- add daily cron job for inserting sensor data
This commit is contained in:
parent
f104e9e74b
commit
fdc5da7373
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@ -1,26 +0,0 @@
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from sqlalchemy import create_engine
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from sqlalchemy import MetaData
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from sqlalchemy import Table
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from sqlalchemy import Column
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from sqlalchemy import Integer, String
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db_url = 'sqlite:///db.sqlite'
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engine = create_engine(db_url )
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# Create a metadata instance
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metadata = MetaData(engine)
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# Declare a table
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table = Table('Example',metadata,
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Column('id',Integer, primary_key=True),
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Column('name',String))
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# Create all tables
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students = Table(
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'students', metadata,
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Column('id', Integer, primary_key = True),
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Column('name', String),
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Column('lastname', String),
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)
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metadata.create_all(engine)
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@ -7,6 +7,8 @@ Python version: 3.7
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import os
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import uuid
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from typing import List
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from itertools import chain
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# import sys, inspect
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# currentdir = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe())))
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# parentdir = os.path.dirname(currentdir)
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@ -25,75 +27,75 @@ from datetime import datetime, date, timedelta
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# print(response.json()) # shows the response's JSON response body, if it has one
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# print(response.content) # get the data content of the response
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def main():
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''' main method '''
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db_user = os.environ.get("POSTGIS_DBUSER")
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print(db_user)
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pg_session: session = create_pg_session()
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platform_sta_identifier = "gschliefgraben_glasfaser"
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# sensor_list = ["inclino1_14", "inclino1_02"]
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sensor_list = os.environ.get("GLASFASER_GSCHLIEFGRABEN_SENSORS")
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# this will print elements along with their index value
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for sensor in enumerate(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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slope_dataset: Dataset = pg_query.filter(
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Phenomenon.sta_identifier == "Slope").first()
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if not slope_dataset:
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print("Sensor " + sensor + " ist noch nicht angelegt!")
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exit()
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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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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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slope_dataset.fk_platform_id = sensor_platform.id
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else:
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exit()
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# create all the observation for the given sensor names
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create_observations(sensor, slope_dataset)
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def create_observations(sensor: str, slope_dataset: Dataset):
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''' create_observations method for given sensor '''
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pg_session: session = create_pg_session()
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# pg_person: Person = pg_session.query(Person).first()
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observation: Observation = pg_session.query(Observation).first()
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# print(pg_person)
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# serialize db data to json
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# person_schema = PersonSchema()
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# dump_data = person_schema.dump(pg_person)
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# print(dump_data)
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# serialize db data to json
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# observation_schema = ObservationSchema()
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# dump_data = observation_schema.dump(observation)
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# print(dump_data)
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# request ortmann api
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# response =
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# requests.get('https://api.dgnss-sensors.com/gschliefgraben?sensors=("inclino1_14")',
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# headers={
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# 'Authorization': 'Bearer' + token,
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# 'cache-control': 'no-cache',
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# 'Content-Type': 'application/x-www-form-urlencoded',
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# 'accept': 'application/json'
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# },
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# data='grant_type=client_credentials&scope=gschliefgraben')
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# print(response)
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sensor: str = "inclino1_14"
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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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slope_dataset: Dataset = pg_query.filter(
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Phenomenon.sta_identifier == "Slope").first()
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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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pg_session.commit()
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# The size of each step in days
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# consider the start date as 2021-february 1 st
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start_date = date(2022, 1, 1)
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# consider the end date as 2021-march 1 st
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end_date = date(2022, 3, 1)
