# import pandas as pd
# from sklearn.metrics import accuracy_score, precision_recall_fscore_support, mean_squared_error
# from math import sqrt
# import sys
#
# data = pd.read_csv('powerlifting_test_predictions.csv')
# y_pred = data['Predictions']
# y_test = data['Actual']
# y_test_binary = (y_test >= 3).astype(int)
#
# build_number = sys.argv[1]
#
# accuracy = accuracy_score(y_test_binary, y_pred.round())
# precision, recall, f1, _ = precision_recall_fscore_support(y_test_binary, y_pred.round(), average='micro')
# rmse = sqrt(mean_squared_error(y_test, y_pred))
#
# print(f'Accuracy: {accuracy}')
# print(f'Micro-avg Precision: {precision}')
# print(f'Micro-avg Recall: {recall}')
# print(f'F1 Score: {f1}')
# print(f'RMSE: {rmse}')

with open(r"metrics.txt", "a") as f:
    f.write(f"{123},{1}\n")