# 1. Open in Codespaces (click badge above) # 2. Install uv # 3. Create the Virtual Environment # 4. Activate the environment (#Linux) pip install uv uv venv source .venv/bin/activate # Run only if the Requirement file is present uv pip install -r requirements.txt

# Run only if the Requirement file is absent uv pip install requests beautifulsoup4

python joss_extractor.py

python helmholtzRSD_extractor.py

The script generates a timestamped CSV file with software repositories:

software_repository "https://github.com/example/awesome-tool" "https://gitlab.com/research/data-analyzer" "https://codeberg.org/dev/ml-framework" 

joss_repositories_YYYYMMDD_HHMMSS.csv Helmholtz_software_repositories_YYYYMMDD_HHMMSS.csv 

Example: joss_repositories_20250805_143022.csv

python joss_extractor.py python helmholtzRSD_extractor.py

🚀 JOSS Papers Data Extractor ================================================== 🕒 Started at: 2025-08-05 14:30:15 Fetching page 1/156... → Retrieved 20 papers (Total: 20) Fetching page 2/156... → Retrieved 20 papers (Total: 40) ... ============================================================ 📊 EXTRACTION SUMMARY ============================================================ 📥 Total papers processed: 3,111 📝 Records written to CSV: 3,089 ❌ Papers without repositories: 22 📈 Repository coverage: 99.3% 📁 Output file: joss_repositories_20250805_143022.csv 🕒 Extraction completed at: 2025-08-05 14:32:18 🔍 VERIFICATION: ✅ Processed 3,111 papers from API ✅ Wrote 3,089 repository URLs to CSV ✅ Data integrity: 3,089 + 22 = 3,111 ✓ ⏱️ Total execution time: 123.4 seconds 

• Python 3.6+
• requests library
• Internet connection

• Base URL: https://joss.theoj.org/papers/published.json
• Pagination: 20 records per page
• Total Pages: ~156 pages
• Rate Limiting: 100ms delay between requests

1. Fetch all pages from JOSS API
2. Filter papers with valid repository URLs
3. Format URLs with explicit quotes
4. Export to timestamped CSV file
5. Verify data integrity

This project was generated with the assistance of Claude AI. Contributions are welcome!

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

6. [TODO : Fix Licence extraction logic for non GITHUB repo's]

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

• JOSS - For providing the excellent API
• Claude AI - For assisting in code generation
• GitHub Codespaces - For seamless development environment