issue on GitHub
• Check existing issues for solutions

🔄 Changelog

v1.0.4 (2024-11-03)

• Auto-save to file: Save results with full content automatically
• Manual save with save_to_file() method
• Comprehensive file format with all data

v1.0.3 (2024-11-03)

• Content extraction: Extract full page content from URLs
• BeautifulSoup4 integration for HTML parsing
• Async content extraction for better performance
• PageContent dataclass with title, content, word count

v1.0.0 (2024-11-03)

• Initial release
• Fast Google search scraping
• Stealth mode with anti-detection
• CLI and Python API
• Auto-installation of Playwright
• JSON and text output formats

See CHANGELOG.md for full version history.

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