geomon/gschliefgraben_glasfaser/main.py

'''
Tutorial link: https://realpython.com/flask-connexion-rest-api-part-2/
https://github.com/realpython/materials/blob/master/flask-connexion-rest-part-2/version_1/people.py
Sqlalchemy version: 1.2.15
Python version: 3.7
'''

import os
import uuid
# import sys, inspect
# currentdir = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe())))
# parentdir = os.path.dirname(currentdir)
# sys.path.insert(0, parentdir)
# import requests
from sqlalchemy.orm import session
from sqlalchemy import func
# from db.pg_models import Platform
from gschliefgraben_glasfaser.models import ObservationSchema, Person, PersonSchema, Observation, create_pg_session, Dataset, Procedure, Phenomenon, Platform
from gschliefgraben_glasfaser.my_api import MyApi
from datetime import datetime, date, timedelta
# from db.pg_models import create_pg_session
#from models import Person, PersonSchema
# response = requests.get('https://api.com/')
# print(response)  # shows the response's HTTP status code
# print(response.json())  # shows the response's JSON response body, if it has one
# print(response.content)  # get the data content of the response


def main():
    ''' main method '''
    db_user = os.environ.get("POSTGIS_DBUSER")
    print(db_user)

    pg_session: session = create_pg_session()
    # pg_person: Person = pg_session.query(Person).first()
    observation: Observation = pg_session.query(Observation).first()
    # print(pg_person)

    # serialize db data to json
    # person_schema = PersonSchema()
    # dump_data = person_schema.dump(pg_person)
    # print(dump_data)
    # serialize db data to json
    # observation_schema = ObservationSchema()
    # dump_data = observation_schema.dump(observation)
    # print(dump_data)   

    # request ortmann api
    # response =
    # requests.get('https://api.dgnss-sensors.com/gschliefgraben?sensors=("inclino1_14")',
    #                         headers={
    #                             'Authorization': 'Bearer' + token,
    #                             'cache-control': 'no-cache',
    #                             'Content-Type': 'application/x-www-form-urlencoded',
    #                             'accept': 'application/json'
    #                         },
    #                         data='grant_type=client_credentials&scope=gschliefgraben')
    # print(response)

    sensor: str = "inclino1_14"
    pg_query = pg_session.query(Dataset) \
        .join(Procedure) \
        .join(Phenomenon) \
        .filter(Procedure.sta_identifier == sensor.lower())
    slope_dataset: Dataset = pg_query.filter(
        Phenomenon.sta_identifier == "Slope").first()
    if not slope_dataset.is_published:
        slope_dataset.is_published = 1
        slope_dataset.is_hidden = 0
        slope_dataset.dataset_type = "timeseries"
        slope_dataset.observation_type = "simple"
        slope_dataset.value_type = "quantity"
        pg_session.commit()
    
    # The size of each step in days
    # consider the start date as 2021-february 1 st
    start_date = date(2022, 1, 1)
    # consider the end date as 2021-march 1 st
    end_date = date(2022, 3, 1)

    # delta time
    delta = timedelta(days=1)
    token_api = os.environ.get("TOKEN_API")
    test_api = MyApi(token_api)

    # iterate over range of dates
    while start_date <= end_date:
        # print(start_date, end="\n")
        query_date = start_date.strftime('%Y-%m-%d')
        create_db_observations(query_date, test_api, pg_session, slope_dataset)
        start_date += delta
    pg_session.commit()

    # for i in rrule(DAILY , dtstart=start_date,until=end_date):
    #     print(i.strftime('%Y%b%d'),sep='\n')

    # query_date = "2022-02-28"
    # create_db_observations(query_date, test_api, pg_session)
    # query_date_obj = datetime.strptime(query_date, "%Y-%m-%d")
    # data = test_api.getSensorData("inclino1_14", query_date)
    # observation_array = (data['FeatureCollection']
    #                      ['Features'][0]['geometry']['properties'][0])
    # print(observation_array)