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end_date = date(2022, 3, 3)
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# delta time
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delta = timedelta(days=1)
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delta = timedelta(days=7)
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token_api = os.environ.get("TOKEN_API")
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test_api = MyApi(token_api)
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# iterate over range of dates
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while start_date <= end_date:
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# print(start_date, end="\n")
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query_date = start_date.strftime('%Y-%m-%d')
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create_db_observations(query_date, test_api, pg_session, slope_dataset)
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start_date += delta
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query_date_start: str = start_date.strftime('%Y-%m-%d')
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end_date_temp: date = start_date + delta # (plus 7 days)
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if end_date_temp > end_date:
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end_date_temp = end_date
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query_date_end: str = end_date_temp.strftime('%Y-%m-%d')
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create_db_observations(sensor, query_date_start, query_date_end, test_api, pg_session, slope_dataset)
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# for next loop step set new start_date (1 day greate then last end_date)
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start_date = end_date_temp + timedelta(days=1)
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pg_session.commit()
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# for i in rrule(DAILY , dtstart=start_date,until=end_date):
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# print(i.strftime('%Y%b%d'),sep='\n')
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# query_date = "2022-02-28"
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# create_db_observations(query_date, test_api, pg_session)
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# query_date_obj = datetime.strptime(query_date, "%Y-%m-%d")
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@ -117,13 +119,20 @@ def main():
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# pg_session.commit()
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def create_db_observations(query_date, test_api, pg_session, dataset: Dataset):
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def create_db_observations(sensor, query_date_start, query_date_end, test_api, pg_session, dataset: Dataset):
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''' to do '''
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query_date_obj = datetime.strptime(query_date, "%Y-%m-%d")
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data = test_api.getSensorData("inclino1_14", query_date)
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query_date_start_obj = datetime.strptime(query_date_start, "%Y-%m-%d")
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query_date_end_obj = datetime.strptime(query_date_end, "%Y-%m-%d")
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data = test_api.getSensorData(sensor, query_date_start, query_date_end)
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observation_array = (data['FeatureCollection']
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['Features'][0]['geometry']['properties'][0])
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# print(observation_array)
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result = (
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pg_session.query(Observation.value_identifier)
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.filter(Observation.fk_dataset_id == dataset.id)
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.all()
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)
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value_identifier_db_list: List[str] = list(chain(*result))
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max_id = pg_session.query(func.max(Observation.id)).scalar()
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if max_id is None:
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@ -132,19 +141,21 @@ def create_db_observations(query_date, test_api, pg_session, dataset: Dataset):
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for observation_json in observation_array:
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ob_date_time = observation_json.get('DateTime')
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datetime_obj = datetime.strptime(ob_date_time, "%Y-%m-%dT%H:%M:%S.%fZ")
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if datetime_obj.date() != query_date_obj.date():
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if datetime_obj.date() < query_date_start_obj.date():
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continue
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if datetime_obj.date() > query_date_end_obj.date():
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continue
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ob_value = observation_json.get('Value')
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if ob_value is None:
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continue
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# max_id = max_id + 1
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max_id = create_observation(
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observation_json, pg_session, max_id, dataset)
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observation_json, pg_session, max_id, dataset, value_identifier_db_list)
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# pg_session.commit()
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print("observations for date " + query_date + "succesfully imported \n")
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print("observations for date " + query_date_start + " to " + query_date_end + " succesfully imported \n")
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def create_observation(observation_json: ObservationSchema, db_session, max_id, dataset: Dataset):
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def create_observation(observation_json: ObservationSchema, db_session, max_id, dataset: Dataset, value_identifier_db_list):
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"""
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This function creates a new observation in the people structure
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based on the passed-in observation data
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ob_id: str = str(observation_json.get('id'))
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# db_session = create_pg_session()
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existing_observation: bool = (
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db_session.query(Observation)
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.filter(Observation.value_identifier == ob_id)
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.one_or_none()
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)
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# existing_observation: bool = (
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# db_session.query(Observation)
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# .filter(Observation.value_identifier == ob_id)
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# .one_or_none()
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# )
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existing_observation: bool = ob_id in value_identifier_db_list
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# Can we insert this observation?
