[ModelicaSystem] update input handling for set*() functions

* use a Pythonic way for input:
  setParameters(a=123)

  param = {'a': 123}
  setParameters(**param)

see input by SengerM in PR OpenModelica#326

Author: syntron

OMPython/ModelicaSystem.py

@@ -1115,7 +1115,8 @@ def getSolutions(self, varList: Optional[str | list[str]] = None, resultfile: Op
 
     @staticmethod
     def _prepare_input_data(
-            raw_input: str | list[str] | dict[str, Any],
+            input_args: Any,
+            input_kwargs: dict[str, Any],
     ) -> dict[str, str]:
         """
         Convert raw input to a structured dictionary {'key1': 'value1', 'key2': 'value2'}.
@@ -1133,38 +1134,42 @@ def prepare_str(str_in: str) -> dict[str, str]:
 
         input_data: dict[str, str] = {}
 
-        if isinstance(raw_input, str):
-            warnings.warn(message="The definition of values to set should use a dictionary, "
-                                  "i.e. {'key1': 'val1', 'key2': 'val2', ...}. Please convert all cases which "
-                                  "use a string ('key=val') or list ['key1=val1', 'key2=val2', ...]",
-                          category=DeprecationWarning,
-                          stacklevel=3)
-            return prepare_str(raw_input)
-
-        if isinstance(raw_input, list):
-            warnings.warn(message="The definition of values to set should use a dictionary, "
-                                  "i.e. {'key1': 'val1', 'key2': 'val2', ...}. Please convert all cases which "
-                                  "use a string ('key=val') or list ['key1=val1', 'key2=val2', ...]",
-                          category=DeprecationWarning,
-                          stacklevel=3)
-
-            for item in raw_input:
-                input_data |= prepare_str(item)
-
-            return input_data
-
-        if isinstance(raw_input, dict):
-            for key, val in raw_input.items():
-                # convert all values to strings to align it on one type: dict[str, str]
-                # spaces have to be removed as setInput() could take list of tuples as input and spaces would
-                str_val = str(val).replace(' ', '')
+        for input_arg in input_args:
+            if isinstance(input_arg, str):
+                warnings.warn(message="The definition of values to set should use a dictionary, "
+                                      "i.e. {'key1': 'val1', 'key2': 'val2', ...}. Please convert all cases which "
+                                      "use a string ('key=val') or list ['key1=val1', 'key2=val2', ...]",
+                              category=DeprecationWarning,
+                              stacklevel=3)
+                input_data = input_data | prepare_str(input_arg)
+            elif isinstance(input_arg, list):
+                warnings.warn(message="The definition of values to set should use a dictionary, "
+                                      "i.e. {'key1': 'val1', 'key2': 'val2', ...}. Please convert all cases which "
+                                      "use a string ('key=val') or list ['key1=val1', 'key2=val2', ...]",
+                              category=DeprecationWarning,
+                              stacklevel=3)
+
+                for item in input_arg:
+                    if not isinstance(item, str):
+                        raise ModelicaSystemError(f"Invalid input data type for set*() function: {type(item)}!")
+                    input_data = input_data | prepare_str(item)
+            else:
+                raise ModelicaSystemError(f"Invalid input data type for set*() function: {type(input_arg)}!")
+
+        if len(input_kwargs):
+            for key, val in input_kwargs.items():
+                # ensure all values are strings to align it on one type: dict[str, str]
+                if not isinstance(val, str):
+                    # spaces have to be removed as setInput() could take list of tuples as input and spaces would
+                    # result in an error on recreating the input data
+                    str_val = str(val).replace(' ', '')
+                else:
+                    str_val = val
                 if ' ' in key or ' ' in str_val:
                     raise ModelicaSystemError(f"Spaces not allowed in key/value pairs: {repr(key)} = {repr(val)}!")
                 input_data[key] = str_val
 
