Configuring GitHub Codespaces using devcontainers

GitHub Codespaces provides full development environments in your browser, and is free to use with anyone with a GitHub account. Each environment has a full Linux container and a browser-based UI using VS Code.

I'm a huge fan of Codespaces for running workshops: it means you can skip that awful half hour at the beginning of any workshop where you try to ensure everyone has a working development environment.

With Codespaces a fresh development environment is a case of clicking a button and then waiting for a couple of minutes. If you break it, click the button again to get a new one.

Codespaces generally launch from a GitHub repository, which can be configured to use a specific configuration. Here's the pattern I'm using for these, inspired by this Python 3.13 example by Pamela Fox.

A Python environment with some VS Code plugins

My simonw/codespaces repository contains a very simple configuration that provides Python 3.13 anh Node.js LTS plus VS Code with some useful plugins.

The only required file is .devcontainer/devcontainer.json. Here's that file in full:

{
  "name": "Python 3.13",
  "image": "mcr.microsoft.com/devcontainers/python:3.13-bullseye",
  "features": {
    "ghcr.io/devcontainers/features/node:1": {
      "version": "latest"
    }
  },
  "customizations": {
    "vscode": {
      "settings": {
        "python.defaultInterpreterPath": "/usr/local/bin/python",
        "python.linting.enabled": true
      },
      "extensions": [
        "ms-python.python",
        "ms-python.vscode-pylance",
        "ms-python.vscode-python-envs",
        "GitHub.copilot"
      ]
    }
  },
  "postCreateCommand": "pip install uv"
}

This would work with just the name and image fields.

I'm using Microsoft's Dev Containers base image for Python 3.13 on Debian Bullseye.

mcr.microsoft.com/devcontainers/python:3.13-bullseye

There's a full list of those images in the src/ directory of their devcontainers/images repository. They have them for Go, Rust, Java, PHP and more.

It's useful to have Node.js LTS installed so that NPM etc works out of the box. Here I'm using the "features" object to add that.

You can find a list of more features in the devcontainers/features repository, again in the src/ directory.

That features/node:1 one is defined by this install.sh script.

I copied the "vscode" block from Pamela, but I added the "GitHub.copilot" extension to enable Copilot in VS Code out of the box.

I also added that last line:

"postCreateCommand": "pip install uv"

Anything in postCreateCommand will be run after the container is first created. Here I'm using pip to install uv, after which uv tool install X etc will be available.

Providing a link to launch the container

Once you have added a .devcontainer/devcontainer.json to a repository you can construct a link that will launch that repository as a Codespace like so:

https://codespaces.new/simonw/codespaces?quickstart=1

Here's the documentation for this feature.

The ?quickstart=1 parameter causes the page to consider any Codespaces you already have running against that repository and suggest using those rather than starting a new one. It's a better option in my opinion.

Bonus: Installing and configuring LLM

I created a second Codespaces repo, simonw/codespaces-llm, which is almost identical to the above except the postCreateCommand contains the following:

"postCreateCommand": "pip install uv && uv tool install llm && llm install llm-github-models && llm models default github/gpt-4.1"

Here's that but more readable:

pip install uv &&
uv tool install llm &&
llm install llm-github-models &&
llm models default github/gpt-4.1

This install uv, then uses uv tool install to install llm, then uses the llm install command to install the llm-github-models plugin, and finally sets the default model used by LLM to github/gpt-4.1.

The net effect of this is that the user will then be able to run commands like this:

llm "Fun facts about pelicans"

GitHub Codespaces automatically sets a GITHUB_TOKEN environment variable with a token for the current user.

The llm-github-models plugin provides access to the GitHub Models collection, which can be accessed using that GITHUB_TOKEN as an API key.

Usage of GPT-4.1 is free using that key (albeit rate-limited), so setting the default model to github/gpt-4.1 means users get access to a very competent model for free!

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