Introduction
- Prerequisites:
- Dependencies:
Project Setup
Docker
Postgres
Gunicorn
Production Dockerfile
Nginx
Static Files
- Development
- Production
Media Files
- Development
- Production
Conclusion

Introduction

Docker is a popular tool for containerizing applications and making them more portable and scalable. Flask is a lightweight web framework for building web applications in Python. In this tutorial, we will show you how to dockerize a Flask application with Nginx, Gunicorn, and Postgres using Docker Compose.

Prerequisites:

Before we begin, you should have the following:

A basic understanding of Docker and Docker Compose
Python 3.x installed on your local machine
A Flask application to containerize
A text editor

Dependencies:

Flask v2.3.1
Docker v20.10.17
Python v3.11.3

Project Setup

Now let’s create a basic Flask application.

First, create a new directory for our Flask application and navigate to it:

$ mkdir flask-on-docker && cd flask-on-docker
$ mkdir services && cd services
$ mkdir web && cd web
$ mkdir project

$ python3.11 -m venv .venv
$ source .venv/bin/activate

(.venv)$ pip install flask==2.3.1

Feel free to swap out virtualenv and Pip for Poetry or Pipenv. For more, review Modern Python Environments.

Next, let’s create a new Flask app.

Add an __init__.py file to the project directory and configure the first route:

# web/project/__init__.py
from flask import Flask, jsonify

app = Flask(__name__)

@app.route("/")
def hello_world():
    return jsonify(hello="world")

Then, to configure the Flask CLI tool to run and manage the app from the command line, add a manage.py file to the web directory:

# web/manage.py
from flask.cli import FlaskGroup

from project import app

cli = FlaskGroup(app)

if __name__ == "__main__":
    cli()

Here, we created a new FlaskGroup instance to extend the normal CLI with commands related to the Flask app.

Run the server from the web directory:

(.venv)$ export FLASK_APP=project/__init__.py
(.venv)$ python manage.py run

Navigate to http://localhost:5050/. You should see:

{
  "hello": "world"
}

Kill the server once done. Exit then remove the virtual environment as well.

Create a requirements.txt file in the web directory and add Flask as a dependency:

# web/requirements.txt
Flask==2.3.1

Your project structure should look like:

└── services
    └── web
        ├── manage.py
        ├── project
        │   └── __init__.py
        └── requirements.txt

Docker

Install Docker, if you don’t already have it, then add a Dockerfile to the web directory:

# pull official base image
FROM python:3.11-slim-buster

# set work directory
WORKDIR /usr/src/app

# set environment variables
ENV PYTHONDONTWRITEBYTECODE 1
ENV PYTHONUNBUFFERED 1

# install dependencies
RUN pip install --upgrade pip
COPY ./requirements.txt /usr/src/app/requirements.txt
RUN pip install -r requirements.txt

# copy project
COPY . /usr/src/app/

We start with a slim-buster based Docker image for Python 3.11. Next, we set a working directory along with two environment variables:

PYTHONDONTWRITEBYTECODE: Prevents Python from writing pyc files to disc (equivalent to python -B option)
PYTHONUNBUFFERED: Prevents Python from buffering stdout and stderr (equivalent to python -u option)

Finally, we updated Pip, copied over the requirements.txt file, installed the dependencies, and copied over the Flask app itself.

Review Docker Best Practices for Python Developers for more on structuring Dockerfiles as well as some best practices for configuring Docker for Python-based development.

Next, add a docker-compose.yml file to the project root:

# flask-on-docker/docker-compose.yml
version: '3.8'

services:
  web:
    build: ./services/web
    command: python manage.py run -h 0.0.0.0 -p 5050
    volumes:
      - ./services/web/:/usr/src/app/
    ports:
      - 5050:5050
    env_file:
      - ./.env.dev

Review the Compose file reference for info on how this file works.

Then, create a .env.dev file in the project root to store environment variables for development:

FLASK_APP=project/__init__.py
FLASK_DEBUG=1

Build the image:

$ docker-compose build

Once the image is built, run the container:

$ docker-compose up -d

Navigate to http://localhost:5050/ to again view the hello world sanity check.

