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openneuro-py

A Python client for accessing OpenNeuro datasets.

openneuro-py in action

Installation

# via conda:
conda install -c conda-forge openneuro-py
# or via pip:
pip install openneuro-py

Jupyter and IPython support

To get basic support for Jupyter Lab, Jupyter Notebook, IPython interactive sessions, and VS Code's interactive Jupyter interface, you will also need to install ipywidgets:

# via conda:
conda install -c conda-forge ipywidgets
# or via pip:
pip install ipywidgets

Basic usage – command line interface

Getting help

openneuro-py --help
openneuro-py download --help
openneuro-py login --help

Download an entire dataset

openneuro-py download --dataset=ds000246

Specify a target directory

To store the downloaded files in a specific directory, use the --target-dir switch. The directory will be created if it doesn't exist already.

openneuro-py download --dataset=ds000246 \
                      --target-dir=data/bids

Continue an interrupted download

Interrupted downloads will resume where they left off when you run the command again.

Advanced usage – command line interface

Exclude a directory from the download

openneuro-py download --dataset=ds000246 \
                      --exclude=sub-emptyroom

Download only a single file

openneuro-py download --dataset=ds000246 \
                      --include=sub-0001/meg/sub-0001_coordsystem.json

Note that a few essential BIDS files are always downloaded in addition.

Download or exclude multiple files

--include and --exclude can be passed multiple times:

openneuro-py download --dataset=ds000246 \
                      --include=sub-0001/meg/sub-0001_coordsystem.json \
                      --include=sub-0001/meg/sub-0001_acq-LPA_photo.jpg

Use an API token to log in

To download private datasets, you will need an API key that grants you access permissions. Go to OpenNeuro.org, My Account → Obtain an API Key. Copy the key, and run:

openneuro-py login

Paste the API key and press return.

Basic usage – Python interface

import openneuro as on
on.download(dataset='ds000246', target-dir='data/bids')