Install via pip or conda#

Hint

If you’re unfamiliar with Python, we recommend using our MNE-Python installers instead.

MNE-Python requires Python version 3.9 or higher. If you need help installing Python, please refer to our Installing Python guide.

Installing MNE-Python with all dependencies#

If you use Anaconda, we suggest installing MNE-Python into its own conda environment.

First, please ensure you’re using a recent version of conda. Run in your terminal:

$ conda update --name=base conda  # update conda
$ conda --version

The installed conda version should be 23.10.0 or newer.

Now, you can install MNE-Python:

$ conda create --channel=conda-forge --strict-channel-priority --name=mne mne

This will create a new conda environment called mne (you can adjust this by passing a different name via --name) and install all dependencies into it.

If you need to convert structural MRI scans into models of the scalp, inner/outer skull, and cortical surfaces, you will also need to install FreeSurfer.

Installing MNE-Python with core dependencies#

If you only need MNE-Python’s core functionality, which includes 2D plotting (but does not support 3D visualization), install via pip:

$ pip install mne

or via conda:

$ conda create --channel=conda-forge --strict-channel-priority --name=mne mne-base

This will create a new conda environment called mne (you can adjust this by passing a different name via --name).

This minimal installation requires only a few dependencies. If you need additional functionality later on, you can install individual packages as needed.

Installing MNE-Python with HDF5 support#

If you plan to use MNE-Python’s functions that require HDF5 I/O (this includes mne.io.read_raw_eeglab(), mne.SourceMorph.save(), and others), you should run via pip:

$ pip install "mne[hdf5]"

or via conda:

$ conda create --override-channels --channel=conda-forge --name=mne mne-base h5io h5py pymatreader

This will create a new conda environment called mne (you can adjust this by passing a different name via --name).

If you have already installed MNE-Python with core dependencies (e.g. via pip install mne), you can install these two packages to unlock HDF5 support:

$ pip install h5io pymatreader

Installing MNE-Python for other scenarios#

The Advanced setup page has additional tips and tricks for special situations (servers, notebooks, CUDA, installing the development version, etc). The Contributing guide has additional installation instructions for (future) contributors to MNE-Python (e.g, extra dependencies for running our tests and building our documentation).

Python IDE integration#

Most users find it convenient to write and run their code in an Integrated Development Environment (IDE). Some popular choices for scientific Python development are:

  • Visual Studio Code (often shortened to “VS Code” or “vscode”) is a development-focused text editor that supports many programming languages in addition to Python, includes an integrated terminal console, and has a rich extension ecosystem. Installing Microsoft’s Python Extension is enough to get most Python users up and running. VS Code is free and open-source.

  • Spyder is a free and open-source IDE developed by and for scientists who use Python. It can be installed via a standalone Spyder installer. To avoid dependency conflicts with Spyder, you should install mne in a separate environment, as explained in previous sections or using our dedicated installer. Then, instruct Spyder to use the MNE-Python interpreter by opening Spyder and navigating to Tools > Preferences > Python Interpreter > Use the following interpreter.

  • PyCharm is an IDE specifically for Python development that provides an all-in-one solution (no extension packages needed). PyCharm comes in a free and open-source Community edition as well as a paid Professional edition.

For these IDEs, you’ll need to provide the path to the Python interpreter you want it to use. If you’re using the MNE-Python installers, on Linux and macOS opening the Prompt will display several lines of information, including a line that will read something like:

Using Python: /some/directory/mne-python_1.7.1_0/bin/python

Altertatively (or on Windows), you can find that path by opening the Python interpreter you want to use (e.g., the one from the MNE-Python installer, or a conda environment that you have activated) and running:

>>> import sys
>>> print(sys.executable)

This should print something like C:\Program Files\MNE-Python\1.7.0_0\bin\python.exe (Windows) or /Users/user/Applications/MNE-Python/1.7.0_0/.mne-python/bin/python (macOS).

For Spyder, if the console cannot start because spyder-kernels is missing, install the required version in the conda environment. For example, with the environment you want to use activated, run conda install spyder-kernels.

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