Use Docker container for local C++ development

Why develop in Docker container?

Docker is the hottest technology to deploy and run the software. The key benefit of Docker is that it allows users to package an application with all of its dependencies into a standardized unit for software development. Compared with virtual machines, containers do not have high overhead and hence enable more efficient usage of the underlying system and resources.

Besides deploying and running applications, Docker containers can also make your local development work easier, especially when you need to set up a specific environment with many dependencies.

In my case, I have a project which is a C++ application running on the Linux platform. But on personal machines I’m running macOS and Windows systems, I didn’t install Linux platform on my computer. Before I start working on this project, I need to fix the platform/environment issue.

The first idea is, of course, using virtual-machines with VirtualBox and install the Linux system in it. This process will be time-consuming and tedious. So I decided to use Docker container to speed up the environment configuration step.

I will share the experience step by step. The whole process is lightweight and quick, also can practice your Docker related skills.

Create the Docker container

To build a Docker image, we need a Dockerfile, which is a text document(without a file extension) that contains the instructions to set up an environment for a Docker container. The Docker official site is the best place to understand those fundamental and important knowledge.

In my case the basic Dockerfile goes as following:

# Download base image ubuntu 20.04
FROM ubuntu:20.04

# Disable Prompt During Packages Installation
ARG DEBIAN_FRONTEND=noninteractive

# Update Ubuntu Software repository
RUN apt-get update && apt-get install -y \
    make \
    cmake \
    g++ \
    libncurses5-dev \
    libncursesw5-dev \
&& rm -rf /var/lib/apt/lists/*

CMD ["bash"]

FROM : the first part is the FROM command, which tells us what image to base this off of (as we know, Docker is following a multi-layer structure). In my case, it’s using the Ubuntu:20.04 image, which again references a Dockerfile to automate the process.

ARG: ARG instruction defines a variable that can be passed at build time to pass environment info. In this case, just to disable the console output during the following Linux package installation process.

RUN: the next set of calls are the RUN commands. This RUN instruction allows you to install your application and packages for it. RUN executes commands in a new layer and creates a new layer by committing the results. Usually, you can find several RUN instructions in a Dockerfile. In this case, I want to install the C++ compiler and build tools (and some other specific dependency packages for development) which is not available in the Ubuntu base image.

CMD: the last instruction CMD allows you to set a default command, which will be executed when you run the container without specifying a command. If Docker container runs with a command, this default one will be ignored.

With this Dockerfile, we can build the image with the next Docker command:

docker build -t linux-cpp .

This will build the desired Docker image tagged as linux-cpp. You can list(find) this new image in your system with command docker images:

REPOSITORY          TAG                 IMAGE ID            CREATED             SIZE
linux-cpp           latest              5463808c4488        8 days ago          320MB

Now you can run the docker container with the newly build linux-cpp image:

docker run -it --name cpp-dev --rm linux-cpp

Mount source code into container

Follow the above steps, you can have a running Docker container with C++ development dependencies in Linux environment.

Next, you can directly start your C++ program inside the container, then build and run your code.

But if you just put your program inside the container, you will have a high risk to lose your code when the container is deleted.

The better way is placing your program source code on your local machine and sync the codes into the container as you program. This is where mount can help you. Mount and Volume is an important topic for Docker, you can find some posts for deeper introduction.

In my case, I can realize my target with the following command:

docker run -it --name cpp-dev  --rm  -v ${PWD}:/develop  linux-cpp

the key and interesting part is: -v ${PWD}:/develop, this will mount the current directory of the host machine into the develop directory inside the container. If develop directory is not there, Docker will make it for you.

Note: the current directory pwd command’s usage has some variants based on your host machine. The above command works for the Powershell of Windows, if you are using git bash on Windows, please try:

-v /$(pwd):/develop

For Mac users, try the following:

-v $(pwd):/develop

Now you can happily code your program in your familiar host machine, save the code change and sync them into the container. Then build and run your code inside the container with every dependency it needs.