The fMRIPrep on Docker wrapper
fMRIprep is a functional magnetic resonance image pre-processing pipeline that is designed to provide an easily accessible, state-of-the-art interface that is robust to differences in scan acquisition protocols and that requires minimal user input, while providing easily interpretable and comprehensive error and output reporting.
This is a lightweight Python wrapper to run fMRIPrep. It generates the appropriate Docker commands, providing an intuitive interface to running the fMRIPrep workflow in a Docker environment. Docker must be installed and running. This can be checked running
docker info
Please acknowledge this work using the citation boilerplate that fMRIPrep includes in the visual report generated for every subject processed. For a more detailed description of the citation boilerplate and its relevance, please check out the NiPreps documentation. Please report any feedback to our GitHub repository.
Release files for fmriprep-docker 25.2.6
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| fmriprep_docker-25.2.6.tar.gz | 9.3 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| fmriprep_docker-25.2.6-py2.py3-none-any.whl | Python 2, Python 3 | none | any | Details |
Total release size: 19.7 kB
Release files / fmriprep_docker-25.2.6.tar.gz
| Download URL | fmriprep_docker-25.2.6.tar.gz |
|---|---|
| Size | 9.3 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.12.14
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Release files / fmriprep_docker-25.2.6-py2.py3-none-any.whl
| Download URL | fmriprep_docker-25.2.6-py2.py3-none-any.whl |
|---|---|
| Size | 10.5 kB |
| Tags | Python 2 Python 3 |
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SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.12.14
|
