Linting and Formatting: add a couple more Ruff checks

code_generation/code_gen.py

@@ -102,10 +102,7 @@ def render_dataset_class_maps(self, template_path: Path, data_path: Path, output
         # create list
         all_map = {}
         for dataset in dataset_meta_data:
-            if dataset.is_template:
-                prefixes = ["sym_", "asym_"]
-            else:
-                prefixes = [""]
+            prefixes = ["sym_", "asym_"] if dataset.is_template else [""]
             for prefix in prefixes:
                 all_components = {}
                 for component in dataset.components:

code_generation/templates/src/power_grid_model/_core/dataset_class_maps.py.jinja

@@ -25,7 +25,7 @@ class _MetaEnum(EnumMeta):
         Returns:
             bool: True if the member is part of the Enum, False otherwise.
         """
-        return member in cls.__members__.keys()
+        return member in cls.__members__
 
 
 class DatasetType(str, Enum, metaclass=_MetaEnum):

pyproject.toml

@@ -113,8 +113,8 @@ select = [
     "FURB",
     "FLY",
     "SLOT",
+    "NPY",
 ]
-ignore = ["SIM108", "SIM118", "SIM110", "SIM211"]
 
 [tool.ruff.lint.isort]
 # Imports that are imported using keyword "as" and are from the same source - are combined.

setup.py

@@ -76,10 +76,7 @@ def get_tag(self):
 class MyBuildExt(build_ext):
     def build_extensions(self):
         if not if_win:
-            if "CXX" in os.environ:
-                cxx = os.environ["CXX"]
-            else:
-                cxx = self.compiler.compiler_cxx[0]
+            cxx = os.environ["CXX"] if "CXX" in os.environ else self.compiler.compiler_cxx[0]
             # check setuptools has an update change in the version 72.2 about cxx compiler options
             # to be compatible with both version, we check if compiler_so_cxx exists
             if not hasattr(self.compiler, "compiler_so_cxx"):
@@ -93,10 +90,7 @@ def build_extensions(self):
             linker_so_cxx[0] = cxx
             self.compiler.compiler_cxx = [cxx]
             # add link time optimization
-            if "clang" in cxx:
-                lto_flag = "-flto=thin"
-            else:
-                lto_flag = "-flto"
+            lto_flag = "-flto=thin" if "clang" in cxx else "-flto"
             compiler_so_cxx += [lto_flag]
             linker_so_cxx += [lto_flag]
             # remove debug and optimization flags

src/power_grid_model/_core/dataset_definitions.py

@@ -22,7 +22,7 @@ def __contains__(cls, member):
         Returns:
             bool: True if the member is part of the Enum, False otherwise.
         """
-        return member in cls.__members__.keys()
+        return member in cls.__members__
 
 
 class DatasetType(str, Enum, metaclass=_MetaEnum):

src/power_grid_model/_core/power_grid_core.py

@@ -126,10 +126,7 @@ def _load_core() -> CDLL:
 
     """
     # first try to find the DLL local
-    if platform.system() == "Windows":
-        dll_file = "_power_grid_core.dll"
-    else:
-        dll_file = "_power_grid_core.so"
+    dll_file = "_power_grid_core.dll" if platform.system() == "Windows" else "_power_grid_core.so"
     dll_path = Path(__file__).parent / dll_file
 
     # if local DLL is not found, try to find the DLL from conda environment
@@ -192,10 +189,7 @@ def make_c_binding(func: Callable):
 
     # binding function
     def cbind_func(self, *args, **kwargs):
-        if "destroy" in name:
-            c_inputs = []
-        else:
-            c_inputs = [self._handle]
+        c_inputs = [] if "destroy" in name else [self._handle]
         args = chain(args, (kwargs[key] for key in py_argnames[len(args) :]))
         for arg in args:
             if isinstance(arg, str):

src/power_grid_model/_core/power_grid_model.py

@@ -189,10 +189,7 @@ def _get_output_component_count(self, calculation_type: CalculationType):
         }.get(calculation_type, [])
 
         def include_type(component_type: ComponentType):
-            for exclude_type in exclude_types:
-                if exclude_type.value in component_type.value:
-                    return False
-            return True
+            return all(exclude_type.value not in component_type.value for exclude_type in exclude_types)
 
         return {ComponentType[k]: v for k, v in self.all_component_count.items() if include_type(k)}
 

src/power_grid_model/_core/utils.py

@@ -651,10 +651,8 @@ def _extract_columnar_data(
     """
     not_columnar_data_message = "Expected columnar data"
 
