Before you begin
- Complete the previous sections of the tutorial, ending with .
- On your local machine:
- .
- Install Python 3 and Pipenv if necessary.
- Clone the
movr-flaskrepository. We’ll reference the source code in this repository throughout the tutorial.
Set up a demo multi-region CockroachDB cluster
For debugging and development purposes, you can use the command. This command starts up a secure, nine-node demo cluster.-
To set up the demo multi-region cluster, run
cockroach demo, with the--nodesand--demo-localityflags. The localities specified below assume GCP region names.Keep this terminal window open. Closing it will shut down the demo cluster. -
In a new terminal, load the
dbinit.sqlscript to the demo database. This file contains themovrdatabase schema that we covered in . -
Verify that the database schema loaded:
A production deployment should ideally have nodes on machines located in different areas of the world. You will deploy a multi-region CockroachDB cluster for this application using CockroachDB Standard in the final section of this tutorial series, .
Set up a virtual development environment
For debugging, usepipenv, a tool that manages dependencies with pip and creates virtual environments with virtualenv.
-
Initialize the project’s virtual environment:
pipenvcreates aPipfilein the current directory, with the requirements needed for the app. -
Install the packages listed in the
Pipfile: -
Activate the virtual environment:
From this shell, you can run any Python 3 application with the required dependencies that you listed in the
Pipfile, and the environment variables that you listed in the.envfile. You can exit the shell subprocess at any time with a simpleexitcommand. -
To test out the application, you can run the server file:
To run Python commands within the virtual environment, you do not need to add
3to the end of the command. For example, runningpython3 server.pyinstead of the above command results in an error. - Navigate to the application’s test URL, which defaults to http://127.0.0.1:5000/.
In production, it is often recommended to containerize your application and deploy it with a deployment orchestration tool like Kubernetes or with a serverless deployment service like Google Cloud Run. You will learn to deploy the application with Google Cloud Run in the final section of this tutorial series, .

