A comprehensive, professional web scraping framework built with Python. This project demonstrates advanced software engineering practices and production-ready features.
- Smart Detection: Automatically detects static vs dynamic content
- User-Agent Rotation: Rotates between multiple browser user agents
- Exponential Backoff: Intelligent retry mechanism with exponential backoff
- Proxy Support: Built-in proxy rotation and management
- Rate Limiting: Configurable delays to respect website limits
- Robots.txt Compliance: Respects robots.txt files automatically
- Multiple Storage Formats: CSV, Excel, JSON, SQLite database
- Automatic Deduplication: Smart duplicate detection and removal
- Data Validation: Comprehensive data validation and cleaning
- Timestamp Management: Automatic timestamping of all records
- Batch Processing: Efficient handling of large datasets
- Selenium Integration: Full Selenium WebDriver support
- Headless Mode: Configurable headless browser operation
- Element Waiting: Smart element waiting and detection
- JavaScript Execution: Execute custom JavaScript if needed
- Fallback Mechanism: Automatic fallback between requests and Selenium
- Comprehensive Arguments: Full-featured command-line interface
- Batch Processing: Process multiple URLs from files
- Scheduling Support: Built-in scheduling functionality
- Progress Reporting: Real-time progress and statistics
- Configuration Management: Save/load configuration files
- Flask Dashboard: Professional web interface
- REST API: Complete REST API for programmatic access
- Real-time Monitoring: Live scraping status and statistics
- File Downloads: Download scraped data through web interface
- Job Management: Manage scheduled scraping jobs
- Comprehensive Charts: Multiple chart types for data analysis
- Statistical Analysis: Automatic statistical insights
- Quality Metrics: Data quality assessment
- Export Capabilities: High-resolution chart exports
web-scraping-project/
├── src/ # Source code
│ ├── core/ # Core scraping engine
│ │ ├── engine.py # Smart scraping engine
│ │ └── scraper.py # Advanced web scraper
│ ├── parsers/ # Data parsing components
│ │ └── data_parser.py # Advanced data parser
│ ├── storage/ # Storage components
│ │ └── advanced_storage.py # Multi-format storage
│ ├── utils/ # Utility components
│ │ ├── config.py # Configuration management
│ │ ├── logger.py # Advanced logging system
│ │ ├── visualization.py # Data visualization
│ │ └── scheduler.py # Scheduling functionality
│ ├── cli/ # Command-line interface
│ │ └── advanced_cli.py # Advanced CLI
│ └── web/ # Web application
│ └── flask_app.py # Flask web app
├── data/ # Database files
├── output/ # Output files (CSV, Excel, JSON)
├── logs/ # Log files
├── config/ # Configuration files
├── main.py # Main entry point
├── requirements.txt # Python dependencies
└── README.md # This file
- Python 3.8 or higher
- Chrome/Chromium browser (for Selenium)
- Git (for cloning)
- Clone the repository
git clone <repository-url>
cd web-scraping-project- Create virtual environment
python -m venv venv
# On Windows
venv\Scripts\activate
# On Unix/MacOS
source venv/bin/activate- Install dependencies
pip install -r requirements.txt- Install ChromeDriver (optional)
# The system will automatically download the required ChromeDriver
# Or install manually: https://chromedriver.chromium.org/# Scrape a single website
python main.py http://books.toscrape.com/
# Scrape multiple pages
python main.py http://books.toscrape.com/ --pages 5
# Save in multiple formats
python main.py http://books.toscrape.com/ --formats csv excel json sqlite# Use Selenium for dynamic content
python main.py https://example.com --selenium --headless
# Concurrent scraping
python main.py http://books.toscrape.com/ --concurrent --pages 10
# Custom rate limiting
python main.py http://books.toscrape.com/ --rate-limit 2.0
# Proxy support
python main.py http://books.toscrape.com/ --proxy http://proxy:8080# Create a file with URLs (urls.txt)
# http://site1.com
# http://site2.com
# http://site3.com
# Scrape all URLs
python main.py urls.txt --batch --batch-delay 5.0# Schedule scraping every 30 minutes
python main.py http://books.toscrape.com/ --schedule 30
# Schedule with maximum runs
python main.py http://books.toscrape.com/ --schedule 60 --max-runs 24# Generate visualizations
python main.py http://books.toscrape.com/ --visualize --pages 5
# Custom visualization filename
python main.py http://books.toscrape.com/ --visualize --output analysis_data# Start the web application
python -c "from src.web.flask_app import run_web_app; run_web_app()"
# Then open http://localhost:5000 in your browserexport SCRAPER_LOG_LEVEL=INFO
export SCRAPER_TIMEOUT=30
export SCRAPER_MAX_RETRIES=3
