The first step is to get the Docker Daemon running on your machine. For Windows and MacOS users, Docker Desktop, is the easiest way to get started. Linux users can install docker desktop or the docker engine/server directly through curl
or apt-get
. For more information see, Docker Engine Installation.
Once docker desktop has been successfully installed and running, you can verify that it is running by running the following command in your terminal:
docker ps
If you see a list of running containers, then you are good to go. If you see an error message, then you may need to restart your machine.
If you open Docker Desktop and are stuck waiting for it to start you may need to close Docker Desktop entirely and open up the terminal. Once inside run the command
wsl --update
The main problem is WSL2 does not auto install the kernel when WSL2 installs, yet Docker Desktop expects it already installed.
If you are using the docker engine, you will need to run the following command to start the docker daemon:
sudo dockerd
You can verify that the docker daemon is running by running the following command in your terminal:
docker ps
The next step is to clone the repository. You can do this by running the following command in your terminal:
git clone https://github.com/SomberTM/merck-label-dashboard-typescript.git
This will clone the repository into a folder called merck-label-dashboard-typescript
in your current directory.
Navigate to the
merck-label-dashboard-typescript
folder by running the following command:cd merck-label-dashboard-typescript
Double check that you are in the
merck-label-dashboard-typescript
folder and that the docker daemon is running. For Windows and MacOS users, having docker desktop open is sufficient. For Linux users, see the Docker Engine section.
The next step is to build the docker image. You can do this by running the following command in your terminal:
docker-compose build
Once the image is build you can run
docker-compose up
to start the server. You can verify that the everything is running by navigating to localhost:3000
in your browser. The api is running on localhost:5000
.