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Current neuroimaging software offer users an incredible opportunity to analyze data using a variety of different algorithms. However, this has resulted in a heterogeneous collection of specialized applications without transparent interoperability or a uniform operating interface.
Nipype, an open-source, community-developed initiative under the umbrella of NiPy, is a Python project that provides a uniform interface to existing neuroimaging software and facilitates interaction between these packages within a single workflow. Nipype provides an environment that encourages interactive exploration of algorithms from different packages (e.g., AFNI, ANTS, BRAINS, BrainSuite, Camino, FreeSurfer, FSL, MNE, MRtrix, Nipy, Slicer, SPM), eases the design of workflows within and between packages, and reduces the learning curve necessary to use different packages. Nipype is creating a collaborative platform for neuroimaging software development in a high-level language and addressing limitations of existing pipeline systems.
Nipype allows you to:
easily interact with tools from different software packages
combine processing steps from different software packages
develop new workflows faster by reusing common steps from old ones
process data faster by running it in parallel on many cores/machines
make your research easily reproducible
share your processing workflows with the community
Documentation
Please see nipy.org/nipype for the Nipype documentation.
Python 2 Statement
Python 2.7 reaches its end-of-life in January 2020, which means it will no longer be maintained by Python developers. Many projects are removing support in advance of this deadline, which will make it increasingly untenable to try to support Python 2, even if we wanted to.
The final series with 2.7 support is 1.3.x. If you have a package using Python 2 and are unable or unwilling to upgrade to Python 3, then you should use the following dependency for Nipype:
nipype<1.4
Bug fixes will be accepted against the maint/1.3.x branch.
Support and Communication
If you have a problem or would like to ask a question about how to do something in Nipype please open an issue to NeuroStars.org with a nipype tag. NeuroStars.org is a platform similar to StackOverflow but dedicated to neuroinformatics.
To participate in the Nipype development related discussions please use the neuroimaging mailing list.
Please add [nipype] to the subject line when posting on the mailing list.
You can even hangout with the Nipype developers in their Gitter channel or in the BrainHack Slack channel. (Click here to join the Slack workspace.)
Contributing to the project
If you’d like to contribute to the project please read our guidelines. Please also read through our code of conduct.
Release files for nipype 1.12.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| nipype-1.12.0.tar.gz | 2.9 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| nipype-1.12.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 6.1 MB
Release files / nipype-1.12.0.tar.gz
| Download URL | nipype-1.12.0.tar.gz |
|---|---|
| Size | 2.9 MB |
| 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/3.13.14
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Release files / nipype-1.12.0-py3-none-any.whl
| Download URL | nipype-1.12.0-py3-none-any.whl |
|---|---|
| Size | 3.2 MB |
| Tags | 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 | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
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