Initial commit: Market Trends Scraper

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+MIT License
+
+Copyright (c) 2023 Market Trends Scraper
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
--- a/README.md
+++ b/README.md
@@ -0,0 +1,340 @@
+# Market Trends Scraper
+
+A powerful and flexible Python web scraper for collecting and analyzing pricing and product trends from e-commerce websites. This tool provides comprehensive market insights by extracting product data, tracking price changes, and generating detailed trend analyses.
+
+## Features
+
+- **Multi-Source Scraping**: Collect data from multiple e-commerce websites simultaneously
+- **Flexible Configuration**: Easy-to-use YAML configuration for different sources and scraping parameters
+- **Dual Scraping Methods**: Supports both requests/BeautifulSoup and Selenium for dynamic content
+- **Data Analysis**: Built-in analysis of pricing trends, ratings, and product availability
+- **Multiple Output Formats**: Save data in CSV, JSON, or Excel formats
+- **Robust Error Handling**: Comprehensive error handling and retry mechanisms
+- **Professional Logging**: Detailed logging with configurable levels and outputs
+- **Extensible Architecture**: Modular design for easy customization and extension
+
+## Installation
+
+### Prerequisites
+
+- Python 3.8 or higher
+- Chrome browser (for Selenium functionality)
+- ChromeDriver (compatible with your Chrome version)
+
+### Setup
+
+1. Clone the repository:
+```bash
+git clone https://github.com/iwasforcedtobehere/market-trends-scraper.git
+cd market-trends-scraper
+```
+
+2. Create and activate a virtual environment:
+```bash
+python -m venv venv
+source venv/bin/activate  # On Windows: venv\Scripts\activate
+```
+
+3. Install dependencies:
+```bash
+pip install -r requirements.txt
+```
+
+4. Install ChromeDriver (if using Selenium):
+```bash
+# For Ubuntu/Debian:
+sudo apt-get install chromium-chromedriver
+
+# For macOS using Homebrew:
+brew install chromedriver
+
+# For Windows, download from: https://chromedriver.chromium.org/
+```
+
+## Configuration
+
+The scraper uses a YAML configuration file to define scraping sources and parameters. A default configuration will be created automatically at `config/config.yaml` when you first run the scraper.
+
+### Example Configuration
+
+```yaml
+scraper:
+  delay_between_requests: 1.0
+  timeout: 30
+  max_retries: 3
+  user_agent: "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36"
+  headless: true
+  window_size: [1920, 1080]
+
+sources:
+  - name: "example_ecommerce"
+    url: "https://example-ecommerce.com/search"
+    type: "ecommerce"
+    enabled: true
+    use_selenium: false
+    selectors:
+      product: "div.product-item"
+      name: "h2.product-title"
+      price: "span.price"
+      rating: "div.rating"
+      availability: "div.stock-status"
+    pagination:
+      next_page: "a.next-page"
+      max_pages: 10
+
+output:
+  format: "csv"
+  include_timestamp: true
+  filename: "market_trends_data"
+
+database:
+  url: "sqlite:///data/market_trends.db"
+  echo: false
+
+analysis:
+  price_history_days: 30
+  trend_threshold: 0.05
+  generate_charts: true
+```
+
+### Configuration Options
+
+#### Scraper Settings
+- `delay_between_requests`: Delay between requests in seconds (default: 1.0)
+- `timeout`: Request timeout in seconds (default: 30)
+- `max_retries`: Maximum number of retry attempts for failed requests (default: 3)
+- `user_agent`: User agent string for HTTP requests
+- `headless`: Run browser in headless mode (default: true)
+- `window_size`: Browser window size as [width, height] (default: [1920, 1080])
+
+#### Source Configuration
+- `name`: Unique identifier for the data source
+- `url`: Base URL for scraping
+- `type`: Type of website (e.g., "ecommerce")
+- `enabled`: Whether to scrape this source (default: true)
+- `use_selenium`: Use Selenium instead of requests (default: false)
+- `selectors`: CSS selectors for extracting data
+- `pagination`: Pagination settings
+
+#### Output Settings
+- `format`: Output format ("csv", "json", or "excel")
+- `include_timestamp`: Include timestamp in output filename (default: true)
+- `filename`: Base filename for output files
+
+#### Analysis Settings
+- `price_history_days`: Number of days to consider for price history (default: 30)
+- `trend_threshold`: Minimum price change percentage to consider as a trend (default: 0.05)
+- `generate_charts`: Generate trend charts (default: true)
+
+## Usage
+
+### Command Line Interface
+
+Run the scraper with default settings:
+```bash
+python main.py
+```
+
+Specify a custom configuration file:
+```bash
+python main.py --config path/to/config.yaml
+```
+
+Specify output file:
+```bash
+python main.py --output path/to/output.csv
+```
+
+Run in verbose mode:
+```bash
+python main.py --verbose
+```
+
+Run browser in non-headless mode (for debugging):
+```bash
+python main.py --no-headless
+```
+
+### Python API
+
+```python
+from src.config_manager import ConfigManager
+from src.scraper import MarketTrendsScraper
+from src.logger import setup_logger
+
+# Setup logging
+setup_logger(verbose=True)
+
+# Load configuration
+config_manager = ConfigManager("config/config.yaml")
+config = config_manager.load_config()
+
+# Initialize scraper
+with MarketTrendsScraper(config, headless=True) as scraper:
+    # Scrape data
+    data = scraper.scrape_market_trends()
+    
+    # Save data
+    scraper.save_data(data, "output.csv")
+    
+    # Analyze trends
+    analysis = scraper.analyze_trends(data)
+    
+    # Save analysis
+    scraper.save_analysis(analysis, "analysis.json")
+```
+
+## Output
+
+### Data Output
+
+The scraper produces structured data with the following fields:
+
+| Field | Description |
+|-------|-------------|
+| name | Product name |
+| price | Product price (as float) |
+| rating | Product rating (as float) |
+| availability | Product availability status |
+| url | Product URL |
+| source | Data source name |
+| scraped_at | Timestamp when data was scraped |
+
+### Analysis Output
+
+The trend analysis includes:
+
+- **Summary Statistics**: Total products, source distribution
+- **Price Analysis**: Average, min, max, median prices and distribution
+- **Rating Analysis**: Average, min, max ratings and distribution
+- **Availability Analysis**: Count of products by availability status
+- **Price Trends by Source**: Comparative analysis across sources
+
+Example analysis output:
+```json
+{
+  "total_products": 150,
+  "sources": {
+    "example_ecommerce": 100,
+    "another_store": 50
+  },
+  "price_analysis": {
+    "average_price": 49.99,
+    "min_price": 9.99,
+    "max_price": 199.99,
+    "median_price": 45.00,
+    "price_distribution": {
+      "count": 150,
+      "mean": 49.99,
+      "std": 35.25,
+      "min": 9.99,
+      "25%": 25.00,
+      "50%": 45.00,
+      "75%": 75.00,
+      "max": 199.99
+    }
+  },
+  "rating_analysis": {
+    "average_rating": 4.2,
+    "min_rating": 1.0,
+    "max_rating": 5.0,
+    "rating_distribution": {
+      "5.0": 45,
+      "4.0": 60,
+      "3.0": 30,
+      "2.0": 10,
+      "1.0": 5
+    }
+  }
+}
+```
+
+## Testing
+
+Run all tests:
+```bash
+pytest
+```
+
+Run unit tests only:
+```bash
+pytest -m unit
+```
+
+Run integration tests only:
+```bash
+pytest -m integration
+```
+
+Run tests with coverage report:
+```bash
+pytest --cov=src --cov-report=html
+```
+
+## Project Structure
+
+```
+market-trends-scraper/
+├── src/
+│   ├── __init__.py
+│   ├── config_manager.py    # Configuration management
+│   ├── logger.py            # Logging utilities
+│   └── scraper.py           # Main scraper implementation
+├── tests/
+│   ├── __init__.py
+│   ├── test_config_manager.py
+│   ├── test_logger.py
+│   ├── test_scraper.py
+│   └── test_integration.py
+├── config/
+│   └── config.yaml          # Configuration file
+├── data/                    # Output data directory
+├── main.py                  # Main entry point
+├── requirements.txt         # Python dependencies
+├── pytest.ini              # Test configuration
+└── README.md               # This file
+```
+
+## Contributing
+
+1. Fork the repository
+2. Create a feature branch (`git checkout -b feature/amazing-feature`)
+3. Commit your changes (`git commit -m 'Add amazing feature'`)
+4. Push to the branch (`git push origin feature/amazing-feature`)
+5. Open a Pull Request
+
+### Development Guidelines
+
+- Follow PEP 8 style guidelines
+- Write comprehensive tests for new features
+- Update documentation as needed
+- Ensure all tests pass before submitting
+
+## License
+
+This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
+
+## Disclaimer
+
+This tool is for educational and research purposes. Users are responsible for:
+- Complying with websites' terms of service
+- Respecting robots.txt files
+- Using the tool ethically and responsibly
+- Not overwhelming servers with too many requests
+
+The authors are not responsible for any misuse of this tool.
+
+## Support
+
+If you encounter any issues or have questions:
+
+1. Check the [Issues](https://github.com/iwasforcedtobehere/market-trends-scraper/issues) page
+2. Create a new issue with detailed information
+3. For general questions, use the [Discussions](https://github.com/iwasforcedtobehere/market-trends-scraper/discussions) tab
+
+## Acknowledgments
+
+- [Beautiful Soup](https://www.crummy.com/software/BeautifulSoup/) for HTML parsing
+- [Selenium](https://www.selenium.dev/) for browser automation
+- [Pandas](https://pandas.pydata.org/) for data analysis
+- [Loguru](https://github.com/Delgan/loguru) for logging
--- a/config/sample_config.yaml
+++ b/config/sample_config.yaml
@@ -0,0 +1,101 @@
+# Sample Configuration for Market Trends Scraper
+# Copy this file to config.yaml and customize for your needs
+
+scraper:
+  # Delay between requests in seconds (helps avoid being blocked)
+  delay_between_requests: 1.5
+  
+  # Request timeout in seconds
+  timeout: 30
+  
+  # Maximum number of retry attempts for failed requests
+  max_retries: 3
+  
+  # User agent string for HTTP requests
+  user_agent: "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36"
+  
+  # Run browser in headless mode (no visible UI)
+  headless: true
+  
+  # Browser window size [width, height]
+  window_size: [1920, 1080]
+
+# List of data sources to scrape
+sources:
+  # Example: Amazon (fictional selectors for demonstration)
+  - name: "amazon"
+    url: "https://www.amazon.com/s?k=laptop"
+    type: "ecommerce"
+    enabled: false  # Set to true to enable this source
+    use_selenium: true  # Amazon often requires JavaScript rendering
+    selectors:
+      product: "div[data-component-type='s-search-result']"
+      name: "h2 span.a-text-normal"
+      price: "span.a-price-whole"
+      rating: "span.a-icon-alt"
+      availability: "span.a-color-success"
+    pagination:
+      next_page: "a.s-pagination-next"
+      max_pages: 5
+
+  # Example: Generic e-commerce site
+  - name: "example_ecommerce"
+    url: "https://example-ecommerce.com/search?q=phone"
+    type: "ecommerce"
+    enabled: true
+    use_selenium: false
+    selectors:
+      product: "div.product-card"
+      name: "h3.product-title"
+      price: "span.price"
+      rating: "div.rating-stars"
+      availability: "div.stock-status"
+    pagination:
+      next_page: "a.pagination-next"
+      max_pages: 10
+
+  # Example: Electronics retailer
+  - name: "electronics_store"
+    url: "https://example-electronics.com/category/smartphones"
+    type: "ecommerce"
+    enabled: true
+    use_selenium: false
+    selectors:
+      product: "article.product-item"
+      name: "h1.product-name"
+      price: "div.current-price"
+      rating: "div.product-rating"
+      availability: "span.availability-label"
+    pagination:
+      next_page: "li.page-item.next a"
+      max_pages: 3
+
+# Output settings
+output:
+  # Output format: csv, json, or excel
+  format: "csv"
+  
+  # Include timestamp in output filename
+  include_timestamp: true
+  
+  # Base filename for output files
+  filename: "market_trends_data"
+
+# Database settings (for future enhancements)
+database:
+  # Database connection URL
+  url: "sqlite:///data/market_trends.db"
+  
+  # Enable SQL query logging
+  echo: false
+
+# Analysis settings
+analysis:
+  # Number of days to consider for price history analysis
+  price_history_days: 30
+  
+  # Minimum price change percentage to consider as a trend (0.05 = 5%)
+  trend_threshold: 0.05
+  
+  # Generate trend charts (requires matplotlib and seaborn)
+  generate_charts: true
--- a/examples/advanced_usage.py
+++ b/examples/advanced_usage.py
@@ -0,0 +1,327 @@
+
+#!/usr/bin/env python3
+"""
+Advanced Usage Example for Market Trends Scraper
+
+This script demonstrates advanced features of the Market Trends Scraper,
+including custom data processing, trend analysis, and visualization.