Check for errors in the logs if this doesn’t work via docker-compose logs -f.

Postgres

To configure Postgres, we need to add a new service to the docker-compose.yml file, set up Flask-SQLAlchemy, and install Psycopg2.

First, add a new service called db to docker-compose.yml:

version: '3.8'

services:
  web:
    build: ./services/web
    command: python manage.py run -h 0.0.0.0 -p 5050
    volumes:
      - ./services/web/:/usr/src/app/
    ports:
      - 5050:5050
    env_file:
      - ./.env.dev
    depends_on:
      - db
  db:
    image: postgres:13-alpine
    volumes:
      - ./postgres_data:/var/lib/postgresql/data/
    environment:
      - POSTGRES_USER=hello_flask
      - POSTGRES_PASSWORD=hello_flask
      - POSTGRES_DB=hello_flask_dev

volumes:
  postgres_data:

To persist the data beyond the life of the container we configured a volume. This config will bind postgres_data to the /var/lib/postgresql/data/ directory in the container.

We also added an environment key to define a name for the default database and set a username and password.

Review the “Environment Variables” section of the Postgres Docker Hub page for more info.

Add a DATABASE_URL environment variable to .env.dev as well:

FLASK_APP=project/__init__.py
FLASK_DEBUG=1
DATABASE_URL=postgresql://hello_flask:hello_flask@db:5432/hello_flask_dev

Then, add a new file called config.py to the project directory, where we’ll define environment-specific configuration variables:

import os

basedir = os.path.abspath(os.path.dirname(__file__))

class Config(object):
    SQLALCHEMY_DATABASE_URI = os.getenv("DATABASE_URL", "sqlite://")
    SQLALCHEMY_TRACK_MODIFICATIONS = False

Here, the database is configured based on the DATABASE_URL environment variable that we just defined. Take note of the default value.

Update __init__.py to pull in the config on init:

from flask import Flask, jsonify

app = Flask(__name__)
app.config.from_object("project.config.Config")

@app.route("/")
def hello_world():
    return jsonify(hello="world")

Add Flask-SQLAlchemy and Psycopg2 to requirements.txt:

Flask==2.3.1
Flask-SQLAlchemy==3.0.3
psycopg2-binary==2.9.6

Update __init__.py again to create a new SQLAlchemy instance and define a database model:

from flask import Flask, jsonify
from flask_sqlalchemy import SQLAlchemy

app = Flask(__name__)
app.config.from_object("project.config.Config")
db = SQLAlchemy(app)

class User(db.Model):
    __tablename__ = "users"

    id = db.Column(db.Integer, primary_key=True)
    email = db.Column(db.String(128), unique=True, nullable=False)
    active = db.Column(db.Boolean(), default=True, nullable=False)

    def __init__(self, email):
        self.email = email

@app.route("/")
def hello_world():
    return jsonify(hello="world")

Finally, update manage.py:

from flask.cli import FlaskGroup

from project import app, db

cli = FlaskGroup(app)

@cli.command("create_db")
def create_db():
    db.drop_all()
    db.create_all()
    db.session.commit()

if __name__ == "__main__":
    cli()

This registers a new command, create_db, to the CLI so that we can run it from the command line, which we’ll use shortly to apply the model to the database.

Build the new image and spin up the two containers:

$ docker-compose up -d --build

Create the table:

$ docker-compose exec web python manage.py create_db

Get the following error?

sqlalchemy.exc.OperationalError: (psycopg2.OperationalError)
FATAL:  database "hello_flask_dev" does not exist

Run docker-compose down -v to remove the volumes along with the containers. Then, re-build the images, run the containers, and apply the migrations.

