# Copyright 2021-2023 H2020 TeraFlow (https://www.teraflow-h2020.eu/)
#
# Licensed 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 "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import logging
import time
from typing import List

from common.proto.asyncio.optical_attack_detector_grpc import (
    OpticalAttackDetectorServiceStub,
)
from common.proto.asyncio.optical_attack_detector_pb2 import DetectionRequest
from common.Settings import get_log_level, get_setting
from grpclib.client import Channel
from opticalattackmanager.Config import MONITORING_INTERVAL
from prometheus_client import Counter, Histogram

# Create a metric to track time spent and requests made.
# TODO: adjust histogram buckets to more realistic values
LOOP_TIME = Histogram(
    "optical_security_loop_seconds", "Time taken by each security loop"
)
DROP_COUNTER = Counter(
    "optical_security_dropped_assessments",
    "Dropped assessments due to detector timeout",
)
log_level = get_log_level()
logging.basicConfig(level=log_level)
LOGGER = logging.getLogger(__name__)


async def detect_attack(
    host: str,
    port: int,
    context_id: str,
    service_id: str,
    kpi_id: str,
    timeout: float = 10.0,
) -> None:
    try:
        LOGGER.info("Sending request for {}...".format(service_id))
        async with Channel(host, port) as channel:
            stub = OpticalAttackDetectorServiceStub(channel)

            request: DetectionRequest = DetectionRequest()
            request.service_id.context_id.context_uuid.uuid = context_id
            request.service_id.service_uuid.uuid = str(service_id)

            request.kpi_id.kpi_id.uuid = kpi_id

            await stub.DetectAttack(request, timeout=timeout)
        LOGGER.info("Monitoring finished for {}".format(service_id))
    except Exception as e:
        LOGGER.warning("Exception while processing service_id {}".format(service_id))
        LOGGER.exception(e)
        DROP_COUNTER.inc()


async def monitor_services(terminate, service_list: List):

    monitoring_interval = int(
        get_setting("MONITORING_INTERVAL", default=MONITORING_INTERVAL)
    )

    host = get_setting("OPTICALATTACKDETECTORSERVICE_SERVICE_HOST")
    port = int(get_setting("OPTICALATTACKDETECTORSERVICE_SERVICE_PORT_GRPC"))

    LOGGER.info("Starting execution of the async loop")

    while not terminate.is_set():

        if len(service_list) == 0:
            LOGGER.debug("No services to monitor...")
            time.sleep(monitoring_interval)
            continue

        LOGGER.info("Starting new monitoring cycle...")

        start_time = time.time()

        tasks = []
        for service in service_list:
            aw = detect_attack(
                host,
                port,
                service["context"],
                service["service"],
                service["kpi"],
                # allow at most 90% of the monitoring interval to succeed
                monitoring_interval * 0.9,
            )
            tasks.append(aw)
        [await aw for aw in tasks]

        end_time = time.time()

        time_taken = end_time - start_time
        LOOP_TIME.observe(time_taken)
        LOGGER.info(
            "Monitoring loop with {} services took {:.3f} seconds ({:.2f}%)... "
            "Waiting for {:.2f} seconds...".format(
                len(service_list),
                time_taken,
                (time_taken / monitoring_interval) * 100,
                monitoring_interval - time_taken,
            )
        )

        if time_taken / monitoring_interval > 0.9:
            LOGGER.warning(
                "Monitoring loop is taking {} % of the desired time "
                "({} seconds)".format(
                    (time_taken / monitoring_interval) * 100, monitoring_interval
                )
            )
        if monitoring_interval - time_taken > 0:
            time.sleep(monitoring_interval - time_taken)