Often in our developer workflows, we find ourselves running routine, or semi-routine, and monotonous tasks. This can be things like compiling code, bootstrapping dev servers, running migrations, etc. The kind of commands that you eventually get rather tired of typing into a terminal over, and over again. These days, many developers often rely on various kinds of task runners to at least partially automate execution of these kinds of tedious and repetitive tasks.

After multiple previous failed attempts, I am finally starting to get the hang of Apache Airflow and, even with a relatively basic mastery, I have been able to do some pretty interesting things with it. What is Airflow? Apache Airflow is a Python-based tool for scheduling and automating various workflows. It was originally created at AirBnB as an internal tool, and later open-sourced, under the Apache license. It has since become a top-level project at the Apache Foundation.

This post follows up on my earlier post about storing json data in Postgres. In this article, I will be going over how to integrate the same JSONB data I used in that post with a Django web application. Modeling the Data Modeling JSONB data with Django’s ORM tool is rather easy, as the framework has built in support for this in the django.contrib module. Therefore, we would model our data like this in our models.

I recently started exploring how to store JSON data in a traditional relational database management system (RDBMS), rather than a dedicated form of JSON/document storage, like MongoDB. While I could write a lot more about the problems with MongoDB, that’s not what I want to do here. Instead, I want to focus primarily on how to store and query JSON in PostgreSQL. However, I should note that PostgreSQL is not the only RDBMS that supports JSON storage.