Ensure the users table was created:

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

psql (13.8)
Type "help" for help.

hello_flask_dev=# \l
                                        List of databases
      Name       |    Owner    | Encoding |  Collate   |   Ctype    |      Access privileges
-----------------+-------------+----------+------------+------------+-----------------------------
 hello_flask_dev | hello_flask | UTF8     | en_US.utf8 | en_US.utf8 |
 postgres        | hello_flask | UTF8     | en_US.utf8 | en_US.utf8 |
 template0       | hello_flask | UTF8     | en_US.utf8 | en_US.utf8 | =c/hello_flask             +
                 |             |          |            |            | hello_flask=CTc/hello_flask
 template1       | hello_flask | UTF8     | en_US.utf8 | en_US.utf8 | =c/hello_flask             +
                 |             |          |            |            | hello_flask=CTc/hello_flask
(4 rows)

hello_flask_dev=# \c hello_flask_dev
You are now connected to database "hello_flask_dev" as user "hello_flask".

hello_flask_dev=# \dt
          List of relations
 Schema | Name  | Type  |    Owner
--------+-------+-------+-------------
 public | users | table | hello_flask
(1 row)

hello_flask_dev=# \q

You can check that the volume was created as well by running:

$ docker volume inspect flask-on-docker_postgres_data

You should see something similar to:

[
    {
        "CreatedAt": "2022-10-11T14:43:49Z",
        "Driver": "local",
        "Labels": {
            "com.docker.compose.project": "flask-on-docker",
            "com.docker.compose.version": "2.10.2",
            "com.docker.compose.volume": "postgres_data"
        },
        "Mountpoint": "/var/lib/docker/volumes/flask-on-docker_postgres_data/_data",
        "Name": "flask-on-docker_postgres_data",
        "Options": null,
        "Scope": "local"
    }
]

Next, add an entrypoint.sh file to the web directory to verify that Postgres is up and healthy before creating the database table and running the Flask development server:

#!/bin/sh

if [ "$DATABASE" = "postgres" ]
then
    echo "Waiting for postgres..."

    while ! nc -z $SQL_HOST $SQL_PORT; do
      sleep 0.1
    done

    echo "PostgreSQL started"
fi

python manage.py create_db

exec "$@"

Take note of the environment variables.

Update the file permissions locally:

$ chmod +x services/web/entrypoint.sh

Then, update the Dockerfile to install netcat, copy over the entrypoint.sh file, and run the file as the Docker entrypoint command:

# pull official base image
FROM python:3.11-slim-buster

# set work directory
WORKDIR /usr/src/app

# set environment variables
ENV PYTHONDONTWRITEBYTECODE 1
ENV PYTHONUNBUFFERED 1

# install system dependencies
RUN apt-get update && apt-get install -y netcat

# install dependencies
RUN pip install --upgrade pip
COPY ./requirements.txt /usr/src/app/requirements.txt
RUN pip install -r requirements.txt

# copy project
COPY . /usr/src/app/

# run entrypoint.sh
ENTRYPOINT ["/usr/src/app/entrypoint.sh"]

Add the SQL_HOST, SQL_PORT, and DATABASE environment variables, for the entrypoint.sh script, to .env.dev:

FLASK_APP=project/__init__.py
FLASK_DEBUG=1
DATABASE_URL=postgresql://hello_flask:hello_flask@db:5432/hello_flask_dev
SQL_HOST=db
SQL_PORT=5432
DATABASE=postgres

Test it out again:

Re-build the images
Run the containers
Try http://localhost:5050/

Let’s also add a CLI seed command for adding sample users to the users table in manage.py:

from flask.cli import FlaskGroup

from project import app, db, User

cli = FlaskGroup(app)

@cli.command("create_db")
def create_db():
    db.drop_all()
    db.create_all()
    db.session.commit()

@cli.command("seed_db")
def seed_db():
    db.session.add(User(email="john@devguide.dev"))
    db.session.commit()

if __name__ == "__main__":
    cli()

Try it out:

$ docker-compose exec web python manage.py seed_db

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

psql (13.8)
Type "help" for help.

hello_flask_dev=# \c hello_flask_dev
You are now connected to database "hello_flask_dev" as user "hello_flask".

hello_flask_dev=# select * from users;
 id |        email        | active
----+---------------------+--------
  1 | john@devguide.dev | t
(1 row)

hello_flask_dev=# \q

Despite adding Postgres, we can still create an independent Docker image for Flask by not setting the DATABASE_URL environment variable. To test, build a new image and then run a new container:

$ docker build -f ./services/web/Dockerfile -t hello_flask:latest ./services/web
$ docker run -p 5007:5050 \
    -e "FLASK_APP=project/__init__.py" -e "FLASK_DEBUG=1" \
    hello_flask python /usr/src/app/manage.py run -h 0.0.0.0

You should be able to view the hello world sanity check at http://localhost:5007.

