Navigate to the Environment Editor

Click the /environment folder to open the Environment Editor. Code Ocean uses Docker as the underlying tool to build and preserve the environment. When adding a package, the Environment Editor writes the information to a Dockerfile in the /environment folder.

Any edit made in the /environment folder triggers a change in the Dockerfile, which could result in a complete rebuild of the Docker image during a subsequent Reproducible Run or Cloud Workstation session. The wait time for the Docker image rebuild varies according to the number and complexity of packages installed.

Selecting a Starter Environment

The first thing to do when setting up the computational environment is to select a Starter Environment, (also known as a Docker base image). The Environment Editor lists all the Starter Environments available and allows you to search by name, version, language, and tags.

Click Select to choose the Starter Environment. If the Starter Environment has multiple versions, you'll be able to choose a specific version.

You can view all of the packages installed in a Starter Environment along with their specific versions by clicking the drop-down menu to expand/collapse the package managers that were installed.

Once you've selected a Starter Environment, clicking on a specific package manager icon as shown below will open an information box listing the packages installed via that package manager along with their versions.

Considerations When Choosing a Starter Environment

When not using a pre-installed language, use a base Ubuntu (16.04,18.04,20.04) environment.
When proprietary software, such as MATLAB or Stata is required, begin from an environment with the proprietary language.
When using a GPU, select an environment with GPU access. These are labeled accordingly, or will reference CUDA or a deep learning framework. You can easily filter for GPU Starter Environments by typing "GPU" in the search box.

Starter Environments for Specific Cloud Workstations

If you would like to work in a Cloud Workstation, it may be required to choose a Starter Environment which supports that Cloud Workstation. Below is a guide to the available Cloud Workstations and their compatible programming languages and Starter Environments.

Cloud Workstation

Compatible Language

Note

Terminal

all

Jupyter Lab/ Jupyter Notebook

mostly Python

You can install other kernels and use different languages

RStudio

MATLAB

View the information box below for more detail.

Code-Server (VSCode)

all

Ubuntu Desktop (IGV,

Pytorch Desktop, etc.)

all

Requires use of Ubuntu Desktop Starter Environment

Shiny

IGV

all

Requires use of Starter Environment with IGV installed (i.e. Ubuntu Desktop)

Streamlit

Python

The MATLAB Cloud Workstation is a MATLAB interface that requires specific licenses and configurations set up in a MATLAB Starter Environment. To use the Matlab Cloud Workstation, you must choose MATLAB as your Starter Environment.

Dockerfiles In Code Ocean

When you first select your Starter Environment, a Dockerfile will be created in your environment folder. This file contains all the necessary commands that will be used to build your custom environment in your Capsule during computations. As more packages are added via the Environment Editor they will be synchronously added to the Dockerfile.

To manually customize your Capsule environment you can open the Dockerfile and unlock it. This is not recommended as it will permanently disable the Environment Editor and all subsequent changes to the environment will need to be made through the Dockerfile.