Feature Requests App

Core Stack

Flask
SQLAlchemy
jQuery
Bootstrap

Development Approach

The first thing that needs to be decided when creating an MVP is a core tech stack to be used.

Flask was chosen as a framework because of it's simplicity and extensive documentation. Therefore, SQLAlchemy followed as the most popular way to provide a powerful and developer-friendly ORM. Bootstrap was chosen for its ease of integration, color-coded buttons, and simple yet powerful grid layout. Mimesis was chosen for generating fake data for initial feature requests.

When it comes to testing, the approach was fairly standard, utilizing stdlib's unittest and unittest.mock.

Ultimately, all the core dependencies were established for a single reason - fast development process.

Deployment

To easily make this deployment automated, Heroku was chosen as a cloud platform. Since Heroku natively supports WSGIs, nginx was managed to be avoided and as a result, only gunicorn needed to be configured (which happens in Procfile).

The project itself is very quick to set-up (provided you have heroku-cli installed and are logged in).

In your terminal (tested on Ubuntu):

heroku create
heroku addons:add heroku-postgresql:hobby-dev
git push heroku master
heroku ps:scale web=1

After executing these commands, you can access the application via a url that was given to you at heroku create stage or simply by typing the following in your terminal:

heroku open

Running a Development Server and Tests

Clone this repository and create a virtualenv in your location of choice. After activating the environment, install the dependencies:

pip install -r requirements.txt

To set up your database of choice, all you need to do is the environment variable DATABASE_URL to your db uri, e.g. sqlite:////tmp/feature_requests.db

After this, you should launch a script dedicated to database setup.

python -m database.setup_database

After the database setup is finished and mock data is generated, you can now run a development server.

python -m flask run

To run tests, execute the following command in your terminal:

python -m nose

Ideas On Future Development