Gunicorn

Moving along, for production environments, let’s add Gunicorn, a production-grade WSGI server, to the requirements.txt file:

Flask==2.3.1
Flask-SQLAlchemy==3.0.3
gunicorn==20.1.0
psycopg2-binary==2.9.6

Since we still want to use Flask’s built-in server in development, create a new compose file called docker-compose.prod.yml for production:

version: '3.8'

services:
  web:
    build: ./services/web
    command: gunicorn --bind 0.0.0.0:5050 manage:app
    ports:
      - 5050:5050
    env_file:
      - ./.env.prod
    depends_on:
      - db
  db:
    image: postgres:13-alpine
    volumes:
      - postgres_data_prod:/var/lib/postgresql/data/
    env_file:
      - ./.env.prod.db

volumes:
  postgres_data_prod:

If you have multiple environments, you may want to look at using a docker-compose.override.yml configuration file. With this approach, you’d add your base config to a docker-compose.yml file and then use a docker-compose.override.yml file to override those config settings based on the environment.

Take note of the default command. We’re running Gunicorn rather than the Flask development server. We also removed the volume from the web service since we don’t need it in production. Finally, we’re using separate environment variable files to define environment variables for both services that will be passed to the container at runtime.

.env.prod:

FLASK_APP=project/__init__.py
FLASK_DEBUG=0
DATABASE_URL=postgresql://hello_flask:hello_flask@db:5432/hello_flask_prod
SQL_HOST=db
SQL_PORT=5432
DATABASE=postgres

.env.prod.db:

POSTGRES_USER=hello_flask
POSTGRES_PASSWORD=hello_flask
POSTGRES_DB=hello_flask_prod

Add the two files to the project root. You’ll probably want to keep them out of version control, so add them to a .gitignore file.

Bring down the development containers (and the associated volumes with the -v flag):

$ docker-compose down -v

Then, build the production images and spin up the containers:

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

Verify that the hello_flask_prod database was created along with the users table. Test out http://localhost:5050/.

Again, if the container fails to start, check for errors in the logs via docker-compose -f docker-compose.prod.yml logs -f.

Production Dockerfile

Did you notice that we’re still running the create_db command, which drops all existing tables and then creates the tables from the models, every time the container is run? This is fine in development, but let’s create a new entrypoint file for production.

entrypoint.prod.sh:

#!/bin/sh

if [ "$DATABASE" = "postgres" ]
then
    echo "Waiting for postgres..."

    while ! nc -z $SQL_HOST $SQL_PORT; do
      sleep 0.1
    done

    echo "PostgreSQL started"
fi

exec "$@"

Alternatively, instead of creating a new entrypoint file, you could alter the existing one like so:

#!/bin/sh

if [ "$DATABASE" = "postgres" ]
then
    echo "Waiting for postgres..."

    while ! nc -z $SQL_HOST $SQL_PORT; do
      sleep 0.1
    done

    echo "PostgreSQL started"
fi

if [ "$FLASK_DEBUG" = "1" ]
then
    echo "Creating the database tables..."
    python manage.py create_db
    echo "Tables created"
fi

exec "$@"

Update the file permissions locally:

$ chmod +x services/web/entrypoint.prod.sh

To use this file, create a new Dockerfile called Dockerfile.prod for use with production builds:

###########
# BUILDER #
###########

# pull official base image
FROM python:3.11-slim-buster as builder

# set work directory
WORKDIR /usr/src/app

# set environment variables
ENV PYTHONDONTWRITEBYTECODE 1
ENV PYTHONUNBUFFERED 1

# install system dependencies
RUN apt-get update && \
    apt-get install -y --no-install-recommends gcc

# lint
RUN pip install --upgrade pip
RUN pip install flake8==5.0.4
COPY . /usr/src/app/
RUN flake8 --ignore=E501,F401 .

# install python dependencies
COPY ./requirements.txt .
RUN pip wheel --no-cache-dir --no-deps --wheel-dir /usr/src/app/wheels -r requirements.txt

