From the manual: "You can use [Train] mode and WFO for training Python machine learning algorithms, f.i. a SVM or neural network. For this, send training data to Python at the end of every WFO cycle, and store the trained models in files for later use in the [Test] or [Trade] session, similar to the neural function for R. A neural function for Python will be provided in a future Zorro version. "

I am trying to understand the best way to send the training data to Python at the end of the training period.

Would I append the signals for each bar to some file on every loop of run()? Or is there some way obtain the entire signals data set over the entire training run to be passed on to Python?