evaluation appends to csv

Dockerfile

@@ -13,6 +13,7 @@ RUN pip3 install torch
 RUN pip3 install seaborn
 RUN pip3 install torchvision
 RUN pip3 install sklearn
+RUN pip3 install csv
 # RUN python3 -m pip install kaggle
 RUN python3 -m pip install pandas
 RUN pip3 install matplotlib

Jenkinsfile_evaluation

@@ -37,8 +37,8 @@ pipeline {
                 copyArtifacts projectName: 's444354-create-dataset'
                 copyArtifacts projectName: 's444354-training/$TRAINING_BRANCH'
                 sh 'python3 ./evaluation.py'
-                archiveArtifacts 'TRAIN_winequality-red.csv'
+                archiveArtifacts 'eval.csv'
-                sh "ls -la"
+               
             }
         }
     }

evaluation.py

@@ -2,6 +2,7 @@ import pandas as pd
 import re
 from sklearn import metrics
 import numpy as np
+import csv 
 
 f = open("result.txt", "r")
 
@@ -16,6 +17,13 @@ for x in f:
 
     list_result.append(result)
     list_predicted.append(predicted)
-print("MAE: ", metrics.mean_absolute_error(list_result, list_predicted))
+metrics = metrics.mean_absolute_error(list_result, list_predicted),  metrics.mean_squared_error(list_result, list_predicted),np.sqrt(metrics.mean_absolute_error(list_result, list_predicted))
-print("MSE: ",metrics.mean_squared_error(list_result, list_predicted))
+print("MAE: ", metrics[0])
-print("RMSE: ",np.sqrt(metrics.mean_absolute_error(list_result, list_predicted)))
+print("MSE: ",metrics[1])
+print("RMSE: ",metrics[2])
+
+
+
+with open('eval.csv', 'a', newline='') as f:
+    writer = csv.writer(f)
+    writer.writerow((metrics[0],metrics[1], metrics[2]))