updated data saving as spec was not clear

src/main.py

@@ -27,6 +27,39 @@ def handleDataset(ds):
         handleTrain(ds)
     elif i =='a':
         handlePredict(ds)
+    elif i=='c':
+        internal(ds)
+
+def internal(ds):
+    print(f"Predicting {ds} with model")
+
+    root = Path(__file__).parent.parent
+    path = root / "models" / datasets[ds]
+
+    files = path.glob('*')
+
+    print("Available predictors: ")
+    for i,val in enumerate(files):
+        print(f"[{i:2<}] {val}")
+    print("[q] Quit")
+
+    i = input()
+    if i == 'q':
+        exit()
+
+    root = Path(__file__).parent.parent
+    testing = root / "resources" / "TestingData{}.csv".format("Multi" if ds =='b' else "Binary")
+    training = root / "resources" / "TrainingData{}.csv".format("Multi" if ds =='b' else "Binary")
+    testingData = read_csv(testing, header=None)
+    trainingData = read_csv(training, header=None)
+
+    x = list(path.glob('*'))
+    f = x[int(i)]
+    predictor = TabularPredictor.load(path=f.absolute().as_posix())
+
+    n = predictor.leaderboard()
+    print(n["model"].values.tolist())
+
 
 def handlePredict(ds):
     print(f"Predicting {ds} with model")
@@ -47,7 +80,6 @@ def handlePredict(ds):
     try:
         i = int(i)
         predict(ds, list(path.glob('*'))[i])
-
     except Exception:
         print()
 
@@ -66,9 +98,7 @@ def predict(ds, model):
     savePath = savePath.absolute().as_posix()
     print(f"Saving to {savePath}")
 
-    with open(savePath, "w") as f:
-        for i in a:
-            f.write(f"{i}\n")
+    testingData.to_csv(savePath, header=False, index=False)
 
 def handleTrain(ds):
     print("Starting training")
@@ -85,7 +115,7 @@ def handleTrain(ds):
                                  eval_metric="accuracy",
                                  path=file.absolute().as_posix()
                                  )
-    predictor.fit(train_data)
+    predictor.fit(train_data,verbosity=4)
     print("Finished predictor!")