''' 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()