- now adding observations to dataset
- addiotonal notes for pip in notes.txt - pip requirements.txt
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@ -6,7 +6,6 @@ Python version: 3.7
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'''
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import os
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from tokenize import String
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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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@ -15,7 +14,8 @@ import uuid
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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 gschliefgraben_glasfaser.models import ObservationSchema, Person, PersonSchema, Observation, create_pg_session
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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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@ -41,13 +41,9 @@ def main():
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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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# # deserialize to db model
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# load_data: Person = person_schema.load(dump_data)
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# print(load_data)
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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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@ -61,10 +57,24 @@ def main():
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# data='grant_type=client_credentials&scope=gschliefgraben')
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# print(response)
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# The size of each step in days
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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(2021, 2, 28)
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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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@ -77,13 +87,13 @@ def main():
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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)
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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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@ -92,8 +102,6 @@ def main():
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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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@ -108,7 +116,8 @@ def main():
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# pg_session.commit()
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def create_db_observations(query_date, test_api, pg_session):
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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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@ -128,13 +137,14 @@ def create_db_observations(query_date, test_api, pg_session):
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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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create_observation(observation_json, pg_session, max_id)
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pg_session.commit()
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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):
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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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@ -142,34 +152,41 @@ def create_observation(observation_json: ObservationSchema, db_session, max_id):
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:return: 201 on success, observation on person exists
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"""
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ob_id = observation_json.get('id')
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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.id == ob_id)
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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 object
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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 + 1
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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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# 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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@ -38,6 +38,51 @@ def create_pg_session() -> sessionmaker:
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# Base.metadata.create_all(engine)
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return _session
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class Platform(Base):
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""" Platform class """
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__tablename__ = 'platform'
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__table_args__ = {"schema": "gba"}
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id = Column('platform_id', Integer, primary_key=True)
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identifier = Column('identifier', String)
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sta_identifier = Column('sta_identifier', String)
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name = Column('name', String)
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# datasets = relationship('Dataset')
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datasets = relationship('Dataset', back_populates="platform", lazy=True)
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def __repr__(self):
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return f'Platform {self.name}'
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class Phenomenon(Base):
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""" phenomenon class """
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__tablename__ = 'phenomenon'
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__table_args__ = {"schema": "gba"}
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id = Column('phenomenon_id', Integer, primary_key=True)
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name = Column('name', String)
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sta_identifier = Column('sta_identifier', String)
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# datasets = relationship('Dataset')
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datasets = relationship('Dataset', back_populates="phenomenon", lazy=True)
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def __repr__(self):
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return f'Phenomenon {self.name}'
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class Procedure(Base):
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""" procedure class """
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__tablename__ = 'procedure'
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__table_args__ = {"schema": "gba"}
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id = Column('procedure_id', Integer, primary_key=True)
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name = Column('name', String)
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sta_identifier = Column('sta_identifier', String)
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# datasets = relationship('Dataset')
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datasets = relationship('Dataset', back_populates="procedure", lazy=True)
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def __repr__(self):
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return f'Procedure {self.name}'
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class Dataset(Base):
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""" dataset class """
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@ -70,8 +115,25 @@ class Dataset(Base):
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# first_observation = relationship("Observation", foreign_keys=[
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# fk_first_observation_id])
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# observations = relationship(
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# 'Observation', back_populates='dataset', lazy=True)
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observations = relationship(
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'Observation', back_populates='dataset', lazy=True)
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fk_phenomenon_id = Column(
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'fk_phenomenon_id', Integer, ForeignKey('gba.phenomenon.phenomenon_id'), nullable=False)
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# phenomenon = relationship("Phenomenon", lazy="joined", foreign_keys=[fk_phenomenon_id])
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phenomenon = relationship(
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"Phenomenon", back_populates="datasets", lazy="joined")
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fk_platform_id = Column('fk_platform_id', Integer, ForeignKey(
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'gba.platform.platform_id'), nullable=True)
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platform = relationship(
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"Platform", back_populates="datasets", lazy="joined")
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fk_procedure_id = Column('fk_procedure_id', Integer, ForeignKey(
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'gba.procedure.procedure_id'), nullable=False)
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# procedure = relationship("Procedure", lazy="joined")
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procedure = relationship(
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"Procedure", back_populates="datasets", lazy="joined")
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def new_id_factory():
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''' test '''
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@ -108,9 +170,9 @@ class Observation(Base):
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value_identifier = Column('value_identifier', String)
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value_quantity = Column('value_quantity', Numeric(20, 10), nullable=False)
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# fk_dataset_id = Column(Integer, ForeignKey(
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# 'gba.dataset.dataset_id'), nullable=False)
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# dataset = relationship("Dataset", back_populates="observations")
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fk_dataset_id = Column(Integer, ForeignKey(
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'gba.dataset.dataset_id'), nullable=False)
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dataset = relationship("Dataset", back_populates="observations")
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class ObservationSchema(SQLAlchemySchema):
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@ -175,7 +237,7 @@ def create_db():
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# session_maker = sessionmaker(bind=engine)
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# session = session_maker()
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Base.metadata.drop_all(bind=engine)
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Base.metadata.create_all(engine)
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# Base.metadata.create_all(engine)
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if __name__ == "__main__":
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@ -1,4 +1,5 @@
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pip freeze > requirements.txt
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pip install -f ./requirements.txt
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===========================================================================================
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python -m venv .venv
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d:/Software/geomon/.venv/Scripts/python.exe -m pip install -U pylint
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requirements.txt
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requirements.txt
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