- add marshmallow-sqlalchemy marshmallow for inserting db data via deserialization
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.vscode/launch.json
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.vscode/launch.json
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{
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// Use IntelliSense to learn about possible attributes.
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// Hover to view descriptions of existing attributes.
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// For more information, visit: https://go.microsoft.com/fwlink/?linkid=830387
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"version": "0.2.0",
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"configurations": [
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{
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"name": "Python: Current File",
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"type": "python",
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"request": "launch",
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"program": "${file}",
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"console": "integratedTerminal"
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}
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]
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}
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3
.vscode/settings.json
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.vscode/settings.json
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@ -7,6 +7,7 @@
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"pylint_flask",
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"pylint_flask_sqlalchemy",
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],
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"python.pythonPath": "d:\\Software\\geomon\\.venv\\Scripts\\python.exe",
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// "python.pythonPath": "d:\\Software\\geomon\\.venv\\Scripts\\python.exe",
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"python.defaultInterpreterPath": "./.venv/Scripts/python.exe",
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"python.envFile": "${workspaceFolder}/.env"
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}
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@ -1,2 +1,3 @@
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# For relative imports to work in Python 3.6
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import os, sys; sys.path.append(os.path.dirname(os.path.realpath(__file__)))
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import os, sys; sys.path.append(os.path.dirname(os.path.realpath(__file__)))
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# print(f'Invoking __init__.py for {__name__}')
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@ -5,8 +5,8 @@ from typing import List
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import uuid
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from sqlalchemy.orm import session
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from sqlalchemy import func, desc, asc
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from fb_models import (create_session, FbObservation, Catena)
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from pg_models import (create_pg_session, Dataset, Observation, Procedure, Phenomenon, Platform)
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from db.fb_models import (create_session, FbObservation, Catena)
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from db.pg_models import (create_pg_session, Dataset, Observation, Procedure, Phenomenon, Platform)
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def main():
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"""
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@ -1,15 +1,82 @@
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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: 3.7
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'''
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import os
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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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from db.pg_models import create_pg_session
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from sqlalchemy.orm import session
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from gschliefgraben_glasfaser.models import PersonSchema
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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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# (for your case this is the downloaded file)
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# print(dir(response)) # shows you all the different methods you can call on this response object
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db_user = os.environ.get("POSTGIS_DBUSER")
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print(db_user)
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def main():
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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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# 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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# deserialize
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load_data: Person = person_schema.load(dump_data)
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print(load_data)
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create(dump_data)
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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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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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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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session.add(new_person)
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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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@ -1,8 +1,9 @@
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'''
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Tutorial link: https://docs.sqlalchemy.org/en/latest/orm/tutorial.html
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Sqlalchemy version: 1.2.15
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Python version: 3.7
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Sqlalchemy version: 1.4.31
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Python version: 3.10
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'''
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#!/usr/bin/python# -*- coding: utf-8 -*-
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from datetime import datetime
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# from config import db, ma
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@ -14,24 +15,32 @@ from sqlalchemy.ext.declarative import declarative_base
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from sqlalchemy.orm import session
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from marshmallow import Schema
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from db.pg_models import create_pg_session
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from marshmallow_sqlalchemy import SQLAlchemyAutoSchema
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Base = declarative_base()
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class Person(Base):
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""" Platform class """
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__tablename__ = 'person'
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person_id = Column(Integer, primary_key=True)
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lname = Column(String(32), index=True)
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fname = Column(String(32))
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timestamp = Column(DateTime, default=datetime.utcnow,
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__tablename__ = 'accounts'
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__table_args__ = {"schema": "gba"}
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person_id = Column('id', Integer, primary_key=True)
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lname = Column('last_name', String(255), index=True)
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fname = Column('first_name', String(255))
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login = Column(String(255))
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timestamp = Column('updated_at', DateTime, default=datetime.utcnow,
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onupdate=datetime.utcnow)
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def __repr__(self):
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return "<User(name='%s', lastname='%s')>" % (
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self.login, self.lname)
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class PersonSchema(Schema):
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class PersonSchema(SQLAlchemyAutoSchema):
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""" Platform class """
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class Meta:
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""" Platform class """
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model = Person
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include_relationships = True
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load_instance = True
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#pg_session: session = create_pg_session()
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sqla_session: session = create_pg_session()
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@ -28,9 +28,9 @@ Install python formatter:
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d:/Software/geomon/.venv/Scripts/python.exe -m pip install -U autopep8
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pip install fdb
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pip install sqlalchemy-firebird
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pip install psycopg2
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python -m pip install fdb
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python -m pip install sqlalchemy-firebird
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python -m pip install psycopg2
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Marshmallow provides functionality to serialize and deserialize Python objects as they flow out of and into our JSON-based REST API. Marshmallow converts Python class instances to objects that can be converted to JSON.
