Updating MNE-Python#

If you want to update MNE-Python to a newer version, there are a few different options, depending on how you originally installed it.


To update via the MNE-Python installers, simply download and run the latest installer for your platform. MNE-Python will be installed in parallel to your existing installation, which you may uninstall or delete if you don’t need it anymore.

If you’re not using the MNE-Python installers, keep reading.


Before performing package upgrade operations, check to make sure that the environment you wish to modify has been activated (and if not, call conda activate name_of_environment first).

Upgrading MNE-Python only#

If you wish to update MNE-Python only and leave other packages in their current state, you can usually safely do this with pip, even if you originally installed via conda. With the mne environment active, do:

$ pip install -U mne

Upgrading all packages#

Generally speaking, if you want to upgrade your whole software stack including all the dependencies, the best approach is to re-create it as a new virtual environment, because neither conda nor pip are fool-proof at making sure all packages remain compatible with one another during upgrades.

Here we’ll demonstrate renaming the old environment first, as a safety measure. We’ll assume that the existing environment is called mne and you want to rename the old one so that the new, upgraded environment can be called mne instead. Unfortunately conda doesn’t have a “rename” command so we’ll first clone the old one with a new name (old_mne), then delete the original, then create the new, updated environment re-using the original name. In the first step we’ll also use conda in --offline mode so that it uses cached copies of all the packages instead of re-downloading them.

$ conda create --name old_mne --clone mne --offline  # copy with new name,
$ conda env remove --name mne --all                  # remove original,
$ conda create --name mne --channel conda-forge mne  # replace with updated


If you installed extra packages into your old mne environment, you’ll need to repeat that process after re-creating the updated environment. Comparing the output of conda list --name old_mne versus conda list --name mne will show you what is missing from the new environment. On Linux, you can automate that comparison like this:

$ diff <(conda list -n mne | cut -d " " -f 1 | sort) <(conda list -n old_mne | cut -d " " -f 1 | sort) | grep "^>" | cut -d " " -f 2

Upgrading to the development version#

Sometimes, new features or bugfixes become available that are important to your research and you just can’t wait for the next official release of MNE-Python to start taking advantage of them. In such cases, you can use pip to install the development version of MNE-Python:

$ pip install -U --no-deps https://github.com/mne-tools/mne-python/archive/main.zip