234 lines
8.5 KiB
Python
234 lines
8.5 KiB
Python
'''
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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: 3.7
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'''
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import os
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import uuid
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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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# sys.path.insert(0, parentdir)
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# import requests
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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, Person, PersonSchema, 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, date, timedelta
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# from db.pg_models import create_pg_session
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#from models import Person, PersonSchema
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# response = requests.get('https://api.com/')
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# print(response) # shows the response's HTTP status code
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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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# 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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# delta time
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delta = timedelta(days=1)
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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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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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# data = test_api.getSensorData("inclino1_14", 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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# max_id = max_id + 1
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# create_observation(observation_json, pg_session, max_id)
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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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''' 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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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)
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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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def create(person_json: PersonSchema):
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"""
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This function creates a new person in the people structure
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based on the passed-in person data
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:param person: person to create in people structure
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:return: 201 on success, 406 on person exists
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"""
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login = person_json.get('login')
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#lname = person.get('lname')
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db_session = create_pg_session()
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# existing_person = Person.query \
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# .filter(Person.login == login) \
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# .one_or_none()
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existing_person: bool = (
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db_session.query(Person)
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.filter(Person.login == login)
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.one_or_none()
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)
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# Can we insert this person?
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if existing_person is None:
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# Create a person instance using the schema and the passed in person
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schema = PersonSchema()
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# deserialize to object
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new_person: Person = schema.load(person_json)
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# Add the person to the database
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db_session.add(new_person)
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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_person)
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return data, 201
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# Otherwise, nope, person exists already
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else:
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print(409, f'Person {login} exists already')
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if __name__ == "__main__":
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main()
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