# 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). Note 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 https://raw.githubusercontent.com/mne-tools/mne-python/master/environment.yml
$conda env create -f environment.yml$ conda activate mne


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

macOS

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!

Windows

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}