    # max_id = pg_session.query(func.max(Observation.id)).scalar()
    # if max_id is None:
    #     max_id = -1
    # # pg_session.bulk_save_objects(observations)
    # for observation_json in observation_array:
    #     ob_date_time = observation_json.get('DateTime')
    #     datetime_obj = datetime.strptime(ob_date_time, "%Y-%m-%dT%H:%M:%S.%fZ")
    #     if datetime_obj.date() != query_date_obj.date():
    #         continue
    #     max_id = max_id + 1
    #     create_observation(observation_json, pg_session, max_id)

    # pg_session.commit()


def create_db_observations(query_date, test_api, pg_session, dataset: Dataset):
    ''' to do '''
    query_date_obj = datetime.strptime(query_date, "%Y-%m-%d")
    data = test_api.getSensorData("inclino1_14", query_date)
    observation_array = (data['FeatureCollection']
                         ['Features'][0]['geometry']['properties'][0])
    # print(observation_array)

    max_id = pg_session.query(func.max(Observation.id)).scalar()
    if max_id is None:
        max_id = -1
    # pg_session.bulk_save_objects(observations)
    for observation_json in observation_array:
        ob_date_time = observation_json.get('DateTime')
        datetime_obj = datetime.strptime(ob_date_time, "%Y-%m-%dT%H:%M:%S.%fZ")
        if datetime_obj.date() != query_date_obj.date():
            continue
        ob_value = observation_json.get('Value')
        if ob_value is None:
            continue
        # max_id = max_id + 1
        max_id = create_observation(
            observation_json, pg_session, max_id, dataset)
    # pg_session.commit()
    print("observations for date " + query_date + "succesfully imported \n")


def create_observation(observation_json: ObservationSchema, db_session, max_id, dataset: Dataset):
    """
    This function creates a new observation in the people structure
    based on the passed-in observation data
    :param observation:  person to create in people structure
    :return:        201 on success, observation on person exists
    """

    ob_id: str = str(observation_json.get('id'))
    # db_session = create_pg_session()

    existing_observation: bool = (
        db_session.query(Observation)
        .filter(Observation.value_identifier == ob_id)
        .one_or_none()
    )

    # Can we insert this observation?
    if existing_observation is None:
        max_id += 1
        # Create a person instance using the schema and the passed in person
        schema = ObservationSchema()
        # deserialize to python object
        new_observation: Observation = schema.load(observation_json)
        new_observation.id = max_id
        new_observation.sta_identifier = str(uuid.uuid4())
        new_observation.sampling_time_start=new_observation.result_time
        new_observation.sampling_time_end=new_observation.result_time
        new_observation.fk_dataset_id = dataset.id

        # Add the person to the database
        db_session.add(new_observation)
        # dataset.observations.append(new_observation)
        # db_session.commit()

        # Serialize and return the newly created person in the response
        # data = schema.dump(new_observation)
        # return data, 201
        return max_id
    # Otherwise, nope, person exists already
    else:
        print(409, f'Observation {ob_id} exists already')
        return max_id


def create(person_json: PersonSchema):
    """
    This function creates a new person in the people structure
    based on the passed-in person data
    :param person:  person to create in people structure
    :return:        201 on success, 406 on person exists
    """

    login = person_json.get('login')
    #lname = person.get('lname')
    db_session = create_pg_session()

    # existing_person = Person.query \
    #     .filter(Person.login == login) \
    #     .one_or_none()
    existing_person: bool = (
        db_session.query(Person)
        .filter(Person.login == login)
        .one_or_none()
    )

    # Can we insert this person?
    if existing_person is None:
        # Create a person instance using the schema and the passed in person
        schema = PersonSchema()
        # deserialize to object
        new_person: Person = schema.load(person_json)

        # Add the person to the database
        db_session.add(new_person)
        db_session.commit()

        # Serialize and return the newly created person in the response
        data = schema.dump(new_person)
        return data, 201
    # Otherwise, nope, person exists already
    else:
        print(409, f'Person {login} exists already')


if __name__ == "__main__":
    main()