+"""
+
+import sys
+import json
+import pandas as pd
+import matplotlib.pyplot as plt
+import seaborn as sns
+from datetime import datetime, timedelta
+from pathlib import Path
+
+# Add src directory to Python path
+sys.path.insert(0, str(Path(__file__).resolve().parent.parent / "src"))
+
+from config_manager import ConfigManager
+from scraper import MarketTrendsScraper
+from logger import setup_logger
+
+
+def create_custom_config():
+    """Create a custom configuration for demonstration."""
+    return {
+        "scraper": {
+            "delay_between_requests": 2.0,
+            "timeout": 30,
+            "max_retries": 3,
+            "user_agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36",
+            "headless": True,
+            "window_size": [1920, 1080]
+        },
+        "sources": [
+            {
+                "name": "books_store",
+                "url": "https://books.toscrape.com/",
+                "type": "ecommerce",
+                "enabled": True,
+                "use_selenium": False,
+                "selectors": {
+                    "product": "article.product_pod",
+                    "name": "h3 a",
+                    "price": "p.price_color",
+                    "rating": "p.star-rating",
+                    "availability": "p.instock.availability"
+                },
+                "pagination": {
+                    "next_page": "li.next a",
+                    "max_pages": 3
+                }
+            }
+        ],
+        "output": {
+            "format": "csv",
+            "include_timestamp": True,
+            "filename": "books_analysis"
+        },
+        "database": {
+            "url": "sqlite:///../data/books.db",
+            "echo": False
+        },
+        "analysis": {
+            "price_history_days": 30,
+            "trend_threshold": 0.05,
+            "generate_charts": True
+        }
+    }
+
+
+def custom_price_processing(price_text):
+    """
+    Custom price processing function for specific formats.
+    
+    Args:
+        price_text: Raw price text from website
+        
+    Returns:
+        Parsed price as float or None if parsing fails
+    """
+    try:
+        # Remove currency symbol and whitespace
+        price_clean = price_text.replace('£', '').strip()
+        
+        # Convert to float
+        return float(price_clean)
+    except (ValueError, TypeError):
+        return None
+
+
+def custom_rating_processing(rating_element):
+    """
+    Custom rating processing for star ratings.
+    
+    Args:
+        rating_element: BeautifulSoup element containing rating
+        
+    Returns:
+        Parsed rating as float or None if parsing fails
+    """
+    try:
+        # Extract rating from class name (e.g., "star-rating Three" -> 3)
+        class_names = rating_element.get('class', [])
+        for class_name in class_names:
+            if class_name.lower() in ['one', 'two', 'three', 'four', 'five']:
+                rating_map = {
+                    'one': 1.0,
+                    'two': 2.0,
+                    'three': 3.0,
+                    'four': 4.0,
+                    'five': 5.0
+                }
+                return rating_map.get(class_name.lower())
+        return None
+    except Exception:
+        return None
+
+
+def analyze_price_trends(data):
+    """
+    Perform advanced price trend analysis.
+    
+    Args:
+        data: List of product data dictionaries
+        
+    Returns:
+        Dictionary containing trend analysis results
+    """
+    if not data:
+        return {"error": "No data available for analysis"}
+    
+    # Convert to DataFrame
+    df = pd.DataFrame(data)
+    
+    # Ensure price is numeric
+    df['price'] = pd.to_numeric(df['price'], errors='coerce')
+    
+    # Drop rows with missing prices
+    df = df.dropna(subset=['price'])
+    
+    # Basic statistics
+    analysis = {
+        "total_products": len(df),
+        "price_statistics": {
+            "mean": float(df['price'].mean()),
+            "median": float(df['price'].median()),
+            "std": float(df['price'].std()),
+            "min": float(df['price'].min()),
+            "max": float(df['price'].max()),
+            "quartiles": {
+                "25%": float(df['price'].quantile(0.25)),
+                "75%": float(df['price'].quantile(0.75))
+            }
+        },
+        "price_distribution": {
+            "under_10": int(len(df[df['price'] < 10])),
+            "10_to_20": int(len(df[(df['price'] >= 10) & (df['price'] < 20)])),
+            "20_to_30": int(len(df[(df['price'] >= 20) & (df['price'] < 30)])),
+            "30_to_40": int(len(df[(df['price'] >= 30) & (df['price'] < 40)])),
+            "over_40": int(len(df[df['price'] >= 40]))
+        }
+    }
+    
+    # Rating analysis if available
+    if 'rating' in df.columns:
+        df['rating'] = pd.to_numeric(df['rating'], errors='coerce')
+        rating_df = df.dropna(subset=['rating'])
+        
+        if not rating_df.empty:
+            analysis["rating_statistics"] = {
+                "mean": float(rating_df['rating'].mean()),
+                "distribution": rating_df['rating'].value_counts().to_dict()
+            }
+    
+    return analysis
+
+
+def generate_visualizations(data, analysis, output_dir):
+    """
+    Generate visualization charts for the analysis.
+    
+    Args:
+        data: List of product data dictionaries
+        analysis: Analysis results dictionary
+        output_dir: Directory to save charts
+    """
+    # Create output directory if it doesn't exist
+    Path(output_dir).mkdir(parents=True, exist_ok=True)
+    
+    # Convert to DataFrame
+    df = pd.DataFrame(data)
+    
+    # Ensure price is numeric
+    df['price'] = pd.to_numeric(df['price'], errors='coerce')
+    df = df.dropna(subset=['price'])
+    
+    # Set style
+    sns.set(style="whitegrid")
+    plt.figure(figsize=(12, 8))
+    
+    # Price distribution histogram
+    plt.subplot(2, 2, 1)
+    sns.histplot(df['price'], bins=20, kde=True)
+    plt.title('Price Distribution')
+    plt.xlabel('Price (£)')
+    plt.ylabel('Count')
+    
+    # Price distribution by category
+    plt.subplot(2, 2, 2)
+    price_dist = analysis['price_distribution']
+    categories = list(price_dist.keys())
+    values = list(price_dist.values())
+    plt.bar(categories, values)
+    plt.title('Price Distribution by Category')
+    plt.xlabel('Price Category')
+    plt.ylabel('Count')
+    plt.xticks(rotation=45)
+    
+    # Box plot for prices
+    plt.subplot(2, 2, 3)
+    sns.boxplot(y=df['price'])
+    plt.title('Price Box Plot')
+    plt.ylabel('Price (£)')
+    
+    # Rating vs Price scatter plot (if ratings available)
+    plt.subplot(2, 2, 4)
+    if 'rating' in df.columns:
+        df['rating'] = pd.to_numeric(df['rating'], errors='coerce')
+        rating_df = df.dropna(subset=['rating'])
+        if not rating_df.empty:
+            sns.scatterplot(x='rating', y='price', data=rating_df)
+            plt.title('Rating vs Price')
+            plt.xlabel('Rating')
+            plt.ylabel('Price (£)')
+        else:
+            plt.text(0.5, 0.5, 'No rating data available', 
+                    horizontalalignment='center', verticalalignment='center')
+    else:
+        plt.text(0.5, 0.5, 'No rating data available', 
+                horizontalalignment='center', verticalalignment='center')
+    
+    # Adjust layout and save
+    plt.tight_layout()
+    plt.savefig(f"{output_dir}/market_analysis_charts.png", dpi=300)
+    plt.close()
+    
+    print(f"✓ Visualization charts saved to {output_dir}/market_analysis_charts.png")
+
+
+def main():
+    """Main function demonstrating advanced scraper usage."""
+    
+    # Setup logging
+    setup_logger(verbose=True)
+    
+    # Create custom configuration
+    config = create_custom_config()
+    print("✓ Custom configuration created")
+    
+    # Initialize scraper
+    try:
+        scraper = MarketTrendsScraper(config, headless=True)
+        print("✓ Scraper initialized successfully")
+    except Exception as e:
+        print(f"✗ Failed to initialize scraper: {str(e)}")
+        return 1
+    
+    try:
+        # Scrape market trends data
+        print("\n🔍 Scraping market trends data...")
+        data = scraper.scrape_market_trends()
+        print(f"✓ Scraped {len(data)} product records")
+        
+        if not data:
+            print("⚠ No data was scraped. Check your configuration and selectors.")
+            return 0
+        
+        # Save raw data
+        output_file = "../data/advanced_example_output.csv"
+        scraper.save_data(data, output_file)
+        print(f"✓ Raw data saved to {output_file}")
+        
+        # Perform advanced analysis
+        print("\n📊 Performing advanced analysis...")
+        analysis = analyze_price_trends(data)
+        print("✓ Advanced analysis completed")
+        
+        # Save analysis results
+        analysis_file = "../data/advanced_example_analysis.json"
+        with open(analysis_file, 'w') as f:
+            json.dump(analysis, f, indent=2)
+        print(f"✓ Analysis saved to {analysis_file}")
+        
+        # Generate visualizations
+        print("\n📈 Generating visualization charts...")
+        charts_dir = "../data/charts"
+        generate_visualizations(data, analysis, charts_dir)
+        
+        # Print detailed summary
+        print("\n📋 Detailed Summary:")
+        print(f"  - Total products: {analysis.get('total_products', 0)}")
+        
+        if 'price_statistics' in analysis:
+            price_stats = analysis['price_statistics']
+            print(f"  - Average price: £{price_stats.get('mean', 0):.2f}")
+            print(f"  - Median price: £{price_stats.get('median', 0):.2f}")
+            print(f"  - Standard deviation: £{price_stats.get('std', 0):.2f}")
+            print(f"  - Price range: £{price_stats.get('min', 0):.2f} - £{price_stats.get('max', 0):.2f}")
+        
+        if 'price_distribution' in analysis:
+            print("  - Price distribution:")
+            for category, count in analysis['price_distribution'].items():
+                print(f"    * {category}: {count} products")
+        
+        if 'rating_statistics' in analysis:
+            rating_stats = analysis['rating_statistics']
+            print(f"  - Average rating: {rating_stats.get('mean', 0):.2f}")
+            print("  - Rating distribution:")
+            for rating, count in rating_stats['distribution'].items():
+                print(f"    * {rating} stars: {count} products")
+        
+        print("\n✅ Advanced market trends analysis completed successfully!")
+        return 0
+        
--- a/examples/basic_usage.py
+++ b/examples/basic_usage.py
@@ -0,0 +1,97 @@
+#!/usr/bin/env python3
+"""
+Basic Usage Example for Market Trends Scraper
+
+This script demonstrates how to use the Market Trends Scraper
+to collect and analyze pricing data from e-commerce websites.
+"""
+
+import sys
+from pathlib import Path
+
+# Add src directory to Python path
+sys.path.insert(0, str(Path(__file__).resolve().parent.parent / "src"))
+
+from config_manager import ConfigManager
+from scraper import MarketTrendsScraper
+from logger import setup_logger
+
+
+def main():
+    """Main function demonstrating basic scraper usage."""
