Installing pySNOW

The first step (suggested) is to create a python environment for installation to avoid confilcts with previously installed libraries or different versions of required modules, e.g.:

LinuxMacWindows

python3 -m venv snowenv
source snowenv/bin/activate

python3 -m venv snowenv
source snowenv/bin/activate

python -m venv snowenv
.\snowenv\Scripts\activate

Note that pySNOW requires a version of python >= 3.9, however users can optionally try to change this in the pyproject.toml file, this however has not been tried and might result in unwanted behaviour. Going below python 3 is sure to cause issues due to syntax differences.

After creating and activating the virtual environment you can clone the repository (or download the code as a zip and uncompressing it in any deisred location):

git clone https://github.com/nanoMLMS/pySNOW.git pysnow && cd pysnow

From here you can install the package by running:

pip install .

Automated tests can be run using pytest with the following command:

pytest .

from the pySNOW folder.

Requirments for pySNOW are NumPy and SciPy, which are automatically installed with pySNOW. Additional optional dependencies is tqdm for progress bars to check progress of long computations