# Copyright 2022-2023 ETSI TeraFlowSDN - TFS OSG (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, time import sqlalchemy import sqlalchemy_utils from sqlalchemy.orm import sessionmaker from sqlalchemy.ext.declarative import declarative_base from kpi_manager.service.database.KpiEngine import KpiEngine from kpi_manager.service.database.KpiModel import Kpi LOGGER = logging.getLogger(__name__) DB_NAME = "kpi" class Kpi_DB: def __init__(self): self.db_engine = KpiEngine.get_engine() if self.db_engine is None: LOGGER.error('Unable to get SQLAlchemy DB Engine...') return False self.db_name = DB_NAME # self.drop_database(self.db_engine) # added to test # self.create_database(self.db_engine) # to add database self.Session = sessionmaker(bind=self.db_engine) @staticmethod def create_database(engine : sqlalchemy.engine.Engine) -> None: if not sqlalchemy_utils.database_exists(engine.url): LOGGER.info("Database created. {:}".format(engine.url)) sqlalchemy_utils.create_database(engine.url) @staticmethod def drop_database(engine : sqlalchemy.engine.Engine) -> None: if sqlalchemy_utils.database_exists(engine.url): sqlalchemy_utils.drop_database(engine.url) def create_tables(self): try: Kpi.metadata.create_all(self.db_engine) # type: ignore LOGGER.info("Tables created in the DB Name: {:}".format(self.db_name)) except Exception as e: LOGGER.info("Tables cannot be created in the kpi database. {:s}".format(str(e))) def verify_tables(self): try: with self.db_engine.connect() as connection: result = connection.execute("SHOW TABLES;") tables = result.fetchall() # type: ignore LOGGER.info("Tables verified: {:}".format(tables)) except Exception as e: LOGGER.info("Unable to fetch Table names. {:s}".format(str(e))) def add_row_to_db(self, row): session = self.Session() try: session.add(row) session.commit() LOGGER.info(f"Row inserted into {row.__class__.__name__} table.") return True except Exception as e: session.rollback() if "psycopg2.errors.UniqueViolation" in str(e): LOGGER.warning(f"Unique key voilation: {row.__class__.__name__} table. {str(e)}") else: LOGGER.error(f"Failed to insert new row into {row.__class__.__name__} table. {str(e)}") return False finally: session.close() def search_db_row_by_id(self, model, col_name, id_to_search): session = self.Session() try: entity = session.query(model).filter_by(**{col_name: id_to_search}).first() if entity: # LOGGER.info(f"{model.__name__} ID found: {str(entity)}") return entity else: LOGGER.warning(f"{model.__name__} ID not found: {str(id_to_search)}") return None except Exception as e: session.rollback() LOGGER.info(f"Failed to retrieve {model.__name__} ID. {str(e)}") raise finally: session.close() def delete_db_row_by_id(self, model, col_name, id_to_search): session = self.Session() try: record = session.query(model).filter_by(**{col_name: id_to_search}).first() if record: session.delete(record) session.commit() LOGGER.info("Deleted %s with %s: %s", model.__name__, col_name, id_to_search) else: LOGGER.warning("%s with %s %s not found", model.__name__, col_name, id_to_search) return None except Exception as e: session.rollback() LOGGER.error("Error deleting %s with %s %s: %s", model.__name__, col_name, id_to_search, e) finally: session.close() def select_with_filter(self, model, **filters): session = self.Session() try: query = session.query(model) for column, value in filters.items(): query = query.filter(getattr(model, column) == value) # type: ignore result = query.all() if result: LOGGER.info(f"Fetched filtered rows from {model.__name__} table with filters: {filters}") # - Results: {result} else: LOGGER.warning(f"No matching row found in {model.__name__} table with filters: {filters}") return result except Exception as e: LOGGER.error(f"Error fetching filtered rows from {model.__name__} table with filters {filters} ::: {e}") return [] finally: session.close()