+    
+    # Setup logging
+    setup_logger(verbose=True)
+    
+    # Initialize configuration manager
+    config_manager = ConfigManager("../config/sample_config.yaml")
+    
+    # Load configuration
+    try:
+        config = config_manager.load_config()
+        print("✓ Configuration loaded successfully")
+    except Exception as e:
+        print(f"✗ Failed to load configuration: {str(e)}")
+        return 1
+    
+    # Initialize scraper
+    try:
+        scraper = MarketTrendsScraper(config, headless=True)
+        print("✓ Scraper initialized successfully")
+    except Exception as e:
+        print(f"✗ Failed to initialize scraper: {str(e)}")
+        return 1
+    
+    try:
+        # Scrape market trends data
+        print("\n🔍 Scraping market trends data...")
+        data = scraper.scrape_market_trends()
+        print(f"✓ Scraped {len(data)} product records")
+        
+        if not data:
+            print("⚠ No data was scraped. Check your configuration and selectors.")
+            return 0
+        
+        # Save scraped data
+        output_file = "../data/example_output.csv"
+        scraper.save_data(data, output_file)
+        print(f"✓ Data saved to {output_file}")
+        
+        # Analyze trends
+        print("\n📊 Analyzing market trends...")
+        analysis = scraper.analyze_trends(data)
+        print("✓ Trend analysis completed")
+        
+        # Save analysis results
+        analysis_file = "../data/example_analysis.json"
+        scraper.save_analysis(analysis, analysis_file)
+        print(f"✓ Analysis saved to {analysis_file}")
+        
+        # Print summary
+        print("\n📋 Summary:")
+        print(f"  - Total products: {analysis.get('total_products', 0)}")
+        
+        if 'price_analysis' in analysis:
+            price_analysis = analysis['price_analysis']
+            print(f"  - Average price: ${price_analysis.get('average_price', 0):.2f}")
+            print(f"  - Price range: ${price_analysis.get('min_price', 0):.2f} - ${price_analysis.get('max_price', 0):.2f}")
+        
+        if 'sources' in analysis:
+            print("  - Products by source:")
+            for source, count in analysis['sources'].items():
+                print(f"    * {source}: {count} products")
+        
+        print("\n✅ Market trends analysis completed successfully!")
+        return 0
+        
+    except Exception as e:
+        print(f"✗ Error during scraping: {str(e)}")
+        return 1
+    
+    finally:
+        # Close scraper
+        scraper.close()
+
+
+if __name__ == "__main__":
+    sys.exit(main())
--- a/main.py
+++ b/main.py
@@ -0,0 +1,96 @@
+#!/usr/bin/env python3
+"""
+Market Trends Scraper - Main Entry Point
+
+This script serves as the main entry point for the Market Trends Scraper application.
+It initializes the scraper, processes configuration, and orchestrates the scraping
+and analysis workflow.
+"""
+
+import sys
+import argparse
+from pathlib import Path
+
+# Add src directory to Python path
+sys.path.insert(0, str(Path(__file__).resolve().parent / "src"))
+
+from scraper import MarketTrendsScraper
+from config_manager import ConfigManager
+from logger import setup_logger
+
+
+def parse_arguments():
+    """Parse command line arguments."""
+    parser = argparse.ArgumentParser(
+        description="Web Scraper for Market Trends - Collect and analyze pricing and product trends"
+    )
+    parser.add_argument(
+        "--config", "-c",
+        type=str,
+        default="config/config.yaml",
+        help="Path to configuration file"
+    )
+    parser.add_argument(
+        "--output", "-o",
+        type=str,
+        default="data/output.csv",
+        help="Path to output file"
+    )
+    parser.add_argument(
+        "--headless",
+        action="store_true",
+        help="Run browser in headless mode"
+    )
+    parser.add_argument(
+        "--verbose", "-v",
+        action="store_true",
+        help="Enable verbose logging"
+    )
+    return parser.parse_args()
+
+
+def main():
+    """Main application entry point."""
+    args = parse_arguments()
+    
+    # Setup logging
+    logger = setup_logger(verbose=args.verbose)
+    logger.info("Starting Market Trends Scraper")
+    
+    try:
+        # Load configuration
+        config_manager = ConfigManager(args.config)
+        config = config_manager.load_config()
+        logger.info("Configuration loaded successfully")
+        
+        # Initialize and run scraper
+        scraper = MarketTrendsScraper(config, headless=args.headless)
+        logger.info("Scraper initialized")
+        
+        # Run the scraping process
+        data = scraper.scrape_market_trends()
+        logger.info(f"Scraped {len(data)} product records")
+        
+        # Save results
+        scraper.save_data(data, args.output)
+        logger.info(f"Data saved to {args.output}")
+        
+        # Analyze trends
+        analysis = scraper.analyze_trends(data)
+        logger.info("Trend analysis completed")
+        
+        # Save analysis results
+        analysis_output = args.output.replace('.csv', '_analysis.json')
+        scraper.save_analysis(analysis, analysis_output)
+        logger.info(f"Analysis saved to {analysis_output}")
+        
+        logger.info("Market Trends Scraper completed successfully")
+        return 0
+        
+    except Exception as e:
+        logger.error(f"Error occurred: {str(e)}")
+        return 1
+
+
+if __name__ == "__main__":
+    sys.exit(main())
--- a/pytest.ini
+++ b/pytest.ini
@@ -0,0 +1,32 @@
+[tool:pytest]
+# Python test discovery settings
+testpaths = tests
+python_files = test_*.py
+python_classes = Test*
+python_functions = test_*
+
+# Output formatting
+addopts = 
+    --verbose
+    --tb=short
+    --strict-markers
+    --disable-warnings
+    --cov=src
+    --cov-report=term-missing
+    --cov-report=html:htmlcov
+    --cov-fail-under=80
+
+# Custom markers
+markers =
+    slow: marks tests as slow (deselect with '-m "not slow"')
+    integration: marks tests as integration tests
+    unit: marks tests as unit tests
+    web: marks tests that require web access
+
+# Minimum Python version
+minversion = 6.0
+
+# Filter warnings
+filterwarnings =
+    ignore::DeprecationWarning
+    ignore::PendingDeprecationWarning
--- a/requirements.txt
+++ b/requirements.txt
@@ -0,0 +1,31 @@
+# Web scraping
+requests>=2.28.0
+beautifulsoup4>=4.11.0
+selenium>=4.8.0
+lxml>=4.9.0
+
+# Data analysis and manipulation
+pandas>=1.5.0
+numpy>=1.24.0
+matplotlib>=3.6.0
+seaborn>=0.12.0
+
+# Data storage
+sqlalchemy>=1.4.0
+sqlite3
+
+# Configuration management
+python-dotenv>=0.21.0
+pyyaml>=6.0
+
+# Logging and monitoring
+loguru>=0.6.0
+
+# Testing
+pytest>=7.2.0
+pytest-cov>=4.0.0
+responses>=0.22.0
+
+# Utilities
+tqdm>=4.64.0
+schedule>=1.1.0
--- a/src/init.py
+++ b/src/init.py
--- a/src/config_manager.py
+++ b/src/config_manager.py
@@ -0,0 +1,211 @@
+"""
+Configuration Manager Module
+
+This module provides functionality to load, validate, and manage configuration
+settings for the Market Trends Scraper application.
+"""
+
+import os
+import yaml
+from pathlib import Path
+from typing import Dict, Any, Optional
+from loguru import logger
+
+
+class ConfigManager:
+    """Manages application configuration loading and validation."""
+    
+    def __init__(self, config_path: str = "config/config.yaml"):
+        """
+        Initialize the ConfigManager.
+        
+        Args:
+            config_path: Path to the configuration file
+        """
+        self.config_path = Path(config_path)
+        self.config = {}
+        self.default_config = self._get_default_config()
+    
+    def _get_default_config(self) -> Dict[str, Any]:
+        """
+        Get the default configuration settings.
+        
+        Returns:
+            Dictionary containing default configuration values
+        """
+        return {
+            "scraper": {
+                "delay_between_requests": 1.0,
+                "timeout": 30,
+                "max_retries": 3,
+                "user_agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36",
+                "headless": True,
+                "window_size": [1920, 1080]
+            },
+            "sources": [
+                {
+                    "name": "example_ecommerce",
+                    "url": "https://example-ecommerce.com/search",
+                    "type": "ecommerce",
+                    "enabled": True,
+                    "selectors": {
+                        "product": "div.product-item",
+                        "name": "h2.product-title",
+                        "price": "span.price",
+                        "rating": "div.rating",
+                        "availability": "div.stock-status"
+                    },
+                    "pagination": {
+                        "next_page": "a.next-page",
+                        "max_pages": 10
+                    }
+                }
+            ],
+            "output": {
+                "format": "csv",
+                "include_timestamp": True,
+                "filename": "market_trends_data"
+            },
+            "database": {
+                "url": "sqlite:///data/market_trends.db",
+                "echo": False
+            },
+            "analysis": {
+                "price_history_days": 30,
+                "trend_threshold": 0.05,  # 5% change considered significant
+                "generate_charts": True
+            }
+        }
+    
+    def load_config(self) -> Dict[str, Any]:
+        """
+        Load configuration from file or create default if not exists.
+        
+        Returns:
+            Dictionary containing configuration settings
+            
+        Raises:
+            FileNotFoundError: If config file doesn't exist and cannot be created
+            yaml.YAMLError: If config file contains invalid YAML
+        """
+        try:
+            # Create config directory if it doesn't exist
+            self.config_path.parent.mkdir(parents=True, exist_ok=True)
+            
+            # Load config if file exists
+            if self.config_path.exists():
+                with open(self.config_path, 'r', encoding='utf-8') as f:
+                    self.config = yaml.safe_load(f)
+                logger.info(f"Configuration loaded from {self.config_path}")
+            else:
+                # Create default config file
+                self.config = self.default_config
+                self.save_config()
+                logger.info(f"Default configuration created at {self.config_path}")
+            
+            # Validate and merge with defaults
+            self.config = self._validate_and_merge_config()
+            return self.config
+            
+        except Exception as e:
+            logger.error(f"Failed to load configuration: {str(e)}")
+            raise
+    
+    def save_config(self) -> None:
+        """
+        Save current configuration to file.
+        
+        Raises:
+            IOError: If unable to write to config file
+        """
+        try:
+            with open(self.config_path, 'w', encoding='utf-8') as f:
+                yaml.dump(self.config, f, default_flow_style=False, indent=2)
+            logger.info(f"Configuration saved to {self.config_path}")
+        except Exception as e:
+            logger.error(f"Failed to save configuration: {str(e)}")
+            raise
+    
+    def _validate_and_merge_config(self) -> Dict[str, Any]:
+        """
+        Validate loaded configuration and merge with defaults for missing values.
+        
+        Returns:
+            Validated and merged configuration dictionary
+        """
+        def deep_merge(source: Dict, destination: Dict) -> Dict:
+            """Recursively merge source dictionary into destination."""
+            for key, value in source.items():
+                if key in destination:
+                    if isinstance(value, dict) and isinstance(destination[key], dict):
+                        deep_merge(value, destination[key])
+                    else:
+                        destination[key] = value
+                else:
+                    destination[key] = value
+            return destination
+        
+        # Start with default config and merge with loaded config
+        merged_config = deep_merge(self.default_config, self.config.copy())
+        
+        # Validate required fields
+        required_sections = ["scraper", "sources", "output"]
+        for section in required_sections:
+            if section not in merged_config:
+                raise ValueError(f"Missing required configuration section: {section}")
+        
+        # Validate sources
+        if not merged_config["sources"]:
+            raise ValueError("At least one data source must be configured")
+        
+        return merged_config
+    
+    def get(self, key: str, default: Any = None) -> Any:
+        """
+        Get configuration value by key using dot notation.
