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from __future__ import annotations

import asyncio
from functools import cached_property
from typing import Any, AsyncIterator

from import GlueJobHook
from import GlueCatalogHook
from airflow.triggers.base import BaseTrigger, TriggerEvent

[docs]class GlueJobCompleteTrigger(BaseTrigger): """ Watches for a glue job, triggers when it finishes. :param job_name: glue job name :param run_id: the ID of the specific run to watch for that job :param verbose: whether to print the job's logs in airflow logs or not :param aws_conn_id: The Airflow connection used for AWS credentials. """ def __init__( self, job_name: str, run_id: str, verbose: bool, aws_conn_id: str, job_poll_interval: int | float, ): super().__init__() self.job_name = job_name self.run_id = run_id self.verbose = verbose self.aws_conn_id = aws_conn_id self.job_poll_interval = job_poll_interval
[docs] def serialize(self) -> tuple[str, dict[str, Any]]: return ( # dynamically generate the fully qualified name of the class self.__class__.__module__ + "." + self.__class__.__qualname__, { "job_name": self.job_name, "run_id": self.run_id, "verbose": str(self.verbose), "aws_conn_id": self.aws_conn_id, "job_poll_interval": self.job_poll_interval, }, )
[docs] async def run(self) -> AsyncIterator[TriggerEvent]: hook = GlueJobHook(aws_conn_id=self.aws_conn_id, job_poll_interval=self.job_poll_interval) await hook.async_job_completion(self.job_name, self.run_id, self.verbose) yield TriggerEvent({"status": "success", "message": "Job done", "value": self.run_id})
[docs]class GlueCatalogPartitionTrigger(BaseTrigger): """ Asynchronously waits for a partition to show up in AWS Glue Catalog. :param database_name: The name of the catalog database where the partitions reside. :param table_name: The name of the table to wait for, supports the dot notation (my_database.my_table) :param expression: The partition clause to wait for. This is passed as is to the AWS Glue Catalog API's get_partitions function, and supports SQL like notation as in ``ds='2015-01-01' AND type='value'`` and comparison operators as in ``"ds>=2015-01-01"``. See #aws-glue-api-catalog-partitions-GetPartitions :param aws_conn_id: ID of the Airflow connection where credentials and extra configuration are stored :param region_name: Optional aws region name (example: us-east-1). Uses region from connection if not specified. :param waiter_delay: Number of seconds to wait between two checks. Default is 60 seconds. """ def __init__( self, database_name: str, table_name: str, expression: str = "", aws_conn_id: str = "aws_default", region_name: str | None = None, waiter_delay: int = 60, ): self.database_name = database_name self.table_name = table_name self.expression = expression self.aws_conn_id = aws_conn_id self.region_name = region_name self.waiter_delay = waiter_delay
[docs] def serialize(self) -> tuple[str, dict[str, Any]]: return ( # dynamically generate the fully qualified name of the class self.__class__.__module__ + "." + self.__class__.__qualname__, { "database_name": self.database_name, "table_name": self.table_name, "expression": self.expression, "aws_conn_id": self.aws_conn_id, "region_name": self.region_name, "waiter_delay": self.waiter_delay, }, )
[docs] def hook(self) -> GlueCatalogHook: return GlueCatalogHook(aws_conn_id=self.aws_conn_id, region_name=self.region_name)
[docs] async def poke(self, client: Any) -> bool: if "." in self.table_name: self.database_name, self.table_name = self.table_name.split(".") "Poking for table %s. %s, expression %s", self.database_name, self.table_name, self.expression ) partitions = await self.hook.async_get_partitions( client=client, database_name=self.database_name, table_name=self.table_name, expression=self.expression, ) return bool(partitions)
[docs] async def run(self) -> AsyncIterator[TriggerEvent]: async with self.hook.async_conn as client: while True: result = await self.poke(client=client) if result: yield TriggerEvent({"status": "success"}) break else: await asyncio.sleep(self.waiter_delay)

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