📄 Code & PDF Generator

A Streamlit-based web dashboard for generating random codes and dummy PDF files. Perfect for testing, development, or generating unique identifiers in bulk.

🚀 Features

• CSV Code Generator: Generate unique random codes with customizable formats
• Dummy PDF Generator: Create PDF files with unique codes for testing purposes
• Custom Format Support: Define your own code patterns using placeholders
• Bulk Generation: Generate up to 1,000,000 codes or 100 PDFs at once
• Download Ready: Export as CSV files or ZIP archives

📋 Requirements

• Python 3.7 or higher
• pip (Python package installer)

🛠️ Installation

1. Clone the repository:

   git clone https://github.com/JasonAldeo/code-generator.git
   cd code-generator

2. Install required packages:

   pip install -r requirements.txt

   Or install packages individually:

   pip install streamlit reportlab

🎯 Usage

1. Start the dashboard:

   streamlit run dashboard.py

2. Open your browser: The dashboard will automatically open at http://localhost:8501

3. Choose your generator type:

   • CSV Codes: Generate random codes in CSV format
   • Dummy PDFs: Generate PDF files with unique codes

🔧 Code Generation Options

Default Format

• Pattern: TVLK#####XXX
• Example: TVLK12345ABC

Custom Format

Use these placeholders to create your own patterns:

Placeholder	Description	Example
{d:X}	X random digits	{d:5} → 12345
{l:X}	X random uppercase letters	{l:3} → ABC
{s:X}	X random lowercase letters	{s:4} → abcd

Custom Format Examples:

• ORDER-{d:6} → ORDER-123456
• USER_{l:2}{d:4} → USER_AB1234
• temp_{s:3}-{d:3} → temp_xyz-789

📁 Output Formats

CSV Codes

• File: generated_codes.csv
• Format: One code per line
• Use case: Import into databases, spreadsheets, or other applications

Dummy PDFs

• File: dummy_pdfs.zip
• Contents: Individual PDF files named {prefix}_{code}.pdf
• Use case: Testing file processing systems, mock data generation

🎨 Dashboard Preview

The dashboard includes:

• Sidebar: Generator type selection and info
• Main Panel: Configuration options and generation controls
• Preview: Live preview of generated codes
• Download: Direct download buttons for generated files

🔒 Features & Guarantees

• ✅ Unique Codes: All codes within a batch are guaranteed to be unique
• ✅ Duplicate Detection: Automatic detection and regeneration of duplicates
• ✅ Memory Efficient: Files generated in-memory without temporary storage
• ✅ Scalable: Handle large batches efficiently

🐛 Troubleshooting

Common Issues

1. Module not found error:

   pip install --upgrade pip
   pip install -r requirements.txt

2. Port already in use:

   streamlit run dashboard.py --server.port 8502

3. Browser doesn't open automatically: Manually navigate to http://localhost:8501

🤝 Contributing

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

📝 License

This project is open source and available under the MIT License.

👨‍💻 Author

Jason Aldeo

• GitHub: @JasonAldeo
• Email: jason.leonard@traveloka.com

🙏 Acknowledgments

• Built with Streamlit
• PDF generation powered by ReportLab

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