feat: Add generated models

src/r2x/models/generated/__init__.py

@@ -0,0 +1,39 @@
+# coding: utf-8
+
+# flake8: noqa
+"""
+PowerSystemModels
+
+No description provided (generated by Openapi Generator https://github.com/openapitools/openapi-generator)
+
+The version of the OpenAPI document: 1.0.0
+Generated by OpenAPI Generator (https://openapi-generator.tech)
+
+Do not edit the class manually.
+"""  # noqa: E501
+
+# import models into model package
+from openapi_client.models.average_rate_curve import AverageRateCurve
+from openapi_client.models.average_rate_curve_function_data import AverageRateCurveFunctionData
+from openapi_client.models.cost_curve import CostCurve
+from openapi_client.models.cost_curve_value_curve import CostCurveValueCurve
+from openapi_client.models.fuel_curve import FuelCurve
+from openapi_client.models.fuel_curve_fuel_cost import FuelCurveFuelCost
+from openapi_client.models.incremental_curve import IncrementalCurve
+from openapi_client.models.incremental_curve_function_data import IncrementalCurveFunctionData
+from openapi_client.models.input_output_curve import InputOutputCurve
+from openapi_client.models.input_output_curve_function_data import InputOutputCurveFunctionData
+from openapi_client.models.linear_function_data import LinearFunctionData
+from openapi_client.models.min_max import MinMax
+from openapi_client.models.piecewise_linear_data import PiecewiseLinearData
+from openapi_client.models.piecewise_linear_data_points_inner import PiecewiseLinearDataPointsInner
+from openapi_client.models.piecewise_step_data import PiecewiseStepData
+from openapi_client.models.quadratic_function_data import QuadraticFunctionData
+from openapi_client.models.start_up_stages import StartUpStages
+from openapi_client.models.thermal_standard import ThermalStandard
+from openapi_client.models.thermal_standard_operation_cost import ThermalStandardOperationCost
+from openapi_client.models.thermal_standard_operation_cost_start_up import ThermalStandardOperationCostStartUp
+from openapi_client.models.thermal_standard_operation_cost_variable import (
+    ThermalStandardOperationCostVariable,
+)
+from openapi_client.models.up_down import UpDown

src/r2x/models/generated/average_rate_curve.py

@@ -0,0 +1,110 @@
+# coding: utf-8
+
+"""
+PowerSystemModels
+
+No description provided (generated by Openapi Generator https://github.com/openapitools/openapi-generator)
+
+The version of the OpenAPI document: 1.0.0
+Generated by OpenAPI Generator (https://openapi-generator.tech)
+
+Do not edit the class manually.
+"""  # noqa: E501
+
+from __future__ import annotations
+import pprint
+import re  # noqa: F401
+import json
+
+from infrasys import Component
+
+from pydantic import BaseModel, ConfigDict, StrictFloat, StrictInt, StrictStr, field_validator
+from typing import Any, ClassVar, Dict, List, Optional, Union
+from openapi_client.models.average_rate_curve_function_data import AverageRateCurveFunctionData
+from typing import Optional, Set
+from typing_extensions import Self
+
+
+class AverageRateCurve(Component):
+    """
+    AverageRateCurve
+    """  # noqa: E501
+
+    curve_type: Optional[StrictStr] = None
+    function_data: AverageRateCurveFunctionData
+    initial_input: Optional[Union[StrictFloat, StrictInt]] = None
+    input_at_zero: Optional[Union[StrictFloat, StrictInt]] = None
+    __properties: ClassVar[List[str]] = ["curve_type", "function_data", "initial_input", "input_at_zero"]
+
+    @field_validator("curve_type")
+    def curve_type_validate_enum(cls, value):
+        """Validates the enum"""
+        if value is None:
+            return value
+
+        if value not in set(["AVERAGE_RATE"]):
+            raise ValueError("must be one of enum values ('AVERAGE_RATE')")
+        return value
+
+    model_config = ConfigDict(
+        populate_by_name=True,
+        validate_assignment=True,
+        protected_namespaces=(),
+    )
+
+    def to_str(self) -> str:
+        """Returns the string representation of the model using alias"""
+        return pprint.pformat(self.model_dump(by_alias=True))
+
+    def to_json(self) -> str:
+        """Returns the JSON representation of the model using alias"""
+        # TODO: pydantic v2: use .model_dump_json(by_alias=True, exclude_unset=True) instead
+        return json.dumps(self.to_dict())
+
+    @classmethod
+    def from_json(cls, json_str: str) -> Optional[Self]:
+        """Create an instance of AverageRateCurve from a JSON string"""
+        return cls.from_dict(json.loads(json_str))
+
+    def to_dict(self) -> Dict[str, Any]:
+        """Return the dictionary representation of the model using alias.
+
+        This has the following differences from calling pydantic's
+        `self.model_dump(by_alias=True)`:
+
+        * `None` is only added to the output dict for nullable fields that
+          were set at model initialization. Other fields with value `None`
+          are ignored.
+        """
+        excluded_fields: Set[str] = set([])
+
+        _dict = self.model_dump(
+            by_alias=True,
+            exclude=excluded_fields,
+            exclude_none=True,
+        )
+        # override the default output from pydantic by calling `to_dict()` of function_data
+        if self.function_data:
+            _dict["function_data"] = self.function_data.to_dict()
+        return _dict
+
+    @classmethod
+    def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
+        """Create an instance of AverageRateCurve from a dict"""
+        if obj is None:
+            return None
+
+        if not isinstance(obj, dict):
+            return cls.model_validate(obj)
+
+        _obj = cls.model_validate(
+            {
+                "curve_type": obj.get("curve_type"),
+                "function_data": AverageRateCurveFunctionData.from_dict(obj["function_data"])
+                if obj.get("function_data") is not None
+                else None,
+                "initial_input": obj.get("initial_input"),
+                "input_at_zero": obj.get("input_at_zero"),
+            }
+        )
+        return _obj

