# 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 uuid
import json
from common.proto.kpi_manager_pb2        import KpiId
from common.proto.analytics_frontend_pb2 import ( AnalyzerOperationMode, AnalyzerId,
                                                Analyzer, AnalyzerFilter )

def create_analyzer_id():
    _create_analyzer_id                  = AnalyzerId()
    # _create_analyzer_id.analyzer_id.uuid = str(uuid.uuid4())
    _create_analyzer_id.analyzer_id.uuid = "9baa306d-d91c-48c2-a92f-76a21bab35b6"
    return _create_analyzer_id

def create_analyzer():
    _create_analyzer                              = Analyzer()
    _create_analyzer.analyzer_id.analyzer_id.uuid = str(uuid.uuid4())
    _create_analyzer.algorithm_name               = "Test_Aggergate_and_Threshold"
    _create_analyzer.operation_mode               = AnalyzerOperationMode.ANALYZEROPERATIONMODE_STREAMING
    
    _kpi_id = KpiId()
    # input IDs to analyze
    _kpi_id.kpi_id.uuid              = str(uuid.uuid4())
    _kpi_id.kpi_id.uuid              = "6e22f180-ba28-4641-b190-2287bf448888"
    _create_analyzer.input_kpi_ids.append(_kpi_id)
    _kpi_id.kpi_id.uuid              = str(uuid.uuid4())
    _kpi_id.kpi_id.uuid              = "1e22f180-ba28-4641-b190-2287bf446666"
    _create_analyzer.input_kpi_ids.append(_kpi_id)
    _kpi_id.kpi_id.uuid              = str(uuid.uuid4())
    _create_analyzer.input_kpi_ids.append(_kpi_id)
    # output IDs after analysis
    _kpi_id.kpi_id.uuid              = str(uuid.uuid4())
    _create_analyzer.output_kpi_ids.append(_kpi_id)
    _kpi_id.kpi_id.uuid              = str(uuid.uuid4())
    _create_analyzer.output_kpi_ids.append(_kpi_id)
    # parameter
    _threshold_dict = {
        # 'avg_value'   :(20, 30), 'min_value'   :(00, 10), 'max_value'   :(45, 50),
        'first_value' :(00, 10), 'last_value'  :(40, 50), 'stdev_value':(00, 10)}
    _create_analyzer.parameters['thresholds']      = json.dumps(_threshold_dict)
    _create_analyzer.parameters['window_size']     = "60 seconds"     # Such as "10 seconds", "2 minutes", "3 hours", "4 days" or "5 weeks" 
    _create_analyzer.parameters['window_slider']   = "30 seconds"     # should be less than window size
    _create_analyzer.parameters['store_aggregate'] = str(False)       # TRUE to store. No implemented yet

    return _create_analyzer

def create_analyzer_filter():
    _create_analyzer_filter           = AnalyzerFilter()

    _analyzer_id_obj                  = AnalyzerId()
    _analyzer_id_obj.analyzer_id.uuid = str(uuid.uuid4())
    _create_analyzer_filter.analyzer_id.append(_analyzer_id_obj)

    _create_analyzer_filter.algorithm_names.append('Algorithum1')

    _input_kpi_id_obj                 = KpiId()
    _input_kpi_id_obj.kpi_id.uuid     = str(uuid.uuid4())
    _create_analyzer_filter.input_kpi_ids.append(_input_kpi_id_obj)
    # another input kpi Id
    # _input_kpi_id_obj.kpi_id.uuid     = str(uuid.uuid4())
    # _create_analyzer_filter.input_kpi_ids.append(_input_kpi_id_obj)

    _output_kpi_id_obj                = KpiId()
    _output_kpi_id_obj.kpi_id.uuid    = str(uuid.uuid4())
    _create_analyzer_filter.output_kpi_ids.append(_output_kpi_id_obj)
    # another output kpi Id
    # _output_kpi_id_obj.kpi_id.uuid     = str(uuid.uuid4())
    # _create_analyzer_filter.input_kpi_ids.append(_output_kpi_id_obj)

    return _create_analyzer_filter