# coding: utf-8
"""
LUSID API
FINBOURNE Technology # noqa: E501
Contact: info@finbourne.com
Generated by OpenAPI Generator (https://openapi-generator.tech)
Do not edit the class manually.
"""
from __future__ import annotations
import pprint
import re # noqa: F401
import json
from typing import Any, Dict, Union
from pydantic.v1 import BaseModel, Field, StrictStr, validator
import lusid.models
[docs]
class MarketDataOptions(BaseModel):
"""
Base class for representing market data options in LUSID. Abstractly, these are any options that one should be able to specify for ComplexMarketData entities. For example, CurveOptions allows one to decide how the data provided in a discountFactorCurve is interpolated. This base class should not be directly instantiated; each supported MarketDataOptionsType has a corresponding inherited class. # noqa: E501
"""
market_data_options_type: StrictStr = Field(..., alias="marketDataOptionsType", description="The available values are: CurveOptions")
__properties = ["marketDataOptionsType"]
[docs]
@validator('market_data_options_type')
def market_data_options_type_validate_enum(cls, value):
"""Validates the enum"""
if value not in ('CurveOptions'):
raise ValueError("must be one of enum values ('CurveOptions')")
return value
[docs]
class Config:
"""Pydantic configuration"""
allow_population_by_field_name = True
validate_assignment = True
# JSON field name that stores the object type
__discriminator_property_name = 'marketDataOptionsType'
# discriminator mappings
__discriminator_value_class_map = {
'CurveOptions': 'CurveOptions'
}
[docs]
@classmethod
def get_discriminator_value(cls, obj: dict) -> str:
"""Returns the discriminator value (object type) of the data"""
discriminator_value = obj[cls.__discriminator_property_name]
if discriminator_value:
return cls.__discriminator_value_class_map.get(discriminator_value)
else:
return None
def __str__(self):
"""For `print` and `pprint`"""
return pprint.pformat(self.dict(by_alias=False))
def __repr__(self):
"""For `print` and `pprint`"""
return self.to_str()
[docs]
def to_str(self) -> str:
"""Returns the string representation of the model using alias"""
return pprint.pformat(self.dict(by_alias=True))
[docs]
def to_json(self) -> str:
"""Returns the JSON representation of the model using alias"""
return json.dumps(self.to_dict())
[docs]
@classmethod
def from_json(cls, json_str: str) -> Union(CurveOptions):
"""Create an instance of MarketDataOptions from a JSON string"""
return cls.from_dict(json.loads(json_str))
[docs]
def to_dict(self):
"""Returns the dictionary representation of the model using alias"""
_dict = self.dict(by_alias=True,
exclude={
},
exclude_none=True)
return _dict
[docs]
@classmethod
def from_dict(cls, obj: dict) -> Union(CurveOptions):
"""Create an instance of MarketDataOptions from a dict"""
# look up the object type based on discriminator mapping
object_type = cls.get_discriminator_value(obj)
if object_type:
klass = getattr(lusid.models, object_type)
return klass.from_dict(obj)
else:
raise ValueError("MarketDataOptions failed to lookup discriminator value from " +
json.dumps(obj) + ". Discriminator property name: " + cls.__discriminator_property_name +
", mapping: " + json.dumps(cls.__discriminator_value_class_map))