-            return input_data
-
-        raise ModelicaSystemError(f"Invalid type of input: {type(raw_input)}")
+        return input_data
 
     def _set_method_helper(
             self,
@@ -1225,17 +1230,21 @@ def isParameterChangeable(
 
     def setContinuous(
             self,
-            cvals: str | list[str] | dict[str, Any],
+            *args: Any,
+            **kwargs: dict[str, Any],
     ) -> bool:
         """
         This method is used to set continuous values. It can be called:
         with a sequence of continuous name and assigning corresponding values as arguments as show in the example below:
         usage
         >>> setContinuous("Name=value")  # depreciated
         >>> setContinuous(["Name1=value1","Name2=value2"])  # depreciated
-        >>> setContinuous(cvals={"Name1": "value1", "Name2": "value2"})
+
+        >>> setContinuous(Name1="value1", Name2="value2")
+        >>> param = {"Name1": "value1", "Name2": "value2"}
+        >>> setContinuous(**param)
         """
-        inputdata = self._prepare_input_data(raw_input=cvals)
+        inputdata = self._prepare_input_data(input_args=args, input_kwargs=kwargs)
 
         return self._set_method_helper(
             inputdata=inputdata,
@@ -1245,17 +1254,21 @@ def setContinuous(
 
     def setParameters(
             self,
-            pvals: str | list[str] | dict[str, Any],
+            *args: Any,
+            **kwargs: dict[str, Any],
     ) -> bool:
         """
         This method is used to set parameter values. It can be called:
         with a sequence of parameter name and assigning corresponding value as arguments as show in the example below:
         usage
         >>> setParameters("Name=value")  # depreciated
         >>> setParameters(["Name1=value1","Name2=value2"])  # depreciated
-        >>> setParameters(pvals={"Name1": "value1", "Name2": "value2"})
+
+        >>> setParameters(Name1="value1", Name2="value2")
+        >>> param = {"Name1": "value1", "Name2": "value2"}
+        >>> setParameters(**param)
         """
-        inputdata = self._prepare_input_data(raw_input=pvals)
+        inputdata = self._prepare_input_data(input_args=args, input_kwargs=kwargs)
 
         return self._set_method_helper(
             inputdata=inputdata,
@@ -1265,17 +1278,21 @@ def setParameters(
 
     def setSimulationOptions(
             self,
-            simOptions: str | list[str] | dict[str, Any],
+            *args: Any,
+            **kwargs: dict[str, Any],
     ) -> bool:
         """
         This method is used to set simulation options. It can be called:
         with a sequence of simulation options name and assigning corresponding values as arguments as show in the example below:
         usage
         >>> setSimulationOptions("Name=value")  # depreciated
         >>> setSimulationOptions(["Name1=value1","Name2=value2"])  # depreciated
-        >>> setSimulationOptions(simOptions={"Name1": "value1", "Name2": "value2"})
+
+        >>> setSimulationOptions(Name1="value1", Name2="value2")
+        >>> param = {"Name1": "value1", "Name2": "value2"}
+        >>> setSimulationOptions(**param)
         """
-        inputdata = self._prepare_input_data(raw_input=simOptions)
+        inputdata = self._prepare_input_data(input_args=args, input_kwargs=kwargs)
 
         return self._set_method_helper(
             inputdata=inputdata,
@@ -1285,17 +1302,21 @@ def setSimulationOptions(
 
     def setLinearizationOptions(
             self,
-            linearizationOptions: str | list[str] | dict[str, Any],
+            *args: Any,
+            **kwargs: dict[str, Any],
     ) -> bool:
         """
         This method is used to set linearization options. It can be called:
         with a sequence of linearization options name and assigning corresponding value as arguments as show in the example below
         usage
         >>> setLinearizationOptions("Name=value")  # depreciated
         >>> setLinearizationOptions(["Name1=value1","Name2=value2"])  # depreciated
-        >>> setLinearizationOptions(linearizationOtions={"Name1": "value1", "Name2": "value2"})
+
+        >>> setLinearizationOptions(Name1="value1", Name2="value2")
+        >>> param = {"Name1": "value1", "Name2": "value2"}
+        >>> setLinearizationOptions(**param)
         """
-        inputdata = self._prepare_input_data(raw_input=linearizationOptions)
+        inputdata = self._prepare_input_data(input_args=args, input_kwargs=kwargs)
 
