dependencies compatibility pandapower 2 and 3 and numpy 1 and 2

dependencies checked: pandapower==3 numpy==1.26.4 pandas==2.2.3 scipy==1.13.1

Signed-off-by: Martijn Govers <[email protected]>

dependencies checked: pandapower==3 numpy>=2 pandas==2.2.3 scipy==1.13.1

Signed-off-by: Martijn Govers <[email protected]>

dependencies checked: pandapower==2.14.11 numpy==1.26.4 pandas==2.2.3 scipy==1.13.1

Signed-off-by: Martijn Govers <[email protected]>

Author: mgovers

pyproject.toml

@@ -40,7 +40,7 @@ dynamic = ["version"]
 
 [project.optional-dependencies]
 dev = [
-    "pandapower>2.11.1, <3.0",
+    "pandapower>2.11.1",
     "pre-commit",
     "pylint",
     "pytest",

src/power_grid_model_io/converters/pandapower_converter.py

@@ -598,7 +598,7 @@ def _create_pgm_input_sym_loads(self):
         if pp_loads.empty:
             return
 
-        if self._get_pp_attr("load", "type", expected_type="O", default=None).any() == "delta":
+        if np.any(self._get_pp_attr("load", "type", expected_type="O", default=None) == "delta"):
             raise NotImplementedError("Delta loads are not implemented, only wye loads are supported in PGM.")
 
         scaling = self._get_pp_attr("load", "scaling", expected_type="f8", default=1.0)
@@ -656,7 +656,7 @@ def _create_pgm_input_asym_loads(self):
         if pp_asym_loads.empty:
             return
 
-        if self._get_pp_attr("asymmetric_load", "type", expected_type="O", default=None).any() == "delta":
+        if np.any(self._get_pp_attr("asymmetric_load", "type", expected_type="O", default=None) == "delta"):
             raise NotImplementedError("Delta loads are not implemented, only wye loads are supported in PGM.")
 
         scaling = self._get_pp_attr("asymmetric_load", "scaling", expected_type="f8")

tests/unit/converters/test_pandapower_converter_input.py

@@ -2,13 +2,15 @@
 #
 # SPDX-License-Identifier: MPL-2.0
 
+from importlib import metadata
 from typing import Callable
 from unittest.mock import ANY, MagicMock, call, patch
 
 import numpy as np
 import pandapower as pp
 import pandas as pd
 import pytest
+from packaging import version
 from power_grid_model import Branch3Side, BranchSide, LoadGenType, WindingType, initialize_array
 
 from power_grid_model_io.converters.pandapower_converter import PandaPowerConverter
@@ -756,14 +758,19 @@ def test_create_pgm_input_transformers__tap_dependent_impedance() -> None:
     pp_net: pp.pandapowerNet = pp.create_empty_network()
     pp.create_bus(net=pp_net, vn_kv=0.0)
     args = [0, 0, 0, 0, 0, 0, 0, 0, 0]
-    pp.create_transformer_from_parameters(pp_net, *args, tap_dependent_impedance=True)
 
-    converter = PandaPowerConverter()
-    converter.pp_input_data = {k: v for k, v in pp_net.items() if isinstance(v, pd.DataFrame)}
+    if version.Version(metadata.version("pandapower")) >= version.Version("3"):
+        with pytest.deprecated_call():
+            pp.create_transformer_from_parameters(pp_net, *args, tap_dependent_impedance=True)
+    else:
+        pp.create_transformer_from_parameters(pp_net, *args, tap_dependent_impedance=True)
 
-    # Act/Assert
-    with pytest.raises(RuntimeError, match="not supported"):
-        converter._create_pgm_input_transformers()
+        converter = PandaPowerConverter()
+        converter.pp_input_data = {k: v for k, v in pp_net.items() if isinstance(v, pd.DataFrame)}
+
+        # Act/Assert
+        with pytest.raises(RuntimeError, match="not supported"):
+            converter._create_pgm_input_transformers()
 
 
 @patch("power_grid_model_io.converters.pandapower_converter.initialize_array")
@@ -1462,14 +1469,19 @@ def test_create_pgm_input_three_winding_transformers__tap_dependent_impedance()
     pp_net: pp.pandapowerNet = pp.create_empty_network()
     pp.create_bus(net=pp_net, vn_kv=0.0)
     args = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
-    pp.create_transformer3w_from_parameters(pp_net, *args, tap_dependent_impedance=True)
 
-    converter = PandaPowerConverter()
-    converter.pp_input_data = {k: v for k, v in pp_net.items() if isinstance(v, pd.DataFrame)}
+    if version.Version(metadata.version("pandapower")) >= version.Version("3"):
+        with pytest.deprecated_call():
+            pp.create_transformer3w_from_parameters(pp_net, *args, tap_dependent_impedance=True)
+    else:
+        pp.create_transformer3w_from_parameters(pp_net, *args, tap_dependent_impedance=True)
 
-    # Act/Assert
-    with pytest.raises(RuntimeError, match="not supported"):
-        converter._create_pgm_input_three_winding_transformers()
+        converter = PandaPowerConverter()
+        converter.pp_input_data = {k: v for k, v in pp_net.items() if isinstance(v, pd.DataFrame)}
+
+        # Act/Assert
+        with pytest.raises(RuntimeError, match="not supported"):
+            converter._create_pgm_input_three_winding_transformers()
 
 
 @patch("power_grid_model_io.converters.pandapower_converter.initialize_array")

tests/utils.py

@@ -4,12 +4,14 @@
 
 import sys
 from copy import copy, deepcopy
+from importlib import metadata
 from itertools import chain
 from typing import Any, Dict, List, Mapping, MutableMapping, Optional, Tuple, Union
 from unittest.mock import MagicMock
 
 import numpy as np
 import pandas as pd
+from packaging import version
 from pandas.core.generic import NDFrame
 
 
@@ -71,7 +73,9 @@ class MockFn:
     __slots__ = ["fn", "args", "kwargs", "postfix"]
 
     __array_struct__ = np.array([]).__array_struct__
-    __array_prepare__ = np.array([]).__array_prepare__
+
+    if version.Version(metadata.version("numpy")) < version.Version("2"):
+        __array_prepare__ = np.array([]).__array_prepare__  # type: ignore[attr-defined]
 
     def __init__(self, fn: str, *args, **kwargs):
         self.fn = fn