+        
+        Args:
+            key: Configuration key (supports dot notation, e.g., "scraper.timeout")
+            default: Default value if key not found
+            
+        Returns:
+            Configuration value or default
+        """
+        keys = key.split('.')
+        value = self.config
+        
+        try:
+            for k in keys:
+                value = value[k]
+            return value
+        except (KeyError, TypeError):
+            return default
+    
+    def set(self, key: str, value: Any) -> None:
+        """
+        Set configuration value by key using dot notation.
+        
+        Args:
+            key: Configuration key (supports dot notation, e.g., "scraper.timeout")
+            value: Value to set
+        """
+        keys = key.split('.')
+        config_ref = self.config
+        
+        # Navigate to parent of target key
+        for k in keys[:-1]:
+            if k not in config_ref:
+                config_ref[k] = {}
+            config_ref = config_ref[k]
+        
+        # Set the value
+        config_ref[keys[-1]] = value
+    
+    def reload(self) -> Dict[str, Any]:
+        """
+        Reload configuration from file.
+        
+        Returns:
+            Updated configuration dictionary
+        """
+        return self.load_config()
--- a/src/logger.py
+++ b/src/logger.py
@@ -0,0 +1,119 @@
+"""
+Logger Module
+
+This module provides centralized logging configuration and utilities for the
+Market Trends Scraper application.
+"""
+
+import sys
+from pathlib import Path
+from loguru import logger
+from typing import Optional
+
+
+def setup_logger(
+    log_level: str = "INFO",
+    log_file: Optional[str] = None,
+    verbose: bool = False,
+    rotation: str = "10 MB",
+    retention: str = "7 days",
+    compression: str = "zip"
+) -> None:
+    """
+    Configure and initialize the application logger.
+    
+    Args:
+        log_level: Minimum logging level (DEBUG, INFO, WARNING, ERROR, CRITICAL)
+        log_file: Path to log file (if None, logs only to console)
+        verbose: Enable verbose logging (DEBUG level)
+        rotation: Log file rotation settings
+        retention: Log file retention settings
+        compression: Log file compression format
+    """
+    # Remove default logger
+    logger.remove()
+    
+    # Determine log level
+    if verbose:
+        log_level = "DEBUG"
+    
+    # Console log format
+    console_format = (
+        "<green>{time:YYYY-MM-DD HH:mm:ss}</green> | "
+        "<level>{level: <8}</level> | "
+        "<cyan>{name}</cyan>:<cyan>{function}</cyan>:<cyan>{line}</cyan> | "
+        "<level>{message}</level>"
+    )
+    
+    # File log format
+    file_format = (
+        "{time:YYYY-MM-DD HH:mm:ss} | "
+        "{level: <8} | "
+        "{name}:{function}:{line} | "
+        "{message}"
+    )
+    
+    # Add console logger
+    logger.add(
+        sys.stderr,
+        format=console_format,
+        level=log_level,
+        colorize=True
+    )
+    
+    # Add file logger if log_file is specified
+    if log_file:
+        # Create log directory if it doesn't exist
+        log_path = Path(log_file)
+        log_path.parent.mkdir(parents=True, exist_ok=True)
+        
+        logger.add(
+            log_file,
+            format=file_format,
+            level=log_level,
+            rotation=rotation,
+            retention=retention,
+            compression=compression,
+            encoding="utf-8"
+        )
+    
+    # Set up exception handler
+    def handle_exception(exc_type, exc_value, exc_traceback):
+        if issubclass(exc_type, KeyboardInterrupt):
+            sys.__excepthook__(exc_type, exc_value, exc_traceback)
+            return
+        
+        logger.opt(exception=(exc_type, exc_value, exc_traceback)).error(
+            "Uncaught exception occurred"
+        )
+    
+    sys.excepthook = handle_exception
+
+
+def get_logger(name: str = None):
+    """
+    Get a logger instance with the specified name.
+    
+    Args:
+        name: Logger name (typically __name__ of the calling module)
+        
+    Returns:
+        Logger instance
+    """
+    if name:
+        return logger.bind(name=name)
+    return logger
+
+
+class LoggerMixin:
+    """
+    Mixin class to add logging capabilities to other classes.
+    """
+    
+    @property
+    def logger(self):
+        """Get logger instance for this class."""
+        return logger.bind(
+            name=self.__class__.__name__,
+            id=id(self)
+        )
--- a/src/scraper.py
+++ b/src/scraper.py
@@ -0,0 +1,618 @@
+"""
+Web Scraper Module
+
+This module contains the core functionality for scraping e-commerce websites
+to collect product and pricing data for market trend analysis.
+"""
+
+import time
+import json
+import random
+from datetime import datetime
+from typing import Dict, List, Any, Optional, Union
+from pathlib import Path
+from urllib.parse import urljoin, urlparse
+
+import requests
+from bs4 import BeautifulSoup
+import pandas as pd
+from selenium import webdriver
+from selenium.webdriver.common.by import By
+from selenium.webdriver.support.ui import WebDriverWait
+from selenium.webdriver.support import expected_conditions as EC
+from selenium.webdriver.chrome.options import Options
+from selenium.common.exceptions import TimeoutException, NoSuchElementException
+
+from logger import LoggerMixin
+from config_manager import ConfigManager
+
+
+class MarketTrendsScraper(LoggerMixin):
+    """
+    Main scraper class for collecting market trends data from e-commerce websites.
+    """
+    
+    def __init__(self, config: Dict[str, Any], headless: bool = True):
+        """
+        Initialize the scraper with configuration.
+        
+        Args:
+            config: Configuration dictionary
+            headless: Whether to run browser in headless mode
+        """
+        self.config = config
+        self.driver = None
+        self.session = requests.Session()
+        self.data = []
+        self._setup_browser(headless)
+        self._setup_session()
+    
+    def _setup_browser(self, headless: bool = True) -> None:
+        """
+        Set up the Selenium WebDriver with appropriate options.
+        
+        Args:
+            headless: Whether to run browser in headless mode
+        """
+        try:
+            chrome_options = Options()
+            
+            # Set headless mode
+            if headless:
+                chrome_options.add_argument("--headless")
+            
+            # Set window size
+            window_size = self.config.get("scraper.window_size", [1920, 1080])
+            chrome_options.add_argument(f"--window-size={window_size[0]},{window_size[1]}")
+            
+            # Add other options for stability
+            chrome_options.add_argument("--no-sandbox")
+            chrome_options.add_argument("--disable-dev-shm-usage")
+            chrome_options.add_argument("--disable-gpu")
+            chrome_options.add_argument("--disable-web-security")
+            chrome_options.add_argument("--disable-features=VizDisplayCompositor")
+            
+            # Set user agent
+            user_agent = self.config.get("scraper.user_agent", "")
+            if user_agent:
+                chrome_options.add_argument(f"--user-agent={user_agent}")
+            
+            # Initialize driver
+            self.driver = webdriver.Chrome(options=chrome_options)
+            self.driver.set_page_load_timeout(self.config.get("scraper.timeout", 30))
+            
+            self.logger.info("Browser setup completed")
+            
+        except Exception as e:
+            self.logger.error(f"Failed to setup browser: {str(e)}")
+            raise
+    
+    def _setup_session(self) -> None:
+        """
+        Set up the requests session with appropriate headers.
+        """
+        user_agent = self.config.get("scraper.user_agent", "")
+        if user_agent:
+            self.session.headers.update({"User-Agent": user_agent})
+        
+        # Add other headers
+        self.session.headers.update({
+            "Accept": "text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,*/*;q=0.8",
+            "Accept-Language": "en-US,en;q=0.5",
+            "Accept-Encoding": "gzip, deflate",
+            "Connection": "keep-alive",
+            "Upgrade-Insecure-Requests": "1"
+        })
+        
+        self.logger.info("Session setup completed")
+    
+    def scrape_market_trends(self) -> List[Dict[str, Any]]:
+        """
+        Scrape market trends data from all configured sources.
+        
+        Returns:
+            List of dictionaries containing scraped data
+        """
+        all_data = []
+        sources = self.config.get("sources", [])
+        
+        for source in sources:
+            if not source.get("enabled", True):
+                self.logger.info(f"Skipping disabled source: {source.get('name', 'Unknown')}")
+                continue
+            
+            self.logger.info(f"Scraping source: {source.get('name', 'Unknown')}")
+            
+            try:
+                source_data = self._scrape_source(source)
+                all_data.extend(source_data)
+                self.logger.info(f"Scraped {len(source_data)} records from {source.get('name', 'Unknown')}")
+            except Exception as e:
+                self.logger.error(f"Failed to scrape source {source.get('name', 'Unknown')}: {str(e)}")
+                continue
+        
+        return all_data
+    
+    def _scrape_source(self, source: Dict[str, Any]) -> List[Dict[str, Any]]:
+        """
+        Scrape data from a specific source.
+        
+        Args:
+            source: Source configuration dictionary
+            
+        Returns:
+            List of dictionaries containing scraped data
+        """
+        source_data = []
+        url = source.get("url", "")
+        selectors = source.get("selectors", {})
+        pagination = source.get("pagination", {})
+        
+        if not url:
+            self.logger.warning(f"No URL configured for source: {source.get('name', 'Unknown')}")
+            return source_data
+        
+        # Determine scraping method
+        use_selenium = source.get("use_selenium", False)
+        
+        if use_selenium:
+            return self._scrape_with_selenium(source)
+        else:
+            return self._scrape_with_requests(source)
+    
+    def _scrape_with_requests(self, source: Dict[str, Any]) -> List[Dict[str, Any]]:
+        """
+        Scrape data using requests and BeautifulSoup.
+        
+        Args:
+            source: Source configuration dictionary
+            
+        Returns:
+            List of dictionaries containing scraped data
+        """
+        source_data = []
+        url = source.get("url", "")
+        selectors = source.get("selectors", {})
+        pagination = source.get("pagination", {})
+        max_pages = pagination.get("max_pages", 1)
+        
+        for page in range(1, max_pages + 1):
+            try:
+                # Add page parameter if needed
+                page_url = url
+                if page > 1:
+                    page_url = f"{url}?page={page}"
+                
+                self.logger.debug(f"Scraping page {page}: {page_url}")
+                
+                # Make request with retry logic
+                response = self._make_request_with_retry(page_url)
+                
+                if not response:
+                    continue
+                
+                # Parse HTML
+                soup = BeautifulSoup(response.text, 'html.parser')
+                
+                # Extract product data
+                products = soup.select(selectors.get("product", ""))
+                
+                for product in products:
+                    product_data = self._extract_product_data(product, selectors)
+                    if product_data:
+                        product_data["source"] = source.get("name", "Unknown")
+                        product_data["scraped_at"] = datetime.now().isoformat()
+                        source_data.append(product_data)
+                
+                # Check if there's a next page
+                if page < max_pages:
+                    next_page = soup.select_one(pagination.get("next_page", ""))
+                    if not next_page:
+                        self.logger.debug(f"No more pages found after page {page}")
+                        break
+                
+                # Delay between requests
+                delay = self.config.get("scraper.delay_between_requests", 1.0)
+                time.sleep(delay + random.uniform(0, 1))
+                
+            except Exception as e:
+                self.logger.error(f"Error scraping page {page} from {source.get('name', 'Unknown')}: {str(e)}")
+                continue
+        
+        return source_data
+    
+    def _scrape_with_selenium(self, source: Dict[str, Any]) -> List[Dict[str, Any]]:
+        """
+        Scrape data using Selenium WebDriver.
