airflow_scheduler/.venv/Lib/site-packages/airflow/metrics/datadog_logger.py

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# 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
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# KIND, either express or implied.  See the License for the
# specific language governing permissions and limitations
# under the License.

from __future__ import annotations

import datetime
import logging
from typing import TYPE_CHECKING

from airflow.configuration import conf
from airflow.metrics.protocols import Timer
from airflow.metrics.validators import (
    AllowListValidator,
    BlockListValidator,
    get_validator,
    validate_stat,
)

if TYPE_CHECKING:
    from datadog import DogStatsd

    from airflow.metrics.protocols import DeltaType, TimerProtocol
    from airflow.metrics.validators import (
        ListValidator,
    )

log = logging.getLogger(__name__)


class SafeDogStatsdLogger:
    """DogStatsd Logger."""

    def __init__(
        self,
        dogstatsd_client: DogStatsd,
        metrics_validator: ListValidator = AllowListValidator(),
        metrics_tags: bool = False,
        metric_tags_validator: ListValidator = AllowListValidator(),
    ) -> None:
        self.dogstatsd = dogstatsd_client
        self.metrics_validator = metrics_validator
        self.metrics_tags = metrics_tags
        self.metric_tags_validator = metric_tags_validator

    @validate_stat
    def incr(
        self,
        stat: str,
        count: int = 1,
        rate: float = 1,
        *,
        tags: dict[str, str] | None = None,
    ) -> None:
        """Increment stat."""
        if self.metrics_tags and isinstance(tags, dict):
            tags_list = [
                f"{key}:{value}" for key, value in tags.items() if self.metric_tags_validator.test(key)
            ]
        else:
            tags_list = []
        if self.metrics_validator.test(stat):
            return self.dogstatsd.increment(metric=stat, value=count, tags=tags_list, sample_rate=rate)
        return None

    @validate_stat
    def decr(
        self,
        stat: str,
        count: int = 1,
        rate: float = 1,
        *,
        tags: dict[str, str] | None = None,
    ) -> None:
        """Decrement stat."""
        if self.metrics_tags and isinstance(tags, dict):
            tags_list = [
                f"{key}:{value}" for key, value in tags.items() if self.metric_tags_validator.test(key)
            ]
        else:
            tags_list = []
        if self.metrics_validator.test(stat):
            return self.dogstatsd.decrement(metric=stat, value=count, tags=tags_list, sample_rate=rate)
        return None

    @validate_stat
    def gauge(
        self,
        stat: str,
        value: int | float,
        rate: float = 1,
        delta: bool = False,
        *,
        tags: dict[str, str] | None = None,
    ) -> None:
        """Gauge stat."""
        if self.metrics_tags and isinstance(tags, dict):
            tags_list = [
                f"{key}:{value}" for key, value in tags.items() if self.metric_tags_validator.test(key)
            ]
        else:
            tags_list = []
        if self.metrics_validator.test(stat):
            return self.dogstatsd.gauge(metric=stat, value=value, tags=tags_list, sample_rate=rate)
        return None

    @validate_stat
    def timing(
        self,
        stat: str,
        dt: DeltaType,
        *,
        tags: dict[str, str] | None = None,
    ) -> None:
        """Stats timing."""
        if self.metrics_tags and isinstance(tags, dict):
            tags_list = [
                f"{key}:{value}" for key, value in tags.items() if self.metric_tags_validator.test(key)
            ]
        else:
            tags_list = []
        if self.metrics_validator.test(stat):
            if isinstance(dt, datetime.timedelta):
                dt = dt.total_seconds()
            return self.dogstatsd.timing(metric=stat, value=dt, tags=tags_list)
        return None

    @validate_stat
    def timer(
        self,
        stat: str | None = None,
        tags: dict[str, str] | None = None,
        **kwargs,
    ) -> TimerProtocol:
        """Timer metric that can be cancelled."""
        if self.metrics_tags and isinstance(tags, dict):
            tags_list = [
                f"{key}:{value}" for key, value in tags.items() if self.metric_tags_validator.test(key)
            ]
        else:
            tags_list = []
        if stat and self.metrics_validator.test(stat):
            return Timer(self.dogstatsd.timed(stat, tags=tags_list, **kwargs))
        return Timer()


def get_dogstatsd_logger(cls) -> SafeDogStatsdLogger:
    """Get DataDog StatsD logger."""
    from datadog import DogStatsd

    dogstatsd = DogStatsd(
        host=conf.get("metrics", "statsd_host"),
        port=conf.getint("metrics", "statsd_port"),
        namespace=conf.get("metrics", "statsd_prefix"),
        constant_tags=cls.get_constant_tags(),
    )
    datadog_metrics_tags = conf.getboolean("metrics", "statsd_datadog_metrics_tags", fallback=True)
    metric_tags_validator = BlockListValidator(conf.get("metrics", "statsd_disabled_tags", fallback=None))
    return SafeDogStatsdLogger(dogstatsd, get_validator(), datadog_metrics_tags, metric_tags_validator)