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if existing_observation is None:
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if existing_observation is False:
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max_id += 1
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# Create a person instance using the schema and the passed in person
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schema = ObservationSchema()
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new_observation: Observation = schema.load(observation_json)
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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.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.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.fk_dataset_id = dataset.id
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# Add the person to the database
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@ -65,10 +65,10 @@ class MyApi():
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# self.access_token = res.json()['access_token']
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# else:
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# # Token expired -> re-authenticate
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def getSensorData(self, sensor: string, date):
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def getSensorData(self, sensor: string, date_start, date_end):
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''' request observations'''
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try:
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request = self.session.get('https://api.dgnss-sensors.com/gschliefgraben?sensors=(\''+sensor+ '\')&start='+date+'&end='+date,
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request = self.session.get('https://api.dgnss-sensors.com/gschliefgraben?sensors=(\''+sensor+ '\')&start=' + date_start+ '&end=' + date_end,
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headers={
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'cache-control': 'no-cache',
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'Content-Type': 'application/x-www-form-urlencoded',
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142
gschliefgraben_glasfaser/update_daily_cron.py
Normal file
142
gschliefgraben_glasfaser/update_daily_cron.py
Normal file
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'''
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Tutorial link: https://realpython.com/flask-connexion-rest-api-part-2/
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https://github.com/realpython/materials/blob/master/flask-connexion-rest-part-2/version_1/people.py
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Sqlalchemy version: 1.2.15
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Python version: 3.10
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'''
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import os
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import uuid
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from sqlalchemy.orm import session
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from sqlalchemy import func
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# from db.pg_models import Platform
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from gschliefgraben_glasfaser.models import ObservationSchema, Observation, create_pg_session, Dataset, Procedure, Phenomenon, Platform
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from gschliefgraben_glasfaser.my_api import MyApi
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from datetime import datetime
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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 = "gschliefgraben_glasfaser"
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# sensor_list = ["inclino1_14", "inclino1_02"]
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sensor_list = os.environ.get("GLASFASER_GSCHLIEFGRABEN_SENSORS")
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# this will print elements along with their index value
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for sensor in enumerate(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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slope_dataset: Dataset = pg_query.filter(
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Phenomenon.sta_identifier == "Slope").first()
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if not slope_dataset:
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print("Sensor " + sensor + " ist noch nicht angelegt!")
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exit()
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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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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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slope_dataset.fk_platform_id = sensor_platform.id
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# create all the observation for the given sensor names
