pycsv2sqlite 0.1.0

read csv/tsv like file/files and produce sqlite3 db file

pycsv2sqlite

🗄️ A fast Python utility for converting CSV/TSV files to SQLite databases with automatic schema detection

✨ Features

• 🚀 Fast CSV/TSV import using Pandas
• 📁 Process single files or entire directories
• 🗄️ Automatic SQLite schema creation
• 🔄 Smart type mapping from Pandas to SQLite
• 📊 Detailed import statistics
• 🗜️ Support for gzipped files
• 🎯 Simple CLI interface with Typer

📦 Installation

Using pip

pip install pycsv2sqlite

Using uv (Recommended)

uv is a blazing-fast Python package installer:

# Install uv
pip install uv

# Install pycsv2sqlite using uv
uv pip install pycsv2sqlite

🚀 Quick Start

Command Line Usage

# Basic usage
pycsv2sqlite import-data data.csv

# Import TSV file
pycsv2sqlite import-data data.tsv --delimiter="\t"

# Import directory of CSVs
pycsv2sqlite import-data ./data/

Python Module Usage

python -m pycsv2sqlite import-data [options] INPUT_PATH

🎛️ Configuration Options

Option	Description	Default
--delimiter	Field delimiter in input files	,
--no-has-headers	Files don't have headers	False
--db-file	Output SQLite database name	YYYYMMDD_HHMMSS.sqlite3

🛠️ Development

Setup Development Environment

1. Clone the repository

git clone https://github.com/fxyzbtc/pycsv2sqlite.git
cd pycsv2sqlite

2. Create and activate virtual environment

uv venv .venv
.venv\Scripts\activate  # Windows
source .venv/bin/activate  # Unix

3. Install development dependencies

uv pip install -r requirements-dev.txt

Running Tests

pytest
pytest --cov=pycsv2sqlite tests/

Code Style

# Format code
black .
# Lint code
ruff check .
# Type checking
mypy .

📝 Example Output

SQLite Table Schema for data:
CREATE TABLE "data" (
    "id" INTEGER,
    "name" TEXT,
    "value" REAL,
    "timestamp" TIMESTAMP
)

Statistics:
- Records added to table: 1000
- Total records in table: 1000
- Columns: 4

🤝 Contributing

1. Fork the repository
2. Create your 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

📄 License

This project is licensed under the MIT License.

🙏 Acknowledgments

• Pandas for data processing
• Typer for the CLI interface
• SQLite for database operations

📞 Support

• 📫 Report issues on GitHub Issues
• 💬 Ask questions in Discussions
• 📚 Read the documentation

---

Made with ❤️ using Python