11 Jun 2018

Flask and SQLAlchemy without the Flask-SQLAlchemy Extension

When using SQLAlchemy with Flask, the standard approach is to use the Flask-SQLAlchemy extension.

However, this extension has some issues. In particular, we have to use a base class for our SQLAlchemy models that creates a dependency on flask (via flask_sqlalchemy.SQLAlchemy.db.Model). Also, an application may not require the additional functionality that the extension provides, such as pagination support.

Let’s see if we can find a way to use plain SQLAlchemy in our Flask applications without relying on this extension.

This article focuses specifically on connecting a Flask application to SQLAlchemy directly, without using any plugins or extensions. It doesn’t address how to get a Flask application working on its own, or how SQLAlchemy works. It may be a good idea to get these parts working separately first.

Below is the code that sets up the SQLAlchemy session (db.py):

import os

from sqlalchemy import create_engine

from sqlalchemy.orm import scoped_session
from sqlalchemy.orm import sessionmaker

engine = create_engine(os.environ['SQLALCHEMY_URL'])

Session = scoped_session(sessionmaker(bind=engine))

The key here is scoped_session: Now when we use Session, SQLAlchemy will check to see if a thread-local session exists. If it already exists, then it will use it, otherwise it will create one first.

The following code bootstraps the Flask application (__init__.py):

from flask import Flask

from .db import Session

from .hello import hello_blueprint

app = Flask(__name__)

def cleanup(resp_or_exc):

The @app.teardown_appcontext decorator will cause the supplied callback, cleanup, to be executed when the current application context is torn down. This happens after each request. That way we make sure to release the resources used by a session after each request.

In our Flask application, we can now use Session to interact with our database. For example (hello.py):

import json

from flask import Blueprint

from .db import Session

from .models import Message

hello_blueprint = Blueprint('hello', __name__)

def messages():
    values = Session.query(Message).all()

    results = [{ 'message': value.message } for value in values]

    return (json.dumps(results), 200, { 'content_type': 'application/json' })

This should be sufficient for integrating SQLAlchemy into a Flask application.

For a more detailed overview of the features Flask-SQLAlchemy provides, see Derrick Gilland’s article, Demystifying Flask-SQLAlchemy

We also get the benefit of not having to create a dependency on Flask for our SQLAlchemy models. Below we’re just using the standard sqlalchemy.ext.declarative.declarative_base (models.py):

from sqlalchemy.ext.declarative import declarative_base

from sqlalchemy import Column, Integer, String

Base = declarative_base()

class Message(Base):
    __tablename__ = 'messages'
    id = Column(Integer, primary_key=True)
    message = Column(String)
    def __repr__(self):
        return "<Message(message='%s')>" % (self.message)

I could be wrong, but I would prefer to start a project with this approach initially, and only to incorporate the Flask-SQLAlchemy extension later if it turns out to be demonstrably useful.

This code is available on github: https://github.com/nestedsoftware/flask_sqlalchemy_starter