""" import firebird, export to postgresql """ #!/usr/bin/python# -*- coding: utf-8 -*- from typing import List import uuid from sqlalchemy.orm import session from sqlalchemy import desc, asc from db.fb_models import (create_session, FbObservation, Catena) from db.models import (create_pg_session, Dataset, Observation, Procedure, Phenomenon, Platform) def main(): """ Main function. """ # parameter: # sensor id in firebird db: # sensor_id = 1 # # name of project area in firebird db # feature_of_interest = 'TAC003-020-0517' # Wolfsegg KB1 # # sensor name in postgis db # sensor = 'wolfsegg_kb1_1' # platform = 'wolfsegg' sensor_id = 0 # name of project area in firebird db feature_of_interest = 'TAC003-020-0517' # Wolfsegg KB1 # sensor name in postgis db sensor = 'wolfsegg_kb1_0' platform = 'wolfsegg_inclinometer' firebird_session: session = create_session() # db_observation = session.query(Observation) \ # .filter_by(name='John Snow').first() query = firebird_session.query(FbObservation).join(FbObservation.catena) \ .filter(FbObservation.sensore == sensor_id) \ .filter(Catena.name == feature_of_interest) # feature_of_interest = query.statement.compile(dialect=firebird.dialect()) firebird_observations: List[FbObservation] = query.all() firebird_session.close() pg_session: session = create_pg_session() # pg_datasets: List[Dataset] = pg_query.all() pg_query = pg_session.query(Dataset) \ .join(Procedure) \ .join(Phenomenon) \ .filter(Procedure.sta_identifier == sensor.lower()) # .join(Platform).all() \ # roll_dataset = [x for x in pg_datasets if x.phenomenon.sta_identifier == "Roll"] roll_dataset = pg_query.filter(Phenomenon.sta_identifier == "Roll").first() roll_dataset.is_published = 1 roll_dataset.is_hidden = 0 roll_dataset.dataset_type = "timeseries" roll_dataset.observation_type = "simple" roll_dataset.value_type = "quantity" slope_dataset = pg_query.filter( Phenomenon.sta_identifier == "Slope").first() slope_dataset.is_published = 1 slope_dataset.is_hidden = 0 slope_dataset.dataset_type = "timeseries" slope_dataset.observation_type = "simple" slope_dataset.value_type = "quantity" temperature_dataset = pg_query.filter( Phenomenon.sta_identifier == "InSystemTemperature").first() temperature_dataset.is_published = 1 temperature_dataset.is_hidden = 0 temperature_dataset.dataset_type = "timeseries" temperature_dataset.observation_type = "simple" temperature_dataset.value_type = "quantity" pg_session.commit() # max_id = pg_session.query(func.max(Observation.id)).scalar() for fb_observation in firebird_observations: # print(fb_observation.catena.name) if(fb_observation.roll is not None and roll_dataset is not None): # max_id = max_id + 1 pg_roll_observation = Observation( # id=max_id, value_type='quantity', sampling_time_start=fb_observation.result_time, sampling_time_end=fb_observation.result_time, result_time=fb_observation.result_time, sta_identifier=str(uuid.uuid4()), value_quantity=fb_observation.roll ) roll_dataset.observations.append(pg_roll_observation) if(fb_observation.pitch is not None and slope_dataset is not None): # max_id = max_id + 1 pg_slope_observation = Observation( # id=max_id, value_type='quantity', sampling_time_start=fb_observation.result_time, sampling_time_end=fb_observation.result_time, result_time=fb_observation.result_time, sta_identifier=str(uuid.uuid4()), value_quantity=fb_observation.pitch ) slope_dataset.observations.append(pg_slope_observation) if(fb_observation.temperature is not None and temperature_dataset is not None): # max_id = max_id + 1 pg_temperature_observation = Observation( # id=max_id, value_type='quantity', sampling_time_start=fb_observation.result_time, sampling_time_end=fb_observation.result_time, result_time=fb_observation.result_time, sta_identifier=str(uuid.uuid4()), value_quantity=fb_observation.temperature ) temperature_dataset.observations.append(pg_temperature_observation) # commit observations: pg_session.commit() last_roll_observation = pg_session.query(Observation) \ .filter(Observation.fk_dataset_id == roll_dataset.id) \ .order_by(desc('sampling_time_start')) \ .first() if last_roll_observation is not None: roll_dataset.last_time = last_roll_observation.sampling_time_start roll_dataset.last_value = last_roll_observation.value_quantity roll_dataset.fk_last_observation_id = last_roll_observation.id last_slope_observation = pg_session.query(Observation) \ .filter(Observation.fk_dataset_id == slope_dataset.id) \ .order_by(desc('sampling_time_start')) \ .first() if last_slope_observation is not None: slope_dataset.last_time = last_slope_observation.sampling_time_start slope_dataset.last_value = last_slope_observation.value_quantity slope_dataset.fk_last_observation_id = last_slope_observation.id last_temperature_observation = pg_session.query(Observation) \ .filter(Observation.fk_dataset_id == temperature_dataset.id) \ .order_by(desc('sampling_time_start')) \ .first() if last_temperature_observation is not None: temperature_dataset.last_time = last_temperature_observation.sampling_time_start temperature_dataset.last_value = last_temperature_observation.value_quantity temperature_dataset.fk_last_observation_id = last_temperature_observation.id first_roll_observation = pg_session.query(Observation) \ .filter(Observation.fk_dataset_id == roll_dataset.id) \ .order_by(asc('sampling_time_start')) \ .first() if first_roll_observation is not None: roll_dataset.first_time = first_roll_observation.sampling_time_start roll_dataset.first_value = first_roll_observation.value_quantity roll_dataset.fk_first_observation_id = first_roll_observation.id first_slope_observation = pg_session.query(Observation) \ .filter(Observation.fk_dataset_id == slope_dataset.id) \ .order_by(asc('sampling_time_start')) \ .first() if first_slope_observation is not None: slope_dataset.first_time = first_slope_observation.sampling_time_start slope_dataset.first_value = first_slope_observation.value_quantity slope_dataset.fk_first_observation_id = first_slope_observation.id first_temperature_observation = pg_session.query(Observation) \ .filter(Observation.fk_dataset_id == temperature_dataset.id) \ .order_by(asc('sampling_time_start')) \ .first() if first_temperature_observation is not None: temperature_dataset.first_time = first_temperature_observation.sampling_time_start temperature_dataset.first_value = first_temperature_observation.value_quantity temperature_dataset.fk_first_observation_id = first_temperature_observation.id platform_exists = pg_session.query(Platform.id).filter_by( name=platform.lower()).scalar() is not None if not platform_exists: sensor_platform = Platform() # max_id = pg_session.query(func.max(Platform.id)).scalar() # sensor_platform.id = max_id + 1 sensor_platform.sta_identifier = platform.lower() sensor_platform.identifier = platform.lower() sensor_platform.name = platform.lower() slope_dataset.platform = sensor_platform roll_dataset.platform = sensor_platform temperature_dataset.platform = sensor_platform else: sensor_platform = pg_session.query(Platform.id) \ .filter(Platform.name == platform.lower()) \ .first() slope_dataset.fk_platform_id = sensor_platform.id roll_dataset.fk_platform_id = sensor_platform.id temperature_dataset.fk_platform_id = sensor_platform.id # commit dataset changes: pg_session.commit() pg_session.close() # ----------------------------------------------------------------------------- if __name__ == "__main__": main()