Module adcp.types.generated_poc.performance_feedback

Classes

class FeedbackSource (*args, **kwds)

Expand source code

class FeedbackSource(Enum):
    buyer_attribution = 'buyer_attribution'
    third_party_measurement = 'third_party_measurement'
    platform_analytics = 'platform_analytics'
    verification_partner = 'verification_partner'

Create a collection of name/value pairs.

Example enumeration:

>>> class Color(Enum):
...     RED = 1
...     BLUE = 2
...     GREEN = 3

Access them by:

• attribute access::

>>> Color.RED
<Color.RED: 1>

• value lookup:

>>> Color(1)
<Color.RED: 1>

• name lookup:

>>> Color['RED']
<Color.RED: 1>

Enumerations can be iterated over, and know how many members they have:

>>> len(Color)
3

>>> list(Color)
[<Color.RED: 1>, <Color.BLUE: 2>, <Color.GREEN: 3>]

Methods can be added to enumerations, and members can have their own attributes – see the documentation for details.

Ancestors

• enum.Enum

Class variables

var buyer_attribution

var platform_analytics

var third_party_measurement

var verification_partner

class MeasurementPeriod (**data: Any)

Expand source code

class MeasurementPeriod(AdCPBaseModel):
    model_config = ConfigDict(
        extra='forbid',
    )
    end: Annotated[
        AwareDatetime, Field(description='ISO 8601 end timestamp for measurement period')
    ]
    start: Annotated[
        AwareDatetime, Field(description='ISO 8601 start timestamp for measurement period')
    ]

Base model for AdCP types with spec-compliant serialization.

AdCP JSON schemas use additionalProperties: false and do not allow null for optional fields. Therefore, optional fields must be omitted entirely when not present (not sent as null).

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.

self is explicitly positional-only to allow self as a field name.

Ancestors

• AdCPBaseModel
• pydantic.main.BaseModel

Class variables

var end : pydantic.types.AwareDatetime

var model_config

var start : pydantic.types.AwareDatetime

Inherited members

• AdCPBaseModel:
  • model_dump
  • model_dump_json

class MetricType (*args, **kwds)

Expand source code

class MetricType(Enum):
    overall_performance = 'overall_performance'
    conversion_rate = 'conversion_rate'
    brand_lift = 'brand_lift'
    click_through_rate = 'click_through_rate'
    completion_rate = 'completion_rate'
    viewability = 'viewability'
    brand_safety = 'brand_safety'
    cost_efficiency = 'cost_efficiency'

Create a collection of name/value pairs.

Example enumeration:

>>> class Color(Enum):
...     RED = 1
...     BLUE = 2
...     GREEN = 3

Access them by:

• attribute access::

>>> Color.RED
<Color.RED: 1>

• value lookup:

>>> Color(1)
<Color.RED: 1>

• name lookup:

>>> Color['RED']
<Color.RED: 1>

Enumerations can be iterated over, and know how many members they have:

>>> len(Color)
3

>>> list(Color)
[<Color.RED: 1>, <Color.BLUE: 2>, <Color.GREEN: 3>]

Methods can be added to enumerations, and members can have their own attributes – see the documentation for details.

Ancestors

• enum.Enum

Class variables

var brand_lift

var brand_safety

var click_through_rate

var completion_rate

var conversion_rate

var cost_efficiency

var overall_performance

var viewability

class PerformanceFeedback (**data: Any)

Expand source code

class PerformanceFeedback(AdCPBaseModel):
    model_config = ConfigDict(
        extra='forbid',
    )
    applied_at: Annotated[
        AwareDatetime | None,
        Field(
            description='ISO 8601 timestamp when feedback was applied to optimization algorithms'
        ),
    ] = None
    creative_id: Annotated[
        str | None, Field(description='Specific creative asset (if feedback is creative-specific)')
    ] = None
    feedback_id: Annotated[
        str, Field(description='Unique identifier for this performance feedback submission')
    ]
    feedback_source: Annotated[FeedbackSource, Field(description='Source of the performance data')]
    measurement_period: Annotated[
        MeasurementPeriod, Field(description='Time period for performance measurement')
    ]
    media_buy_id: Annotated[str, Field(description="Publisher's media buy identifier")]
    metric_type: Annotated[MetricType, Field(description='The business metric being measured')]
    package_id: Annotated[
        str | None,
        Field(
            description='Specific package within the media buy (if feedback is package-specific)'
        ),
    ] = None
    performance_index: Annotated[
        float,
        Field(
            description='Normalized performance score (0.0 = no value, 1.0 = expected, >1.0 = above expected)',
            ge=0.0,
        ),
    ]
    status: Annotated[Status, Field(description='Processing status of the performance feedback')]
    submitted_at: Annotated[
        AwareDatetime, Field(description='ISO 8601 timestamp when feedback was submitted')
    ]

Base model for AdCP types with spec-compliant serialization.

AdCP JSON schemas use additionalProperties: false and do not allow null for optional fields. Therefore, optional fields must be omitted entirely when not present (not sent as null).

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.

self is explicitly positional-only to allow self as a field name.

Ancestors

• AdCPBaseModel
• pydantic.main.BaseModel

Class variables

var applied_at : pydantic.types.AwareDatetime | None

var creative_id : str | None

var feedback_id : str

var feedback_source : FeedbackSource

var measurement_period : MeasurementPeriod

var media_buy_id : str

var metric_type : MetricType

var model_config

var package_id : str | None

var performance_index : float

var status : Status

var submitted_at : pydantic.types.AwareDatetime

Inherited members

• AdCPBaseModel:
  • model_dump
  • model_dump_json

class Status (*args, **kwds)

Expand source code

class Status(Enum):
    accepted = 'accepted'
    queued = 'queued'
    applied = 'applied'
    rejected = 'rejected'

Create a collection of name/value pairs.

Example enumeration:

>>> class Color(Enum):
...     RED = 1
...     BLUE = 2
...     GREEN = 3

Access them by:

• attribute access::

>>> Color.RED
<Color.RED: 1>

• value lookup:

>>> Color(1)
<Color.RED: 1>

• name lookup:

>>> Color['RED']
<Color.RED: 1>

Enumerations can be iterated over, and know how many members they have:

>>> len(Color)
3

>>> list(Color)
[<Color.RED: 1>, <Color.BLUE: 2>, <Color.GREEN: 3>]

Methods can be added to enumerations, and members can have their own attributes – see the documentation for details.

Ancestors

• enum.Enum

Class variables

var accepted

var applied

var queued

var rejected