-    if is_batch is not None:
-        allowed_dims = [2, 3] if is_batch else [1, 2]
-    else:
-        allowed_dims = [1, 2, 3]
+    if_is_batch = [2, 3] if is_batch else [1, 2]
+    allowed_dims = (if_is_batch) if is_batch is not None else [1, 2, 3]
 
     sub_data = data["data"] if is_sparse(data) else data
 
@@ -683,10 +681,8 @@ def _extract_row_based_data(
     Returns:
         SingleArray | DenseBatchArray: the contents of row based data
     """
-    if is_batch is not None:
-        allowed_dims = [2] if is_batch else [1]
-    else:
-        allowed_dims = [1, 2]
+    if_is_batch = [2] if is_batch else [1]
+    allowed_dims = if_is_batch if is_batch is not None else [1, 2]
 
     sub_data = data["data"] if is_sparse(data) else data
 

src/power_grid_model/validation/_rules.py

@@ -892,10 +892,7 @@ def none_missing(data: SingleDataset, component: ComponentType, fields: str | li
         fields = [fields]
     for field in fields:
         nan = _nan_type(component, field)
-        if np.isnan(nan):
-            invalid = np.isnan(data[component][field])
-        else:
-            invalid = np.equal(data[component][field], nan)
+        invalid = np.isnan(data[component][field]) if np.isnan(nan) else np.equal(data[component][field], nan)
 
         if invalid.any():
             # handle both symmetric and asymmetric values

src/power_grid_model/validation/utils.py

@@ -101,7 +101,7 @@ def _update_input_data(input_data: SingleDataset, update_data: SingleDataset):
     """
 
     merged_data = {component: array.copy() for component, array in input_data.items()}
-    for component in update_data.keys():
+    for component in update_data:
         _update_component_data(component, merged_data[component], update_data[component])
     return merged_data
 
@@ -140,10 +140,7 @@ def _update_component_array_data(
         if field == "id":
             continue
         nan = _nan_type(component, field, DatasetType.update)
-        if np.isnan(nan):
-            mask = ~np.isnan(update_data[field])
-        else:
-            mask = np.not_equal(update_data[field], nan)
+        mask = ~np.isnan(update_data[field]) if np.isnan(nan) else np.not_equal(update_data[field], nan)
 
         if mask.ndim == 2:
             for phase in range(mask.shape[1]):

tests/unit/test_0Z_model_validation.py

@@ -122,7 +122,8 @@ def test_single_validation(
     # test get indexer
     for component_name, input_array in case_data["input"].items():
         ids_array = input_array["id"].copy()
-        np.random.shuffle(ids_array)
+        rng = np.random.default_rng(3)
+        rng.shuffle(ids_array)
         indexer_array = model.get_indexer(component_name, ids_array)
         # check
         assert np.all(input_array["id"][indexer_array] == ids_array)

tests/unit/test_data_handling.py

@@ -123,7 +123,7 @@ def test_create_output_data(output_component_types, expected_fns, batch_size):
         output_component_types=output_component_types,
         output_type=DT.sym_output,
         all_component_count=all_component_count,
-        is_batch=False if batch_size == 1 else True,
+        is_batch=batch_size != 1,
         batch_size=batch_size,
     )
 

tests/unit/test_internal_utils.py

@@ -855,7 +855,7 @@ def row_data(request):
 def compare_row_data(actual_row_data, desired_row_data):
     assert actual_row_data.keys() == desired_row_data.keys()
 
-    for comp_name in actual_row_data.keys():
+    for comp_name in actual_row_data:
         actual_component = actual_row_data[comp_name]
         desired_component = desired_row_data[comp_name]
         if is_sparse(actual_component):

tests/unit/test_meta_data.py

@@ -59,15 +59,9 @@ def test_sensor_meta_data():
             assert "id" in attr_names
             # check specific attributes
             if "voltage" in sensor:
-                if "output" in meta_type:
-                    expected_attrs = output_voltage
-                else:
-                    expected_attrs = input_voltage
+                expected_attrs = output_voltage if "output" in meta_type else input_voltage
             else:
-                if "output" in meta_type:
-                    expected_attrs = output_power
-                else:
-                    expected_attrs = input_power
+                expected_attrs = output_power if "output" in meta_type else input_power
 
             for name in expected_attrs:
                 assert name in attr_names

tests/unit/test_serialization.py

@@ -512,7 +512,7 @@ def assert_individual_data_entry(serialized_dataset, data_filter, component, ser
                     if is_attribute_filtered_out(data_filter, component, attr):
                         assert attr not in deserialized_output
                         continue
-                    assert attr in deserialized_output.keys()
+                    assert attr in deserialized_output
                     assert_almost_equal(
                         deserialized_output[attr][comp_idx],
                         serialized_input[comp_idx][attr],
@@ -530,7 +530,7 @@ def assert_individual_data_entry(serialized_dataset, data_filter, component, ser
                     if is_attribute_filtered_out(data_filter, component, attr):
                         assert attr not in deserialized_output
                         continue
-                    assert attr in deserialized_output.keys()
+                    assert attr in deserialized_output
                     assert_almost_equal(
                         deserialized_output[attr][comp_idx],
                         serialized_input[comp_idx][attr_idx],

tests/unit/utils.py

@@ -180,10 +180,7 @@ def _add_cases(case_dir: Path, calculation_type: str, **kwargs):
 
 
 def pytest_cases(get_batch_cases: bool = False, data_dir: str | None = None, test_cases: list[str] | None = None):
-    if data_dir is not None:
-        relevant_calculations = [data_dir]
-    else:
-        relevant_calculations = ["power_flow", "state_estimation", "short_circuit"]
+    relevant_calculations = [data_dir] if data_dir is not None else ["power_flow", "state_estimation", "short_circuit"]
 
     for calculation_type in relevant_calculations:
         test_case_paths = get_test_case_paths(calculation_type=calculation_type, test_cases=test_cases)