--- a/generalized_linear.xml	Tue Jul 10 03:13:00 2018 -0400
+++ b/generalized_linear.xml	Fri Jul 13 03:56:33 2018 -0400
@@ -26,7 +26,8 @@
 @GET_X_y_FUNCTION@
 
 input_json_path = sys.argv[1]
-params = json.load(open(input_json_path, "r"))
+with open(input_json_path, "r") as param_handler:
+    params = json.load(param_handler)
 
 #if $selected_tasks.selected_task == "train":
 
@@ -38,10 +39,12 @@
 my_class = getattr(sklearn.linear_model, algorithm)
 estimator = my_class(**options)
 estimator.fit(X,y)
-pickle.dump(estimator,open("$outfile_fit", 'w+'), pickle.HIGHEST_PROTOCOL)
+with open("$outfile_fit", 'wb') as out_handler:
+    pickle.dump(estimator, out_handler, pickle.HIGHEST_PROTOCOL)
 
 #else:
-classifier_object = pickle.load(open("$selected_tasks.infile_model", 'r'))
+with open("$selected_tasks.infile_model", 'rb') as model_handler:
+    classifier_object = pickle.load(model_handler)
 data = pandas.read_csv("$selected_tasks.infile_data", sep='\t', header=None, index_col=None, parse_dates=True, encoding=None, tupleize_cols=False )
 prediction = classifier_object.predict(data)
 prediction_df = pandas.DataFrame(prediction, columns=["predicted"])