Codespaces Airflow training environment

This repository contains the code for the Airflow training environment.

Getting started

1. Check that you have enough memory allocated to your codespaces instance. In the terminal (ctrl + ` ) check you have more than 4GB of allocated memory:

   docker run --rm "debian:bullseye-slim" bash -c 'numfmt --to iec $(echo $(($(getconf _PHYS_PAGES) * $(getconf PAGE_SIZE))))'
   

   An no, 3.9 is not enough. If you see 3.9 means that you did not selected the right machine in step 2.

2. Run database migrations (ONLY RUN ONCE)

   You need to run database migrations and create the first user account. It is all defined in the docker compose file so just run:

   docker compose up airflow-init
   

3. Now you can start all services:

   docker compose up
   

   This will make Airflow available at: http://localhost:8080

4. Login to Airflow:

   

Running Airflow in a Python Environment

If for some reason its not possible to you to run Airflow using docker, you can also do it using python.

1. Install airflow

   pip install apache-airflow
   

   or

   poetry add apache-airflow
   

   Make sure you have a virtual environment activated in which you can isolate your code/dependencies

2. initialize the database

   airflow db init
   

3. Create a new user

   airflow users create --username airflow --password airflow --firstname anon --lastname nymus --role Admin --email user@company.com 
   

4. Copy your dags to the dags/ folder

   cp dags/mydag.py ~/airflow/dags/
   

5. In a termnial initialize the webserver

   airflow webserver -p 8080
   

6. In a second terminal initialize the scheduler

   airflow scheduler