Download and install

This page covers the necessary steps to install Nipype.


Release 0.10.0: [zip tar.gz]

Development: [zip tar.gz]

Prior downloads

To check out the latest development version:

git clone git://


The installation process is similar to other Python packages.

If you already have a Python environment setup that has the dependencies listed below, you can do:

easy_install nipype


pip install nipype

Debian and Ubuntu

Add the NeuroDebian repository and install the python-nipype package using apt-get or your favorite package manager.

Mac OS X

The easiest way to get nipype running on Mac OS X is to install Anaconda or Canopy and then add nibabel and nipype by executing:

easy_install nibabel
easy_install nipype

From source

If you downloaded the source distribution named something like nipype-x.y.tar.gz, then unpack the tarball, change into the nipype-x.y directory and install nipype using:

python install

Note: Depending on permissions you may need to use sudo.

Testing the install

The best way to test the install is to run the test suite. If you have nose installed, then do the following:

python -c "import nipype; nipype.test()"

you can also test with nosetests:

nosetests --with-doctest /software/nipy-repo/masternipype/nipype
--exclude=external --exclude=testing

All tests should pass (unless you’re missing a dependency). If SUBJECTS_DIR variable is not set some FreeSurfer related tests will fail. If any tests fail, please report them on our bug tracker.

On Debian systems, set the following environment variable before running tests:

export MATLABCMD=$pathtomatlabdir/bin/$platform/MATLAB

where, $pathtomatlabdir is the path to your matlab installation and $platform is the directory referring to x86 or x64 installations (typically glnxa64 on 64-bit installations).

Avoiding any MATLAB calls from testing

On unix systems, set an empty environment variable:


This will skip any tests that require matlab.


Below is a list of required dependencies, along with additional software recommendations.

Must Have

Python 2.7

Nibabel 1.0 - 1.4
Neuroimaging file i/o library
NetworkX 1.0 - 1.8
Python package for working with complex networks.

NumPy 1.3 - 1.7

SciPy 0.7 - 0.12
Numpy and Scipy are high-level, optimized scientific computing libraries.

Enthought Traits 4.0.0 - 4.3.0

Dateutil 1.5 -


Full distributions such as Anaconda or Canopy provide the above packages, except Nibabel.

Strong Recommendations

IPython 0.10.2 - 1.0.0
Interactive python environment. This is necessary for some parallel components of the pipeline engine.
Matplotlib 1.0 - 1.2
Plotting library

RDFLib 4.1 RDFLibrary required for provenance export as RDF

Sphinx 1.1
Required for building the documentation
Required for building the documentation

Interface Dependencies

These are the software packages that nipype.interfaces wraps:

4.1.0 or later
2008a or later
FreeSurfer version 4 and higher
2009_12_31_1431 or later
3.6 or later
0.1.2+20110404 or later