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.