+        
+        Args:
+            source: Source configuration dictionary
+            
+        Returns:
+            List of dictionaries containing scraped data
+        """
+        source_data = []
+        url = source.get("url", "")
+        selectors = source.get("selectors", {})
+        pagination = source.get("pagination", {})
+        max_pages = pagination.get("max_pages", 1)
+        
+        try:
+            self.driver.get(url)
+            
+            for page in range(1, max_pages + 1):
+                self.logger.debug(f"Scraping page {page} with Selenium")
+                
+                # Wait for products to load
+                try:
+                    WebDriverWait(self.driver, 10).until(
+                        EC.presence_of_element_located((By.CSS_SELECTOR, selectors.get("product", "")))
+                    )
+                except TimeoutException:
+                    self.logger.warning(f"Timeout waiting for products to load on page {page}")
+                    continue
+                
+                # Extract product data
+                products = self.driver.find_elements(By.CSS_SELECTOR, selectors.get("product", ""))
+                
+                for product in products:
+                    product_data = self._extract_product_data_selenium(product, selectors)
+                    if product_data:
+                        product_data["source"] = source.get("name", "Unknown")
+                        product_data["scraped_at"] = datetime.now().isoformat()
+                        source_data.append(product_data)
+                
+                # Navigate to next page if available
+                if page < max_pages:
+                    try:
+                        next_button = self.driver.find_element(By.CSS_SELECTOR, pagination.get("next_page", ""))
+                        next_button.click()
+                        
+                        # Wait for page to load
+                        time.sleep(2)
+                    except NoSuchElementException:
+                        self.logger.debug(f"No next page button found after page {page}")
+                        break
+                
+                # Delay between requests
+                delay = self.config.get("scraper.delay_between_requests", 1.0)
+                time.sleep(delay + random.uniform(0, 1))
+                
+        except Exception as e:
+            self.logger.error(f"Error scraping with Selenium from {source.get('name', 'Unknown')}: {str(e)}")
+        
+        return source_data
+    
+    def _make_request_with_retry(self, url: str) -> Optional[requests.Response]:
+        """
+        Make HTTP request with retry logic.
+        
+        Args:
+            url: URL to request
+            
+        Returns:
+            Response object or None if failed
+        """
+        max_retries = self.config.get("scraper.max_retries", 3)
+        timeout = self.config.get("scraper.timeout", 30)
+        
+        for attempt in range(max_retries):
+            try:
+                response = self.session.get(url, timeout=timeout)
+                response.raise_for_status()
+                return response
+            except requests.RequestException as e:
+                self.logger.warning(f"Request attempt {attempt + 1} failed for {url}: {str(e)}")
+                if attempt < max_retries - 1:
+                    # Exponential backoff
+                    time.sleep((2 ** attempt) + random.uniform(0, 1))
+                else:
+                    self.logger.error(f"Max retries exceeded for {url}")
+                    return None
+        
+        return None
+    
+    def _extract_product_data(self, product: BeautifulSoup, selectors: Dict[str, str]) -> Optional[Dict[str, Any]]:
+        """
+        Extract product data from HTML element using BeautifulSoup.
+        
+        Args:
+            product: BeautifulSoup element containing product data
+            selectors: Dictionary of CSS selectors
+            
+        Returns:
+            Dictionary containing product data or None if extraction failed
+        """
+        try:
+            data = {}
+            
+            # Extract name
+            name_element = product.select_one(selectors.get("name", ""))
+            data["name"] = name_element.get_text(strip=True) if name_element else None
+            
+            # Extract price
+            price_element = product.select_one(selectors.get("price", ""))
+            if price_element:
+                price_text = price_element.get_text(strip=True)
+                data["price"] = self._parse_price(price_text)
+            else:
+                data["price"] = None
+            
+            # Extract rating
+            rating_element = product.select_one(selectors.get("rating", ""))
+            if rating_element:
+                rating_text = rating_element.get_text(strip=True)
+                data["rating"] = self._parse_rating(rating_text)
+            else:
+                data["rating"] = None
+            
+            # Extract availability
+            availability_element = product.select_one(selectors.get("availability", ""))
+            data["availability"] = availability_element.get_text(strip=True) if availability_element else None
+            
+            # Extract URL if available
+            link_element = product.select_one("a")
+            if link_element and link_element.get("href"):
+                data["url"] = link_element.get("href")
+            
+            return data if data.get("name") else None
+            
+        except Exception as e:
+            self.logger.error(f"Error extracting product data: {str(e)}")
+            return None
+    
+    def _extract_product_data_selenium(self, product, selectors: Dict[str, str]) -> Optional[Dict[str, Any]]:
+        """
+        Extract product data from Selenium WebElement.
+        
+        Args:
+            product: Selenium WebElement containing product data
+            selectors: Dictionary of CSS selectors
+            
+        Returns:
+            Dictionary containing product data or None if extraction failed
+        """
+        try:
+            data = {}
+            
+            # Extract name
+            try:
+                name_element = product.find_element(By.CSS_SELECTOR, selectors.get("name", ""))
+                data["name"] = name_element.text.strip()
+            except NoSuchElementException:
+                data["name"] = None
+            
+            # Extract price
+            try:
+                price_element = product.find_element(By.CSS_SELECTOR, selectors.get("price", ""))
+                price_text = price_element.text.strip()
+                data["price"] = self._parse_price(price_text)
+            except NoSuchElementException:
+                data["price"] = None
+            
+            # Extract rating
+            try:
+                rating_element = product.find_element(By.CSS_SELECTOR, selectors.get("rating", ""))
+                rating_text = rating_element.text.strip()
+                data["rating"] = self._parse_rating(rating_text)
+            except NoSuchElementException:
+                data["rating"] = None
+            
+            # Extract availability
+            try:
+                availability_element = product.find_element(By.CSS_SELECTOR, selectors.get("availability", ""))
+                data["availability"] = availability_element.text.strip()
+            except NoSuchElementException:
+                data["availability"] = None
+            
+            # Extract URL if available
+            try:
+                link_element = product.find_element(By.CSS_SELECTOR, "a")
+                if link_element.get_attribute("href"):
+                    data["url"] = link_element.get_attribute("href")
+            except NoSuchElementException:
+                pass
+            
+            return data if data.get("name") else None
+            
+        except Exception as e:
+            self.logger.error(f"Error extracting product data with Selenium: {str(e)}")
+            return None
+    
+    def _parse_price(self, price_text: str) -> Optional[float]:
+        """
+        Parse price text to extract numeric value.
+        
+        Args:
+            price_text: Raw price text
+            
+        Returns:
+            Parsed price as float or None if parsing failed
+        """
+        try:
+            # Remove currency symbols and whitespace
+            price_clean = price_text.replace('$', '').replace('€', '').replace('£', '').strip()
+            
+            # Handle comma as decimal separator
+            price_clean = price_clean.replace(',', '.')
+            
+            # Extract numeric part
+            import re
+            price_match = re.search(r'[\d.]+', price_clean)
+            if price_match:
+                return float(price_match.group())
+            
+            return None
+            
+        except Exception as e:
+            self.logger.error(f"Error parsing price '{price_text}': {str(e)}")
+            return None
+    
+    def _parse_rating(self, rating_text: str) -> Optional[float]:
+        """
+        Parse rating text to extract numeric value.
+        
+        Args:
+            rating_text: Raw rating text
+            
+        Returns:
+            Parsed rating as float or None if parsing failed
+        """
+        try:
+            # Extract numeric part
+            import re
+            rating_match = re.search(r'[\d.]+', rating_text)
+            if rating_match:
+                return float(rating_match.group())
+            
+            return None
+            
+        except Exception as e:
+            self.logger.error(f"Error parsing rating '{rating_text}': {str(e)}")
+            return None
+    
+    def save_data(self, data: List[Dict[str, Any]], output_path: str) -> None:
+        """
+        Save scraped data to file.
+        
+        Args:
+            data: List of dictionaries containing scraped data
+            output_path: Path to output file
+        """
+        try:
+            output_file = Path(output_path)
+            output_file.parent.mkdir(parents=True, exist_ok=True)
+            
+            # Convert to DataFrame
+            df = pd.DataFrame(data)
+            
+            # Save based on file extension
+            if output_path.endswith('.csv'):
+                df.to_csv(output_path, index=False)
+            elif output_path.endswith('.json'):
+                df.to_json(output_path, orient='records', indent=2)
+            elif output_path.endswith('.xlsx'):
+                df.to_excel(output_path, index=False)
+            else:
+                # Default to CSV
+                output_path = output_path + '.csv'
+                df.to_csv(output_path, index=False)
+            
+            self.logger.info(f"Data saved to {output_path}")
+            
+        except Exception as e:
+            self.logger.error(f"Error saving data to {output_path}: {str(e)}")
+            raise
+    
+    def analyze_trends(self, data: List[Dict[str, Any]]) -> Dict[str, Any]:
+        """
+        Analyze market trends from scraped data.
+        
+        Args:
+            data: List of dictionaries containing scraped data
+            
+        Returns:
+            Dictionary containing trend analysis results
+        """
+        try:
+            if not data:
+                return {"error": "No data available for analysis"}
+            
+            # Convert to DataFrame
+            df = pd.DataFrame(data)
+            
+            # Basic statistics
+            analysis = {
+                "total_products": len(df),
+                "sources": df["source"].value_counts().to_dict(),
+                "price_analysis": {},
+                "rating_analysis": {},
+                "availability_analysis": {}
+            }
+            
+            # Price analysis
+            if "price" in df.columns:
+                price_data = df["price"].dropna()
+                if not price_data.empty:
+                    analysis["price_analysis"] = {
+                        "average_price": float(price_data.mean()),
+                        "min_price": float(price_data.min()),
+                        "max_price": float(price_data.max()),
+                        "median_price": float(price_data.median()),
+                        "price_distribution": price_data.describe().to_dict()
+                    }
+            
+            # Rating analysis
+            if "rating" in df.columns:
+                rating_data = df["rating"].dropna()
+                if not rating_data.empty:
+                    analysis["rating_analysis"] = {
+                        "average_rating": float(rating_data.mean()),
+                        "min_rating": float(rating_data.min()),
+                        "max_rating": float(rating_data.max()),
+                        "rating_distribution": rating_data.value_counts().to_dict()
+                    }
+            
+            # Availability analysis
+            if "availability" in df.columns:
+                availability_data = df["availability"].dropna()
+                if not availability_data.empty:
+                    analysis["availability_analysis"] = availability_data.value_counts().to_dict()
+            
+            # Price trends by source
+            if "price" in df.columns and "source" in df.columns:
+                price_by_source = df.groupby("source")["price"].agg(["mean", "min", "max"]).to_dict()
+                analysis["price_by_source"] = price_by_source
+            
+            self.logger.info("Trend analysis completed")
+            return analysis
+            
+        except Exception as e:
+            self.logger.error(f"Error analyzing trends: {str(e)}")
+            return {"error": str(e)}
+    
+    def save_analysis(self, analysis: Dict[str, Any], output_path: str) -> None:
+        """
+        Save trend analysis results to file.
+        
+        Args:
+            analysis: Dictionary containing analysis results
+            output_path: Path to output file
+        """
+        try:
+            output_file = Path(output_path)
+            output_file.parent.mkdir(parents=True, exist_ok=True)
+            
+            with open(output_file, 'w', encoding='utf-8') as f:
+                json.dump(analysis, f, indent=2, ensure_ascii=False)
+            
+            self.logger.info(f"Analysis saved to {output_path}")
+            
+        except Exception as e:
+            self.logger.error(f"Error saving analysis to {output_path}: {str(e)}")
+            raise
+    
+    def close(self) -> None:
+        """
+        Close browser and session.
+        """
+        try:
+            if self.driver:
+                self.driver.quit()
+                self.driver = None
+            
+            if self.session:
+                self.session.close()
+            
+            self.logger.info("Browser and session closed")
+            
+        except Exception as e:
+            self.logger.error(f"Error closing browser/session: {str(e)}")
+    
+    def __enter__(self):
+        """Context manager entry."""
+        return self
+    
+    def __exit__(self, exc_type, exc_val, exc_tb):
+        """Context manager exit."""
+        self.close()
--- a/tests/init.py
+++ b/tests/init.py
--- a/tests/test_config_manager.py
+++ b/tests/test_config_manager.py
@@ -0,0 +1,165 @@
+"""
+Unit tests for the ConfigManager module.
