# Path: autopush/logging.py
# IGNORED_KEYS = frozenset([
#     "factory",
#     "failure",
#     "format",
#     "isError",
#     "log_failure",
#     "log_format",
#     "log_flattened",
#     "log_level",
#     "log_legacy",
#     "log_logger",
#     "log_source",
#     "log_system",
#     "log_text",
#     "log_time",
#     "log_trace",
#     "message",
#     "message_type",
#     "severity",
#     "task_level",
#     "time",
#     "timestamp",
#     "type",
#     "why",
# ])
#     RECORD_SEPARATOR = u"\x1e"
#     MAX_RECORD_SIZE = 1024 * 1024
#     MAX_REQUEST_SIZE = 4 * 1024 * 1024
#     MAX_RECORD_BATCH = 500
#     MAX_INTERVAL = 30
# def begin_or_register(observer, redirectStandardIO=False, **kwargs):
#     def __init__(self, logger_name, log_level="debug", log_format="json",
#                  log_output="stdout", sentry_dsn=None,
#                  firehose_delivery_stream=None):
#     def __call__(self, event):
#     def raven_log(self, event):
#     def json_format(self, event):
#         def to_fields(kv):
#     def start(self):
#     def stop(self):
#     def setup_logging(cls, logger_name, log_level="info", log_format="json",
#                       log_output="stdout", sentry_dsn=None,
#                       firehose_delivery_stream=None,
#                       no_aws=False):
#     def __init__(self, stream_name, maxsize=0):
#     def start(self):
#     def stop(self):
#     def process(self, record):
#     def _worker(self):
#     def _send_record_batch(self):
# class PushLogger(object):
# class FirehoseProcessor(object):


from typing import (  # noqa
    TYPE_CHECKING,
    Any,
    Optional,
    Sequence
)
from twisted.internet import reactor
from txstatsd.client import StatsDClientProtocol, TwistedStatsDClient
from txstatsd.metrics.metrics import Metrics
from datadog import ThreadStats
from autopush import logging
    from autopush.config import AutopushConfig  # noqa
import datadog
        self._client = ThreadStats()
        self._flush_interval = flush_interval
        self._host = hostname
        self._namespace = namespace

    def _prefix_name(self, name):
        return "%s.%s" % (self._namespace, name)

    def start(self):
        self._client.start(flush_interval=self._flush_interval,
                           roll_up_interval=self._flush_interval)

    def increment(self, name, count=1, **kwargs):
        self._client.increment(self._prefix_name(name), count, host=self._host,
                               **kwargs)

    def gauge(self, name, count, **kwargs):
        self._client.gauge(self._prefix_name(name), count, host=self._host,
                           **kwargs)

    def timing(self, name, duration, **kwargs):
        self._client.timing(self._prefix_name(name), value=duration,
                            host=self._host, **kwargs)


def from_config(conf):
    # type: (AutopushConfig) -> IMetrics
    """Create an IMetrics from the given config"""
    if conf.datadog_api_key:
        return DatadogMetrics(

# Path: autopush/logging.py
# IGNORED_KEYS = frozenset([
#     "factory",
#     "failure",
#     "format",
#     "isError",
#     "log_failure",
#     "log_format",
#     "log_flattened",
#     "log_level",
#     "log_legacy",
#     "log_logger",
#     "log_source",
#     "log_system",
#     "log_text",
#     "log_time",
#     "log_trace",
#     "message",
#     "message_type",
#     "severity",
#     "task_level",
#     "time",
#     "timestamp",
#     "type",
#     "why",
# ])
#     RECORD_SEPARATOR = u"\x1e"
#     MAX_RECORD_SIZE = 1024 * 1024
#     MAX_REQUEST_SIZE = 4 * 1024 * 1024
#     MAX_RECORD_BATCH = 500
#     MAX_INTERVAL = 30
# def begin_or_register(observer, redirectStandardIO=False, **kwargs):
#     def __init__(self, logger_name, log_level="debug", log_format="json",
#                  log_output="stdout", sentry_dsn=None,
#                  firehose_delivery_stream=None):
#     def __call__(self, event):
#     def raven_log(self, event):
#     def json_format(self, event):
#         def to_fields(kv):
#     def start(self):
#     def stop(self):
#     def setup_logging(cls, logger_name, log_level="info", log_format="json",
#                       log_output="stdout", sentry_dsn=None,
#                       firehose_delivery_stream=None,
#                       no_aws=False):
#     def __init__(self, stream_name, maxsize=0):
#     def start(self):
#     def stop(self):
#     def process(self, record):
#     def _worker(self):
#     def _send_record_batch(self):
# class PushLogger(object):
# class FirehoseProcessor(object):


# Path: autopush/metrics.py
from typing import (  # noqa
    TYPE_CHECKING,
    Any,
    Optional,
    Sequence
)
from twisted.internet import reactor
from txstatsd.client import StatsDClientProtocol, TwistedStatsDClient
from txstatsd.metrics.metrics import Metrics
from datadog import ThreadStats
from autopush import logging
    from autopush.config import AutopushConfig  # noqa
import datadog

        self._client = ThreadStats()
        self._flush_interval = flush_interval
        self._host = hostname
        self._namespace = namespace

    def _prefix_name(self, name):
        return "%s.%s" % (self._namespace, name)

    def start(self):
        self._client.start(flush_interval=self._flush_interval,
                           roll_up_interval=self._flush_interval)

    def increment(self, name, count=1, **kwargs):
        self._client.increment(self._prefix_name(name), count, host=self._host,
                               **kwargs)

    def gauge(self, name, count, **kwargs):
        self._client.gauge(self._prefix_name(name), count, host=self._host,
                           **kwargs)

    def timing(self, name, duration, **kwargs):
        self._client.timing(self._prefix_name(name), value=duration,
                            host=self._host, **kwargs)


def from_config(conf):
    # type: (AutopushConfig) -> IMetrics
    """Create an IMetrics from the given config"""
    if conf.datadog_api_key:
        return DatadogMetrics(

            hostname=logging.instance_id_or_hostname if conf.ami_id else