         return self._set_method_helper(
             inputdata=inputdata,
@@ -1305,17 +1326,21 @@ def setLinearizationOptions(
 
     def setOptimizationOptions(
             self,
-            optimizationOptions: str | list[str] | dict[str, Any],
+            *args: Any,
+            **kwargs: dict[str, Any],
     ) -> bool:
         """
         This method is used to set optimization options. It can be called:
         with a sequence of optimization options name and assigning corresponding values as arguments as show in the example below:
         usage
         >>> setOptimizationOptions("Name=value")  # depreciated
         >>> setOptimizationOptions(["Name1=value1","Name2=value2"])  # depreciated
-        >>> setOptimizationOptions(optimizationOptions={"Name1": "value1", "Name2": "value2"})
+
+        >>> setOptimizationOptions(Name1="value1", Name2="value2")
+        >>> param = {"Name1": "value1", "Name2": "value2"}
+        >>> setOptimizationOptions(**param)
         """
-        inputdata = self._prepare_input_data(raw_input=optimizationOptions)
+        inputdata = self._prepare_input_data(input_args=args, input_kwargs=kwargs)
 
         return self._set_method_helper(
             inputdata=inputdata,
@@ -1325,7 +1350,8 @@ def setOptimizationOptions(
 
     def setInputs(
             self,
-            name: str | list[str] | dict[str, Any],
+            *args: Any,
+            **kwargs: dict[str, Any],
     ) -> bool:
         """
         This method is used to set input values. It can be called with a sequence of input name and assigning
@@ -1335,9 +1361,12 @@ def setInputs(
 
         >>> setInputs("Name=value")  # depreciated
         >>> setInputs(["Name1=value1","Name2=value2"])  # depreciated
-        >>> setInputs(name={"Name1": "value1", "Name2": "value2"})
+
+        >>> setInputs(Name1="value1", Name2="value2")
+        >>> param = {"Name1": "value1", "Name2": "value2"}
+        >>> setInputs(**param)
         """
-        inputdata = self._prepare_input_data(raw_input=name)
+        inputdata = self._prepare_input_data(input_args=args, input_kwargs=kwargs)
 
         for key, val in inputdata.items():
             if key not in self._inputs:

tests/test_ModelicaSystem.py

@@ -34,9 +34,9 @@ def test_setParameters():
     model_path = omc.sendExpression("getInstallationDirectoryPath()") + "/share/doc/omc/testmodels/"
     mod = OMPython.ModelicaSystem(model_path + "BouncingBall.mo", "BouncingBall")
 
-    # method 1
-    mod.setParameters(pvals={"e": 1.234})
-    mod.setParameters(pvals={"g": 321.0})
+    # method 1 (test depreciated variants)
+    mod.setParameters("e=1.234")
+    mod.setParameters(["g=321.0"])
     assert mod.getParameters("e") == ["1.234"]
     assert mod.getParameters("g") == ["321.0"]
     assert mod.getParameters() == {
@@ -46,8 +46,9 @@ def test_setParameters():
     with pytest.raises(KeyError):
         mod.getParameters("thisParameterDoesNotExist")
 
-    # method 2
-    mod.setParameters(pvals={"e": 21.3, "g": 0.12})
+    # method 2 (new style)
+    pvals = {"e": 21.3, "g": 0.12}
+    mod.setParameters(**pvals)
     assert mod.getParameters() == {
         "e": "21.3",
         "g": "0.12",