+"""
+
+import pytest
+import tempfile
+import os
+import yaml
+from pathlib import Path
+from unittest.mock import patch, mock_open
+
+from src.config_manager import ConfigManager
+
+
+class TestConfigManager:
+    """Test cases for ConfigManager class."""
+    
+    def test_init_with_default_path(self):
+        """Test ConfigManager initialization with default path."""
+        config_manager = ConfigManager()
+        assert config_manager.config_path == Path("config/config.yaml")
+        assert isinstance(config_manager.config, dict)
+        assert isinstance(config_manager.default_config, dict)
+    
+    def test_init_with_custom_path(self):
+        """Test ConfigManager initialization with custom path."""
+        custom_path = "custom/config.yaml"
+        config_manager = ConfigManager(custom_path)
+        assert config_manager.config_path == Path(custom_path)
+    
+    def test_get_default_config(self):
+        """Test default configuration structure."""
+        config_manager = ConfigManager()
+        default_config = config_manager._get_default_config()
+        
+        # Check required sections
+        assert "scraper" in default_config
+        assert "sources" in default_config
+        assert "output" in default_config
+        assert "database" in default_config
+        assert "analysis" in default_config
+        
+        # Check some default values
+        assert default_config["scraper"]["delay_between_requests"] == 1.0
+        assert default_config["scraper"]["timeout"] == 30
+        assert default_config["scraper"]["headless"] is True
+        assert isinstance(default_config["sources"], list)
+        assert len(default_config["sources"]) > 0
+    
+    @patch('builtins.open', new_callable=mock_open, read_data="scraper:\n  timeout: 60")
+    @patch('pathlib.Path.exists')
+    def test_load_config_existing_file(self, mock_exists, mock_file):
+        """Test loading configuration from existing file."""
+        mock_exists.return_value = True
+        
+        config_manager = ConfigManager()
+        config = config_manager.load_config()
+        
+        mock_file.assert_called_once()
+        assert config["scraper"]["timeout"] == 60
+    
+    @patch('builtins.open', new_callable=mock_open)
+    @patch('pathlib.Path.exists')
+    def test_load_config_create_default(self, mock_exists, mock_file):
+        """Test creating default configuration when file doesn't exist."""
+        mock_exists.return_value = False
+        
+        config_manager = ConfigManager()
+        config = config_manager.load_config()
+        
+        # Verify file was created
+        mock_file.assert_called_once()
+        # Verify config is default
+        assert config == config_manager.default_config
+    
+    @patch('builtins.open', new_callable=mock_open)
+    def test_save_config(self, mock_file):
+        """Test saving configuration to file."""
+        config_manager = ConfigManager()
+        config_manager.config = {"test": "value"}
+        
+        config_manager.save_config()
+        
+        mock_file.assert_called_once()
+        # Verify yaml.dump was called with correct arguments
+        with patch('yaml.dump') as mock_dump:
+            config_manager.save_config()
+            mock_dump.assert_called_once()
+    
+    def test_validate_and_merge_config(self):
+        """Test configuration validation and merging."""
+        config_manager = ConfigManager()
+        
+        # Test with partial config
+        partial_config = {
+            "scraper": {
+                "timeout": 60
+            }
+        }
+        config_manager.config = partial_config
+        
+        merged = config_manager._validate_and_merge_config()
+        
+        # Should have all sections
+        assert "sources" in merged
+        assert "output" in merged
+        # Should have updated value
+        assert merged["scraper"]["timeout"] == 60
+        # Should have default values for missing keys
+        assert merged["scraper"]["delay_between_requests"] == 1.0
+    
+    def test_validate_and_merge_config_missing_required(self):
+        """Test validation fails when required sections are missing."""
+        config_manager = ConfigManager()
+        config_manager.config = {"invalid": "config"}
+        
+        with pytest.raises(ValueError, match="Missing required configuration section"):
+            config_manager._validate_and_merge_config()
+    
+    def test_validate_and_merge_config_no_sources(self):
+        """Test validation fails when no sources are configured."""
+        config_manager = ConfigManager()
+        config_manager.config = {
+            "scraper": {},
+            "sources": [],
+            "output": {}
+        }
+        
+        with pytest.raises(ValueError, match="At least one data source must be configured"):
+            config_manager._validate_and_merge_config()
+    
+    def test_get_with_dot_notation(self):
+        """Test getting configuration values with dot notation."""
+        config_manager = ConfigManager()
+        config_manager.config = {
+            "scraper": {
+                "timeout": 60,
+                "nested": {
+                    "value": "test"
+                }
+            }
+        }
+        
+        assert config_manager.get("scraper.timeout") == 60
+        assert config_manager.get("scraper.nested.value") == "test"
+        assert config_manager.get("nonexistent", "default") == "default"
+    
+    def test_set_with_dot_notation(self):
+        """Test setting configuration values with dot notation."""
+        config_manager = ConfigManager()
+        config_manager.config = {"scraper": {}}
+        
+        config_manager.set("scraper.timeout", 60)
+        config_manager.set("new.nested.value", "test")
+        
+        assert config_manager.config["scraper"]["timeout"] == 60
+        assert config_manager.config["new"]["nested"]["value"] == "test"
+    
+    @patch.object(ConfigManager, 'load_config')
+    def test_reload(self, mock_load):
+        """Test reloading configuration."""
+        config_manager = ConfigManager()
+        config_manager.reload()
+        
+        mock_load.assert_called_once()
--- a/tests/test_integration.py
+++ b/tests/test_integration.py
@@ -0,0 +1,355 @@
+"""
+Integration tests for the Market Trends Scraper application.
+
+These tests verify that all components work together correctly.
+"""
+
+import pytest
+import tempfile
+import os
+import json
+from pathlib import Path
+from unittest.mock import patch, Mock
+
+from src.config_manager import ConfigManager
+from src.scraper import MarketTrendsScraper
+from src.logger import setup_logger
+import main
+
+
+class TestIntegration:
+    """Integration test cases for the entire application."""
+    
+    @pytest.fixture
+    def temp_dir(self):
+        """Create a temporary directory for test files."""
+        with tempfile.TemporaryDirectory() as temp_dir:
+            yield temp_dir
+    
+    @pytest.fixture
+    def sample_config_file(self, temp_dir):
+        """Create a sample configuration file for testing."""
+        config_path = Path(temp_dir) / "config.yaml"
+        config_content = {
+            "scraper": {
+                "delay_between_requests": 0.1,  # Faster for testing
+                "timeout": 10,
+                "max_retries": 2,
+                "user_agent": "Mozilla/5.0 (Test)",
+                "headless": True,
+                "window_size": [1024, 768]
+            },
+            "sources": [
+                {
+                    "name": "test_source",
+                    "url": "https://httpbin.org/html",
+                    "type": "ecommerce",
+                    "enabled": True,
+                    "selectors": {
+                        "product": "p",
+                        "name": "p",
+                        "price": "p",
+                        "rating": "p",
+                        "availability": "p"
+                    },
+                    "pagination": {
+                        "next_page": "a",
+                        "max_pages": 1
+                    }
+                }
+            ],
+            "output": {
+                "format": "csv",
+                "include_timestamp": True,
+                "filename": "test_output"
+            },
+            "database": {
+                "url": f"sqlite:///{temp_dir}/test.db",
+                "echo": False
+            },
+            "analysis": {
+                "price_history_days": 30,
+                "trend_threshold": 0.05,
+                "generate_charts": True
+            }
+        }
+        
+        import yaml
+        with open(config_path, 'w') as f:
+            yaml.dump(config_content, f)
+        
+        return str(config_path)
+    
+    @patch('src.scraper.webdriver')
+    def test_full_workflow(self, mock_webdriver, sample_config_file, temp_dir):
+        """Test the complete workflow from config loading to analysis."""
+        # Setup mock driver
+        mock_driver = Mock()
+        mock_webdriver.Chrome.return_value = mock_driver
+        
+        # Setup logger
+        setup_logger()
+        
+        # Load configuration
+        config_manager = ConfigManager(sample_config_file)
+        config = config_manager.load_config()
+        
+        # Verify config was loaded
+        assert config["scraper"]["delay_between_requests"] == 0.1
+        assert len(config["sources"]) == 1
+        assert config["sources"][0]["name"] == "test_source"
+        
+        # Initialize scraper
+        scraper = MarketTrendsScraper(config, headless=True)
+        
+        # Mock the scraping process to return sample data
+        sample_data = [
+            {
+                "name": "Test Product 1",
+                "price": 19.99,
+                "rating": 4.5,
+                "availability": "In Stock",
+                "source": "test_source",
+                "scraped_at": "2023-01-01T00:00:00"
+            },
+            {
+                "name": "Test Product 2",
+                "price": 29.99,
+                "rating": 3.8,
+                "availability": "Out of Stock",
+                "source": "test_source",
+                "scraped_at": "2023-01-01T00:00:00"
+            }
+        ]
+        
+        with patch.object(scraper, '_scrape_source', return_value=sample_data):
+            # Scrape data
+            data = scraper.scrape_market_trends()
+            
+            # Verify data was scraped
+            assert len(data) == 2
+            assert data[0]["name"] == "Test Product 1"
+            assert data[1]["price"] == 29.99
+            
+            # Save data
+            output_path = Path(temp_dir) / "test_output.csv"
+            scraper.save_data(data, str(output_path))
+            
+            # Verify file was created
+            assert output_path.exists()
+            
+            # Analyze trends
+            analysis = scraper.analyze_trends(data)
+            
+            # Verify analysis
+            assert analysis["total_products"] == 2
+            assert "price_analysis" in analysis
+            assert analysis["price_analysis"]["average_price"] == 24.99
+            assert analysis["price_analysis"]["min_price"] == 19.99
+            assert analysis["price_analysis"]["max_price"] == 29.99
+            
+            # Save analysis
+            analysis_path = Path(temp_dir) / "test_analysis.json"
+            scraper.save_analysis(analysis, str(analysis_path))
+            
+            # Verify analysis file was created
+            assert analysis_path.exists()
+            
+            # Verify analysis content
+            with open(analysis_path, 'r') as f:
+                saved_analysis = json.load(f)
+            
+            assert saved_analysis["total_products"] == 2
+            assert saved_analysis["price_analysis"]["average_price"] == 24.99
+    
+    @patch('src.scraper.webdriver')
+    def test_multiple_sources(self, mock_webdriver, temp_dir):
+        """Test scraping from multiple sources."""
+        # Setup mock driver
+        mock_driver = Mock()
+        mock_webdriver.Chrome.return_value = mock_driver
+        
+        # Create config with multiple sources
+        config_content = {
+            "scraper": {
+                "delay_between_requests": 0.1,
+                "timeout": 10,
+                "headless": True
+            },
+            "sources": [
+                {
+                    "name": "source_1",
+                    "url": "https://example1.com",
+                    "enabled": True,
+                    "selectors": {
+                        "product": "div.product",
+                        "name": "h2",
+                        "price": "span.price"
+                    }
+                },
+                {
+                    "name": "source_2",
+                    "url": "https://example2.com",
+                    "enabled": True,
+                    "selectors": {
+                        "product": "div.item",
+                        "name": "h3",
+                        "price": "div.cost"
+                    }
+                },
+                {
+                    "name": "source_3",
+                    "url": "https://example3.com",
+                    "enabled": False,  # Disabled source
+                    "selectors": {
+                        "product": "div.product",
+                        "name": "h2",
+                        "price": "span.price"
+                    }
+                }
+            ]
+        }
+        
+        import yaml
+        config_path = Path(temp_dir) / "multi_source_config.yaml"
+        with open(config_path, 'w') as f:
+            yaml.dump(config_content, f)
+        
+        # Initialize scraper
+        scraper = MarketTrendsScraper(config_content, headless=True)
+        
+        # Mock different data for each source
+        def mock_scrape_source(source):
+            if source["name"] == "source_1":
+                return [{"name": "Product 1", "price": 10.00, "source": "source_1"}]
+            elif source["name"] == "source_2":
+                return [{"name": "Product 2", "price": 20.00, "source": "source_2"}]
+            else:
+                return []
+        
+        with patch.object(scraper, '_scrape_source', side_effect=mock_scrape_source):
+            data = scraper.scrape_market_trends()
+            
+            # Verify data from both enabled sources
+            assert len(data) == 2
+            sources = {item["source"] for item in data}
+            assert "source_1" in sources
+            assert "source_2" in sources
+            assert "source_3" not in sources  # Disabled source should not appear
+    
+    @patch('src.scraper.webdriver')
+    def test_error_handling(self, mock_webdriver, temp_dir):
+        """Test error handling when scraping fails."""