#########
# FINAL #
#########

# pull official base image
FROM python:3.11-slim-buster

# create directory for the app user
RUN mkdir -p /home/app

# create the app user
RUN addgroup --system app && adduser --system --group app

# create the appropriate directories
ENV HOME=/home/app
ENV APP_HOME=/home/app/web
RUN mkdir $APP_HOME
WORKDIR $APP_HOME

# install dependencies
RUN apt-get update && apt-get install -y --no-install-recommends netcat
COPY --from=builder /usr/src/app/wheels /wheels
COPY --from=builder /usr/src/app/requirements.txt .
RUN pip install --upgrade pip
RUN pip install --no-cache /wheels/*

# copy entrypoint-prod.sh
COPY ./entrypoint.prod.sh $APP_HOME

# copy project
COPY . $APP_HOME

# chown all the files to the app user
RUN chown -R app:app $APP_HOME

# change to the app user
USER app

# run entrypoint.prod.sh
ENTRYPOINT ["/home/app/web/entrypoint.prod.sh"]

Here, we used a Docker multi-stage build to reduce the final image size. Essentially, builder is a temporary image that’s used for building the Python wheels. The wheels are then copied over to the final production image and the builder image is discarded.

You could take the multi-stage build approach a step further and use a single Dockerfile instead of creating two Dockerfiles. Think of the pros and cons of using this approach over two different files.

Here, we created a non-root user. By default, Docker runs container processes as root inside of a container. This is a bad practice since attackers can gain root access to the Docker host if they manage to break out of the container. If you’re root in the container, you’ll be root on the host.

Update the web service within the docker-compose.prod.yml file to build with Dockerfile.prod:

web:
  build:
    context: ./services/web
    dockerfile: Dockerfile.prod
  command: gunicorn --bind 0.0.0.0:5050 manage:app
  ports:
    - 5050:5050
  env_file:
    - ./.env.prod
  depends_on:
    - db

Try it out:

$ docker-compose -f docker-compose.prod.yml down -v
$ docker-compose -f docker-compose.prod.yml up -d --build
$ docker-compose -f docker-compose.prod.yml exec web python manage.py create_db

Nginx

Next, let’s add Nginx into the mix to act as a reverse proxy for Gunicorn to handle client requests as well as serve up static files.

Add the service to docker-compose.prod.yml:

nginx:
  build: ./services/nginx
  ports:
    - 5337:80
  depends_on:
    - web

Then, in the services directory, create the following files and folders:

└── nginx
    ├── Dockerfile
    └── nginx.conf

Dockerfile:

FROM nginx:1.23-alpine

RUN rm /etc/nginx/conf.d/default.conf
COPY nginx.conf /etc/nginx/conf.d

nginx.conf:


upstream hello_flask {
    server web:5050;
}

server {

    listen 80;

    location / {
        proxy_pass http://hello_flask;
        proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
        proxy_set_header Host $host;
        proxy_redirect off;
    }

}

Review How to Configure NGINX for a Flask Web Application for more info on configuring Nginx to work with Flask.

Then, update the web service, in docker-compose.prod.yml, replacing ports with expose:

web:
  build:
    context: ./services/web
    dockerfile: Dockerfile.prod
  command: gunicorn --bind 0.0.0.0:5050 manage:app
  expose:
    - 5050
  env_file:
    - ./.env.prod
  depends_on:
    - db

Now, port 5050 is only exposed internally, to other Docker services. The port will no longer be published to the host machine.

For more on ports vs expose, review this Stack Overflow question.

Test it out again:

$ docker-compose -f docker-compose.prod.yml down -v
$ docker-compose -f docker-compose.prod.yml up -d --build
$ docker-compose -f docker-compose.prod.yml exec web python manage.py create_db

Ensure the app is up and running at http://localhost:5337.

