# Copyright 2022-2024 ETSI OSG/SDG TeraFlowSDN (TFS) (https://tfs.etsi.org/)
#
# 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, grpc, json, requests
from typing import Tuple, Any, List, Dict
from datetime import datetime
from common.method_wrappers.Decorator import MetricsPool, safe_and_metered_rpc_method
from common.tools.kafka.Variables import KafkaConfig, KafkaTopic

from common.proto.context_pb2 import Empty
from common.proto.kpi_value_api_pb2_grpc import KpiValueAPIServiceServicer
from common.proto.kpi_value_api_pb2 import KpiValueList, KpiValueFilter, KpiValue, KpiValueType

from confluent_kafka import Producer as KafkaProducer

from .NameMapping import NameMapping


LOGGER       = logging.getLogger(__name__)
METRICS_POOL = MetricsPool('KpiValueAPI', 'NBIgRPC')
PROM_URL     = "http://localhost:9090"

class KpiValueApiServiceServicerImpl(KpiValueAPIServiceServicer):
    def __init__(self, name_mapping : NameMapping):
        LOGGER.debug('Init KpiValueApiService')
    
    @safe_and_metered_rpc_method(METRICS_POOL, LOGGER)
    def StoreKpiValues(self, request: KpiValueList, grpc_context: grpc.ServicerContext
                       ) -> Empty:
        LOGGER.debug('StoreKpiValues: Received gRPC message object: {:}'.format(request))
        
        producer_obj = KafkaProducer({
            'bootstrap.servers' : KafkaConfig.SERVER_IP.value    
        })
        
        for kpi_value in request.kpi_value_list:
            kpi_value_to_produce : Tuple [str, Any, Any] = (
                kpi_value.kpi_id.kpi_id,            # kpi_value.kpi_id.kpi_id.uuid
                kpi_value.timestamp,                # kpi_value.timestamp.timestamp
                kpi_value.kpi_value_type            # kpi_value.kpi_value_type.(many options) how?
            )
            LOGGER.debug('KPI to produce is {:}'.format(kpi_value_to_produce))
            msg_key = "gRPC-kpivalueapi"        # str(__class__.__name__) can be used
            # write this KPI to Kafka
        
            producer_obj.produce(
                KafkaTopic.VALUE.value, 
                key   = msg_key,
                # value = json.dumps(kpi_value_to_produce),
                value = kpi_value.SerializeToString(),
                callback = self.delivery_callback
            )
            producer_obj.flush()
        return Empty()

    @safe_and_metered_rpc_method(METRICS_POOL, LOGGER)
    def SelectKpiValues(self, request: KpiValueFilter, grpc_context: grpc.ServicerContext
                        ) -> KpiValueList:
        LOGGER.debug('StoreKpiValues: Received gRPC message object: {:}'.format(request))
        response = KpiValueList()
        metrics          = [kpi.kpi_id for kpi in request.kpi_id]
        start_timestamps = [timestamp for timestamp in request.start_timestamp]
        end_timestamps   = [timestamp for timestamp in request.end_timestamp]
        results = []

        for start, end in zip(start_timestamps, end_timestamps):
            start_str = datetime.fromtimestamp(start.seconds).isoformat() + "Z"
            end_str = datetime.fromtimestamp(end.seconds).isoformat() + "Z"

            for metric in metrics:
                url    = f'{PROM_URL}/api/v1/query_range'
                params = {
                    'query': metric,
                    'start': start_str,
                    'end'  : end_str,
                    'step' : '30s'           # or any other step you need
                }
                response = requests.get(url, params=params)
                if response.status_code == 200:
                    data = response.json()
                    for result in data['data']['result']:
                        for value in result['values']:
                            kpi_value = KpiValue(
                                kpi_id=metric,
                                timestamp=str(seconds=value[0]),
                                kpi_value_type=self._convert_value_to_kpi_value_type(value[1])
                            )
                            results.append(kpi_value)

    def _convert_value_to_kpi_value_type(self, value):
        # Check if the value is an integer (int64)
        try:
            int64_value = int(value)
            return KpiValueType(int64Val=int64_value)
        except ValueError:
            pass
        # Check if the value is a float
        try:
            float_value = float(value)
            return KpiValueType(floatVal=float_value)
        except ValueError:
            pass
        # Check if the value is a boolean
        if value.lower() in ['true', 'false']:
            bool_value = value.lower() == 'true'
            return KpiValueType(boolVal=bool_value)
        # If none of the above, treat it as a string
        return KpiValueType(stringVal=value)


    def delivery_callback(self, err, msg):
        if err: LOGGER.debug('Message delivery failed: {:}'.format(err))
        else:   LOGGER.debug('Message delivered to topic {:}'.format(msg.topic()))