imrichardwu commented on code in PR #62583:
URL: https://github.com/apache/airflow/pull/62583#discussion_r3023650957
##########
airflow-core/src/airflow/api_fastapi/core_api/datamodels/ui/deadline.py:
##########
@@ -44,3 +44,58 @@ class DeadlineCollectionResponse(BaseModel):
deadlines: Iterable[DeadlineResponse]
total_entries: int
+
+
+class DeadlineWithDagRunResponse(BaseModel):
+ """Deadline serializer for responses that includes DAG and DAG run
identifiers."""
+
+ id: UUID
+ deadline_time: datetime
+ missed: bool
+ created_at: datetime
+ dag_id: str = Field(validation_alias=AliasPath("dagrun", "dag_id"))
+ dag_run_id: str = Field(validation_alias=AliasPath("dagrun", "run_id"))
+ alert_name: str | None =
Field(validation_alias=AliasPath("deadline_alert", "name"), default=None)
+ alert_description: str | None = Field(
+ validation_alias=AliasPath("deadline_alert", "description"),
default=None
+ )
+
+
+class DeadlineWithDagRunCollectionResponse(BaseModel):
+ """Deadline Collection serializer for responses that includes DAG and DAG
run identifiers."""
+
+ deadlines: Iterable[DeadlineWithDagRunResponse]
+ total_entries: int
+
+
+class DeadlineAlertResponse(BaseModel):
+ """DeadlineAlert serializer for responses."""
+
+ id: UUID
+ name: str | None = None
+ description: str | None = None
+ reference_type: str
+ interval: float
+ created_at: datetime
+
+ @model_validator(mode="before")
+ @classmethod
+ def extract_reference_type(cls, data):
+ """Extract reference_type from the JSON reference column when
validating from an ORM object."""
+ if not isinstance(data, dict) and hasattr(data, "reference"):
+ return {
+ "id": data.id,
+ "name": data.name,
+ "description": data.description,
+ "reference_type": data.reference.get("reference_type", "") if
data.reference else "",
+ "interval": data.interval,
+ "created_at": data.created_at,
+ }
+ return data
Review Comment:
Just wondering, but is it always better to go declarative over imperative?
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