Your project structure should now look like:

├── .env.dev
├── .env.prod
├── .env.prod.db
├── .gitignore
├── docker-compose.prod.yml
├── docker-compose.yml
└── services
    ├── nginx
    │   ├── Dockerfile
    │   └── nginx.conf
    └── web
        ├── Dockerfile
        ├── Dockerfile.prod
        ├── entrypoint.prod.sh
        ├── entrypoint.sh
        ├── manage.py
        ├── project
        │   ├── __init__.py
        │   └── config.py
        └── requirements.txt

Bring the containers down once done:

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

Since Gunicorn is an application server, it will not serve up static files. So, how should both static and media files be handled in this particular configuration?

Static Files

Start by creating the following files and folders in the services/web/project folder:

└── static
    └── hello.txt

Add some text to hello.txt:

Hello from static file!

Add a new route handler to __init__.py:

@app.route("/static/<path:filename>")
def staticfiles(filename):
    return send_from_directory(app.config["STATIC_FOLDER"], filename)

Don’t forget to import send_from_directory:

from flask import Flask, jsonify, send_from_directory

Finally, add the STATIC_FOLDER config to services/web/project/config.py

import os

basedir = os.path.abspath(os.path.dirname(__file__))

class Config(object):
    SQLALCHEMY_DATABASE_URI = os.getenv("DATABASE_URL", "sqlite://")
    SQLALCHEMY_TRACK_MODIFICATIONS = False
    STATIC_FOLDER = f"{os.getenv('APP_FOLDER')}/project/static"

Development

Add the APP_FOLDER environment variable to .env.dev:

FLASK_APP=project/__init__.py
FLASK_DEBUG=1
DATABASE_URL=postgresql://hello_flask:hello_flask@db:5432/hello_flask_dev
SQL_HOST=db
SQL_PORT=5432
DATABASE=postgres
APP_FOLDER=/usr/src/app

To test, first re-build the images and spin up the new containers per usual. Once done, ensure http://localhost:5050/static/hello.txt serves up the file correctly.

Production

For production, add a volume to the web and nginx services in docker-compose.prod.yml so that each container will share a directory named “static”:

version: '3.8'

services:
  web:
    build:
      context: ./services/web
      dockerfile: Dockerfile.prod
    command: gunicorn --bind 0.0.0.0:5050 manage:app
    volumes:
      - static_volume:/home/app/web/project/static
    expose:
      - 5050
    env_file:
      - ./.env.prod
    depends_on:
      - db
  db:
    image: postgres:13-alpine
    volumes:
      - postgres_data_prod:/var/lib/postgresql/data/
    env_file:
      - ./.env.prod.db
  nginx:
    build: ./services/nginx
    volumes:
      - static_volume:/home/app/web/project/static
    ports:
      - 5337:80
    depends_on:
      - web

volumes:
  postgres_data_prod:
  static_volume:

Next, update the Nginx configuration to route static file requests to the “static” folder:

upstream hello_flask {
    server web:5050;
}

server {

    listen 80;

    location / {
        proxy_pass http://hello_flask;
        proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
        proxy_set_header Host $host;
        proxy_redirect off;
    }

    location /static/ {
        alias /home/app/web/project/static/;
    }

}

Add the APP_FOLDER environment variable to .env.prod:

FLASK_APP=project/__init__.py
FLASK_DEBUG=0
DATABASE_URL=postgresql://hello_flask:hello_flask@db:5432/hello_flask_prod
SQL_HOST=db
SQL_PORT=5432
DATABASE=postgres
APP_FOLDER=/home/app/web

Where does this directory path come from? Compare this path to the path added to .env.dev.

Spin down the development containers:

$ docker-compose down -v

Test:

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

Again, requests to http://localhost:5337/static/ will be served from the “static” directory.

Navigate to http://localhost:5337/static/hello.txt and ensure the static asset is loaded correctly.

