Source code for airflow.providers.datadog.sensors.datadog
#
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# 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
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# Unless required by applicable law or agreed to in writing,
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from __future__ import annotations
from typing import TYPE_CHECKING, Any, Callable
from datadog import api
from airflow.exceptions import AirflowException
from airflow.providers.datadog.hooks.datadog import DatadogHook
from airflow.sensors.base import BaseSensorOperator
if TYPE_CHECKING:
from airflow.utils.context import Context
[docs]class DatadogSensor(BaseSensorOperator):
"""
A sensor to listen, with a filter, to datadog event streams and determine if some event was emitted.
Depends on the datadog API, which has to be deployed on the same server where Airflow runs.
:param datadog_conn_id: The connection to datadog, containing metadata for api keys.
:param from_seconds_ago: POSIX timestamp start (default 3600).
:param up_to_seconds_from_now: POSIX timestamp end (default 0).
:param priority: Priority of your events, either low or normal.
:param sources: A comma separated list indicating what tags, if any,
should be used to filter the list of monitors by scope
:param tags: Get datadog events from specific sources.
:param response_check: A check against the 'requests' response object. The callable takes
the response object as the first positional argument and optionally any number of
keyword arguments available in the context dictionary. It should return True for
'pass' and False otherwise.
:param response_check: Callable[[dict[str, Any]], bool] | None
"""
def __init__(
self,
*,
datadog_conn_id: str = "datadog_default",
from_seconds_ago: int = 3600,
up_to_seconds_from_now: int = 0,
priority: str | None = None,
sources: str | None = None,
tags: list[str] | None = None,
response_check: Callable[[dict[str, Any]], bool] | None = None,
**kwargs,
) -> None:
super().__init__(**kwargs)
self.datadog_conn_id = datadog_conn_id
self.from_seconds_ago = from_seconds_ago
self.up_to_seconds_from_now = up_to_seconds_from_now
self.priority = priority
self.sources = sources
self.tags = tags
self.response_check = response_check
[docs] def poke(self, context: Context) -> bool:
# This instantiates the hook, but doesn't need it further,
# because the API authenticates globally (unfortunately),
# but for airflow this shouldn't matter too much, because each
# task instance runs in its own process anyway.
DatadogHook(datadog_conn_id=self.datadog_conn_id)
response = api.Event.query(
start=self.from_seconds_ago,
end=self.up_to_seconds_from_now,
priority=self.priority,
sources=self.sources,
tags=self.tags,
)
if isinstance(response, dict) and response.get("status", "ok") != "ok":
self.log.error("Unexpected Datadog result: %s", response)
message = "Datadog returned unexpected result"
raise AirflowException(message)
if self.response_check:
# run content check on response
return self.response_check(response)
# If no check was inserted, assume any event that matched yields true.
return bool(response)