PowerGridModel · mgovers · Jun 10, 2025 · May 14, 2025 · May 14, 2025 · May 19, 2025
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
@@ -13,6 +13,7 @@ repos:
     hooks:
       # Run the linter.
       - id: ruff-check
+        args: [ --fix ]
       # Run the formatter.
       - id: ruff-format
   - repo: https://github.com/pre-commit/mirrors-mypy

diff --git a/code_generation/templates/src/power_grid_model/_core/dataset_class_maps.py.jinja b/code_generation/templates/src/power_grid_model/_core/dataset_class_maps.py.jinja
@@ -14,8 +14,6 @@ from typing import Any, Mapping, TypeAlias, TypeVar
 
 # fmt: off
 
-# pylint: disable=invalid-name
-
 class _MetaEnum(EnumMeta):
     def __contains__(cls, member):
         """
@@ -58,8 +56,6 @@ class ComponentType(str, Enum, metaclass=_MetaEnum):
 {%- endfor %}
 
 
-# pylint: enable=invalid-name
-
 DatasetTypeLike: TypeAlias = DatasetType | str
 DatasetTypeVar = TypeVar("DatasetTypeVar", bound=DatasetTypeLike)  # helper used for type deduction
 

diff --git a/docs/conf.py b/docs/conf.py
@@ -15,7 +15,7 @@
 
 # -- Setup
 
-import os
+import os  # noqa: E402
 
 # Fix linking in github and rtd
 link_head_gh = "https://github.com/PowerGridModel/power-grid-model/"

diff --git a/docs/examples/Asymmetric Calculation Example.ipynb b/docs/examples/Asymmetric Calculation Example.ipynb
@@ -48,9 +48,16 @@
     "import numpy as np\n",
     "import pandas as pd\n",
     "\n",
-    "from power_grid_model import LoadGenType, ComponentType, DatasetType\n",
-    "from power_grid_model import PowerGridModel, CalculationMethod, CalculationType, MeasuredTerminalType\n",
-    "from power_grid_model import initialize_array"
+    "from power_grid_model import (\n",
+    "    CalculationMethod,\n",
+    "    CalculationType,\n",
+    "    ComponentType,\n",
+    "    DatasetType,\n",
+    "    LoadGenType,\n",
+    "    MeasuredTerminalType,\n",
+    "    PowerGridModel,\n",
+    "    initialize_array,\n",
+    ")"
    ]
   },
   {

diff --git a/docs/examples/Asymmetric Line.ipynb b/docs/examples/Asymmetric Line.ipynb
@@ -40,9 +40,16 @@
     "import numpy as np\n",
     "import pandas as pd\n",
     "\n",
-    "from power_grid_model import LoadGenType, DatasetType, ComponentType\n",
-    "from power_grid_model import PowerGridModel, CalculationMethod, CalculationType, MeasuredTerminalType\n",
-    "from power_grid_model import initialize_array"
+    "from power_grid_model import (\n",
+    "    CalculationMethod,\n",
+    "    CalculationType,\n",
+    "    ComponentType,\n",
+    "    DatasetType,\n",
+    "    LoadGenType,\n",
+    "    MeasuredTerminalType,\n",
+    "    PowerGridModel,\n",
+    "    initialize_array,\n",
+    ")"
    ]
   },
   {
@@ -329,7 +336,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.0"
+   "version": "3.13.3"
   }
  },
  "nbformat": 4,

