
Column ( JSON ) def _init_ ( self, url, result_all, result_no_stop_words ): self. Column ( JSON ) result_no_stop_words = db. Model ): _tablename_ = 'results' id = db. Once you have Postgres installed and running, create a database called wordcount_dev to use as our local development database:įrom app import db from import JSON class Result ( db. If you don’t have Postgres installed, Postgres.app is an easy way to get up and running for Mac OS X users. Since Heroku uses Postgres, it will be good for us to develop locally on the same database. To get started, install Postgres on your local computer, if you don’t have it already.


Part Two: Set up a PostgreSQL database along with SQLAlchemy and Alembic to handle migrations.Part One: Set up a local development environment and then deploy both a staging and a production environment on Heroku.Remember: Here’s what we’re building - A Flask app that calculates word-frequency pairs based on the text from a given URL. : Upgraded to Python version 3.5.1 as well as the latest versions of Psycopg2, Flask-SQLAlchemy, and Flask-Migrate.Explicitly install and use Flask-Script due to change of Flask-Migrate internal interface. : Upgraded to Python version 3.8.1 as well as the latest versions of Psycopg2, Flask-SQLAlchemy, and Flask-Migrate.Free Bonus: Click here to get access to a free Flask + Python video tutorial that shows you how to build Flask web app, step-by-step.
