SIENTIAPDE-1645: Refactor temporary directory cleanup activity by extracting processing and deletion logic into dedicated helper methods. Update train_test_split to use a local numpy.random generator for improved reproducibility. Remove an unnecessary else: pass block.

model_manager/utils/repository/data_manager_repository.py

@@ -42,15 +42,13 @@ def train_test_split(
     random_state: int | None = None,
     shuffle: bool = True,
 ) -> tuple[pd.DataFrame, pd.DataFrame]:
-    # 1. Definir a semente (seed) para reprodutibilidade
-    if random_state is not None:
-        np.random.seed(random_state)
-
     # 2. Gerar índices e embaralhar se necessário
     indices = np.arange(len(data))
 
     if shuffle:
-        np.random.shuffle(indices)
+        # 1. Generator local (em vez do estado global np.random) para reprodutibilidade
+        rng = np.random.default_rng(random_state)
+        rng.shuffle(indices)
 
     # 3. Calcular o ponto de corte (split point)
     # Cálculo: N_treino = tamanho_total * proporcao_treino