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Analyzer_DB.py

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  • Waleed Akbar's avatar
    Waleed Akbar authored
    Refactor in Analytics, Telemetry, and KpiManager Services and Manifest Files to Reflect Generic DB Changes.
    
    - Improvements made to `tfs.sh` script.
    - Added `CRDB_DATABASE` environment variable to all monitoring service manifest files and the context manifest file.
    - Removed the DB engine file from all monitoring services and moved it to `common.tools.database`.
    - Each `<service_name>_DB.py` will now retrieve the database name from the environment variable.
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    Analyzer_DB.py 2.75 KiB
    # 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
    from common.Settings import get_setting
    from common.method_wrappers.Decorator import MetricsPool
    from .AnalyzerModel import Analyzer as Model
    from common.tools.database.GenericDatabase import Database
    from common.method_wrappers.ServiceExceptions import OperationFailedException
    
    LOGGER       = logging.getLogger(__name__)
    METRICS_POOL = MetricsPool('KpiManager', 'Database')
    DB_NAME      = get_setting('CRDB_DATABASE', default=None)
    
    class AnalyzerDB(Database):
        def __init__(self) -> None:
            LOGGER.info('Init KpiManagerService')
            super().__init__(DB_NAME, Model)
    
        def select_with_filter(self, model, filter_object):
            """
            Generic method to create filters dynamically based on filter_object attributes.
            params:     model:         SQLAlchemy model class to query.
                        filter_object: Object that contains filtering criteria as attributes.
            return:     SQLAlchemy session, query and Model
            """
            session = self.Session()
            try:
                query = session.query(Model)
                # Apply filters based on the filter_object
                if filter_object.analyzer_id:
                    query = query.filter(Model.analyzer_id.in_([a.analyzer_id.uuid for a in filter_object.analyzer_id]))
    
                if filter_object.algorithm_names:
                    query = query.filter(Model.algorithm_name.in_(filter_object.algorithm_names))
    
                if filter_object.input_kpi_ids:
                    input_kpi_uuids = [k.kpi_id.uuid for k in filter_object.input_kpi_ids]
                    query = query.filter(Model.input_kpi_ids.op('&&')(input_kpi_uuids))
    
                if filter_object.output_kpi_ids:
                    output_kpi_uuids = [k.kpi_id.uuid for k in filter_object.output_kpi_ids]
                    query = query.filter(Model.output_kpi_ids.op('&&')(output_kpi_uuids))
            except Exception as e:
                LOGGER.error(f"Error creating filter of {model.__name__} table. ERROR: {e}")
                raise OperationFailedException ("CreateKpiDescriptorFilter", extra_details=["unable to create the filter {:}".format(e)]) 
            
            return super().select_with_filter(query, session, Model)