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Nipoppy docs are moving

Nipoppy is undergoing a major refactor to move from scripts to a command-line interface (CLI) and Python API. The new documentation website (work in progress) can be found at

If you are using the (soon-to-be legacy) scripts from Nipoppy 0.1.0, this is still the correct place to be. But we encourage you to check out the new website!

Code installation and dataset setup

The Nipoppy workflow comprises a Nipoppy codebase that operates on a Nipoppy dataset with a specific directory structure (initialized with a script).

Nipoppy code+env installation

  1. Change directory to where you want to clone this repo, e.g.: cd /home/<user>/projects/<my_project>/code/
  2. Create a new venv: python3 -m venv nipoppy_env
    • Alternatively (if using Anaconda/Miniconda), create a conda environment: conda create --name nipoppy_env python=3.9
  3. Activate your env: source nipoppy_env/bin/activate
    • If using Anaconda/Miniconda: conda activate nipoppy_env
  4. Clone this repo: git clone
  5. Change directory to nipoppy
  6. Install python dependencies: pip install -e .

Nipoppy dataset directory setup

Run nipoppy/ to create the Nipoppy dataset directory tree:

python nipoppy/ --nipoppy_root <DATASET_ROOT>

  • DATASET_ROOT: root (starting point) of the Nipoppy structured dataset


We suggest naming DATASET_ROOT directory after a study or a cohort.