diff --git a/docs/examples/Generic Branch Example.ipynb b/docs/examples/Generic Branch Example.ipynb
@@ -129,7 +129,6 @@
     }
    ],
    "source": [
-    "import numpy as np\n",
     "import warnings\n",
     "\n",
     "with warnings.catch_warnings():\n",
@@ -138,9 +137,15 @@
     "\n",
     "import pandas as pd\n",
     "\n",
-    "from power_grid_model import LoadGenType, ComponentType, DatasetType\n",
-    "from power_grid_model import PowerGridModel, CalculationMethod, CalculationType\n",
-    "from power_grid_model import initialize_array\n",
+    "from power_grid_model import (\n",
+    "    CalculationMethod,\n",
+    "    CalculationType,\n",
+    "    ComponentType,\n",
+    "    DatasetType,\n",
+    "    LoadGenType,\n",
+    "    PowerGridModel,\n",
+    "    initialize_array,\n",
+    ")\n",
     "from power_grid_model.validation import assert_valid_input_data\n",
     "\n",
     "# network\n",
@@ -242,9 +247,17 @@
     "    symmetric=True, error_tolerance=1e-8, max_iterations=20, calculation_method=CalculationMethod.newton_raphson\n",
     ")\n",
     "\n",
-    "e3 = lambda x: x / 1e3\n",
-    "e6 = lambda x: x / 1e6\n",
-    "percent = lambda x: x * 100\n",
+    "\n",
+    "def e3(x):\n",
+    "    return x / 1e3\n",
+    "\n",
+    "\n",
+    "def e6(x):\n",
+    "    return x / 1e6\n",
+    "\n",
+    "\n",
+    "def percent(x):\n",
+    "    return x * 100\n",
     "\n",
     "\n",
     "def print_node_input(input_data):\n",
@@ -519,18 +532,22 @@
    ],
    "source": [
     "# some basic imports\n",
-    "import numpy as np\n",
     "import warnings\n",
     "\n",
     "with warnings.catch_warnings():\n",
     "    warnings.simplefilter(\"ignore\", category=DeprecationWarning)\n",
     "    # Suppress warning about pyarrow as future required dependency\n",
     "\n",
-    "import pandas as pd\n",
     "\n",
-    "from power_grid_model import LoadGenType, ComponentType, DatasetType\n",
-    "from power_grid_model import PowerGridModel, CalculationMethod, CalculationType\n",
-    "from power_grid_model import initialize_array\n",
+    "from power_grid_model import (\n",
+    "    CalculationMethod,\n",
+    "    CalculationType,\n",
+    "    ComponentType,\n",
+    "    DatasetType,\n",
+    "    LoadGenType,\n",
+    "    PowerGridModel,\n",
+    "    initialize_array,\n",
+    ")\n",
     "from power_grid_model.validation import assert_valid_input_data\n",
     "\n",
     "# network\n",
@@ -621,9 +638,17 @@
     "pd.set_option(\"display.max_columns\", None)\n",
     "pd.set_option(\"display.max_colwidth\", None)\n",
     "\n",
-    "e3 = lambda x: x / 1e3\n",
-    "e6 = lambda x: x / 1e6\n",
-    "percent = lambda x: x * 100\n",
+    "\n",
+    "def e3(x):\n",
+    "    return x / 1e3\n",
+    "\n",
+    "\n",
+    "def e6(x):\n",
+    "    return x / 1e6\n",
+    "\n",
+    "\n",
+    "def percent(x):\n",
+    "    return x * 100\n",
     "\n",
     "\n",
     "def print_node_input(input_data):\n",
@@ -1039,7 +1064,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.13.0"
+   "version": "3.13.3"
   }
  },
  "nbformat": 4,

diff --git a/docs/examples/Make Test Dataset.ipynb b/docs/examples/Make Test Dataset.ipynb
@@ -163,9 +163,7 @@
     "import numpy as np\n",
     "import pandas as pd\n",
     "\n",
-    "from power_grid_model import LoadGenType, ComponentType, DatasetType\n",
-    "from power_grid_model import PowerGridModel\n",
-    "from power_grid_model import initialize_array\n",
+    "from power_grid_model import ComponentType, DatasetType, LoadGenType, PowerGridModel, initialize_array\n",
     "\n",
     "# network\n",
     "\n",
@@ -229,10 +227,11 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from power_grid_model.utils import json_serialize_to_file\n",
     "import tempfile\n",
     "from pathlib import Path\n",
     "\n",
+    "from power_grid_model.utils import json_serialize_to_file\n",
+    "\n",
     "temp_path = Path(tempfile.gettempdir())\n",
     "json_serialize_to_file(temp_path / \"input.json\", input_data)"
    ]