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create_observations(sensor, slope_dataset)
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def create_observations(sensor: str, slope_dataset: Dataset):
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''' create_observations method for given sensor '''
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pg_session: session = create_pg_session()
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# create access token
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token_api = os.environ.get("TOKEN_API")
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test_api = MyApi(token_api)
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# The size of each step in days
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# consider the start date as 2021-february 1 st
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start_date = datetime.today()
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query_date = start_date.strftime('%Y-%m-%d')
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create_db_observations(sensor, query_date, test_api, pg_session, slope_dataset)
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pg_session.commit()
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def create_db_observations(sensor: str, query_date, test_api, pg_session, dataset: Dataset):
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''' to do '''
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query_date_obj = datetime.strptime(query_date, "%Y-%m-%d")
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data = test_api.getSensorData(sensor, query_date, query_date)
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observation_array = (data['FeatureCollection']
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['Features'][0]['geometry']['properties'][0])
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# print(observation_array)
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max_id = pg_session.query(func.max(Observation.id)).scalar()
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if max_id is None:
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max_id = -1
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# pg_session.bulk_save_objects(observations)
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for observation_json in observation_array:
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ob_date_time = observation_json.get('DateTime')
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datetime_obj = datetime.strptime(ob_date_time, "%Y-%m-%dT%H:%M:%S.%fZ")
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if datetime_obj.date() != query_date_obj.date():
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continue
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ob_value = observation_json.get('Value')
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if ob_value is None:
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continue
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# max_id = max_id + 1
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max_id = create_observation(
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observation_json, pg_session, max_id, dataset)
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# pg_session.commit()
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print("observations for date " + query_date + " succesfully imported \n")
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def create_observation(observation_json: ObservationSchema, db_session, max_id, dataset: Dataset):
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"""
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This function creates a new observation in the people structure
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based on the passed-in observation data
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:param observation: person to create in people structure
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:return: 201 on success, observation on person exists
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"""
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ob_id: str = str(observation_json.get('id'))
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# db_session = create_pg_session()
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existing_observation: bool = (
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db_session.query(Observation)
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.filter(Observation.value_identifier == ob_id, Observation.fk_dataset_id == 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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max_id += 1
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# Create a person instance using the schema and the passed in person
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schema = ObservationSchema()
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# deserialize to python object
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new_observation: Observation = schema.load(observation_json)
