# 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 List, Dict, Optional, Any, Union, TYPE_CHECKING
from typing_extensions import Annotated
from pydantic.v1 import BaseModel, StrictStr, StrictInt, StrictBool, StrictFloat, StrictBytes, Field, validator, ValidationError, conlist, constr
from datetime import datetime
[docs]
class MarketOptions(BaseModel):
"""
The set of options that control miscellaneous and default market resolution behaviour. A default scope entered here will cause duplicate (\"default\") rules to be created across all asset types, pointing at that scope. These are aimed at a 'crude' level of control for those who do not wish to fine tune the way that data is resolved. For clients who wish to simply match instruments to prices this is quite possibly sufficient. For those wishing to control market data sources according to requirements based on accuracy or timeliness it is not recommended. In more advanced cases the options should largely be ignored and rules specified per source. If no default scope is supplied, no default rules are created. Where a default scope is supplied, a default rule is constructed per asset type, pointing at that scope, and appended after all specified rules so it is only tried as a last resort. Each default rule is wild-carded within its asset type (for example Quote.{instrumentCodeType}.* or Fx.*.*) rather than being a single fully wild-carded rule, and one (two for Rates) is generated per asset type. Consequently, where no specified rule matches a dependency, the failure reported is this constructed default rule in the provided default scope. It is not recommended to rely on this behaviour, as these rules match a wide range of data and are likely to be slow to resolve. It is better to specify rules for the data you require in the MarketRules of the MarketContext. # noqa: E501
"""
default_supplier: Optional[StrictStr] = Field(None,alias="defaultSupplier", description="The default supplier of data. This controls which 'dialect' is used to find particular market data. e.g. one supplier might address data by RIC, another by PermId")
default_instrument_code_type: Optional[StrictStr] = Field(None,alias="defaultInstrumentCodeType", description="When instrument quotes are searched for, what identifier should be used by default")
default_scope: Optional[StrictStr] = Field(None,alias="defaultScope", description="The scope in which to search for data when applying default rules. This is optional: if omitted, no default rules are created and market data is resolved only via the explicitly specified market data key rules.")
attempt_to_infer_missing_fx: Optional[StrictBool] = Field(default=None, description="if true will calculate a missing Fx pair (e.g. THBJPY) from the inverse JPYTHB or from standardised pairs against USD, e.g. THBUSD and JPYUSD", alias="attemptToInferMissingFx")
calendar_scope: Optional[StrictStr] = Field(None,alias="calendarScope", description="The scope in which holiday calendars stored")
convention_scope: Optional[StrictStr] = Field(None,alias="conventionScope", description="The scope in which conventions stored")
__properties = ["defaultSupplier", "defaultInstrumentCodeType", "defaultScope", "attemptToInferMissingFx", "calendarScope", "conventionScope"]
[docs]
class Config:
"""Pydantic configuration"""
allow_population_by_field_name = True
validate_assignment = True
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) -> MarketOptions:
"""Create an instance of MarketOptions 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)
# set to None if default_supplier (nullable) is None
# and __fields_set__ contains the field
if self.default_supplier is None and "default_supplier" in self.__fields_set__:
_dict['defaultSupplier'] = None
# set to None if default_instrument_code_type (nullable) is None
# and __fields_set__ contains the field
if self.default_instrument_code_type is None and "default_instrument_code_type" in self.__fields_set__:
_dict['defaultInstrumentCodeType'] = None
# set to None if default_scope (nullable) is None
# and __fields_set__ contains the field
if self.default_scope is None and "default_scope" in self.__fields_set__:
_dict['defaultScope'] = None
# set to None if calendar_scope (nullable) is None
# and __fields_set__ contains the field
if self.calendar_scope is None and "calendar_scope" in self.__fields_set__:
_dict['calendarScope'] = None
# set to None if convention_scope (nullable) is None
# and __fields_set__ contains the field
if self.convention_scope is None and "convention_scope" in self.__fields_set__:
_dict['conventionScope'] = None
return _dict
[docs]
@classmethod
def from_dict(cls, obj: dict) -> MarketOptions:
"""Create an instance of MarketOptions from a dict"""
if obj is None:
return None
if not isinstance(obj, dict):
return MarketOptions.parse_obj(obj)
_obj = MarketOptions.parse_obj({
"default_supplier": obj.get("defaultSupplier"),
"default_instrument_code_type": obj.get("defaultInstrumentCodeType"),
"default_scope": obj.get("defaultScope"),
"attempt_to_infer_missing_fx": obj.get("attemptToInferMissingFx"),
"calendar_scope": obj.get("calendarScope"),
"convention_scope": obj.get("conventionScope")
})
return _obj
MarketOptions.update_forward_refs()