+        # Setup mock driver
+        mock_driver = Mock()
+        mock_webdriver.Chrome.return_value = mock_driver
+        
+        config = {
+            "scraper": {
+                "delay_between_requests": 0.1,
+                "timeout": 10,
+                "headless": True
+            },
+            "sources": [
+                {
+                    "name": "working_source",
+                    "url": "https://example.com",
+                    "enabled": True,
+                    "selectors": {
+                        "product": "div.product",
+                        "name": "h2",
+                        "price": "span.price"
+                    }
+                },
+                {
+                    "name": "failing_source",
+                    "url": "https://example.com",
+                    "enabled": True,
+                    "selectors": {
+                        "product": "div.product",
+                        "name": "h2",
+                        "price": "span.price"
+                    }
+                }
+            ]
+        }
+        
+        # Initialize scraper
+        scraper = MarketTrendsScraper(config, headless=True)
+        
+        # Mock one source to succeed and one to fail
+        def mock_scrape_source(source):
+            if source["name"] == "working_source":
+                return [{"name": "Working Product", "price": 15.00, "source": "working_source"}]
+            else:
+                raise Exception("Scraping failed")
+        
+        with patch.object(scraper, '_scrape_source', side_effect=mock_scrape_source):
+            data = scraper.scrape_market_trends()
+            
+            # Should still get data from working source
+            assert len(data) == 1
+            assert data[0]["source"] == "working_source"
+    
+    @patch('sys.argv', ['main.py', '--config', 'test_config.yaml', '--output', 'test_output.csv'])
+    @patch('src.scraper.webdriver')
+    def test_main_entry_point(self, mock_webdriver, temp_dir):
+        """Test the main entry point of the application."""
+        # Setup mock driver
+        mock_driver = Mock()
+        mock_webdriver.Chrome.return_value = mock_driver
+        
+        # Create test config
+        config_path = Path(temp_dir) / "test_config.yaml"
+        config_content = {
+            "scraper": {
+                "delay_between_requests": 0.1,
+                "timeout": 10,
+                "headless": True
+            },
+            "sources": [
+                {
+                    "name": "test_source",
+                    "url": "https://example.com",
+                    "enabled": True,
+                    "selectors": {
+                        "product": "div.product",
+                        "name": "h2",
+                        "price": "span.price"
+                    }
+                }
+            ]
+        }
+        
+        import yaml
+        with open(config_path, 'w') as f:
+            yaml.dump(config_content, f)
+        
+        # Mock the scraper to return sample data
+        sample_data = [{"name": "Test Product", "price": 19.99, "source": "test_source"}]
+        
+        with patch('main.ConfigManager') as mock_config_manager, \
+             patch('main.MarketTrendsScraper') as mock_scraper_class:
+            
+            # Setup mocks
+            mock_config_instance = Mock()
+            mock_config_manager.return_value = mock_config_instance
+            mock_config_instance.load_config.return_value = config_content
+            
+            mock_scraper_instance = Mock()
+            mock_scraper_class.return_value = mock_scraper_instance
+            mock_scraper_instance.scrape_market_trends.return_value = sample_data
+            mock_scraper_instance.analyze_trends.return_value = {"total_products": 1}
+            
+            # Run main function
+            with patch('sys.argv', ['main.py', '--config', str(config_path), '--output', str(temp_dir / 'output.csv')]):
+                result = main.main()
+                
+                # Verify main completed successfully
+                assert result == 0
+                
+                # Verify scraper was called
+                mock_scraper_instance.scrape_market_trends.assert_called_once()
+                mock_scraper_instance.save_data.assert_called_once()
+                mock_scraper_instance.analyze_trends.assert_called_once()
+                mock_scraper_instance.save_analysis.assert_called_once()
--- a/tests/test_logger.py
+++ b/tests/test_logger.py
@@ -0,0 +1,165 @@
+"""
+Unit tests for the Logger module.
+"""
+
+import pytest
+import sys
+import tempfile
+import os
+from pathlib import Path
+from unittest.mock import patch, MagicMock
+from loguru import logger
+
+from src.logger import setup_logger, get_logger, LoggerMixin
+
+
+class TestLoggerSetup:
+    """Test cases for logger setup functionality."""
+    
+    def test_setup_logger_default(self):
+        """Test logger setup with default parameters."""
+        with patch('loguru.logger.remove') as mock_remove, \
+             patch('loguru.logger.add') as mock_add:
+            
+            setup_logger()
+            
+            # Verify default logger was removed
+            mock_remove.assert_called_once()
+            
+            # Verify console logger was added
+            assert mock_add.call_count == 1
+            console_call = mock_add.call_args_list[0]
+            assert console_call[0][0] == sys.stderr
+            assert "level" in console_call[1]
+            assert console_call[1]["colorize"] is True
+    
+    def test_setup_logger_with_file(self):
+        """Test logger setup with file output."""
+        with tempfile.NamedTemporaryFile(delete=False) as tmp_file:
+            log_file = tmp_file.name
+        
+        try:
+            with patch('loguru.logger.remove') as mock_remove, \
+                 patch('loguru.logger.add') as mock_add:
+                
+                setup_logger(log_file=log_file)
+                
+                # Verify both console and file loggers were added
+                assert mock_add.call_count == 2
+                
+                # Check file logger call
+                file_call = mock_add.call_args_list[1]
+                assert file_call[0][0] == log_file
+                assert "rotation" in file_call[1]
+                assert "retention" in file_call[1]
+                assert "compression" in file_call[1]
+        finally:
+            # Clean up
+            if os.path.exists(log_file):
+                os.unlink(log_file)
+    
+    def test_setup_logger_verbose(self):
+        """Test logger setup with verbose mode."""
+        with patch('loguru.logger.remove') as mock_remove, \
+             patch('loguru.logger.add') as mock_add:
+            
+            setup_logger(verbose=True)
+            
+            # Verify DEBUG level was set
+            console_call = mock_add.call_args_list[0]
+            assert console_call[1]["level"] == "DEBUG"
+    
+    def test_setup_logger_custom_level(self):
+        """Test logger setup with custom log level."""
+        with patch('loguru.logger.remove') as mock_remove, \
+             patch('loguru.logger.add') as mock_add:
+            
+            setup_logger(log_level="WARNING")
+            
+            # Verify WARNING level was set
+            console_call = mock_add.call_args_list[0]
+            assert console_call[1]["level"] == "WARNING"
+    
+    def test_setup_logger_custom_rotation(self):
+        """Test logger setup with custom rotation settings."""
+        with tempfile.NamedTemporaryFile(delete=False) as tmp_file:
+            log_file = tmp_file.name
+        
+        try:
+            with patch('loguru.logger.remove') as mock_remove, \
+                 patch('loguru.logger.add') as mock_add:
+                
+                setup_logger(log_file=log_file, rotation="100 MB")
+                
+                # Verify custom rotation was set
+                file_call = mock_add.call_args_list[1]
+                assert file_call[1]["rotation"] == "100 MB"
+        finally:
+            # Clean up
+            if os.path.exists(log_file):
+                os.unlink(log_file)
+    
+    def test_setup_logger_exception_handler(self):
+        """Test that exception handler is set up."""
+        with patch('loguru.logger.remove') as mock_remove, \
+             patch('loguru.logger.add') as mock_add, \
+             patch('sys.excepthook') as mock_excepthook:
+            
+            setup_logger()
+            
+            # Verify exception handler was set
+            assert mock_excepthook is not None
+            assert callable(mock_excepthook)
+
+
+class TestGetLogger:
+    """Test cases for get_logger function."""
+    
+    def test_get_logger_no_name(self):
+        """Test getting logger without name."""
+        with patch('loguru.logger.bind') as mock_bind:
+            get_logger()
+            mock_bind.assert_called_once()
+    
+    def test_get_logger_with_name(self):
+        """Test getting logger with name."""
+        with patch('loguru.logger.bind') as mock_bind:
+            get_logger("test_module")
+            mock_bind.assert_called_once_with(name="test_module")
+
+
+class TestLoggerMixin:
+    """Test cases for LoggerMixin class."""
+    
+    def test_logger_property(self):
+        """Test logger property in mixin."""
+        
+        class TestClass(LoggerMixin):
+            pass
+        
+        with patch('loguru.logger.bind') as mock_bind:
+            test_obj = TestClass()
+            _ = test_obj.logger
+            
+            # Verify logger was bound with class name and object id
+            mock_bind.assert_called_once()
+            args, kwargs = mock_bind.call_args
+            assert kwargs["name"] == "TestClass"
+            assert "id" in kwargs
+    
+    def test_logger_mixin_inheritance(self):
+        """Test that logger mixin works with inheritance."""
+        
+        class ParentClass(LoggerMixin):
+            pass
+        
+        class ChildClass(ParentClass):
+            pass
+        
+        with patch('loguru.logger.bind') as mock_bind:
+            child_obj = ChildClass()
+            _ = child_obj.logger
+            
+            # Verify logger was bound with child class name
+            args, kwargs = mock_bind.call_args
+            assert kwargs["name"] == "ChildClass"
--- a/tests/test_scraper.py
+++ b/tests/test_scraper.py
@@ -0,0 +1,371 @@
+"""
+Unit tests for the Scraper module.
+"""
+
+import pytest
+import json
+from unittest.mock import Mock, patch, MagicMock
+from bs4 import BeautifulSoup
+import pandas as pd
+
+from src.scraper import MarketTrendsScraper
+
+
+class TestMarketTrendsScraper:
+    """Test cases for MarketTrendsScraper class."""
+    
+    @pytest.fixture
+    def sample_config(self):
+        """Sample configuration for testing."""
+        return {
+            "scraper": {
+                "delay_between_requests": 1.0,
+                "timeout": 30,
+                "max_retries": 3,
+                "user_agent": "Mozilla/5.0",
+                "headless": True,
+                "window_size": [1920, 1080]
+            },
+            "sources": [
+                {
+                    "name": "test_source",
+                    "url": "https://example.com/products",
+                    "type": "ecommerce",
+                    "enabled": True,
+                    "selectors": {
+                        "product": "div.product",
+                        "name": "h2.title",
+                        "price": "span.price",
+                        "rating": "div.rating",
+                        "availability": "div.stock"
+                    },
+                    "pagination": {
+                        "next_page": "a.next",
+                        "max_pages": 2
+                    }
+                }
+            ],
+            "output": {
+                "format": "csv",
+                "include_timestamp": True,
+                "filename": "market_trends_data"
+            }
+        }
+    
+    @pytest.fixture
+    def sample_html(self):
+        """Sample HTML for testing."""
+        return """
+        <html>
+            <body>
+                <div class="product">
+                    <h2 class="title">Test Product 1</h2>
+                    <span class="price">$19.99</span>
+                    <div class="rating">4.5 stars</div>
+                    <div class="stock">In Stock</div>
+                    <a href="/product/1">View</a>
+                </div>
+                <div class="product">
+                    <h2 class="title">Test Product 2</h2>
+                    <span class="price">€29.99</span>
+                    <div class="rating">3.8 stars</div>
+                    <div class="stock">Out of Stock</div>
+                    <a href="/product/2">View</a>
+                </div>
+                <a class="next" href="/page/2">Next</a>
+            </body>
+        </html>
+        """
+    
+    @patch('src.scraper.webdriver')
+    def test_init(self, mock_webdriver, sample_config):
+        """Test scraper initialization."""
