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KpiValueApiServiceServicerImpl.py 5.37 KiB
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    # 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
    
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    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
    
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    from confluent_kafka import Producer as KafkaProducer
    
    from .NameMapping import NameMapping
    
    
    
    LOGGER       = logging.getLogger(__name__)
    
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    METRICS_POOL = MetricsPool('KpiValueAPI', 'NBIgRPC')
    
    PROM_URL     = "http://localhost:9090"
    
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    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    
            })
            
    
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            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?
    
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                )
                LOGGER.debug('KPI to produce is {:}'.format(kpi_value_to_produce))
    
                msg_key = "gRPC-kpivalueapi"        # str(__class__.__name__) can be used
    
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                # 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
                )
    
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                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)
    
    
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        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()))