Docker containerization in Django - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ component_behavior

intermediate

What happens when you run this Dockerfile for a Django app?

Consider this Dockerfile for a Django project. What will be the output when you build and run the container?

FROM python:3.12-slim
WORKDIR /app
COPY requirements.txt ./
RUN pip install -r requirements.txt
COPY . .
CMD ["python", "manage.py", "runserver", "0.0.0.0:8000"]

Django

FROM python:3.12-slim
WORKDIR /app
COPY requirements.txt ./
RUN pip install -r requirements.txt
COPY . .
CMD ["python", "manage.py", "runserver", "0.0.0.0:8000"]

A The Django development server starts inside the container and listens on port 8000 on all interfaces.

B The Django server will start but only listen on localhost inside the container, so it won't be accessible externally.

C The container will fail because the requirements.txt file is not copied before pip install.

D The container will run but exit immediately because CMD is missing the entrypoint.

💡 Hint

Think about what the CMD command does and how the server binds to network interfaces.

The CMD runs the Django development server binding to 0.0.0.0:8000, which means it listens on all network interfaces inside the container, making it accessible if the port is published.

📝 Syntax

intermediate

Identify the syntax error in this Docker Compose service for Django

Look at this docker-compose.yml snippet for a Django service. Which option correctly identifies the syntax error?

version: '3.9'
services:
  web:
    build: .
    ports:
      - "8000:8000"
    volumes:
      - .:/app
    command: python manage.py runserver 0.0.0.0:8000
    environment:
      - DEBUG=True
      - SECRET_KEY='mysecret'
    depends_on:
      - db
  db:
    image: postgres:15
    environment:
      - POSTGRES_DB: mydb
      - POSTGRES_USER: user
      - POSTGRES_PASSWORD: pass

Django

version: '3.9'
services:
  web:
    build: .
    ports:
      - "8000:8000"
    volumes:
      - .:/app
    command: python manage.py runserver 0.0.0.0:8000
    environment:
      - DEBUG=True
      - SECRET_KEY='mysecret'
    depends_on:
      - db
  db:
    image: postgres:15
    environment:
      - POSTGRES_DB: mydb
      - POSTGRES_USER: user
      - POSTGRES_PASSWORD: pass

A The 'depends_on' field must be a string, not a list.

B The environment variables under 'db' use colon syntax instead of dash list syntax, causing a syntax error.

C The 'command' field must be a list, not a string.

D The 'volumes' mapping is invalid because it uses relative path without quotes.

💡 Hint

Check how environment variables are defined in YAML for lists vs mappings.

In docker-compose.yml, the 'environment' key expects either a list of strings ('- KEY=value') or a mapping ('KEY: value'). Under 'db', it uses a list of mappings ('- KEY: value'), which is invalid YAML structure for Docker Compose environment variables and causes a configuration parsing error.

❓ state_output

advanced

What is the value of the environment variable DEBUG inside the Django container?

Given this docker-compose.yml snippet, what will be the value of DEBUG inside the running Django container?

services:
  web:
    image: django:latest
    environment:
      DEBUG: 'False'
      SECRET_KEY: 'abc123'
    command: python manage.py runserver 0.0.0.0:8000

Django

services:
  web:
    image: django:latest
    environment:
      DEBUG: 'False'
      SECRET_KEY: 'abc123'
    command: python manage.py runserver 0.0.0.0:8000

A The boolean value False.

B The value will be undefined because environment variables cannot be set this way.

C The string 'False' (not a boolean false).

D An empty string because environment variables are always strings.

💡 Hint

Remember environment variables are always strings inside containers.

Environment variables in Docker are always strings. So DEBUG will be the string 'False', not a boolean false.

🔧 Debug

advanced

Why does the Django container fail to connect to the database?

You have this docker-compose.yml:

services:
  web:
    build: .
    ports:
      - "8000:8000"
    depends_on:
      - db
    environment:
      DATABASE_URL: postgres://user:pass@db:5432/mydb
  db:
    image: postgres:15
    environment:
      POSTGRES_DB: mydb
      POSTGRES_USER: user
      POSTGRES_PASSWORD: pass

The Django app inside 'web' fails to connect to the database. What is the most likely cause?

Django

services:
  web:
    build: .
    ports:
      - "8000:8000"
    depends_on:
      - db
    environment:
      DATABASE_URL: postgres://user:pass@db:5432/mydb
  db:
    image: postgres:15
    environment:
      POSTGRES_DB: mydb
      POSTGRES_USER: user
      POSTGRES_PASSWORD: pass

A The 'depends_on' does not wait for the database to be ready, so Django connects too early.

B The DATABASE_URL environment variable is incorrectly formatted and missing the password.

C The database container 'db' is not ready when Django tries to connect, causing connection failure.

D The port 5432 is not exposed on the 'db' container, so Django cannot reach it.

💡 Hint

Think about what 'depends_on' controls and what it does not guarantee.

'depends_on' only controls container startup order but does not wait for the database service to be ready to accept connections. Django tries to connect before Postgres is ready, causing failure.

🧠 Conceptual

expert

Which Dockerfile instruction best improves build caching for a Django app?

You want to optimize Docker image build times for your Django app. Which Dockerfile instruction order helps maximize cache reuse?

1. COPY . .
2. RUN pip install -r requirements.txt
3. COPY requirements.txt ./
4. WORKDIR /app

Django

COPY . .
RUN pip install -r requirements.txt
COPY requirements.txt ./
WORKDIR /app

A 1,2,4,3

B 4,3,2,1

C 1,3,2,4

D 1,2,3,4

💡 Hint

Think about which files change most often and how Docker caches layers.

To maximize cache reuse, first set the working directory, then copy only requirements.txt, then install dependencies, then copy the rest of the app. This way, if only app code changes, Docker reuses the cached pip install layer.