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