Deploying and Maintaining a Web App Part 2: Setting up the Database and App Configuration

It is good practice when developing a web application to set up different environments for deploying changes. The number and nature of environments that are used can vary, but we’ll be using the following commonplace architecture:

  • Development Environment: Where you develop the web application, typically on your local machine.
  • Testing Environment: Where you perform tests to help ensure the quality of your application.
  • Staging Environment: Where you deploy the application for the purpose of conducting “integration tests” that testing the broader functionality of your web app.
  • Production Environment: Where you deploy your web app to your users.

In this Part 2 of our web app deployment and maintenance project, we’ll begin to set up some of these environments, including a database with an extremely simple schema as well as some additions to our application to incorporate the database and configure the app.

To follow along, you can clone the repository:

git clone

And then go to the appropriate location in the code changes with the following command:

git checkout 75521eb0e3d

Finally, create the python environment with:

conda env create -f environment.yml

Installing Additional Python Packages

To start off, we’ll install a couple of additional packages to our app’s Conda environment:

  • Flask-SQLAlchemy: SQLAlchemy is a fantastic Python library that provides a way of interacting with your database purely in python, without having to write SQL query strings. Another benefit of using SQLAlchemy and similar ORMs is the ability to easily swap out databases if you decide you want to change in the future. Flask-SQLAlchemy is an extension for Flask that makes it easier to incorporate SQLAlchemy into Flask apps.
  • Flask-Migrate: A Flask extension that provides a lightweight wrapper around the Alembic database migration framework. This will come in handy later when we need to make changes to our database schema after it’s already been deployed to production.
  • Flask-WTF: A Flask extension that makes it easy to work with web forms.
  • psycopg2: An adapter for PostgreSQL databases in Python. PostgreSQL will be our database of choice and this package is required to connect it up to our application.

To install these applications, first start up the Conda environment with the following command:

source activate app-deploy

Then install the packages above with the following commands:

pip install Flask-SQLAlchemy

pip install flask-migrate

pip install Flask-WTF

conda install psycopg2

Installing and Setting Up the PostgreSQL Databases

Next, we need to install PostgreSQL. You can find the proper install for your system here.

Postgres comes with a handy front end terminal program called psql, which allows you to examine your database’s tables and records using SQL queries. We first use psql to initialize two of the databases we’ll be working with for our program: the development database and the test database.

First enter into psql by typing psql into the terminal:

From here, you can run a bunch of useful commands. For example \l lists all the databases you currently have in postgres:

For now, we’ll need to use psql to create two databases that we’ll call app_deploy_development and app_deploy_test. This is as simple as running the two commands below.

Running the command \l shows that these two databases have been created:

You can then exit postgres with the command \q or simply press control-d.

To be able to connect to this database from Flask / SQL Alchemy, we need the URL string associated with the database. In PostgreSQL, this takes the form:


We’ll eventually be running the the development and test databases on localhost, so the hostname is ‘localhost’, the port is 5432 (this is a postgres default) and database is ’app_deploy_development’. You can confirm the port Postgres is running on by running the following command:

Configuring our Flask App

Now we’ll make some changes to the app so that the database is actually used.

FIrst we will begin to incorporate the application environments that we need. The main way to do this in Flask is through the configuration variables, which are stored in app.config variable (where app is the instance of your application).

The simplistic version of app.config is treated like a simple dictionary (e.g. you can set app.config[‘SECRET_KEY’] = ‘some_secret’), but this does not account for the fact that you need to work with different sets of configurations depending on how you’re running your application. Instead, a more flexible way to set up the app.config variable is to use a hierarchy of configuration classes, defined like this:

SQLALCHEMY_DATABASE_URI is an environmental variable required by SQLAlchemy to tell the extension where to find the database. Since these environmental variables are sensitive (they contain username and password information that you would not want to share), they are defined in your system’s environmental variables rather than including them in version control (you define these using the export command). Add the configuration code above is to a file called in the app’s top directory.

Refactoring our App to use the Application Factory Pattern

We need to do some restructuring of our application to account for the database and implement the “application factory” pattern in Flask that allows us to provide different app instances with different configurations. We first move our file into the /app folder. We also create an app/templates/ folder to store the front-end template that will hold the template for our front end form to enter names the and “hello world” message.

