Review comment about unpacking tuple returns of functions,

src/_gettsim/interface.py

@@ -132,11 +132,12 @@ def compute_taxes_and_transfers(  # noqa: PLR0913
         input_structure=input_structure,
         check_minimal_specification=check_minimal_specification,
     ).nodes
-    # Select functions that are nodes of the DAG.
-    _, necessary_functions = _filter_tree_by_name_list(functions_not_overridden, nodes)
-    # Round and partial parameters into functions.
+
+    # Round and partial parameters into functions that are nodes in the DAG.
     processed_functions = _round_and_partial_parameters_to_functions(
-        necessary_functions, environment.params, rounding
+        _filter_tree_by_name_list(functions_not_overridden, nodes)[1],
+        environment.params,
+        rounding,
     )
 
     # Input structure for final DAG.
@@ -189,7 +190,7 @@ def build_targets_tree(targets: NestedTargetDict | list[str] | str) -> NestedTar
     if isinstance(targets, str):
         targets = [targets]
 
-    flattened_targets, _ = tree_flatten(targets)
+    flattened_targets = tree_flatten(targets)[0]
     all_leafs_none = all(el is None for el in flattened_targets)
     all_leafs_str_or_list = all(isinstance(el, str | list) for el in flattened_targets)
 

src/_gettsim/visualization.py

@@ -92,10 +92,10 @@ def plot_dag(
         targets=targets,
         names_of_columns_in_data=names_of_columns_overriding_functions,
     )
-    functions_not_overridden, _ = _filter_tree_by_name_list(
+    functions_not_overridden = _filter_tree_by_name_list(
         tree=all_functions,
         qualified_names_list=names_of_columns_overriding_functions,
-    )
+    )[0]
 
     # Create parameter input structure.
     input_structure = dags.dag_tree.create_input_structure_tree(
@@ -112,11 +112,8 @@ def plot_dag(
         check_minimal_specification=check_minimal_specification,
     )
 
-    _, necessary_functions = _filter_tree_by_name_list(
-        functions_not_overridden, dag.nodes
-    )
     processed_functions = _round_and_partial_parameters_to_functions(
-        necessary_functions,
+        _filter_tree_by_name_list(functions_not_overridden, dag.nodes)[1],
         environment.params,
         rounding=False,
     )

src/_gettsim_tests/test_policy_environment.py

@@ -231,7 +231,7 @@ def test_convert_function_to_correct_type(tree, expected_module_name):
         _convert_function_to_correct_type,
         tree,
     )
-    func_list, _ = tree_flatten(funcs_with_correct_type)
+    func_list = tree_flatten(funcs_with_correct_type)[0]
     for func in func_list:
         assert func.module_name == expected_module_name
         assert isinstance(func, PolicyFunction)

src/_gettsim_tests/test_rounding.py

@@ -260,9 +260,9 @@ def test_decorator_for_all_functions_with_rounding_spec():
     # addressed.
     time_dependent_functions = {}
     for year in range(1990, 2023):
-        year_functions, _ = tree_flatten(
+        year_functions = tree_flatten(
             load_functions_tree_for_date(datetime.date(year=year, month=1, day=1))
-        )
+        )[0]
         function_name_to_name_in_dag_dict = {
             func.function.__name__: func.name_in_dag for func in year_functions
         }