src/r2x/models/generated/average_rate_curve_function_data.py

@@ -0,0 +1,169 @@
+# coding: utf-8
+
+"""
+PowerSystemModels
+
+No description provided (generated by Openapi Generator https://github.com/openapitools/openapi-generator)
+
+The version of the OpenAPI document: 1.0.0
+Generated by OpenAPI Generator (https://openapi-generator.tech)
+
+Do not edit the class manually.
+"""  # noqa: E501
+
+from __future__ import annotations
+import json
+import pprint
+from pydantic import BaseModel, ConfigDict, Field, StrictStr, ValidationError, field_validator
+from typing import Any, List, Optional
+from openapi_client.models.linear_function_data import LinearFunctionData
+from openapi_client.models.piecewise_linear_data import PiecewiseLinearData
+from openapi_client.models.quadratic_function_data import QuadraticFunctionData
+from pydantic import StrictStr, Field
+from typing import Union, List, Set, Optional, Dict
+from typing_extensions import Literal, Self
+
+AVERAGERATECURVEFUNCTIONDATA_ONE_OF_SCHEMAS = [
+    "LinearFunctionData",
+    "PiecewiseLinearData",
+    "QuadraticFunctionData",
+]
+
+
+class AverageRateCurveFunctionData(BaseModel):
+    """
+    AverageRateCurveFunctionData
+    """
+
+    # data type: LinearFunctionData
+    oneof_schema_1_validator: Optional[LinearFunctionData] = None
+    # data type: QuadraticFunctionData
+    oneof_schema_2_validator: Optional[QuadraticFunctionData] = None
+    # data type: PiecewiseLinearData
+    oneof_schema_3_validator: Optional[PiecewiseLinearData] = None
+    actual_instance: Optional[Union[LinearFunctionData, PiecewiseLinearData, QuadraticFunctionData]] = None
+    one_of_schemas: Set[str] = {"LinearFunctionData", "PiecewiseLinearData", "QuadraticFunctionData"}
+
+    model_config = ConfigDict(
+        validate_assignment=True,
+        protected_namespaces=(),
+    )
+
+    discriminator_value_class_map: Dict[str, str] = {}
+
+    def __init__(self, *args, **kwargs) -> None:
+        if args:
+            if len(args) > 1:
+                raise ValueError("If a position argument is used, only 1 is allowed to set `actual_instance`")
+            if kwargs:
+                raise ValueError("If a position argument is used, keyword arguments cannot be used.")
+            super().__init__(actual_instance=args[0])
+        else:
+            super().__init__(**kwargs)
+
+    @field_validator("actual_instance")
+    def actual_instance_must_validate_oneof(cls, v):
+        instance = AverageRateCurveFunctionData.model_construct()
+        error_messages = []
+        match = 0
+        # validate data type: LinearFunctionData
+        if not isinstance(v, LinearFunctionData):
+            error_messages.append(f"Error! Input type `{type(v)}` is not `LinearFunctionData`")
+        else:
+            match += 1
+        # validate data type: QuadraticFunctionData
+        if not isinstance(v, QuadraticFunctionData):
+            error_messages.append(f"Error! Input type `{type(v)}` is not `QuadraticFunctionData`")
+        else:
+            match += 1
+        # validate data type: PiecewiseLinearData
+        if not isinstance(v, PiecewiseLinearData):
+            error_messages.append(f"Error! Input type `{type(v)}` is not `PiecewiseLinearData`")
+        else:
+            match += 1
+        if match > 1:
+            # more than 1 match
+            raise ValueError(
