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Data management and scoring tools for the M2C2 project

Project description

m2c2-datakit

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

This is the Python package 🐍

PyPI version

Installation for End Users

  • pip install m2c2-datakit
  • pip3 install m2c2-datakit

Developers:


Changelog

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

See CHANGELOG.md


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)

🚀 Getting Started

Installation for Scoring Developers

# 1. Create the virtual environment
pip install uv # or pip3 install uv
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

💡 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.


Acknowledgements

The development of m2c2-datakit was made possible with support from NIA (1U2CAG060408-01).


[TASKNAME].score_trials [TASKNAME].summarize


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


🚀 Let's go study some brains!

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