#
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
from __future__ import annotations
import asyncio
import json
from datetime import datetime
from typing import Any, Sequence
from dateutil import parser
from google.cloud.orchestration.airflow.service_v1.types import ExecuteAirflowCommandResponse
from airflow.exceptions import AirflowException
from airflow.providers.google.cloud.hooks.cloud_composer import CloudComposerAsyncHook
from airflow.triggers.base import BaseTrigger, TriggerEvent
[docs]class CloudComposerExecutionTrigger(BaseTrigger):
"""The trigger handles the async communication with the Google Cloud Composer."""
def __init__(
self,
project_id: str,
region: str,
operation_name: str,
gcp_conn_id: str = "google_cloud_default",
impersonation_chain: str | Sequence[str] | None = None,
pooling_period_seconds: int = 30,
):
super().__init__()
self.project_id = project_id
self.region = region
self.operation_name = operation_name
self.gcp_conn_id = gcp_conn_id
self.impersonation_chain = impersonation_chain
self.pooling_period_seconds = pooling_period_seconds
self.gcp_hook = CloudComposerAsyncHook(
gcp_conn_id=self.gcp_conn_id,
impersonation_chain=self.impersonation_chain,
)
[docs] def serialize(self) -> tuple[str, dict[str, Any]]:
return (
"airflow.providers.google.cloud.triggers.cloud_composer.CloudComposerExecutionTrigger",
{
"project_id": self.project_id,
"region": self.region,
"operation_name": self.operation_name,
"gcp_conn_id": self.gcp_conn_id,
"impersonation_chain": self.impersonation_chain,
"pooling_period_seconds": self.pooling_period_seconds,
},
)
[docs] async def run(self):
while True:
operation = await self.gcp_hook.get_operation(operation_name=self.operation_name)
if operation.done:
break
elif operation.error.message:
raise AirflowException(f"Cloud Composer Environment error: {operation.error.message}")
await asyncio.sleep(self.pooling_period_seconds)
yield TriggerEvent(
{
"operation_name": operation.name,
"operation_done": operation.done,
}
)
[docs]class CloudComposerAirflowCLICommandTrigger(BaseTrigger):
"""The trigger wait for the Airflow CLI command result."""
def __init__(
self,
project_id: str,
region: str,
environment_id: str,
execution_cmd_info: dict,
gcp_conn_id: str = "google_cloud_default",
impersonation_chain: str | Sequence[str] | None = None,
poll_interval: int = 10,
):
super().__init__()
self.project_id = project_id
self.region = region
self.environment_id = environment_id
self.execution_cmd_info = execution_cmd_info
self.gcp_conn_id = gcp_conn_id
self.impersonation_chain = impersonation_chain
self.poll_interval = poll_interval
self.gcp_hook = CloudComposerAsyncHook(
gcp_conn_id=self.gcp_conn_id,
impersonation_chain=self.impersonation_chain,
)
[docs] def serialize(self) -> tuple[str, dict[str, Any]]:
return (
"airflow.providers.google.cloud.triggers.cloud_composer.CloudComposerAirflowCLICommandTrigger",
{
"project_id": self.project_id,
"region": self.region,
"environment_id": self.environment_id,
"execution_cmd_info": self.execution_cmd_info,
"gcp_conn_id": self.gcp_conn_id,
"impersonation_chain": self.impersonation_chain,
"poll_interval": self.poll_interval,
},
)
[docs] async def run(self):
try:
result = await self.gcp_hook.wait_command_execution_result(
project_id=self.project_id,
region=self.region,
environment_id=self.environment_id,
execution_cmd_info=self.execution_cmd_info,
poll_interval=self.poll_interval,
)
except AirflowException as ex:
yield TriggerEvent(
{
"status": "error",
"message": str(ex),
}
)
return
yield TriggerEvent(
{
"status": "success",
"result": result,
}
)
return
[docs]class CloudComposerDAGRunTrigger(BaseTrigger):
"""The trigger wait for the DAG run completion."""
def __init__(
self,
project_id: str,
region: str,
environment_id: str,
composer_dag_id: str,
start_date: datetime,
end_date: datetime,
allowed_states: list[str],
gcp_conn_id: str = "google_cloud_default",
impersonation_chain: str | Sequence[str] | None = None,
poll_interval: int = 10,
):
super().__init__()
self.project_id = project_id
self.region = region
self.environment_id = environment_id
self.composer_dag_id = composer_dag_id
self.start_date = start_date
self.end_date = end_date
self.allowed_states = allowed_states
self.gcp_conn_id = gcp_conn_id
self.impersonation_chain = impersonation_chain
self.poll_interval = poll_interval
self.gcp_hook = CloudComposerAsyncHook(
gcp_conn_id=self.gcp_conn_id,
impersonation_chain=self.impersonation_chain,
)
[docs] def serialize(self) -> tuple[str, dict[str, Any]]:
return (
"airflow.providers.google.cloud.triggers.cloud_composer.CloudComposerDAGRunTrigger",
{
"project_id": self.project_id,
"region": self.region,
"environment_id": self.environment_id,
"composer_dag_id": self.composer_dag_id,
"start_date": self.start_date,
"end_date": self.end_date,
"allowed_states": self.allowed_states,
"gcp_conn_id": self.gcp_conn_id,
"impersonation_chain": self.impersonation_chain,
"poll_interval": self.poll_interval,
},
)
async def _pull_dag_runs(self) -> list[dict]:
"""Pull the list of dag runs."""
dag_runs_cmd = await self.gcp_hook.execute_airflow_command(
project_id=self.project_id,
region=self.region,
environment_id=self.environment_id,
command="dags",
subcommand="list-runs",
parameters=["-d", self.composer_dag_id, "-o", "json"],
)
cmd_result = await self.gcp_hook.wait_command_execution_result(
project_id=self.project_id,
region=self.region,
environment_id=self.environment_id,
execution_cmd_info=ExecuteAirflowCommandResponse.to_dict(dag_runs_cmd),
)
dag_runs = json.loads(cmd_result["output"][0]["content"])
return dag_runs
def _check_dag_runs_states(
self,
dag_runs: list[dict],
start_date: datetime,
end_date: datetime,
) -> bool:
for dag_run in dag_runs:
if (
start_date.timestamp()
< parser.parse(dag_run["execution_date"]).timestamp()
< end_date.timestamp()
) and dag_run["state"] not in self.allowed_states:
return False
return True
[docs] async def run(self):
try:
while True:
if datetime.now(self.end_date.tzinfo).timestamp() > self.end_date.timestamp():
dag_runs = await self._pull_dag_runs()
self.log.info("Sensor waits for allowed states: %s", self.allowed_states)
if self._check_dag_runs_states(
dag_runs=dag_runs,
start_date=self.start_date,
end_date=self.end_date,
):
yield TriggerEvent({"status": "success"})
return
self.log.info("Sleeping for %s seconds.", self.poll_interval)
await asyncio.sleep(self.poll_interval)
except AirflowException as ex:
yield TriggerEvent(
{
"status": "error",
"message": str(ex),
}
)
return