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import datetime
from functools import cached_property
from typing import TYPE_CHECKING, Optional

from airflow.executors.executor_loader import ExecutorLoader
from airflow.jobs.base_job_runner import BaseJobRunner
from airflow.utils.pydantic import BaseModel as BaseModelPydantic, ConfigDict


def check_runner_initialized(job_runner: Optional[BaseJobRunner], job_type: str) -> BaseJobRunner:
    if job_runner is None:
        raise ValueError(f"In order to run {job_type} you need to initialize the {job_type}Runner first.")
    return job_runner


class JobPydantic(BaseModelPydantic):
    """Serializable representation of the Job ORM SqlAlchemyModel used by internal API."""

    id: Optional[int]
    dag_id: Optional[str]
    state: Optional[str]
    job_type: Optional[str]
    start_date: Optional[datetime.datetime]
    end_date: Optional[datetime.datetime]
    latest_heartbeat: datetime.datetime
    executor_class: Optional[str]
    hostname: Optional[str]
    unixname: Optional[str]
    grace_multiplier: float = 2.1

    model_config = ConfigDict(from_attributes=True)

    @cached_property
    def executor(self):
        return ExecutorLoader.get_default_executor()

    @cached_property
    def heartrate(self) -> float:
        from airflow.jobs.job import Job

        if TYPE_CHECKING:
            assert self.job_type is not None
        return Job._heartrate(self.job_type)

    def is_alive(self) -> bool:
        """Is this job currently alive."""
        from airflow.jobs.job import Job, health_check_threshold

        return Job._is_alive(
            state=self.state,
            health_check_threshold_value=health_check_threshold(self.job_type, self.heartrate),
            latest_heartbeat=self.latest_heartbeat,
        )
