[F] A2 pyta warnings

assignments/A2/a2_part2.py

@@ -205,13 +205,13 @@ def part2_runner(d: int, n: int, white_greedy: bool) -> None:
 
 
 if __name__ == '__main__':
-    # import python_ta
-    # python_ta.check_all(config={
-    #     'max-line-length': 100,
-    #     'max-nested-blocks': 4,
-    #     'disable': ['E1136'],
-    #     'extra-imports': ['random', 'a2_minichess', 'a2_game_tree']
-    # })
+    import python_ta
+    python_ta.check_all(config={
+        'max-line-length': 100,
+        'max-nested-blocks': 4,
+        'disable': ['E1136'],
+        'extra-imports': ['random', 'a2_minichess', 'a2_game_tree']
+    })
 
     # Sample call to part2_runner (you can change this, just keep it in the main block!)
     part2_runner(5, 50, True)

assignments/A2/a2_part3.py

@@ -54,7 +54,7 @@ class ExploringPlayer(a2_minichess.Player):
             self._game_tree = self._game_tree.find_subtree_by_move(previous_move)
 
         # Tree has been explored, make a random choice
-        if self._game_tree is None or len(self._game_tree.get_subtrees()) == 0 :
+        if self._game_tree is None or len(self._game_tree.get_subtrees()) == 0:
             move = random.choice(game.get_valid_moves())
 
         # "If the random number is < p, the player chooses a random move from among all valid moves
@@ -119,6 +119,7 @@ def run_learning_algorithm(exploration_probabilities: list[float],
                                             a2_minichess.RandomPlayer())
         # After the game, insert move sequence with white win probability
         game_tree.insert_move_sequence(seq, float(winner == 'White'))
+        results_so_far.append(winner)
         # Print progress
         print(f'Winner: {winner}')