m2c2-datakit 0.1.0

Data management and scoring tools for the M2C2 project

m2c2kit-scoring-workspace

🚀 A set of R, Python, and NPM packages for scoring M2C2kit Data! 🚀

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Developers:

• Dr. Nelson Roque | ORCID: https://orcid.org/0000-0003-1184-202X
• Dr. Scott Yabiku | ORCID: https://orcid.org/0000-0003-1184-202X

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Changelog

Source: https://github.com/nelsonroque/m2c2kit-data

See CHANGELOG.md

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Features

Current Features

1. Load a JSON file of a query export from MongoDB
2. Load a folder of JSON files, one folder per participant, with subfolders for sessions, from Metricwire
3. Interoperable Data exports (csv, tsv, pkl)

Feature Roadmap

1. In General: Feature and Data parity from R, Python, and NPM scoring tools (same data + different tool = same scores)
2. CLI in Python for simplifying scoring with one-liners (e.g., m2data --score --summarise --file data.json)
3. Load a folder of JSON files, one folder per participant, with subfolders for sessions, from REDCAP (Coming Soon)
4. Load a file export, containing columns for each trial, for each task, from Qualtrics (Coming Soon)

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🚀 Getting Started

Installation for Scoring Developers

• Python
• Visual Studio Code with Jupyter Notebook Extension or Jupyter Lab (or Anaconda)
• uv venv

# 1. Create the virtual environment
uv venv .venv

# 2. Activate the virtual environment
source .venv/bin/activate  # macOS/Linux
# .venv\Scripts\Activate    # Windows (PowerShell)

# 3. Install dependencies
uv pip install -e .

# 4. Run formatting, linting, and type checking
make install

Installation for End Users

• pip3 install m2c2kit-data

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💡 Contributions Welcome!

📌 Have ideas? Found a bug? Want to improve the package? Open an issue!.

📜 Code of Conduct - Please be respectful and follow community guidelines.

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Acknowledgements

The development of m2c2kit-data (tentative name) was made possible with support from NIA (XXXXXXXXXXXXX).

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🌎 More Resources:
📌 M2C2 Official Website 📌 M2C2kit Official Documentation Website 📌 Pushing to PyPI

• https://docs.astral.sh/uv/guides/integration/github/#setting-up-python What is JSON?

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🚀 Let's go study some brains!