You can also verify in the logs via docker-compose -f docker-compose.prod.yml logs -f:

192.168.80.1 - - [11/Oct/2022:15:20:25 +0000] "GET /static/hello.txt HTTP/1.1" 200 4 "-"
"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_6) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/96.0.4664.110 Safari/537.36" "-"

Bring the containers once done:

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

Media Files

To test out the handling of user-uploaded media files, add two new route handlers to __init__.py:

@app.route("/media/<path:filename>")
def mediafiles(filename):
    return send_from_directory(app.config["MEDIA_FOLDER"], filename)

@app.route("/upload", methods=["GET", "POST"])
def upload_file():
    if request.method == "POST":
        file = request.files["file"]
        filename = secure_filename(file.filename)
        file.save(os.path.join(app.config["MEDIA_FOLDER"], filename))
    return """
    <!doctype html>
    <title>upload new File</title>
    <form action="" method=post enctype=multipart/form-data>
      <p><input type=file name=file><input type=submit value=Upload>
    </form>
    """

You need to update the imports as well to __init__.py:

import os

from flask import (
    Flask,
    jsonify,
    send_from_directory,
    request,
)
from flask_sqlalchemy import SQLAlchemy
from werkzeug.utils import secure_filename

Add the MEDIA_FOLDER config to services/web/project/config.py:

import os

basedir = os.path.abspath(os.path.dirname(__file__))

class Config(object):
    SQLALCHEMY_DATABASE_URI = os.getenv("DATABASE_URL", "sqlite://")
    SQLALCHEMY_TRACK_MODIFICATIONS = False
    STATIC_FOLDER = f"{os.getenv('APP_FOLDER')}/project/static"
    MEDIA_FOLDER = f"{os.getenv('APP_FOLDER')}/project/media"

Finally, create a new folder called media in the project folder.

Development

Test:

$ docker-compose up -d --build

You should be able to upload an image at http://localhost:5050/upload, and then view the image at http://localhost:5050/media/IMAGE_FILE_NAME.

Production

For production, add another volume named media_volume to the web and nginx services:

version: '3.8'

services:
  web:
    build:
      context: ./services/web
      dockerfile: Dockerfile.prod
    command: gunicorn --bind 0.0.0.0:5050 manage:app
    volumes:
      - static_volume:/home/app/web/project/static
      - media_volume:/home/app/web/project/media
    expose:
      - 5050
    env_file:
      - ./.env.prod
    depends_on:
      - db
  db:
    image: postgres:13-alpine
    volumes:
      - postgres_data_prod:/var/lib/postgresql/data/
    env_file:
      - ./.env.prod.db
  nginx:
    build: ./services/nginx
    volumes:
      - static_volume:/home/app/web/project/static
      - media_volume:/home/app/web/project/media
    ports:
      - 5337:80
    depends_on:
      - web

volumes:
  postgres_data_prod:
  static_volume:
  media_volume:

Next, update the Nginx configuration to route media file requests to the media folder:

upstream hello_flask {
    server web:5050;
}

server {

    listen 80;

    location / {
        proxy_pass http://hello_flask;
        proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
        proxy_set_header Host $host;
        proxy_redirect off;
    }

    location /static/ {
        alias /home/app/web/project/static/;
    }

    location /media/ {
        alias /home/app/web/project/media/;
    }

}

Re-build:

$ docker-compose down -v

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

Test it out one final time:

Upload an image at http://localhost:5337/upload. Then, view the image at http://localhost:5337/media/IMAGE_FILE_NAME.

Conclusion

In this tutorial, we walked through how to containerize a Flask application with Postgres for development. We also created a production-ready Docker Compose file that adds Gunicorn and Nginx into the mix to handle static and media files. You can now test out a production setup locally.

In terms of actual deployment to a production environment, you’ll probably want to use a:

Fully managed database service — like RDS or Cloud SQL — rather than managing your own Postgres instance within a container.
Non-root user for the db and nginx services

Thanks for reading!

Dockerizing flask with Postgres, Gunicorn and Nginx

Table of contents

Introduction

Prerequisites:

Dependencies:

Project Setup

Docker

Postgres

Gunicorn

Production Dockerfile

Nginx

Static Files

Development

Production

Media Files

Development

Production

Conclusion