181 lines
7.2 KiB
Python
181 lines
7.2 KiB
Python
'''
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Sqlalchemy version: 1.2.15
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Python version: 3.7
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'''
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import json
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import os
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import uuid
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from datetime import datetime
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from sqlalchemy.orm import session
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from sqlalchemy import asc, desc, func
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from dotenv import load_dotenv, find_dotenv
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import requests
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from db.models import (
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Observation,
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create_pg_session,
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Dataset,
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Procedure,
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Phenomenon,
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Platform,
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Format
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)
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def main():
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''' main method '''
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pg_session: session = create_pg_session()
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platform_sta_identifier = "pechgraben_piezometer"
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# sensor = "bohrloch1"
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# sensor_list = os.environ.get('PIEZOMETER_GSCHLIEFGRABEN_SENSORS', [])
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sensor_list = json.loads(os.environ['PIEZOMETER_GSCHLIEFGRABEN_SENSORS'])
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url = 'https://jaa5ixl2y0.execute-api.ap-southeast-2.amazonaws.com/v1/data'
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params = {}
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headers = {'content-type': 'application/json'}
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resp = requests.get(url=url, params=params, headers=headers)
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data: json = resp.json() # Check the JSON Response Content documentation below
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for sensor in sensor_list:
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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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elevation_dataset: Dataset = pg_query.filter(
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Phenomenon.sta_identifier == "Elevation").first()
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if not elevation_dataset:
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print("Sensor " + sensor + " ist noch nicht angelegt!")
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continue
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if not elevation_dataset.is_published:
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elevation_dataset.is_published = 1
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elevation_dataset.is_hidden = 0
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elevation_dataset.dataset_type = "timeseries"
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elevation_dataset.observation_type = "simple"
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elevation_dataset.value_type = "text"
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pg_session.commit()
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platform_exists: bool = pg_session.query(Platform.id).filter_by(
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sta_identifier=platform_sta_identifier).scalar() is not None
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# if platform_exists:
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# sensor_platform = pg_session.query(Platform.id) \
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# .filter(Platform.sta_identifier == platform_sta_identifier) \
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# .first()
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# elevation_dataset.fk_platform_id = sensor_platform.id
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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_sta_identifier.lower()
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sensor_platform.identifier = platform_sta_identifier.lower()
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sensor_platform.name = platform_sta_identifier.lower()
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elevation_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.sta_identifier == platform_sta_identifier) \
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.first()
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elevation_dataset.fk_platform_id = sensor_platform.id
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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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elevation_dataset.fk_format_id = sensor_format.id
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if sensor in data:
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create_observation(elevation_dataset, sensor, data, pg_session)
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pg_session.commit()
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first_elevation_observation = pg_session.query(Observation) \
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.filter(Observation.fk_dataset_id == elevation_dataset.id) \
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.order_by(asc('sampling_time_start')) \
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.first()
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if first_elevation_observation is not None:
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elevation_dataset.first_time = first_elevation_observation.sampling_time_start
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elevation_dataset.first_value = first_elevation_observation.value_quantity
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elevation_dataset.fk_first_observation_id = first_elevation_observation.id
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last_elevation_observation = pg_session.query(Observation) \
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.filter(Observation.fk_dataset_id == elevation_dataset.id) \
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.order_by(desc('sampling_time_start')) \
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.first()
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if last_elevation_observation is not None:
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elevation_dataset.last_time = last_elevation_observation.sampling_time_start
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elevation_dataset.last_value = last_elevation_observation.value_quantity
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elevation_dataset.fk_last_observation_id = last_elevation_observation.id
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pg_session.commit()
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pg_session.close()
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def create_observation(elevation_dataset: Dataset,
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sensor_key: str,
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data: json,
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db_session: session):
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''' create observation in db'''
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print("Sesnor key exist in JSON data")
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sensor_object = data[sensor_key]
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zeitstempel = sensor_object["zeitstempel"]
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abstich = sensor_object["abstich"]
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date_obj = datetime.strptime(
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zeitstempel, '%Y-%m-%d %H:%M:%S')
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existing_observation: bool = (
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db_session.query(Observation)
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.filter(Observation.result_time ==
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date_obj, Observation.fk_dataset_id == elevation_dataset.id)
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.one_or_none()
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)
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# Can we insert this observation?
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if existing_observation is None:
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# insert bew observation
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new_observation: Observation = Observation()
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# new_observation.id = max_id
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new_observation.sta_identifier = str(uuid.uuid4())
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new_observation.result_time = date_obj
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new_observation.sampling_time_start = new_observation.result_time
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new_observation.sampling_time_end = new_observation.result_time
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new_observation.value_type = "quantity"
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new_observation.value_quantity = abstich
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new_observation.fk_dataset_id = elevation_dataset.id
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db_session.add(new_observation)
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def test():
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''' test method '''
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sensor_key = 'bohrloch1'
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url = 'https://jaa5ixl2y0.execute-api.ap-southeast-2.amazonaws.com/v1/data'
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params = {}
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headers = {'content-type': 'application/json'}
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resp = requests.get(url=url, params=params, headers=headers)
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data = resp.json() # Check the JSON Response Content documentation below
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# sensor_data = json.dumps(data)
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if sensor_key in data:
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print("Sesnor key exist in JSON data")
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sensor_object = data[sensor_key]
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zeitstempel = sensor_object["zeitstempel"]
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abstich = sensor_object["abstich"]
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date_obj = datetime.strptime(
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zeitstempel, '%Y-%m-%d %H:%M:%S')
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new_observation: Observation = Observation()
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# new_observation.id = max_id
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new_observation.sta_identifier = str(uuid.uuid4())
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new_observation.result_time = date_obj
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new_observation.sampling_time_start = new_observation.result_time
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new_observation.sampling_time_end = new_observation.result_time
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new_observation.value_type = "quantity"
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new_observation.value_quantity = abstich
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# new_observation.fk_dataset_id = dataset.id
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if __name__ == "__main__":
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load_dotenv(find_dotenv())
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sensor_list1 = os.environ.get('PIEZOMETER_GSCHLIEFGRABEN_SENSORS', [])
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print(f'sensors: {sensor_list1} .')
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main()
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