DagsterDocs

Source code for dagster_datadog.resources

from dagster import Field, StringSource, resource
from datadog import DogStatsd, initialize, statsd


class DataDogResource:
    # Mirroring levels from the dogstatsd library
    OK, WARNING, CRITICAL, UNKNOWN = (
        DogStatsd.OK,
        DogStatsd.WARNING,
        DogStatsd.CRITICAL,
        DogStatsd.UNKNOWN,
    )

    def __init__(self, api_key, app_key):
        initialize(api_key=api_key, app_key=app_key)

        # Pull in methods from the dogstatsd library
        for method in [
            "event",
            "gauge",
            "increment",
            "decrement",
            "histogram",
            "distribution",
            "set",
            "service_check",
            "timed",
            "timing",
        ]:
            setattr(self, method, getattr(statsd, method))


[docs]@resource( { "api_key": Field(StringSource, description="Datadog API key"), "app_key": Field(StringSource, description="Datadog application key"), }, description="This resource is for publishing to DataDog", ) def datadog_resource(context): """This resource is a thin wrapper over the `dogstatsd library <https://datadogpy.readthedocs.io/en/latest/>`_. As such, we directly mirror the public API methods of DogStatsd here; you can refer to the `DataDog documentation <https://docs.datadoghq.com/developers/dogstatsd/>`_ for how to use this resource. Examples: .. code-block:: python @solid(required_resource_keys={'datadog'}) def datadog_solid(context): dd = context.resources.datadog dd.event('Man down!', 'This server needs assistance.') dd.gauge('users.online', 1001, tags=["protocol:http"]) dd.increment('page.views') dd.decrement('page.views') dd.histogram('album.photo.count', 26, tags=["gender:female"]) dd.distribution('album.photo.count', 26, tags=["color:blue"]) dd.set('visitors.uniques', 999, tags=["browser:ie"]) dd.service_check('svc.check_name', dd.WARNING) dd.timing("query.response.time", 1234) # Use timed decorator @dd.timed('run_fn') def run_fn(): pass run_fn() @pipeline(mode_defs=[ModeDefinition(resource_defs={'datadog': datadog_resource})]) def dd_pipeline(): datadog_solid() result = execute_pipeline( dd_pipeline, {'resources': {'datadog': {'config': {'api_key': 'YOUR_KEY', 'app_key': 'YOUR_KEY'}}}}, ) """ return DataDogResource( context.resource_config.get("api_key"), context.resource_config.get("app_key") )