diff --git a/docs/examples/Power Flow Example.ipynb b/docs/examples/Power Flow Example.ipynb
@@ -47,9 +47,17 @@
     "import numpy as np\n",
     "import pandas as pd\n",
     "\n",
-    "from power_grid_model import LoadGenType, ComponentType, DatasetType, ComponentAttributeFilterOptions\n",
-    "from power_grid_model import PowerGridModel, CalculationMethod, CalculationType\n",
-    "from power_grid_model import initialize_array, attribute_dtype"
+    "from power_grid_model import (\n",
+    "    CalculationMethod,\n",
+    "    CalculationType,\n",
+    "    ComponentAttributeFilterOptions,\n",
+    "    ComponentType,\n",
+    "    DatasetType,\n",
+    "    LoadGenType,\n",
+    "    PowerGridModel,\n",
+    "    attribute_dtype,\n",
+    "    initialize_array,\n",
+    ")"
    ]
   },
   {
@@ -464,9 +472,12 @@
     "    max_iterations=20,\n",
     "    calculation_method=CalculationMethod.newton_raphson,\n",
     "    output_component_types={\n",
-    "        ComponentType.node: None,  # node output as row-based\n",
-    "        ComponentType.line: [\"id\", \"p_from\"],  # line output columns id and p_from\n",
-    "        ComponentType.sym_load: ComponentAttributeFilterOptions.everything,  # all sym_load attributes as columns\n",
+    "        # node output as row-based\n",
+    "        ComponentType.node: None,\n",
+    "        # line output columns id and p_from\n",
+    "        ComponentType.line: [\"id\", \"p_from\"],\n",
+    "        # all sym_load attributes as columns\n",
+    "        ComponentType.sym_load: ComponentAttributeFilterOptions.everything,\n",
     "    },\n",
     ")\n",
     "\n",
@@ -515,7 +526,8 @@
     "    error_tolerance=1e-8,\n",
     "    max_iterations=20,\n",
     "    calculation_method=CalculationMethod.newton_raphson,\n",
-    "    output_component_types=ComponentAttributeFilterOptions.everything,  # all attributes for all component types as columns\n",
+    "    # all attributes for all component types as columns\n",
+    "    output_component_types=ComponentAttributeFilterOptions.everything,\n",
     ")\n",
     "\n",
     "print(\"List of component types in result dataset\")\n",
@@ -1216,7 +1228,7 @@
     }
    ],
    "source": [
-    "from power_grid_model.errors import PowerGridError, ConflictVoltage\n",
+    "from power_grid_model.errors import ConflictVoltage, PowerGridError\n",
     "\n",
     "# node\n",
     "node_error = initialize_array(DatasetType.input, ComponentType.node, 2)\n",
@@ -1372,7 +1384,7 @@
       "\n",
       "Failed scenarios: [3 7]\n",
       "Succeeded scenarios: [0 1 2 4 5 6 8 9]\n",
-      "Error messages: ['The id cannot be found: 1000\\n', 'Iteration failed to converge after 20 iterations! Max deviation: 5.81174e+85, error tolerance: 1e-08.\\n']\n"
+      "Error messages: ['The id cannot be found: 1000\\n', 'Sparse matrix error, possibly singular matrix!\\nIf you get this error from state estimation, it might mean the system is not fully observable, i.e. not enough measurements.\\nIt might also mean that you are running into a corner case where PGM cannot resolve yet.See https://github.com/PowerGridModel/power-grid-model/issues/864.']\n"
      ]
     }
    ],
@@ -1403,16 +1415,16 @@
      "output_type": "stream",
      "text": [
       "Node data with invalid results\n",
-      "[[9.99401170e-001 9.92685785e-001 9.94521366e-001]\n",
-      " [9.99347687e-001 9.86226389e-001 9.89352855e-001]\n",
-      " [9.99288384e-001 9.79654011e-001 9.84095542e-001]\n",
-      " [3.94357132e+180 2.87518198e+161 2.04418455e+214]\n",
-      " [9.99151380e-001 9.66149483e-001 9.73298790e-001]\n",
-      " [9.99073166e-001 9.59205860e-001 9.67750710e-001]\n",
-      " [9.98988099e-001 9.52126208e-001 9.62096474e-001]\n",
-      " [0.00000000e+000 0.00000000e+000 0.00000000e+000]\n",
-      " [9.98796126e-001 9.37530046e-001 9.50447962e-001]\n",
-      " [9.98688504e-001 9.29997471e-001 9.44441670e-001]]\n",
+      "[[ 9.99401170e-001  9.92685785e-001  9.94521366e-001]\n",
+      " [ 9.99347687e-001  9.86226389e-001  9.89352855e-001]\n",
+      " [ 9.99288384e-001  9.79654011e-001  9.84095542e-001]\n",
+      " [-2.66881060e+116  2.33997016e-302  6.70346672e-198]\n",
+      " [ 9.99151380e-001  9.66149483e-001  9.73298790e-001]\n",
+      " [ 9.99073166e-001  9.59205860e-001  9.67750710e-001]\n",
+      " [ 9.98988099e-001  9.52126208e-001  9.62096474e-001]\n",
+      " [-2.44756775e+092  5.35663612e-256  1.91838796e-203]\n",
+      " [ 9.98796126e-001  9.37530046e-001  9.50447962e-001]\n",
+      " [ 9.98688504e-001  9.29997471e-001  9.44441670e-001]]\n",
       "Node data with only valid results\n",
       "[[0.99940117 0.99268579 0.99452137]\n",
       " [0.99934769 0.98622639 0.98935286]\n",
@@ -1469,7 +1481,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.13.0"
+   "version": "3.13.3"
   }
  },
  "nbformat": 4,

