From Project to Productionized with Python

Summary

The post presents a hands-on tutorial for Python developers moving a local Django application into production on Heroku. It frames the work around 12-factor practices and covers repository hygiene, modular settings, continuous delivery stages, static-asset middleware, environment configuration, database provisioning, deployment, scaling, and troubleshooting. The configuration changes include excluding virtual environments, caches, SQLite data, and generated static files; moving settings.py to settings/base.py; updating DJANGO_SETTINGS_MODULE; adding Whitenoise; and supplying SECRET_KEY and a Heroku Postgres add-on. The deployment uses Git, the Heroku CLI, git push heroku main, and heroku ps:scale web=1, with heroku logs --tail and heroku run bash for diagnosis. The walkthrough concludes with the app deployed and accessible through heroku open.

Takeaways

1. 1

   The Django settings are split by moving settings.py to settings/base.py and updating manage.py and wsgi.py to use gettingstarted.settings.base.

2. 2

   The deployment provisions Postgres with heroku addons:create heroku-postgresql:hobby-dev instead of relying on the local SQLite database.

3. 3

   After git push heroku main, the web process is scaled with heroku ps:scale web=1; heroku logs --tail and heroku run bash support troubleshooting.