325 lines
14 KiB
Python
325 lines
14 KiB
Python
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""" import firebird, export to postgresql:
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SELECT dataset_id, dataset_type, observation_type, value_type, fk_procedure_id, fk_phenomenon_id,
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fk_offering_id, fk_category_id, fk_feature_id, fk_platform_id, fk_format_id, fk_unit_id,
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is_deleted, is_disabled, is_published, is_mobile, is_insitu, is_hidden, origin_timezone,
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first_time, last_time, first_value, last_value, fk_first_observation_id, fk_last_observation_id,
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decimals, identifier, fk_identifier_codespace_id, name, fk_name_codespace_id, description,
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fk_value_profile_id
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FROM gba.dataset
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where fk_platform_id = 6 and fk_feature_id = 43
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ORDER BY dataset_id ASC;
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"""
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#!/usr/bin/python# -*- coding: utf-8 -*-
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import os
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import time
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from typing import List
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from itertools import chain
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import uuid
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import json
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from dotenv import load_dotenv, find_dotenv
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from sqlalchemy.orm import session
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from sqlalchemy import asc, desc
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from sqlalchemy.dialects import firebird
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from sqlalchemy.sql import or_
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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,
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Observation, Procedure, Phenomenon, Platform, Format)
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def main():
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"""
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Main function.
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"""
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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 = 'TAC003-020-0521' # Gschliefgraben KB1
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# sensor name in postgis db
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# sensor = 'wolfsegg_kb1_0'
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platform = 'gschliefgraben_inclinometer'
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sensor_env_list = os.getenv('GSCHLIEFGRABEN_KB1_SENSORS').replace('\n', '')
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sensor_list = json.loads(sensor_env_list)
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# print(sensor_list)
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firebird_session: session = create_session()
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# this will print elements along with their index value
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for sensor_id, sensor in enumerate(sensor_list):
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# db_observation = session.query(Observation) \
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# .filter_by(name='John Snow').first()
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query_count = firebird_session.query(FbObservation).join(Catena) \
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.filter(FbObservation.sensore == sensor_id) \
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.filter(Catena.name == feature_of_interest) \
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.filter(
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or_(
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FbObservation.temperature != None,
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FbObservation.pitch != None # this is used to check NULL values
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)) \
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.count()
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# if query_count == 0:
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# print(f"sensor {sensor} "
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# f"doesn't have any observations with measured values in firebird database!")
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# # hop to next for iteration, next sensor in list
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# continue
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# test = query_count.statement.compile(dialect=firebird.dialect())
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firebird_observations: List[FbObservation] = []
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if query_count > 0:
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query = firebird_session.query(FbObservation).join(Catena) \
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.filter(FbObservation.sensore == sensor_id) \
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.filter(Catena.name == feature_of_interest)
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print (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: Dataset = pg_query.filter(
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Phenomenon.sta_identifier == "Roll").first()
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slope_dataset: Dataset = pg_query.filter(
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Phenomenon.sta_identifier == "Slope").first()
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temperature_dataset: Dataset = pg_query.filter(
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Phenomenon.sta_identifier == "InSystemTemperature").first()
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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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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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format_exists: bool = pg_session.query(Format.id).filter_by(
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definition="http://www.opengis.net/def/observationType/OGC-OM/2.0/OM_Measurement"
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).scalar() is not None
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if format_exists:
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sensor_format = pg_session.query(Format.id) \
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.filter(Format.definition ==
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"http://www.opengis.net/def/observationType/OGC-OM/2.0/OM_Measurement") \
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.first()
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slope_dataset.fk_format_id = sensor_format.id
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roll_dataset.fk_format_id = sensor_format.id
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temperature_dataset.fk_format_id = sensor_format.id
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pg_session.commit()
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if query_count == 0:
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print(f"sensor {sensor} "
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f"doesn't have any observations with measured values in firebird database!")
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# hop to next for iteration, next sensor in list, don't insert any observations
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continue
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create_db_observations(firebird_observations, roll_dataset,
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slope_dataset, temperature_dataset, pg_session)
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# commit new observations:
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pg_session.commit()
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if len(roll_dataset.observations) > 0:
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# if not published yet, publish the roll dataset
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if not roll_dataset.is_published:
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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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if len(slope_dataset.observations) > 0:
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# if not published yet, publish the roll dataset
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if not slope_dataset.is_published:
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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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if len(temperature_dataset.observations) > 0:
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# if not published yet, publish the temperature dataset
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if not temperature_dataset.is_published:
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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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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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pg_session.commit()
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# for loop sensors end
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pg_session.close()
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# firebird_session.close()
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def create_db_observations(firebird_observations: List[FbObservation],
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roll_dataset: Dataset,
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slope_dataset: Dataset,
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temperature_dataset: Dataset,
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pg_session: session):
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''' insert new observations ito db '''
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roll_result = (
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pg_session.query(Observation.result_time)
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.filter(Observation.fk_dataset_id == roll_dataset.id)
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.all()
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)
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roll_result_time_db_list1: List[str] = list(chain(*roll_result))
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roll_result_time_db_list: List[float] = [time.mktime(
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date_obj.timetuple()) for date_obj in roll_result_time_db_list1]
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slope_result = (
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pg_session.query(Observation.result_time)
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.filter(Observation.fk_dataset_id == slope_dataset.id)
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.all()
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)
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slope_result_time_db_list1: List[str] = list(chain(*slope_result))
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slope_result_time_db_list: List[float] = [time.mktime(
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date_obj.timetuple()) for date_obj in slope_result_time_db_list1]
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temperature_result = (
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pg_session.query(Observation.result_time)
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.filter(Observation.fk_dataset_id == temperature_dataset.id)
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.all()
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)
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temperature_result_time_db_list1: List[str] = list(
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chain(*temperature_result))
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temperature_result_time_db_list: List[float] = [time.mktime(
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date_obj.timetuple()) for date_obj in temperature_result_time_db_list1]
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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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value = fb_observation.roll
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add_observation(roll_dataset, fb_observation,
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value, roll_result_time_db_list)
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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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value = fb_observation.pitch
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add_observation(slope_dataset, fb_observation,
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value, slope_result_time_db_list)
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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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value = fb_observation.temperature
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add_observation(temperature_dataset, fb_observation,
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value, temperature_result_time_db_list)
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def add_observation(
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dataset: Dataset,
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fb_observation: FbObservation,
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value: str,
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value_identifier_db_list: List[float]):
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''' check if observation still extists in db,
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otherwise add it to fb'''
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# ob_id: str = str(observation_json.get('id'))
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# existing_observation: bool = (
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# db_session.query(Observation)
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# .filter(Observation.result_time == fb_observation.result_time,
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# Observation.fk_dataset_id == dataset.id)
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# .one_or_none()
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# )
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existing_observation: bool = time.mktime(
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fb_observation.result_time.timetuple()) in value_identifier_db_list
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# Can we insert this observation?
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if existing_observation is False:
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# insert bew observation
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new_observation: Observation = Observation()
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new_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_identifier=str(time.mktime(
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fb_observation.result_time.timetuple())),
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value_quantity=value
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)
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dataset.observations.append(new_observation)
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print(f"new observation with result time {new_observation.result_time} "
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f"for inclinometer {dataset.procedure.name} succesfully imported!")
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else:
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print(f"observation with result time {fb_observation.result_time} "
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f"for inclinometer {dataset.procedure.name} already exists!")
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# -----------------------------------------------------------------------------
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if __name__ == "__main__":
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load_dotenv(find_dotenv())
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main()
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