We also create /app/

This file stores our factory function ‘create_app’ that returns instances of the application. create_app takes a config_name argument, allowing us to create an app with the desired configuration option (e.g. create_app(‘development’), create_app(‘testing’), etc.) The configuration is assigned to the app within the factory function using the Flask app.config.from_object function along with the dictionary of configuration classes defined in

Adding the Database to our App

Rather than having just “Hello World”, we want to have our application make use of the database in some minimal way. So, we add a form where the user can enter names which are stored in the database inside a single table, consisting of a single column holding the names.

To define the database schema, we create a file called

This file imports our database instance db. Here we define a ‘name’ string column, and an integer id that serves as a primary key (your table must have a primary key).

We also create a file in the app’s top directory:

This file is tasked with creating the instances of app from the create_app function defined in app/ This function is what allows us to choose a particular configuration, which we define in an environment variable on our system called FLASK_CONFIG. It is also a place where we can do additional configuring of our newly generated application instance (e.g. creating commands for your app with the flask command line program by decorating functions with @app.cli.command()). This file may seem a little unnecessary now but it will come in handy later.

We also need to insert a form for the user to enter in data. We’ll use the assistance of the great Flask extension, Flask-WTF. With Flask-WTF, you define forms as classes that inherit from FlaskForm. Each of the class variables represents a field in the form that takes in certain types of values. Here our form is quite simple as it only takes a single field where the user can enter in names. There is also a ‘submit’ button which provides exactly what you expect.

Now that we have a form defined, we can define the new front end template index.html.

In our main application, we need to pass our NameForm class to render this template so we add the following code to Also note that, because of the way that we used the app_factory pattern, we must now use ‘BluePrints” for our view functions rather than defining routes in a single file directly to the app instance (blueprints are basically objects that can hold a bunch of an app’s routes and code and then can be registered with the application in the apps factory function).

Running our Updated App With the Database

To run the application first define environmental variables:

  • FLASK_APP, which tells the flask command line program where the flask application is located so that it can run it:
  • FLASK_CONFIG, which is the environmental variable that tells the program what environment your app should be running in. As a reminder, this value is used in and references one of the values in the dict found in
export FLASK_CONFIG=development
  • DEV_DATABASE_URL, which points to your development database. As a reminder, this is assigned to the environment variable SQLALCHEMY_DATABASE_URI in
export DEV_DATABASE_URL=”postgresql://<insert username>:<insert password>@localhost:5432/app_deploy_development”

Before you run the application the first time, you have to initialize the database. You only have to do this once, using the db.create_all() method provided by Flask-SQLAlchemy. From the top application directory run:

flask shell
>> from app import db
>> db.create_all()

Then you can exit the python interpreter with quit() or control-d.

Finally, run the application with:

flask run

Now, when you visit, you should see this:

Your app should now be running with a live development database in the background ready to store whatever is entered into the form. To make sure it’s working, enter a few names into the form (for my test, I typed in “Foobar”, “Mark”, and “Joanna”). Then, in the terminal from the top directory in your app, write the command “flask shell” to run the python interpreter in the context of your app. This throws you into the python interpreter. We’ll then query the database to make sure our names exist:

Looks like we’re good to go! Just to be sure, I loop through the names to make sure they’re the values we expect:

Workflow to Deploy and Maintain a Web App

In this series, I’m going to work through the process of deploying and maintaining a simple web application. The goal is for you to get an understanding of all the steps that may be involved in deploying a web app and maintaining it in production with modern tools and techniques.

To follow along in this series, it would help to have an understanding of the command line, python programming, and basic web application development. I’ll be using the Flask web development framework. You’re in my target audience if you’ve built simple Flask applications running locally, and you now want to deploy it and use related best practices, such as implementing development, staging, and production environments, using docker containers, and making changes to the application via continuous integration / continuous deployment (CI / CD) tools.

