In this repository, we develop a Flask application to run using Docker. The application supports basic static webpages as well as allowing the user to upload an image and view their uploaded images. Postgres was used for the database, and Nginx and Gunicorn were included to support the production environment in order to help handle the static and media file upload/view functionalities. Docker allowed us to containerize the application, and we built separate Dockerfiles for both development and production environments. This project was inspired from a tutorial.

Below, we can see an example demo of uploading an image.

Note that to run the following commands, you need to install docker-compose. Successfully running

$ pip3 install docker-compose

will do it for you.

All the following commands should be run from the root directory.

First, we can use docker-compose to build the Docker image and run the container (the -d flag allows us to run it in the background):

$ docker-compose up -d --build

We now need to start and create the database:

$ docker-compose exec web python manage.py create_db

To test, we can access http://localhost:1365 and see output similar to below:

$ curl http://localhost:1365
{
  "hello": "world"
}

Aside: In the above demo, you might note that I am accessing http://localhost:8080. I enabled this using port forwarding as I was working on a lambda server. For normal testing, http://localhost:1365 is the correct endpoint.

To confirm that the table was successfully created:

$ docker-compose exec db psql --username=hello_flask --dbname=hello_flask_dev

hello_flask_dev=# \l

and you should see the hello_flask_dev table.

If we access http://localhost:1365/static/hello.txt, we can see the following output:

$ curl http://localhost:1365/static/hello.txt
hi!

In order to upload an image, access http://localhost:1365/upload.

To view the image uploaded, access: http://localhost:1365/media/IMAGE_FILE_NAME.

Finally, we can bring down the development containers (the -v flag also brings down the associated volumes):

$ docker-compose down -v

Note that this repository does not contain the .env.prod and .env.prod.db environment variable files that are necessary for the services to run from the container for security purposes.

Again, we need to build the production Docker image and run the container (the -f flag specifies the Docker production configuration file over the default docker-compose.yml and the -d flag allows us to run it in the background):

$ docker-compose -f docker-compose.prod.yml up -d --build

Similar to above, we create the table:

$ docker-compose -f docker-compose.prod.yml exec web python manage.py create_db

To test, we can access http://localhost:1365 and see output similar to below:

$ curl http://localhost:1365
{"hello": "world"}

If we access http://localhost:1365/static/hello.txt, we can see the following output:

$ curl http://localhost:1365/static/hello.txt
hi!

In order to upload an image, access http://localhost:1365/upload.

To view the image uploaded, access: http://localhost:1365/media/IMAGE_FILE_NAME.

Finally, we can bring down the containers:

$ docker-compose -f docker-compose.prod.yml down -v