export SCRAPER_PROXY_ENABLED=false
export SCRAPER_SELENIUM_ENABLED=trueCreate config/scraper_config.json:
{
"DEFAULT_TIMEOUT": 30,
"MAX_RETRIES": 3,
"DEFAULT_MAX_PAGES": 5,
"RATE_LIMIT_DELAY": 1.0,
"PROXY_ENABLED": false,
"SELENIUM_ENABLED": true,
"VISUALIZATION_ENABLED": true
}curl -X POST http://localhost:5000/api/scrape \
-H "Content-Type: application/json" \
-d '{
"url": "http://books.toscrape.com/",
"max_pages": 3,
"formats": ["csv", "excel"],
"concurrent": true
}'curl http://localhost:5000/api/scrape/scrape_1234567890/statuscurl http://localhost:5000/api/data?limit=100curl -X POST http://localhost:5000/api/schedule \
-H "Content-Type: application/json" \
-d '{
"url": "http://books.toscrape.com/",
"schedule_pattern": "every 30 minutes",
"max_pages": 5
}'The system automatically generates comprehensive visualizations:
- Price Distribution: Histogram and box plots
- Rating Analysis: Distribution, pie charts, and price correlations
- Temporal Analysis: Time-based patterns and trends
- Data Quality: Completeness and missing value analysis
- Statistical Summaries: Key metrics and insights
- Multi-threaded scraping for improved performance
- Configurable concurrency limits
- Rate limiting to prevent overwhelming servers
- Batch processing for large datasets
- Efficient memory usage patterns
- Garbage collection optimization
- Automatic retry with exponential backoff
- Graceful degradation on failures
- Comprehensive error logging
- Request caching to avoid duplicate calls
- Configuration caching
- Result caching for repeated queries
The system includes built-in features for ethical scraping:
- Robots.txt Compliance: Automatically respects robots.txt files
- Rate Limiting: Configurable delays between requests
- User-Agent Rotation: Mimics real browser behavior
- Request Headers: Proper browser headers
- Session Management: Efficient connection reuse
# Run CLI
python main.py http://example.com/
# Run web app
python -c "from src.web.flask_app import run_web_app; run_web_app()"FROM python:3.9-slim
WORKDIR /app
COPY requirements.txt .
RUN pip install -r requirements.txt
COPY . .
EXPOSE 5000
CMD ["python", "-c", "from src.web.flask_app import run_web_app; run_web_app()"]- AWS Lambda: Serverless scraping functions
- Google Cloud Run: Containerized web app
- Azure Functions: Event-driven scraping
- Heroku: Easy web app deployment
This system can be packaged as various freelance services:
- E-commerce Data Scraping: Product prices, descriptions, reviews
- Real Estate Listings: Property details, prices, images
- Job Market Analysis: Job postings, salaries, requirements
- Social Media Monitoring: Public posts, trends, analytics
- Website Monitoring: Track changes, price drops, new content
- Competitor Analysis: Monitor competitor websites and strategies
- Market Research: Collect industry data and trends
- Lead Generation: Extract contact information and leads
- Scraping Strategy: Help companies design ethical scraping approaches
- Compliance Consulting: Ensure scraping practices are legal and ethical
- Performance Optimization: Improve existing scraping systems
- Training: Teach teams how to implement scraping solutions
- Per Project: Fixed price for specific scraping tasks
- Hourly Rate: $50-150/hour depending on complexity
- Retainer: Monthly fee for ongoing monitoring
- Data-as-a-Service: Subscription for regular data delivery
# Install test dependencies
pip install pytest pytest-cov
# Run tests
pytest tests/ -v --cov=src
# Run specific test
pytest tests/test_engine.py -v# Format code
black src/
# Lint code
flake8 src/
# Type checking
mypy src/- Create feature branch:
git checkout -b feature/new-feature - Implement changes with tests
- Run quality checks
- Submit pull request
- Fork the repository
- Create a feature branch
- Make your changes
- Add tests for new functionality
- Ensure all tests pass
- Submit a pull request
This project is licensed under the MIT License - see the LICENSE file for details.
For support and questions:
- Documentation: Check the inline code documentation
- Issues: Create an issue on GitHub
- Email: contact@advancedscraper.com
- Discord: Join our community server
This project demonstrates:
- Advanced Python Programming: Modern Python practices
- Software Architecture: Clean, modular design
- Performance Optimization: Efficient algorithms and data structures
- Professional Development: Industry-standard practices
- Full-Stack Skills: CLI, web app, API development
- Data Engineering: ETL pipelines and data processing
Perfect for:
- Portfolio Projects: Showcase advanced development skills
- Job Applications: Demonstrate professional expertise
- Freelance Work: Ready-to-use scraping solutions
- Learning: Study advanced Python and web scraping techniques