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🌐 Twitter Trends Analytics Platform

Python Selenium MongoDB Flask License PRs Welcome

A sophisticated platform for real-time Twitter trends analysis with enterprise-grade features

✨ Key Features

🔍 Advanced Scraping

  • Real-time trend monitoring
  • Intelligent data extraction
  • Rate limit handling
  • Automatic retry mechanism

🛡️ Enterprise Security

  • ProxyMesh integration
  • IP rotation & anonymity
  • Request encryption
  • Access control

💾 Robust Storage

  • MongoDB integration
  • Data versioning
  • Automated backups
  • Index optimization

📊 Analytics Dashboard

  • Real-time visualization
  • Trend analytics
  • Custom reporting
  • Data export (JSON/CSV)

🏗️ System Architecture

Loading
graph LR
    A[Web UI] --> B[Flask API]
    B --> C[Selenium Engine]
    C --> D[ProxyMesh]
    D --> E[Twitter]
    C --> F[MongoDB]
    B --> F

🚀 Quick Start Guide

Prerequisites

# System Requirements
✓ Python 3.8+
✓ MongoDB 5.0+
✓ Chrome/Chromium
✓ Twitter Account
✓ ProxyMesh Account

Installation

# Clone repository
git clone https://github.com/alphamoris/Web-Scraper.git
cd twitter-trends-scraper

# Create virtual environment
python -m venv venv
source venv/bin/activate  # Linux/macOS
.\venv\Scripts\activate   # Windows

# Install dependencies
pip install -r requirements.txt

Configuration

Create a .env file in the root directory:

# Required Environment Variables
MONGO_URI=mongodb://localhost:27017/
TWITTER_USERNAME=your_username
TWITTER_PASSWORD=your_password
PROXYMESH_USERNAME=your_proxymesh_username
PROXYMESH_PASSWORD=your_proxymesh_password

Launch

# Start the application
python app.py

# Access the dashboard at http://localhost:5000

💡 Advanced Usage

Selenium Configuration

options = {
    'headless': True,             # Run in background
    'proxy_rotation': True,       # Enable IP rotation
    'retry_attempts': 3,          # Failed request retries
    'timeout': 30,               # Request timeout (seconds)
    'user_agent_rotation': True  # Browser fingerprint protection
}

MongoDB Schema

{
  "_id": "uuid-v4",
  "timestamp": ISODate("2024-12-25T17:08:30.123Z"),
  "metadata": {
    "ip_address": "xxx.xxx.xxx.xxx",
    "proxy_region": "us-east",
    "execution_time": 1.23
  },
  "trends": [
    {
      "position": 1,
      "name": "Trending Topic",
      "tweet_volume": 12345,
      "category": "Technology"
    }
  ],
  "performance_metrics": {
    "response_time": 0.45,
    "processing_time": 0.78
  }
}

📈 Performance Metrics

Metric Value
Average Response Time < 2s
Success Rate 99.9%
Data Accuracy 99.99%
Concurrent Users 1000+

🔍 Monitoring & Logging

LOGGING = {
    'version': 1,
    'handlers': {
        'console': {
            'class': 'logging.StreamHandler',
            'level': 'INFO'
        },
        'file': {
            'class': 'logging.FileHandler',
            'filename': 'app.log',
            'level': 'DEBUG'
        }
    }
}

🛠️ Development

Code Quality

# Run tests
pytest tests/

# Code formatting
black .
flake8 .

# Type checking
mypy .

Contributing

We welcome contributions! Please follow these steps:

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

🙌 Acknowledgments

Special thanks to:

  • Twitter - Platform & API
  • ProxyMesh - Enterprise proxy solutions
  • MongoDB - Database infrastructure
  • Selenium - Web automation
  • Flask - Web framework

Created with ❤️ by Alpha

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