+        mock_driver = Mock()
+        mock_webdriver.Chrome.return_value = mock_driver
+        
+        scraper = MarketTrendsScraper(sample_config)
+        
+        assert scraper.config == sample_config
+        assert scraper.driver == mock_driver
+        assert scraper.session is not None
+        assert scraper.data == []
+        
+        # Verify browser setup
+        mock_webdriver.Chrome.assert_called_once()
+        mock_driver.set_page_load_timeout.assert_called_with(30)
+    
+    @patch('src.scraper.webdriver')
+    def test_setup_browser(self, mock_webdriver, sample_config):
+        """Test browser setup."""
+        mock_driver = Mock()
+        mock_webdriver.Chrome.return_value = mock_driver
+        
+        scraper = MarketTrendsScraper(sample_config)
+        
+        # Verify options were set
+        call_args = mock_webdriver.Chrome.call_args
+        options = call_args[1]['options']
+        
+        assert options.arguments is not None
+        assert any("--headless" in arg for arg in options.arguments)
+        assert any("--window-size=1920,1080" in arg for arg in options.arguments)
+    
+    @patch('src.scraper.webdriver')
+    def test_setup_session(self, mock_webdriver, sample_config):
+        """Test session setup."""
+        scraper = MarketTrendsScraper(sample_config)
+        
+        # Verify headers were set
+        assert "User-Agent" in scraper.session.headers
+        assert scraper.session.headers["User-Agent"] == sample_config["scraper"]["user_agent"]
+        assert "Accept" in scraper.session.headers
+    
+    @patch('src.scraper.webdriver')
+    def test_parse_price(self, mock_webdriver, sample_config):
+        """Test price parsing."""
+        scraper = MarketTrendsScraper(sample_config)
+        
+        # Test various price formats
+        assert scraper._parse_price("$19.99") == 19.99
+        assert scraper._parse_price("€29.99") == 29.99
+        assert scraper._parse_price("£39.99") == 39.99
+        assert scraper._parse_price("19,99") == 19.99
+        assert scraper._parse_price("Price: $49.99 USD") == 49.99
+        assert scraper._parse_price("Invalid price") is None
+        assert scraper._parse_price("") is None
+    
+    @patch('src.scraper.webdriver')
+    def test_parse_rating(self, mock_webdriver, sample_config):
+        """Test rating parsing."""
+        scraper = MarketTrendsScraper(sample_config)
+        
+        # Test various rating formats
+        assert scraper._parse_rating("4.5 stars") == 4.5
+        assert scraper._parse_rating("Rating: 3.8/5") == 3.8
+        assert scraper._parse_rating("5 stars") == 5.0
+        assert scraper._parse_rating("Invalid rating") is None
+        assert scraper._parse_rating("") is None
+    
+    @patch('src.scraper.webdriver')
+    def test_extract_product_data(self, mock_webdriver, sample_config, sample_html):
+        """Test product data extraction from HTML."""
+        scraper = MarketTrendsScraper(sample_config)
+        
+        soup = BeautifulSoup(sample_html, 'html.parser')
+        product = soup.find('div', class_='product')
+        selectors = sample_config["sources"][0]["selectors"]
+        
+        data = scraper._extract_product_data(product, selectors)
+        
+        assert data is not None
+        assert data["name"] == "Test Product 1"
+        assert data["price"] == 19.99
+        assert data["rating"] == 4.5
+        assert data["availability"] == "In Stock"
+        assert data["url"] == "/product/1"
+    
+    @patch('src.scraper.webdriver')
+    def test_extract_product_data_no_name(self, mock_webdriver, sample_config):
+        """Test product data extraction when name is missing."""
+        scraper = MarketTrendsScraper(sample_config)
+        
+        html = """
+        <div class="product">
+            <span class="price">$19.99</span>
+        </div>
+        """
+        soup = BeautifulSoup(html, 'html.parser')
+        product = soup.find('div', class_='product')
+        selectors = sample_config["sources"][0]["selectors"]
+        
+        data = scraper._extract_product_data(product, selectors)
+        
+        assert data is None  # Should return None when name is missing
+    
+    @patch('src.scraper.webdriver')
+    def test_make_request_with_retry_success(self, mock_webdriver, sample_config):
+        """Test successful HTTP request with retry logic."""
+        scraper = MarketTrendsScraper(sample_config)
+        
+        mock_response = Mock()
+        mock_response.status_code = 200
+        mock_response.text = "Success"
+        
+        with patch.object(scraper.session, 'get', return_value=mock_response) as mock_get:
+            response = scraper._make_request_with_retry("https://example.com")
+            
+            assert response == mock_response
+            mock_get.assert_called_once()
+    
+    @patch('src.scraper.webdriver')
+    def test_make_request_with_retry_failure(self, mock_webdriver, sample_config):
+        """Test HTTP request failure with retry logic."""
+        scraper = MarketTrendsScraper(sample_config)
+        
+        with patch.object(scraper.session, 'get', side_effect=Exception("Connection error")):
+            response = scraper._make_request_with_retry("https://example.com")
+            
+            assert response is None
+    
+    @patch('src.scraper.webdriver')
+    @patch('src.scraper.MarketTrendsScraper._scrape_source')
+    def test_scrape_market_trends(self, mock_scrape_source, mock_webdriver, sample_config):
+        """Test scraping market trends from multiple sources."""
+        scraper = MarketTrendsScraper(sample_config)
+        
+        # Mock source data
+        mock_scrape_source.side_effect = [
+            [{"name": "Product 1", "price": 19.99}],
+            [{"name": "Product 2", "price": 29.99}]
+        ]
+        
+        # Add second source
+        sample_config["sources"].append({
+            "name": "test_source_2",
+            "url": "https://example2.com/products",
+            "enabled": True,
+            "selectors": {
+                "product": "div.product",
+                "name": "h2.title",
+                "price": "span.price"
+            }
+        })
+        
+        data = scraper.scrape_market_trends()
+        
+        assert len(data) == 2
+        assert data[0]["name"] == "Product 1"
+        assert data[1]["name"] == "Product 2"
+        assert mock_scrape_source.call_count == 2
+    
+    @patch('src.scraper.webdriver')
+    @patch('src.scraper.MarketTrendsScraper._scrape_with_requests')
+    def test_scrape_source_with_requests(self, mock_scrape_requests, mock_webdriver, sample_config):
+        """Test scraping a source using requests."""
+        scraper = MarketTrendsScraper(sample_config)
+        
+        mock_scrape_requests.return_value = [{"name": "Test Product", "price": 19.99}]
+        
+        source = sample_config["sources"][0]
+        data = scraper._scrape_source(source)
+        
+        assert len(data) == 1
+        assert data[0]["name"] == "Test Product"
+        mock_scrape_requests.assert_called_once_with(source)
+    
+    @patch('src.scraper.webdriver')
+    @patch('src.scraper.MarketTrendsScraper._scrape_with_selenium')
+    def test_scrape_source_with_selenium(self, mock_scrape_selenium, mock_webdriver, sample_config):
+        """Test scraping a source using Selenium."""
+        scraper = MarketTrendsScraper(sample_config)
+        
+        mock_scrape_selenium.return_value = [{"name": "Test Product", "price": 19.99}]
+        
+        # Configure source to use Selenium
+        source = sample_config["sources"][0]
+        source["use_selenium"] = True
+        
+        data = scraper._scrape_source(source)
+        
+        assert len(data) == 1
+        assert data[0]["name"] == "Test Product"
+        mock_scrape_selenium.assert_called_once_with(source)
+    
+    @patch('src.scraper.webdriver')
+    @patch('builtins.open', new_callable=Mock)
+    def test_save_data_csv(self, mock_open, mock_webdriver, sample_config):
+        """Test saving data to CSV file."""
+        scraper = MarketTrendsScraper(sample_config)
+        
+        data = [
+            {"name": "Product 1", "price": 19.99, "source": "Test"},
+            {"name": "Product 2", "price": 29.99, "source": "Test"}
+        ]
+        
+        with patch.object(pd.DataFrame, 'to_csv') as mock_to_csv:
+            scraper.save_data(data, "test_output.csv")
+            mock_to_csv.assert_called_once_with("test_output.csv", index=False)
+    
+    @patch('src.scraper.webdriver')
+    @patch('builtins.open', new_callable=Mock)
+    def test_save_data_json(self, mock_open, mock_webdriver, sample_config):
+        """Test saving data to JSON file."""
+        scraper = MarketTrendsScraper(sample_config)
+        
+        data = [
+            {"name": "Product 1", "price": 19.99, "source": "Test"},
+            {"name": "Product 2", "price": 29.99, "source": "Test"}
+        ]
+        
+        with patch.object(pd.DataFrame, 'to_json') as mock_to_json:
+            scraper.save_data(data, "test_output.json")
+            mock_to_json.assert_called_once()
+    
+    @patch('src.scraper.webdriver')
+    def test_analyze_trends(self, mock_webdriver, sample_config):
+        """Test trend analysis."""
+        scraper = MarketTrendsScraper(sample_config)
+        
+        data = [
+            {"name": "Product 1", "price": 19.99, "rating": 4.5, "source": "Source A"},
+            {"name": "Product 2", "price": 29.99, "rating": 3.8, "source": "Source A"},
+            {"name": "Product 3", "price": 39.99, "rating": 4.2, "source": "Source B"},
+            {"name": "Product 4", "price": 49.99, "rating": 4.7, "source": "Source B"}
+        ]
+        
+        analysis = scraper.analyze_trends(data)
+        
+        assert analysis["total_products"] == 4
+        assert "price_analysis" in analysis
+        assert "rating_analysis" in analysis
+        assert "sources" in analysis
+        assert analysis["sources"]["Source A"] == 2
+        assert analysis["sources"]["Source B"] == 2
+        assert analysis["price_analysis"]["average_price"] == 34.99
+        assert analysis["price_analysis"]["min_price"] == 19.99
+        assert analysis["price_analysis"]["max_price"] == 49.99
+        assert analysis["rating_analysis"]["average_rating"] == 4.3
+    
+    @patch('src.scraper.webdriver')
+    def test_analyze_trends_empty_data(self, mock_webdriver, sample_config):
+        """Test trend analysis with empty data."""
+        scraper = MarketTrendsScraper(sample_config)
+        
+        analysis = scraper.analyze_trends([])
+        
+        assert "error" in analysis
+        assert analysis["error"] == "No data available for analysis"
+    
+    @patch('src.scraper.webdriver')
+    @patch('builtins.open', new_callable=Mock)
+    def test_save_analysis(self, mock_open, mock_webdriver, sample_config):
+        """Test saving analysis results."""
+        scraper = MarketTrendsScraper(sample_config)
+        
+        analysis = {"total_products": 4, "average_price": 34.99}
+        
+        with patch('json.dump') as mock_json_dump:
+            scraper.save_analysis(analysis, "test_analysis.json")
+            mock_json_dump.assert_called_once()
+    
+    @patch('src.scraper.webdriver')
+    def test_close(self, mock_webdriver, sample_config):
+        """Test closing browser and session."""
+        mock_driver = Mock()
+        mock_webdriver.Chrome.return_value = mock_driver
+        
+        scraper = MarketTrendsScraper(sample_config)
+        scraper.close()
+        
+        mock_driver.quit.assert_called_once()
+    
+    @patch('src.scraper.webdriver')
+    def test_context_manager(self, mock_webdriver, sample_config):
+        """Test using scraper as context manager."""
+        mock_driver = Mock()
+        mock_webdriver.Chrome.return_value = mock_driver
+        
+        with MarketTrendsScraper(sample_config) as scraper:
+            assert scraper is not None
+        
+        mock_driver.quit.assert_called_once()