zenodo-sync 0.1.0

A lightweight CLI and Python library to synchronise local research data, results and analysis artifacts with Zenodo

zenodo-sync

A lightweight CLI and Python library to synchronise local research data, results and analysis artifacts with Zenodo. Designed for reproducible science and seamless data publishing workflows.

Status

🚧 Active Development - This repository is currently in active development. The core functionality is being implemented and the API may change.

The package is available on PyPI as a placeholder to reserve the name. Full functionality will be available in upcoming releases.

Features (Planned)

• 📤 Upload & Publish: Upload metadata, READMEs, and digital assets from local filesystem to Zenodo
• 📥 Download: Download published datasets to local filesystem for reproducible research
• 🔄 Sync: Bidirectional synchronization between local directories and Zenodo records
• 🔐 Authentication: Secure API token-based authentication with Zenodo
• 🧪 Sandbox Support: Test your workflows safely with Zenodo's sandbox environment
• 🎯 Semantic Versioning: Built-in support for semantic versioning of your research outputs
• 🐍 Python API: Comprehensive Python API for integration into existing workflows
• ⌨️ CLI Interface: Easy-to-use command-line interface for quick operations

Installation

From PyPI (Recommended)

pip install zenodo-sync

Development Installation

# Clone the repository
git clone https://github.com/causaliq/zenodo-sync.git
cd zenodo-sync

# Set up development environment (Windows)
scripts\setup-dev.bat

# Set up development environment (Unix/Linux/macOS)
chmod +x scripts/setup-dev.sh
./scripts/setup-dev.sh

# Or manually:
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate
pip install -e ".[dev,test]"

Quick Start

1. Get Your Zenodo API Token

1. Visit Zenodo (or Zenodo Sandbox for testing)
2. Go to Account Settings → Applications → Personal access tokens
3. Create a new token with appropriate scopes

2. Configure Authentication

# Set environment variable
export ZENODO_TOKEN="your-api-token-here"

# Or create a .env file
cp .env.example .env
# Edit .env and add your token

3. Use the CLI

# Upload a file (to sandbox by default)
zenodo-sync upload my-dataset.csv

# Download files from a record
zenodo-sync download 12345 ./downloads/

# Sync a directory with Zenodo
zenodo-sync sync ./my-research-project/

4. Use the Python API

from zenodo_sync import ZenodoSync

# Initialize (uses sandbox by default for safety)
sync = ZenodoSync(token="your-token", sandbox=True)

# Upload a file
result = sync.upload_file("my-dataset.csv")

# Download files
files = sync.download_file("12345", "./downloads/")

# Sync directory
result = sync.sync_directory("./my-project/")

Configuration

You can configure zenodo-sync using:

1. Environment variables:

   • ZENODO_TOKEN: Your Zenodo API token
   • ZENODO_SANDBOX: Use sandbox (default: true)

2. Configuration file (.env):

   ZENODO_TOKEN=your_token_here
   ZENODO_SANDBOX=true
   

3. Command-line arguments:

   zenodo-sync --token your-token --production upload file.txt
   

Development

Requirements

• Python 3.9 or higher
• pip (latest version recommended)

Development Setup

# Clone and setup
git clone https://github.com/causaliq/zenodo-sync.git
cd zenodo-sync

# Quick setup using task runner
python tasks.py setup

# Or manual setup
pip install -e ".[dev,test]"
pre-commit install

Running Tests

# Run all tests with coverage
python tasks.py test

# Quick tests (no coverage)
python tasks.py test-quick

# Or directly with pytest
pytest -v

Code Quality

# Run all checks (lint, type-check, test)
python tasks.py check

# Format code
python tasks.py format

# Run linting only
python tasks.py lint

# Type checking
python tasks.py type-check

Building and Publishing

# Build package
python tasks.py build

# Using the build script (Windows)
scripts\build-and-publish.bat

# Manual build and upload
python -m build
twine upload --repository testpypi dist/*  # Test PyPI
twine upload dist/*  # Production PyPI

Contributing

We welcome contributions! Please see our contributing guidelines for details.

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Make your changes
4. Run tests (python tasks.py check)
5. Commit your changes (git commit -m 'Add amazing feature')
6. Push to the branch (git push origin feature/amazing-feature)
7. Open a Pull Request

License

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

Changelog

See CHANGELOG.md for a detailed list of changes and version history.

Support

• 🐛 Bug Reports: GitHub Issues
• 💬 Discussions: GitHub Discussions
• 📚 Documentation: GitHub README

Acknowledgments

• Built for the research community
• Powered by the Zenodo platform
• Inspired by the need for reproducible science

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Supported Python Versions: 3.9, 3.10, 3.11, 3.12
Default Python Version: 3.11