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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.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.fk_dataset_id = dataset.id
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# Add the person to the database
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db_session.add(new_observation)
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# dataset.observations.append(new_observation)
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# db_session.commit()
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# Serialize and return the newly created person in the response
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# data = schema.dump(new_observation)
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# return data, 201
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return max_id
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# Otherwise, nope, person exists already
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else:
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print(409, f'Observation {ob_id} exists already')
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return max_id
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if __name__ == "__main__":
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main()
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@ -54,18 +54,6 @@
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<swe:uom code=\"deg\"/>
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</swe:Quantity>
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</sml:output>
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<sml:output name=\"Roll\">
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<swe:Quantity definition=\"Roll\">
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<swe:label>Roll</swe:label>
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<swe:uom code=\"deg\"/>
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</swe:Quantity>
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</sml:output>
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<sml:output name=\"InSystemTemperature\">
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<swe:Quantity definition=\"InSystemTemperature\">
|
||||
<swe:label>InSystemTemperature</swe:label>
|
||||
<swe:uom code=\"degC\"/>
|
||||
</swe:Quantity>
|
||||
</sml:output>
|
||||
</sml:OutputList>
|
||||
</sml:outputs>
|
||||
<sml:position>
|
||||
|
|
|
@ -50,10 +50,10 @@ def main():
|
|||
####################### Gschliefgraben Glasfaser
|
||||
offering = Offering(
|
||||
"https://geomon.geologie.ac.at/52n-sos-webapp/api/offerings/",
|
||||
"inclino1_14",
|
||||
"Inklinometer inclino1_14, Gschliefgraben Glasfaser"
|
||||
"inclino1_02",
|
||||
"Inklinometer inclino1_02, Gschliefgraben Glasfaser"
|
||||
)
|
||||
procedure = Procedure( "inclino1_14","inclino1_14")
|
||||
procedure = Procedure( "inclino1_02","inclino1_02")
|
||||
|
||||
foi = FoI("degree", "m", (47.910849, 13.774966, 0.0),
|
||||
"FBGuard23", "Glasfaser Untersuchungen am Gschliefgraben (Gmunden)")
|
||||
|
|
|
@ -79,7 +79,7 @@ def insert_sensor(offering, procedure, foi, sensor_type):
|
|||
"service": "SOS",
|
||||
"version": "2.0.0",
|
||||
"procedureDescriptionFormat": "http://www.opengis.net/sensorml/2.0",
|
||||
"procedureDescription": f'<sml:PhysicalSystem gml:id={off_name} xmlns:swes=\"http://www.opengis.net/swes/2.0\" xmlns:sos=\"http://www.opengis.net/sos/2.0\" xmlns:swe=\"http://www.opengis.net/swe/2.0\" xmlns:sml=\"http://www.opengis.net/sensorml/2.0\" xmlns:gml=\"http://www.opengis.net/gml/3.2\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" xmlns:xsi=\"http://www.w3.org/2001/XMLSchema-instance\" xmlns:gco=\"http://www.isotc211.org/2005/gco\" xmlns:gmd=\"http://www.isotc211.org/2005/gmd\"><gml:identifier codeSpace=\"uniqueID\">{procedure_identifier}</gml:identifier><sml:identification><sml:IdentifierList><sml:identifier><sml:Term definition=\"urn:ogc:def:identifier:OGC:1.0:shortName\"><sml:label>shortName</sml:label><sml:value>{procedure_name}</sml:value></sml:Term></sml:identifier></sml:IdentifierList></sml:identification><sml:capabilities name=\"offerings\"><sml:CapabilityList><sml:capability name=\"offeringID\"><swe:Text definition=\"urn:ogc:def:identifier:OGC:offeringID\"><swe:label>{offering_label}</swe:label><swe:value>{offering_name}</swe:value></swe:Text></sml:capability></sml:CapabilityList></sml:capabilities><sml:featuresOfInterest><sml:FeatureList definition=\"http://www.opengis.net/def/featureOfInterest/identifier\"><swe:label>featuresOfInterest</swe:label><sml:feature><sams:SF_SpatialSamplingFeature xmlns:sams=\"http://www.opengis.net/samplingSpatial/2.0\" gml:id=\"ssf_b3a826dd44012201b01323232323041f7a92e0cc47260eb9888f6a4e9f747\"><gml:identifier codeSpace=\"http://www.opengis.net/def/nil/OGC/0/unknown\">{feature_id}</gml:identifier><gml:name codeSpace=\"http://www.opengis.net/def/nil/OGC/0/unknown\">{feature_name}</gml:name><sf:type xmlns:sf=\"http://www.opengis.net/sampling/2.0\" xlink:href=\"http://www.opengis.net/def/samplingFeatureType/OGC-OM/2.0/SF_SamplingPoint\"/><sf:sampledFeature