This step is optional. Python can be used in a number of eddy covariance data packages (e.g., some of these flux data post-processing and QA/QC resources).
Python is also necessary for those interested in running high-frequency data reprocessing described in this EddyPro API or gap-filling fluxes using the approach described in the paper "Gap-filling eddy covariance methane fluxes: Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands".
However, you can skip this step if you do no plan to use any of the resources above.