README.md

More information about NMRlipids Docker images

Right now there are:

1. nmrlipids/gromacs: This is the base gromacs image, only contains gromacs.

Then we have one image extending this gromacs base:

3. nmrlipids/core: features everything developers need to work on the project

Installation using Docker

We provide a Docker-based development environment that allows for easy testing of new code and features. This method is recommended for development and testing purposes.

1. Install Docker

Before using the Docker-based development environment, you'll need to have Docker installed on your system:

• Linux: Follow the official Docker installation guide for Linux: https://docs.docker.com/engine/install/
• macOS: Download and install Docker Desktop for Mac from https://www.docker.com/products/docker-desktop/
• Windows: Download and install Docker Desktop for Windows from https://www.docker.com/products/docker-desktop/ (requires Windows Subsystem for Linux)

2. Using the Docker Development Environment

Setting Up the Development Environment

Go to the directory where you have the fairmd-lipids repository. Then,

1. Download the latest fairmd-lipids core image:

   docker pull nmrlipids/core:latest
   

2. Alternatively the Docker image can be built locally:

   docker build -t NAME_OF_THE_DOCKER_IMAGE .

3. Initialize the submodule data:

   git submodule update --init

Testing Code

1. Start the container with your code mounted:

   docker run -it -v $(pwd):/github/workspace NAME_OF_THE_DOCKER_IMAGE

   or if you pulled the latest image,

   docker run -it -v $(pwd):/github/workspace fairmd-lipids/core:latest

2. Inside the container:

   # Install base requirements and the fairmd-lipids package in editable mode
   pip install -e .
   
   # Run tests
   ./runtests.sh
   ./runtests-regression.sh

   You can specify additional arguments to the pytest via tox -e tests

   For full list of accepted flags, please look at pytest documentation.

   Do not forget to add this new package to the requirements.txt!

3. When done testing:

   # Exit container
   exit

Managing Different Test Environments

By default the core image features the dev requirements from this repository but you can easily create different testing environments with different dependencies:

1. Start container again:

   docker run -it -v $(pwd):/workspace NAME_OF_THE_DOCKER_IMAGE

2. Inside container, create a new virtual environment using Conda as previously described. (Must update this)

Tips for Docker Development

• Your local code changes are automatically reflected in the container since we use a volume mount
• You can run multiple test environments simultaneously by creating different virtual environments
• To see all running containers: docker ps
• To stop a container: docker stop <container_id>
• To remove all resources related to docker including images, container, build-resources: docker system prune -a