+                "Multiple matches found when setting `actual_instance` in AverageRateCurveFunctionData with oneOf schemas: LinearFunctionData, PiecewiseLinearData, QuadraticFunctionData. Details: "
+                + ", ".join(error_messages)
+            )
+        elif match == 0:
+            # no match
+            raise ValueError(
+                "No match found when setting `actual_instance` in AverageRateCurveFunctionData with oneOf schemas: LinearFunctionData, PiecewiseLinearData, QuadraticFunctionData. Details: "
+                + ", ".join(error_messages)
+            )
+        else:
+            return v
+
+    @classmethod
+    def from_dict(cls, obj: Union[str, Dict[str, Any]]) -> Self:
+        return cls.from_json(json.dumps(obj))
+
+    @classmethod
+    def from_json(cls, json_str: str) -> Self:
+        """Returns the object represented by the json string"""
+        instance = cls.model_construct()
+        error_messages = []
+        match = 0
+
+        # deserialize data into LinearFunctionData
+        try:
+            instance.actual_instance = LinearFunctionData.from_json(json_str)
+            match += 1
+        except (ValidationError, ValueError) as e:
+            error_messages.append(str(e))
+        # deserialize data into QuadraticFunctionData
+        try:
+            instance.actual_instance = QuadraticFunctionData.from_json(json_str)
+            match += 1
+        except (ValidationError, ValueError) as e:
+            error_messages.append(str(e))
+        # deserialize data into PiecewiseLinearData
+        try:
+            instance.actual_instance = PiecewiseLinearData.from_json(json_str)
+            match += 1
+        except (ValidationError, ValueError) as e:
+            error_messages.append(str(e))
+
+        if match > 1:
+            # more than 1 match
+            raise ValueError(
+                "Multiple matches found when deserializing the JSON string into AverageRateCurveFunctionData with oneOf schemas: LinearFunctionData, PiecewiseLinearData, QuadraticFunctionData. Details: "
+                + ", ".join(error_messages)
+            )
+        elif match == 0:
+            # no match
+            raise ValueError(
+                "No match found when deserializing the JSON string into AverageRateCurveFunctionData with oneOf schemas: LinearFunctionData, PiecewiseLinearData, QuadraticFunctionData. Details: "
+                + ", ".join(error_messages)
+            )
+        else:
+            return instance
+
+    def to_json(self) -> str:
+        """Returns the JSON representation of the actual instance"""
+        if self.actual_instance is None:
+            return "null"
+
+        if hasattr(self.actual_instance, "to_json") and callable(self.actual_instance.to_json):
+            return self.actual_instance.to_json()
+        else:
+            return json.dumps(self.actual_instance)
+
+    def to_dict(
+        self,
+    ) -> Optional[Union[Dict[str, Any], LinearFunctionData, PiecewiseLinearData, QuadraticFunctionData]]:
+        """Returns the dict representation of the actual instance"""
+        if self.actual_instance is None:
+            return None
+
+        if hasattr(self.actual_instance, "to_dict") and callable(self.actual_instance.to_dict):
+            return self.actual_instance.to_dict()
+        else:
+            # primitive type
+            return self.actual_instance
+
+    def to_str(self) -> str:
+        """Returns the string representation of the actual instance"""
+        return pprint.pformat(self.model_dump())