The focus here is not on the web application itself –  rather, it’s on the process of deployment and maintenance. I’m going to get into all the nuts and bolts related to getting the app running live and maintaining it in a smart way. Along the way, we’ll learn about the best practices around deploying a web application that I find are not readily available in many tutorials.

Table of contents:

Part 1 – Setting up the server (currently reading)
Part 2 – Setting up the Database and App Configuration
Part 3 – Adding Tests with Pytest
… To come, as I finish the series 🙂

Getting Started

As the basis for our adventure, we’ll start with the simplest Flask app possible: the hello world app from the Flask website.

To get the full code for this application, run:

git clone

You need install Conda, which is the tool I use for managing the python environments (see my related post here). The environment information is stored in environment.yml in the repository.

To create the python environment from the environment.yml file, run the following command in the main project directory (i.e. app-deploy/):

conda env create -f environment.yml

The conda environment is called ‘app-deploy’. To run the environment after you’ve created it, simply type (on Mac or Linux):

source activate app-deploy

Or on Windows:

activate app-deploy

For each part of this series, I will provide a git checkout command that will allow you to see the code in the state relevant to that part of the series.

To start off with the initial, most basic version of the application, run:

git checkout 75521eb0e3

The main document in the repository is a file called that looks like this:

First activate the environment, which will add ‘(app-deploy)’ to your command line to indicate you are in the environment, like this:

Now that you are in the appropriate python environment, you can run:


Which runs Flask’s development server and serves the app to

If you visit the site in the browser, you should see this:

Part 1 – Setting up the Server

As a first step in this process, we’re going to spin up a server that will ultimately run the web application in production.

An aside for data scientists: Running and configuring web servers is a valuable skill for data scientists. You often need to do this to run data-driven applications you build for others (you don’t want to be running these things on your desktop computer). Furthermore, there are many valuable tools and services out there for data scientists and their coworkers that are designed to run on a server, rather than as a desktop application (e.g. Apache Superset, which is a free and open source business intelligence dashboard like Tableau or PowerBI). Servers also come in handy for your own personal use even if you have no plans to deploy a web application. For example, your server can run scripts that automatically create reports and send you email notifications, or you can run web scrapers that collect data while you sleep.

Back in the day, you needed an on-site physical server to do this. Thankfully, modern cloud computing makes it incredibly easy and cheap to run your own server. There are a few good options out there, but in this series, I’m going to use a Digital Ocean “droplet”. 

First, create an account with Digital Ocean. Then, choose the option to create a droplet:

Then, choose the operating system that you want your server to run on. I went with Ubuntu, since it’s what I’m most familiar with. It has a large user base, and as a result, there is lots of online tutorials / documentation to help you troubleshoot when things go wrong.

Then choose the memory and CPU power of your server. I went with the smallest / cheapest one. It’s easy to “resize” your droplet later on if you realize you need more juice.

Now choose a datacenter region – this is the location where your server will run. I suggest picking a data center closest to you, or closest to where your users will be. For me, that’s their Toronto data center.

Finally, you have to specify an SSH key. This will allow you to use the ssh command line program to log into your server remotely (you’ll be working with your server entirely through the command line). DigitalOcean gives you the option to enter it right inside their online dashboard interface as a step in creating the droplet. They also provide this useful guide. Here’s what I did on my Mac.

  1. Run the command:

This generates two files which represent the public-private key pairs that you’ll need to authenticate via SSH. Save these files in your ~/.ssh directory (this is the directory where the ssh program will automatically look when you attempt to log into the server). You’ll also get an option to add a password to the file, which is recommended as protection against your laptop being stolen and someone getting access to the files.

id_rsa and are the default names for these public / private key pairs. Since these already exist in my .ssh directory, I chose a different filename: app-deploy and  

Once you create these files, you then need to copy the contents of the public key (i.e. the file ending in ‘.pub’) into the “New SSH Key” form that Digital Ocean provides when setting up your droplet:

After entering in your public key, you can click the button to create your server.

Finally, to login to my server I run:

ssh -i ~/.ssh/app_deploy root@server_ip_address

If you chose the default filename (id_rsa and, then you only need to run:

ssh root@server_ip_address

And congratulations – you are now logged into your own personal server running in the cloud!