File size: 1,781 Bytes
26e6f31 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 | import json
from typing import Dict, Optional
from typing_extensions import Literal
from aws_lambda_powertools import Logger, Tracer
from aws_lambda_powertools.utilities.batch import (
BatchProcessor,
EventType,
process_partial_response,
)
from aws_lambda_powertools.utilities.parser import BaseModel, field_validator
from aws_lambda_powertools.utilities.parser.models import (
DynamoDBStreamChangedRecordModel,
DynamoDBStreamRecordModel,
)
from aws_lambda_powertools.utilities.typing import LambdaContext
class Order(BaseModel):
item: dict
class OrderDynamoDB(BaseModel):
Message: Order
# auto transform json string
# so Pydantic can auto-initialize nested Order model
@field_validator("Message", mode="before")
def transform_message_to_dict(cls, value: Dict[Literal["S"], str]):
return json.loads(value["S"])
class OrderDynamoDBChangeRecord(DynamoDBStreamChangedRecordModel): # type: ignore[override]
NewImage: Optional[OrderDynamoDB]
OldImage: Optional[OrderDynamoDB]
class OrderDynamoDBRecord(DynamoDBStreamRecordModel): # type: ignore[override]
dynamodb: OrderDynamoDBChangeRecord
processor = BatchProcessor(event_type=EventType.DynamoDBStreams, model=OrderDynamoDBRecord)
tracer = Tracer()
logger = Logger()
@tracer.capture_method
def record_handler(record: OrderDynamoDBRecord):
if record.dynamodb.NewImage and record.dynamodb.NewImage.Message:
logger.info(record.dynamodb.NewImage.Message.item)
return record.dynamodb.NewImage.Message.item
@logger.inject_lambda_context
@tracer.capture_lambda_handler
def lambda_handler(event, context: LambdaContext):
return process_partial_response(event=event, record_handler=record_handler, processor=processor, context=context)
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