Module adcp.types.domains.pricing_options.price_guidance
Classes
class PriceGuidance (**data: Any)-
Expand source code
class PriceGuidance(AdCPBaseModel): model_config = ConfigDict( extra='allow', ) p25: Annotated[ StrictFloat | None, Field(description='25th percentile of recent winning bids', ge=0.0) ] = None p50: Annotated[ StrictFloat | None, Field(description='Median of recent winning bids', ge=0.0) ] = None p75: Annotated[ StrictFloat | None, Field(description='75th percentile of recent winning bids', ge=0.0) ] = None p90: Annotated[ StrictFloat | None, Field(description='90th percentile of recent winning bids', ge=0.0) ] = NoneBase model for AdCP types with spec-compliant serialization.
Defaults to
extra='ignore'so unknown fields from newer spec versions are silently dropped rather than causing validation errors. Generated types whose schemas setadditionalProperties: trueoverride this withextra='allow'in their ownmodel_config.Set
ADCP_STRICT_VALIDATION=1in the environment ("1","true","yes","on"are accepted) to flip the default toextra='forbid'. Use this during spec upgrades to catch silently-dropped renamed fields in tests. See :func:_resolve_extra_policy.Important
The env var is resolved once at module import time. Set it in your shell or CI environment before
import adcpruns — mutatingos.environ["ADCP_STRICT_VALIDATION"]after the firstadcpimport has no effect on already-imported model classes (they captured the policy at class-body evaluation).Consumers who want per-model strict validation can override
model_configon their subclass.Create a new model by parsing and validating input data from keyword arguments.
Raises [
ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.selfis explicitly positional-only to allowselfas a field name.Ancestors
- AdCPBaseModel
- pydantic.main.BaseModel
Class variables
var model_configvar p25 : float | Nonevar p50 : float | Nonevar p75 : float | Nonevar p90 : float | None
Inherited members