Module `aws_lambda_powertools.utilities.parser.models.kafka`

Classes

class KafkaBaseEventModel (**data: Any)

Usage docs: https://docs.pydantic.dev/2.10/concepts/models/

A base class for creating Pydantic models.

Attributes

__class_vars__: The names of the class variables defined on the model.
__private_attributes__: Metadata about the private attributes of the model.
__signature__: The synthesized __init__ [Signature][inspect.Signature] of the model.
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.
__pydantic_core_schema__: The core schema of the model.
__pydantic_custom_init__: Whether the model has a custom __init__ function.
__pydantic_decorators__: Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.
__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to args, origin, parameters in typing-module generics. May eventually be replaced by these.
__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.
__pydantic_post_init__: The name of the post-init method for the model, if defined.
__pydantic_root_model__: Whether the model is a [RootModel][pydantic.root_model.RootModel].
__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.
__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.
__pydantic_fields__: A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects.
__pydantic_computed_fields__: A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.
__pydantic_extra__: A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.
__pydantic_fields_set__: The names of fields explicitly set during instantiation.
__pydantic_private__: Values of private attributes set on the model instance.

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.

Expand source code

class KafkaBaseEventModel(BaseModel):
    bootstrapServers: List[str]
    records: Dict[str, List[KafkaRecordModel]]

    @field_validator("bootstrapServers", mode="before")
    def split_servers(cls, value):
        return None if not value else value.split(SERVERS_DELIMITER)

Ancestors

pydantic.main.BaseModel

Class variables

var bootstrapServers : List[str]
var model_config
var records : Dict[str, List[KafkaRecordModel]]

Static methods

def split_servers(value)

class KafkaMskEventModel (**data: Any)

Fully-managed AWS Apache Kafka event trigger Documentation:

https://docs.aws.amazon.com/lambda/latest/dg/with-msk.html

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.

Expand source code

class KafkaMskEventModel(KafkaBaseEventModel):
    """Fully-managed AWS Apache Kafka event trigger
    Documentation:
    --------------
    - https://docs.aws.amazon.com/lambda/latest/dg/with-msk.html
    """

    eventSource: Literal["aws:kafka"]
    eventSourceArn: str

Ancestors

KafkaBaseEventModel
pydantic.main.BaseModel

Class variables

var eventSource : Literal['aws:kafka']
var eventSourceArn : str
var model_config

class KafkaRecordModel (**data: Any)

Usage docs: https://docs.pydantic.dev/2.10/concepts/models/

A base class for creating Pydantic models.

Attributes

__class_vars__: The names of the class variables defined on the model.
__private_attributes__: Metadata about the private attributes of the model.
__signature__: The synthesized __init__ [Signature][inspect.Signature] of the model.
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.
__pydantic_core_schema__: The core schema of the model.
__pydantic_custom_init__: Whether the model has a custom __init__ function.
__pydantic_decorators__: Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.
__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to args, origin, parameters in typing-module generics. May eventually be replaced by these.
__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.
__pydantic_post_init__: The name of the post-init method for the model, if defined.
__pydantic_root_model__: Whether the model is a [RootModel][pydantic.root_model.RootModel].
__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.
__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.
__pydantic_fields__: A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects.
__pydantic_computed_fields__: A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.
__pydantic_extra__: A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.
__pydantic_fields_set__: The names of fields explicitly set during instantiation.
__pydantic_private__: Values of private attributes set on the model instance.

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.

Expand source code

class KafkaRecordModel(BaseModel):
    topic: str
    partition: int
    offset: int
    timestamp: datetime
    timestampType: str
    key: bytes
    value: Union[str, Type[BaseModel]]
    headers: List[Dict[str, bytes]]

    # Added type ignore to keep compatibility between Pydantic v1 and v2
    _decode_key = field_validator("key")(base64_decode)  # type: ignore[type-var, unused-ignore]

    @field_validator("value", mode="before")
    def data_base64_decode(cls, value):
        as_bytes = base64_decode(value)
        return bytes_to_string(as_bytes)

    @field_validator("headers", mode="before")
    def decode_headers_list(cls, value):
        for header in value:
            for key, values in header.items():
                header[key] = bytes(values)
        return value

Ancestors

pydantic.main.BaseModel

Class variables

var headers : List[Dict[str, bytes]]
var key : bytes
var model_config
var offset : int
var partition : int
var timestamp : datetime.datetime
var timestampType : str
var topic : str
var value : Union[str, Type[pydantic.main.BaseModel]]

Static methods

def data_base64_decode(value)
def decode_headers_list(value)

class KafkaSelfManagedEventModel (**data: Any)

Self-managed Apache Kafka event trigger Documentation:

https://docs.aws.amazon.com/lambda/latest/dg/with-kafka.html

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.

Expand source code

class KafkaSelfManagedEventModel(KafkaBaseEventModel):
    """Self-managed Apache Kafka event trigger
    Documentation:
    --------------
    - https://docs.aws.amazon.com/lambda/latest/dg/with-kafka.html
    """

    eventSource: Literal["SelfManagedKafka"]

Ancestors

KafkaBaseEventModel
pydantic.main.BaseModel

Class variables

var eventSource : Literal['SelfManagedKafka']
var model_config