devcontainer.json

{
    // Uses the same prebuilt image as Binder, built by .github/workflows/build-image.yml.
    // Building the conda environment at container-create time took tens of minutes and ran
    // out of resources on the default Codespaces machine, so we pull instead of solve.
    "name": "festim-workshop",
    "image": "ghcr.io/festim-dev/festim-workshop:latest",

    // repo2docker images run as jovyan (uid 1000) and install into /srv/conda/envs/notebook
    // -- not into an env named after `name:` in environment.yml, which repo2docker discards.
    "remoteUser": "jovyan",

    // conda is activated by /etc/profile.d/activate-conda.sh, which only runs for login
    // shells; without this the VS Code terminal and Jupyter extension would miss the env.
    "remoteEnv": {
        "PATH": "/srv/conda/envs/notebook/bin:${containerEnv:PATH}"
    },

    // Deliberately NO "hostRequirements". It filters the machine-type list, and asking for
    // storage 64gb matched nothing (the common Codespaces tiers ship 32 GB), which surfaces as
    // "A codespace cannot be created because no machine types are available" with Machine
    // type: None. There is also nothing left to resource: the environment is a prebuilt image
    // now, so container creation is a pull, not a conda solve. If you ever re-add a floor, set
    // only cpus/memory, never storage, and check the org's allowed machine types first.

    // Configure tool-specific properties.
    "customizations": {
        // Configure properties specific to VS Code.
        "vscode": {
            // Set *default* container specific settings.json values on container create.
            "settings": {
                "python.defaultInterpreterPath": "/srv/conda/envs/notebook/bin/python"
            },
            // Add the IDs of extensions you want installed when the container is created.
            "extensions": [
                "ms-python.python",
                "ms-python.vscode-pylance",
                "ms-toolsai.jupyter"
            ]
        }
    },

    // Allows port 8888 used for Jupyter Notebook to be available locally.
    "forwardPorts": [
        8888
    ]
}