if len(new_test_frame) > 0:
test_frame = test_frame.append(new_test_frame)
else:
logger.info("Test frame has length 0")
// write out the training and test files
write_frame(train_frame, directory, train_file, extension, separator)
write_frame(test_frame, directory, test_file, extension, separator)
// run the model pipeline
After Change
if len(new_train_frame) > 0:
train_frame = train_frame.append(new_train_frame)
else:
raise Exception("Training frame has length 0. Adjust training date.")
new_test_frame = df.loc[df.date >= predict_date]
if len(new_test_frame) > 0:
test_frame = test_frame.append(new_test_frame)
else:
