SQLAlchemy and you – making SQL the best thing since sliced bread

Are you writing SQL strings in your code? Have you only used ORMs and want to start getting more control over your SQL?

SQLAlchemy is the gold-standard for working with SQL in Python and this tutorial will get you comfortable working in it, so you can take advantage of its power.

We will go through Core and ORM abstractions, so you'll be comfortable navigating through the different layers and be able to fully use the power of Python when writing your SQL

Project setup

If you have your own, preferred setup for installing packages - go right ahead and use that. There's a requirements.txt and an environment.yml file you can use. Alternatively, if you have docker and docker compose installed, you can use the provided docker-compose setup

Docker compose

docker compose up -d
docker compose logs jupyter

In the logs you should see a URL that looks similar to

http://127.0.0.1:8888/lab?token=39ec5120ee84b090487a822b991269732a264629c894803e

Copy-paste that into your browser, you should be able to login to the Jupyter instance

Conda-based

If you have Anaconda distribution installed, you can run the following

conda env create

This will install all the packages defined in the environment.yml file into an environment named sqlalchemy-tutorial.

To activate this environment, run

conda activate sqlalchemy-tutorial

Virtualenv-based

This tutorial was written in 3.9.13 - ensure that you have at least 3.9.X installed on your machine

To create a new virtualenv run

python -m venv venv

To activate the virtualenv - run one of the following:

Windows

./venv/Scripts/activate

MacOS/Linux

source venv/bin/activate

You'll then need to install the packages

python -m pip install -r requirements.txt

After you've installed the packages run jupyter lab to start the Jupyter lab server