Import tensorflow

WebServer/AIPython/main.py

@@ -1,25 +1,9 @@
-from datetime import date, datetime
-from datapuller import DataPuller
-from database import DataBase
+import tensorflow as tf
+import keras
+from keras.layers import Dense, Flatten, Conv2D
+from keras import Model
 
 def main():
-
-    # Load the database object
-    db = DataBase()
-
-    # If we havent already pulled the stock data today
-    if db.GetKey("LastRun") != str(date.today()):
-        # Update the data store in the data folder
-        DataPuller.pull()
-        # Update the last run to today
-        db.SetKey("LastRun", str(date.today()))
-
-    # Lazy Load in the AI algorithms so yfinance works properly
-    import tensorflow as tf
-    import keras
-    from keras.layers import Dense, Flatten, Conv2D
-    from keras import Model
-
     mnist = keras.datasets.mnist
 
     (x_train, y_train), (x_test, y_test) = mnist.load_data()
@@ -33,7 +17,4 @@ def main():
     train_ds = tf.data.Dataset.from_tensor_slices(
         (x_train, y_train)).shuffle(10000).batch(32)
 
-    test_ds = tf.data.Dataset.from_tensor_slices((x_test, y_test)).batch(32)
-
-if __name__ == "__main__":
-    main()
+    test_ds = tf.data.Dataset.from_tensor_slices((x_test, y_test)).batch(32)