Source code for airflow.providers.datadog.hooks.datadog

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from __future__ import annotations

import time
from typing import Any

from datadog import api, initialize  # type: ignore[attr-defined]

from airflow.exceptions import AirflowException
from airflow.hooks.base import BaseHook
from airflow.utils.log.logging_mixin import LoggingMixin

[docs]class DatadogHook(BaseHook, LoggingMixin): """ Uses datadog API to send metrics of practically anything measurable. It's possible to track # of db records inserted/deleted, records read from file and many other useful metrics. 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. """
[docs] conn_name_attr = "datadog_conn_id"
[docs] default_conn_name = "datadog_default"
[docs] conn_type = "datadog"
[docs] hook_name = "Datadog"
def __init__(self, datadog_conn_id: str = "datadog_default") -> None: super().__init__() conn = self.get_connection(datadog_conn_id) self.api_key = conn.extra_dejson.get("api_key", None) self.app_key = conn.extra_dejson.get("app_key", None) self.api_host = conn.extra_dejson.get("api_host", None) self.source_type_name = conn.extra_dejson.get("source_type_name", None) # If the host is populated, it will use that hostname instead. # for all metric submissions. = if self.api_key is None: raise AirflowException("api_key must be specified in the Datadog connection details")"Setting up api keys for Datadog") initialize(api_key=self.api_key, app_key=self.app_key, api_host=self.api_host)
[docs] def validate_response(self, response: dict[str, Any]) -> None: """Validate Datadog response.""" if response["status"] != "ok": self.log.error("Datadog returned: %s", response) raise AirflowException("Error status received from Datadog")
[docs] def send_metric( self, metric_name: str, datapoint: float | int, tags: list[str] | None = None, type_: str | None = None, interval: int | None = None, ) -> dict[str, Any]: """ Send a single datapoint metric to Datadog. :param metric_name: The name of the metric :param datapoint: A single integer or float related to the metric :param tags: A list of tags associated with the metric :param type_: Type of your metric: gauge, rate, or count :param interval: If the type of the metric is rate or count, define the corresponding interval """ response = api.Metric.send( metric=metric_name, points=datapoint,, tags=tags, type=type_, interval=interval ) self.validate_response(response) return response
[docs] def query_metric(self, query: str, from_seconds_ago: int, to_seconds_ago: int) -> dict[str, Any]: """ Query datadog for a metric, potentially with some function applied to it and return the result. :param query: The datadog query to execute (see datadog docs) :param from_seconds_ago: How many seconds ago to start querying for. :param to_seconds_ago: Up to how many seconds ago to query for. """ now = int(time.time()) response = api.Metric.query(start=now - from_seconds_ago, end=now - to_seconds_ago, query=query) self.validate_response(response) return response
[docs] def post_event( self, title: str, text: str, aggregation_key: str | None = None, alert_type: str | None = None, date_happened: int | None = None, handle: str | None = None, priority: str | None = None, related_event_id: int | None = None, tags: list[str] | None = None, device_name: list[str] | None = None, ) -> dict[str, Any]: """ Post an event to datadog (processing finished, potentially alerts, other issues). Think about this as a means to maintain persistence of alerts, rather than alerting itself. :param title: The title of the event :param text: The body of the event (more information) :param aggregation_key: Key that can be used to aggregate this event in a stream :param alert_type: The alert type for the event, one of ["error", "warning", "info", "success"] :param date_happened: POSIX timestamp of the event; defaults to now :handle: User to post the event as; defaults to owner of the application key used to submit. :param handle: str :param priority: Priority to post the event as. ("normal" or "low", defaults to "normal") :param related_event_id: Post event as a child of the given event :param tags: List of tags to apply to the event :param device_name: device_name to post the event with """ response = api.Event.create( title=title, text=text, aggregation_key=aggregation_key, alert_type=alert_type, date_happened=date_happened, handle=handle, priority=priority, related_event_id=related_event_id, tags=tags,, device_name=device_name, source_type_name=self.source_type_name, ) self.validate_response(response) return response
[docs] def get_connection_form_widgets(cls) -> dict[str, Any]: """Return connection widgets to add to connection form.""" from flask_appbuilder.fieldwidgets import BS3TextFieldWidget from flask_babel import lazy_gettext from wtforms import StringField return { "api_host": StringField(lazy_gettext("API endpoint"), widget=BS3TextFieldWidget()), "api_key": StringField(lazy_gettext("API key"), widget=BS3TextFieldWidget()), "app_key": StringField(lazy_gettext("Application key"), widget=BS3TextFieldWidget()), "source_type_name": StringField(lazy_gettext("Source type name"), widget=BS3TextFieldWidget()), }
[docs] def get_ui_field_behaviour(cls) -> dict[str, Any]: """Return custom field behaviour.""" return { "hidden_fields": ["schema", "login", "password", "port", "extra"], "relabeling": {"host": "Events host name"}, }

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