diff --git a/docs/examples/Serialization Example.ipynb b/docs/examples/Serialization Example.ipynb
@@ -23,10 +23,11 @@
    "outputs": [],
    "source": [
     "import json\n",
-    "from pandas import DataFrame\n",
     "import pprint\n",
     "\n",
-    "from power_grid_model import PowerGridModel, ComponentType, ComponentAttributeFilterOptions\n",
+    "from pandas import DataFrame\n",
+    "\n",
+    "from power_grid_model import ComponentAttributeFilterOptions, ComponentType, PowerGridModel\n",
     "from power_grid_model.utils import json_deserialize, json_serialize"
    ]
   },

diff --git a/docs/examples/Short Circuit Example.ipynb b/docs/examples/Short Circuit Example.ipynb
@@ -48,18 +48,19 @@
    "source": [
     "# some basic imports\n",
     "import numpy as np\n",
-    "import pandas as pd\n",
     "\n",
-    "from power_grid_model import LoadGenType, ComponentType, DatasetType\n",
     "from power_grid_model import (\n",
-    "    PowerGridModel,\n",
     "    CalculationMethod,\n",
     "    CalculationType,\n",
-    "    FaultType,\n",
+    "    ComponentType,\n",
+    "    DatasetType,\n",
     "    FaultPhase,\n",
+    "    FaultType,\n",
+    "    LoadGenType,\n",
+    "    PowerGridModel,\n",
     "    ShortCircuitVoltageScaling,\n",
-    ")\n",
-    "from power_grid_model import initialize_array"
+    "    initialize_array,\n",
+    ")"
    ]
   },
   {
@@ -337,7 +338,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.13.0"
+   "version": "3.13.3"
   }
  },
  "nbformat": 4,