CSV2Sendy

A powerful CSV processor for Sendy.co with Brazilian data format support.

Documentation | GitHub Repository

🌟 Features

• 🔄 Intelligent CSV Processing

  • Auto-detection of delimiters (, or ;)
  • Multiple encoding support (utf-8-sig, latin1, iso-8859-1, cp1252)
  • Smart column mapping and normalization
  • Robust error handling

• 📧 Email Validation

  • RFC-compliant email validation
  • Case normalization
  • Duplicate removal
  • Invalid email filtering

• 📱 Phone Number Processing

  • Brazilian format support
  • Format standardization
  • Invalid number filtering
  • DDD (area code) validation

• 👤 Name Processing

  • First/last name splitting
  • Proper capitalization
  • Special character handling
  • Empty name filtering

• 🔒 Security

  • Secure file handling
  • Automatic file cleanup
  • Input sanitization
  • File size limits

💻 Web Interface

Transform your CSV files into Sendy.co-ready formats with our intuitive web interface:

The web interface provides:

• 📤 Drag & drop file upload
• 🔄 Automatic CSV processing
• 📋 Column mapping
• ✨ Data validation and cleaning
• ⬇️ Download processed files

📦 Installation

Using pip

pip install csv2sendy

From source

git clone https://github.com/skaisser/csv2sendy.git
cd csv2sendy
pip install -e ".[dev]"

🚀 Quick Start

Web Interface

# Start the web server
python -m csv2sendy.web.app

Visit http://localhost:5000 in your browser.

Command Line Interface (CLI)

# Start the web server on default port (5000)
csv2sendy

# Start the web server on a specific port
csv2sendy 3000

# Get help
csv2sendy --help

The CLI provides a convenient way to start the web interface. By default, it starts the server on port 5000, but you can specify a different port as a command-line argument.

Python API

from csv2sendy.core import CSVProcessor

# Process a CSV file
processor = CSVProcessor()
df = processor.process_file('input.csv')
df.to_csv('output.csv', index=False)

# Process CSV content directly
content = '''name,email,phone
John Doe,john@example.com,(11) 98765-4321'''
df = processor.process_file(content)

🔧 Dependencies

Core dependencies (automatically installed):

• Python >=3.9
• pandas >=1.3.0
• email-validator >=1.1.0
• flask >=2.0.0
• werkzeug >=2.0.0

Development dependencies (install with .[dev]):

• pytest >=7.0.0
• pytest-cov >=4.0.0
• mypy >=1.13.0
• types-flask >=1.1.0
• types-werkzeug >=1.0.0
• pandas-stubs >=2.0.0

Documentation dependencies (install with .[docs]):

• sphinx >=7.0.0

🤝 Contributing

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Install development dependencies (pip install -e ".[dev,test,doc]")
4. Make your changes
5. Run tests and type checking (pytest and mypy csv2sendy)
6. Commit your changes (git commit -m 'Add amazing feature')
7. Push to the branch (git push origin feature/amazing-feature)
8. Open a Pull Request

📄 License

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

👤 Author

Shirleyson Kaisser

• GitHub: @skaisser
• Email: skaisser@gmail.com