Using Jupyter for Exploring a Heroku Database25 Mar 2016
If you want to establish a connection to a Heroku database and import data into Jupyter for some analysis, here’s some boilerplate to help:
# Python 3 from sqlalchemy import create_engine import pandas as pd import subprocess DATABASE_URL = subprocess.check_output("heroku config:get DATABASE_URL --app <your heroku app name here>", shell=True).decode('utf-8') engine = create_engine(DATABASE_URL) result = pd.read_sql_query( ''' SELECT * FROM my_table; ''', con=engine)
Now you have
result, which is a Pandas DataFrame. Happy data exploration!
Note: It probably goes without saying this is a bad idea to do on a production system. You should use a read-only replica for running queries in production, or use a dump of the database loaded onto another server.