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pip install marshmallow-sqlalchemy marshmallowll
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python -m pip install marshmallow-sqlalchemy marshmallow
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pg_models.py
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pg_models.py
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'''
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Tutorial link: https://docs.sqlalchemy.org/en/latest/orm/tutorial.html
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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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from sqlalchemy import (create_engine, Column, Integer,
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SmallInteger, String, ForeignKey, DateTime, Numeric)
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from sqlalchemy.ext.declarative import declarative_base
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from sqlalchemy.orm import sessionmaker, relationship
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import sqlalchemy.orm.session
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Base = declarative_base()
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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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__tablename__ = 'dataset'
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__table_args__ = {"schema": "gba"}
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id = Column('dataset_id', Integer, primary_key=True)
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name = Column('name', String)
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is_published = Column('is_published', SmallInteger)
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is_hidden = Column('is_hidden', SmallInteger)
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dataset_type = Column('dataset_type', String)
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observation_type = Column('observation_type', String)
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value_type = Column('value_type', String)
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last_time = Column('last_time', DateTime)
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last_value = Column('last_value', Numeric(20, 10))
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fk_last_observation_id = Column(
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'fk_last_observation_id',
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Integer
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)
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# last_observation = relationship(
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# "Observation", foreign_keys=[fk_last_observation_id])
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first_time = Column('first_time', DateTime)
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first_value = Column('first_value', Numeric(20, 10))
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fk_first_observation_id = Column(
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'fk_first_observation_id',
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Integer
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)
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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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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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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(
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# 'fk_platform_id', Integer, ForeignKey('gba.platform.platform_id'), nullable=True)
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# # platform = relationship("Platform", lazy="joined", foreign_keys=[fk_platform_id])
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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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def __repr__(self):
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return f'Dataset {self.name}'
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class Observation(Base):
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""" observation class """
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__tablename__ = 'observation'
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__table_args__ = {"schema": "gba"}
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id = Column('observation_id', Integer, primary_key=True)
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name = Column('name', String)
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value_type = Column('value_type', String)
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# pitch = Column('PITCH', String)
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# roll = Column('ROLL', String)
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sampling_time_start = Column('sampling_time_start', DateTime)
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sampling_time_end = Column('sampling_time_end', DateTime)
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result_time = Column('result_time', DateTime)
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sta_identifier = Column('sta_identifier', String)
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value_quantity = Column('value_quantity', Numeric(20, 10), nullable=False)
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# fk_dataset_id = Column('fk_dataset_id', Integer,
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# ForeignKey('gba.dataset.dataset_id'))
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# dataset = relationship("Dataset", lazy="joined",
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# foreign_keys=[fk_dataset_id])
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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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def __repr__(self):
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return f'Observation {self.name}'
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# @property
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# def result_time(self):
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# ''' Create a datetime object '''
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# start_datetime = datetime.datetime.combine(self.date, self.ora)
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# return start_datetime
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def create_pg_session() -> sqlalchemy.orm.sessionmaker:
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"""Return the sum of x and y."""
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dbschema = ''
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db_user = os.environ.get("POSTGIS_DBUSER")
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db_password = os.environ.get("POSTGIS_DBPASSWORD")
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db_url = os.environ.get("POSTGIS_DBURL")
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engine = create_engine(
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"postgresql+psycopg2://" + db_user + ":" + db_password + "@" + db_url,
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connect_args={'options': '-csearch_path={}'.format(dbschema)},
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isolation_level="READ UNCOMMITTED")
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session_maker = sessionmaker(bind=engine)
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session = session_maker()
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Base.metadata.create_all(engine)
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return session
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