xmlns:sf=\"http://www.opengis.net/sampling/2.0\" xlink:href=\"http://www.opengis.net/def/nil/OGC/0/unknown\"/><sams:shape><ns:Point xmlns:ns=\"http://www.opengis.net/gml/3.2\" ns:id=\"Point_ssf_b3a826dd44012201b013c90c51da28c041f7a92e0cc47260eb9888f6a4e9f747\"><ns:pos srsName=\"http://www.opengis.net/def/crs/EPSG/0/4326\">{coordinates}</ns:pos></ns:Point></sams:shape></sams:SF_SpatialSamplingFeature></sml:feature></sml:FeatureList></sml:featuresOfInterest><sml:outputs><sml:OutputList><sml:output name=\"Slope\"><swe:Quantity definition=\"Slope\"><swe:label>Slope</swe:label><swe:uom code=\"deg\"/></swe:Quantity></sml:output><sml:output name=\"Roll\"><swe:Quantity definition=\"Roll\"><swe:label>Roll</swe:label><swe:uom code=\"deg\"/></swe:Quantity></sml:output><sml:output name=\"InSystemTemperature\"><swe:Quantity definition=\"InSystemTemperature\"><swe:label>InSystemTemperature</swe:label><swe:uom code=\"degC\"/></swe:Quantity></sml:output></sml:OutputList></sml:outputs><sml:position><swe:Vector referenceFrame=\"urn:ogc:def:crs:EPSG::4326\"><swe:coordinate name=\"easting\"><swe:Quantity axisID=\"x\"><swe:uom code=\"degree\" /><swe:value>{cordX}</swe:value></swe:Quantity></swe:coordinate><swe:coordinate name=\"northing\"><swe:Quantity axisID=\"y\"><swe:uom code=\"degree\" /><swe:value>{cordY}</swe:value></swe:Quantity></swe:coordinate><swe:coordinate name=\"altitude\"><swe:Quantity axisID=\"z\"><swe:uom code=\"m\" /><swe:value>{height}</swe:value></swe:Quantity></swe:coordinate></swe:Vector></sml:position></sml:PhysicalSystem>',
|
||||
"procedureDescription": f'<sml:PhysicalSystem gml:id={off_name} xmlns:swes=\"http://www.opengis.net/swes/2.0\" xmlns:sos=\"http://www.opengis.net/sos/2.0\" xmlns:swe=\"http://www.opengis.net/swe/2.0\" xmlns:sml=\"http://www.opengis.net/sensorml/2.0\" xmlns:gml=\"http://www.opengis.net/gml/3.2\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" xmlns:xsi=\"http://www.w3.org/2001/XMLSchema-instance\" xmlns:gco=\"http://www.isotc211.org/2005/gco\" xmlns:gmd=\"http://www.isotc211.org/2005/gmd\"><gml:identifier codeSpace=\"uniqueID\">{procedure_identifier}</gml:identifier><sml:identification><sml:IdentifierList><sml:identifier><sml:Term definition=\"urn:ogc:def:identifier:OGC:1.0:shortName\"><sml:label>shortName</sml:label><sml:value>{procedure_name}</sml:value></sml:Term></sml:identifier></sml:IdentifierList></sml:identification><sml:capabilities name=\"offerings\"><sml:CapabilityList><sml:capability name=\"offeringID\"><swe:Text definition=\"urn:ogc:def:identifier:OGC:offeringID\"><swe:label>{offering_label}</swe:label><swe:value>{offering_name}</swe:value></swe:Text></sml:capability></sml:CapabilityList></sml:capabilities><sml:featuresOfInterest><sml:FeatureList definition=\"http://www.opengis.net/def/featureOfInterest/identifier\"><swe:label>featuresOfInterest</swe:label><sml:feature><sams:SF_SpatialSamplingFeature xmlns:sams=\"http://www.opengis.net/samplingSpatial/2.0\" gml:id=\"ssf_b3a826dd44012201b01323232323041f7a92e0cc47260eb9888f6a4e9f747\"><gml:identifier codeSpace=\"http://www.opengis.net/def/nil/OGC/0/unknown\">{feature_id}</gml:identifier><gml:name codeSpace=\"http://www.opengis.net/def/nil/OGC/0/unknown\">{feature_name}</gml:name><sf:type xmlns:sf=\"http://www.opengis.net/sampling/2.0\" xlink:href=\"http://www.opengis.net/def/samplingFeatureType/OGC-OM/2.0/SF_SamplingPoint\"/><sf:sampledFeature xmlns:sf=\"http://www.opengis.net/sampling/2.0\" xlink:href=\"http://www.opengis.net/def/nil/OGC/0/unknown\"/><sams:shape><ns:Point xmlns:ns=\"http://www.opengis.net/gml/3.2\" ns:id=\"Point_ssf_b3a826dd44012201b013c90c51da28c041f7a92e0cc47260eb9888f6a4e9f747\"><ns:pos srsName=\"http://www.opengis.net/def/crs/EPSG/0/4326\">{coordinates}</ns:pos></ns:Point></sams:shape></sams:SF_SpatialSamplingFeature></sml:feature></sml:FeatureList></sml:featuresOfInterest><sml:outputs><sml:OutputList><sml:output name=\"Slope\"><swe:Quantity definition=\"Slope\"><swe:label>Slope</swe:label><swe:uom code=\"deg\"/></swe:Quantity></sml:output></sml:OutputList></sml:outputs><sml:position><swe:Vector referenceFrame=\"urn:ogc:def:crs:EPSG::4326\"><swe:coordinate name=\"easting\"><swe:Quantity axisID=\"x\"><swe:uom code=\"degree\" /><swe:value>{cordX}</swe:value></swe:Quantity></swe:coordinate><swe:coordinate name=\"northing\"><swe:Quantity axisID=\"y\"><swe:uom code=\"degree\" /><swe:value>{cordY}</swe:value></swe:Quantity></swe:coordinate><swe:coordinate name=\"altitude\"><swe:Quantity axisID=\"z\"><swe:uom code=\"m\" /><swe:value>{height}</swe:value></swe:Quantity></swe:coordinate></swe:Vector></sml:position></sml:PhysicalSystem>',
|
||||
"observableProperty": [
|
||||
"Slope",
|
||||
"Roll",
|
||||
|
|
|
@ -1,5 +1,5 @@
|
|||
pip freeze > requirements.txt
|
||||
pip install -f ./requirements.txt
|
||||
pip install -r requirements.txt
|
||||
===========================================================================================
|
||||
python -m venv .venv
|
||||
d:/Software/geomon/.venv/Scripts/python.exe -m pip install -U pylint
|
||||
|
|
BIN
requirements.txt
BIN
requirements.txt
Binary file not shown.
Loading…
Reference in New Issue
Block a user