# How to Install neurosynchro¶

Neurosynchro is a pure-Python package, so it is not difficult to install by itself. However, it requires heavyweight Python libraries like Keras, which contain a lot of compiled code, so the recommended means of installation is though an Anaconda Python system.

Pre-built packages of neurosynchro are available through conda-forge, a community-based project that uses the conda package manager. If you are using a conda-based Python installation, the quickest path to getting neurosynchro going is to run the following commands in your terminal:

$conda config --add channels conda-forge$ conda install neurosynchro


Note, however, that conda-forge provides rebuilds of virtually every package in the stock Anaconda system, and this installation method will configure your system to prefer them. You may suddenly see lots of package version changes related to this. You can install neurosynchro without committing to using conda-forge for everything by skipping the conda config command and instead running:

\$ conda install -c conda-forge neurosynchro


In the author’s experience, however, it is better to go the first route. This latter route won’t get package updates from conda-forge and can lead to vexing dependency mismatches further down the line.

Finally, it is also possible to try to install neurosynchro through pip in the standard fashion, with pip install neurosynchro. However, as mentioned above, this can easily get hairy if one of the big binary dependencies isn’t available. See neurosynchro’s requirements list for a list of what you’ll need.