Installing MNE-Python

There are many ways to install a Python interpreter and MNE. Here we show a simple well tested solution.

1. Get Python

We recommend the Anaconda distribution. Follow the installation instructions. When you are done, you should see a similar output if you type the following command in a terminal:

$ conda --version && python --version
conda 4.5.4
Python 3.6.5 :: Anaconda, Inc.

If you get an error message, consult the Anaconda documentation and search for Anaconda install tips (Stack Overflow results are often helpful).


MNE-Python 0.17 will be the last release to support Python 2. From MNE-Python 0.18, only Python 3 will be supported.

2. Get MNE and its dependencies

From the command line, install the MNE dependencies to a dedicated mne Anaconda environment.

$ curl -O
$ conda env create -f environment.yml
$ conda activate mne

You can also use a web browser to download the required environment file if you do not have curl.


If you are on macOS, you need to manually update PyQt5. This step is not needed on Linux, and even breaks things on Windows.

$ pip install --upgrade "pyqt5>=5.10"

3. Check that everything works

To make sure everything installed correctly, type the following command in a terminal:

$ python

This should open an interactive Python prompt, where you can type:

>>> import mne

If you get a new prompt with no error messages, you should be good to go!


If you are on Windows, you might have to use the IPython magic command %gui qt after importing MNE, Mayavi or PySurfer (see here):

In [1]: from mayavi import mlab
In [2]: %gui qt

The $ conda env create ... step sometimes emits warnings, but you can ensure all default dependencies are installed by listing their versions with:

>>> mne.sys_info()  
Platform:      Linux-4.4.0-112-generic-x86_64-with-debian-jessie-sid
Python:        3.6.6 |Anaconda, Inc.| (default, Jun 28 2018, 17:14:51)  [GCC 7.2.0]
Executable:    /home/travis/miniconda/envs/test/bin/python
CPU:           x86_64: 48 cores
Memory:        62.7 GB

mne:           0.16.2
numpy:         1.15.0 {blas=mkl_rt, lapack=mkl_rt}
scipy:         1.1.0
matplotlib:    2.2.2 {backend=Qt5Agg}

sklearn:       0.19.1
nibabel:       2.3.0
mayavi:        4.6.1 {qt_api=pyqt5, PyQt5=5.10.1}
cupy:          Not found
pandas:        0.23.4

For advanced topics like how to get CUDA (NVIDIA GPU acceleration) support or if you are experiencing other issues, check out Advanced setup and troubleshooting.