Module adcp.types.domains.collection.base_collection_source

Classes

class BaseCollectionSource1 (**data: Any)

Expand source code

class BaseCollectionSource1(AdCPBaseModel):
    model_config = ConfigDict(
        extra='forbid',
    )
    selection_type: Annotated[
        Literal['distribution_ids'],
        Field(
            description='Discriminator indicating selection by platform-independent distribution identifiers'
        ),
    ] = 'distribution_ids'
    identifiers: Annotated[
        list[Identifier],
        Field(
            description='Platform-independent identifiers (imdb_id, gracenote_id, eidr_id, etc.). Each identifier uniquely identifies a collection across all publishers. platform_channel_id is not allowed here: its identity is the tuple (publisher_domain, value), which this bare {type, value} shape cannot carry.',
            min_length=1,
        ),
    ]

Base 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 set additionalProperties: true override this with extra='allow' in their own model_config.

Set ADCP_STRICT_VALIDATION=1 in the environment ("1", "true", "yes", "on" are accepted) to flip the default to extra='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 adcp runs — mutating os.environ["ADCP_STRICT_VALIDATION"] after the first adcp import 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_config on 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.

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

Ancestors

• AdCPBaseModel
• pydantic.main.BaseModel

Class variables

var identifiers : list[Identifier]

var model_config

var selection_type : Literal['distribution_ids']

Inherited members

• AdCPBaseModel:
  • model_dump
  • model_dump_json
  • model_summary

class BaseCollectionSource2 (**data: Any)

Expand source code

class BaseCollectionSource2(AdCPBaseModel):
    model_config = ConfigDict(
        extra='forbid',
    )
    selection_type: Annotated[
        Literal['publisher_collections'],
        Field(
            description='Discriminator indicating selection by specific collection IDs within a publisher'
        ),
    ] = 'publisher_collections'
    publisher_domain: Annotated[
        str,
        Field(
            description="Domain where publisher's adagents.json is hosted",
            pattern='^[a-z0-9]([a-z0-9-]*[a-z0-9])?(\\.[a-z0-9]([a-z0-9-]*[a-z0-9])?)*$',
        ),
    ]
    collection_ids: Annotated[
        list[str],
        Field(
            description="Specific collection IDs from the publisher's adagents.json", min_length=1
        ),
    ]

Base 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 set additionalProperties: true override this with extra='allow' in their own model_config.

Set ADCP_STRICT_VALIDATION=1 in the environment ("1", "true", "yes", "on" are accepted) to flip the default to extra='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 adcp runs — mutating os.environ["ADCP_STRICT_VALIDATION"] after the first adcp import 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_config on 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.

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

Ancestors

• AdCPBaseModel
• pydantic.main.BaseModel

Class variables

var collection_ids : list[str]

var model_config

var publisher_domain : str

var selection_type : Literal['publisher_collections']

Inherited members

• AdCPBaseModel:
  • model_dump
  • model_dump_json
  • model_summary

class BaseCollectionSource3 (**data: Any)

Expand source code

class BaseCollectionSource3(AdCPBaseModel):
    model_config = ConfigDict(
        extra='forbid',
    )
    selection_type: Annotated[
        Literal['publisher_genres'],
        Field(description='Discriminator indicating selection by genre within a publisher'),
    ] = 'publisher_genres'
    publisher_domain: Annotated[
        str,
        Field(
            description="Domain where publisher's adagents.json is hosted",
            pattern='^[a-z0-9]([a-z0-9-]*[a-z0-9])?(\\.[a-z0-9]([a-z0-9-]*[a-z0-9])?)*$',
        ),
    ]
    genres: Annotated[
        list[str],
        Field(
            description="Genre values to match against the publisher's collections", min_length=1
        ),
    ]
    genre_taxonomy: Annotated[
        genre_taxonomy_1.GenreTaxonomy,
        Field(
            description="Taxonomy for the genre values. Required so sellers can interpret genre strings unambiguously. Use 'custom' for free-form values negotiated out of band."
        ),
    ]

Base 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 set additionalProperties: true override this with extra='allow' in their own model_config.

Set ADCP_STRICT_VALIDATION=1 in the environment ("1", "true", "yes", "on" are accepted) to flip the default to extra='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 adcp runs — mutating os.environ["ADCP_STRICT_VALIDATION"] after the first adcp import 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_config on 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.

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

Ancestors

• AdCPBaseModel
• pydantic.main.BaseModel

Class variables

var genre_taxonomy : GenreTaxonomy

var genres : list[str]

var model_config

var publisher_domain : str

var selection_type : Literal['publisher_genres']

Inherited members

• AdCPBaseModel:
  • model_dump
  • model_dump_json
  • model_summary

class Identifier (**data: Any)

Expand source code

class Identifier(AdCPBaseModel):
    model_config = ConfigDict(
        extra='forbid',
    )
    type: Annotated[
        distribution_identifier_type.DistributionIdentifierType,
        Field(description='Type of distribution identifier'),
    ]
    value: Annotated[str, Field(description='The identifier value')]

Base 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 set additionalProperties: true override this with extra='allow' in their own model_config.

Set ADCP_STRICT_VALIDATION=1 in the environment ("1", "true", "yes", "on" are accepted) to flip the default to extra='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 adcp runs — mutating os.environ["ADCP_STRICT_VALIDATION"] after the first adcp import 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_config on 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.

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

Ancestors

• AdCPBaseModel
• pydantic.main.BaseModel

Class variables

var model_config

var type : DistributionIdentifierType

var value : str

Inherited members

• AdCPBaseModel:
  • model_dump
  • model_dump_json
  • model_summary