flash-dash template with plotly dash, made with cookiecutter-flask
This app can be run completely using Docker
and docker-compose
. Using Docker is recommended, as it guarantees the application is run using compatible versions of Python and Node.
There are three main services:
To run the development version of the app
docker-compose up flask-dev
To run the production version of the app
docker-compose up flask-prod
The list of environment:
variables in the docker-compose.yml
file takes precedence over any variables specified in .env
.
To run any commands using the Flask CLI
docker-compose run --rm manage <<COMMAND>>
Therefore, to initialize a database you would run
docker-compose run --rm manage db init
docker-compose run --rm manage db migrate
docker-compose run --rm manage db upgrade
A docker volume node-modules
is created to store NPM packages and is reused across the dev and prod versions of the application. For the purposes of DB testing with sqlite
, the file dev.db
is mounted to all containers. This volume mount should be removed from docker-compose.yml
if a production DB server is used.
Run the following commands to bootstrap your environment if you are unable to run the application using Docker
cd flask_dash_template
pipenv install --dev
pipenv shell
npm install
npm start # run the webpack dev server and flask server using concurrently
You will see a pretty welcome screen.
Once you have installed your DBMS, run the following to create your app's database tables and perform the initial migration
flask db init
flask db migrate
flask db upgrade
When using Docker, reasonable production defaults are set in docker-compose.yml
FLASK_ENV=production
FLASK_DEBUG=0
Therefore, starting the app in "production" mode is as simple as
docker-compose up flask-prod
If running without Docker
export FLASK_ENV=production
export FLASK_DEBUG=0
export DATABASE_URL="<YOUR DATABASE URL>"
npm run build # build assets with webpack
flask run # start the flask server
To open the interactive shell, run
docker-compose run --rm manage db shell
flask shell # If running locally without Docker
By default, you will have access to the flask app
.
To run all tests, run
docker-compose run --rm manage test
flask test # If running locally without Docker
To run the linter, run
docker-compose run --rm manage lint
flask lint # If running locally without Docker
The lint
command will attempt to fix any linting/style errors in the code. If you only want to know if the code will pass CI and do not wish for the linter to make changes, add the --check
argument.
Whenever a database migration needs to be made. Run the following commands
docker-compose run --rm manage db migrate
flask db migrate # If running locally without Docker
This will generate a new migration script. Then run
docker-compose run --rm manage db upgrade
flask db upgrade # If running locally without Docker
To apply the migration.
For a full migration command reference, run docker-compose run --rm manage db --help
.
If you will deploy your application remotely (e.g on Heroku) you should add the migrations
folder to version control.
You can do this after flask db migrate
by running the following commands
git add migrations/*
git commit -m "Add migrations"
Make sure folder migrations/versions
is not empty.
Files placed inside the assets
directory and its subdirectories
(excluding js
and css
) will be copied by webpack's
file-loader
into the static/build
directory. In production, the plugin
Flask-Static-Digest
zips the webpack content and tags them with a MD5 hash.
As a result, you must use the static_url_for
function when including static content,
as it resolves the correct file name, including the MD5 hash.
For example
<link rel="shortcut icon" href="{{static_url_for('static', filename='build/img/favicon.ico') }}">
If all of your static files are managed this way, then their filenames will change whenever their
contents do, and you can ask Flask to tell web browsers that they
should cache all your assets forever by including the following line
in .env
:
SEND_FILE_MAX_AGE_DEFAULT=31556926 # one year
Before deploying to Heroku you should be familiar with the basic concepts of Git and Heroku.
Remember to add migrations to your repository. Please check Migrations
_ section.
Since the filesystem on Heroku is ephemeral, non-version controlled files (like a SQLite database) will be lost at least once every 24 hours. Therefore, a persistent, standalone database like PostgreSQL is recommended. This application will work with any database backend that is compatible with SQLAlchemy, but we provide specific instructions for Postgres, (including the required library psycopg2-binary
).
Note: psycopg2-binary
package is a practical choice for development and testing but in production it is advised to use the package built from sources. Read more in the psycopg2 documentation.
If you keep your project on GitHub you can use 'Deploy to Heroku' button thanks to which the deployment can be done in web browser with minimal configuration required.
The configuration used by the button is stored in app.json
file.
Deployment by using Heroku CLI:
-
Create Heroku App. You can leave your app name, change it, or leave it blank (random name will be generated)
heroku create flask_dash_template
-
Add buildpacks
heroku buildpacks:add --index=1 heroku/nodejs heroku buildpacks:add --index=1 heroku/python
-
Add database addon which creates a persistent PostgresSQL database. These instructions assume you're using the free hobby-dev plan. This command also sets a
DATABASE_URL
environmental variable that your app will use to communicate with the DB.heroku addons:create heroku-postgresql:hobby-dev --version=11
-
Set environmental variables (change
SECRET_KEY
value)heroku config:set SECRET_KEY=not-so-secret heroku config:set FLASK_APP=autoapp.py heroku config:set SEND_FILE_MAX_AGE_DEFAULT=31556926
-
Please check
.env.example
to see which environmental variables are used in the project and also need to be set. The exception isDATABASE_URL
, which Heroku sets automatically. -
Deploy on Heroku by pushing to the
heroku
branchgit push heroku master