better codespace instructions

Author: scottyhq

.devcontainer/scipy2025/Dockerfile

@@ -0,0 +1,13 @@
+FROM mcr.microsoft.com/devcontainers/base:noble
+
+ARG PIXI_VERSION=v0.49.0
+
+RUN curl -L -o /usr/local/bin/pixi -fsSL --compressed "https://github.com/prefix-dev/pixi/releases/download/${PIXI_VERSION}/pixi-$(uname -m)-unknown-linux-musl" \
+    && chmod +x /usr/local/bin/pixi \
+    && pixi info
+
+# set some user and workdir settings to work nicely with vscode
+USER vscode
+WORKDIR /home/vscode
+
+RUN echo 'eval "$(pixi completion -s bash)"' >> /home/vscode/.bashrc

.devcontainer/scipy2025/devcontainer.json

@@ -0,0 +1,42 @@
+// https://pixi.sh/latest/integration/editor/vscode/#devcontainer-extension
+{
+  "name": "scipy2025-xarray-tutorial",
+  "build": {
+    "dockerfile": "Dockerfile",
+    "context": "../../"
+  },
+  "customizations": {
+    "vscode": {
+      "settings": {},
+      "extensions": [
+        "ms-toolsai.jupyter",
+        "ms-python.python",
+        "executablebookproject.myst-highlight"
+      ]
+    }
+  },
+  "features": {
+    // ensure GitHub Codespace 'Open with JupyterLab' works
+    // TODO: figure out why it doesn't work w/ jupyterlab in the pixi environment
+    "ghcr.io/devcontainers/features/python:1": {
+      "version": "3.12",
+      "installTools": false,
+      // NOTE: not working, so install with pip in postCreateCommand
+      // "toolsToInstall":"jupyterlab_myst,pixi-kernel",
+      "installJupyterlab": true
+    }
+  },
+  "mounts": [
+    "source=${localWorkspaceFolderBasename}-pixi,target=${containerWorkspaceFolder}/.pixi,type=volume"
+  ],
+  // These should execute in order below
+  "onCreateCommand": {
+    "configure_jupyterlab": "pip install jupyterlab_myst pixi-kernel"
+  },
+  "postCreateCommand": {
+    "set_pixi_permissions": "sudo chown vscode .pixi"
+  },
+  "postStartCommand": {
+    "configure_jupyterlab": "pixi install"
+  }
+}

README.md

@@ -1,8 +1,8 @@
 # Xarray Tutorial
 
-[![CI](https://github.com/xarray-contrib/xarray-tutorial/workflows/CI/badge.svg?branch=main)](https://github.com/xarray-contrib/xarray-tutorial/actions?query=branch%3Amain)
+[![Deploy Website to GitHub Pages](https://github.com/xarray-contrib/xarray-tutorial/actions/workflows/main.yaml/badge.svg)](https://github.com/xarray-contrib/xarray-tutorial/actions/workflows/main.yaml)
 [![Jupyter Book Badge](https://jupyterbook.org/badge.svg)](https://tutorial.xarray.dev)
-[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/xarray-contrib/xarray-tutorial/HEAD?labpath=workshops/scipy2024/index.ipynb)
+[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/xarray-contrib/xarray-tutorial/HEAD?labpath=overview/xarray-in-45-min.ipynb)
 
 This is the repository for a Jupyter Book website with tutorial material for [Xarray](https://github.com/pydata/xarray), _an open source project and Python package that makes working with labelled multi-dimensional arrays simple, efficient, and fun!_
 

overview/get-started.md

@@ -19,14 +19,14 @@ Many notebooks use special formatting ([Myst Markdown](https://mystmd.org/guide/
 
 The easiest way to start modifying and experimenting with tutorial content is to launch a pre-configured server on the Cloud. This is easy thanks to several free resources which offer ephemeral computing instances (be aware you may loose your connection or work at any time)
 
+```{warning}
+Be patient, it can take a few minutes for a server to become available on the Cloud!
+```
+
 #### Mybinder.org
 
 Clicking [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/xarray-contrib/xarray-tutorial/HEAD) will load a pre-configured Jupyter Lab interface with _all_ tutorial notebooks for you to run. _You have minimal computing resources and any changes you make will not be saved._ Any page with executable content also has a {octicon}`rocket;2em` icon in the upper right that will launch an interactive session for that particular page.
 
-```{warning}
-Be patient, it can take a few minutes for a server to become available on the Cloud (Mybinder.org)!
-```
-
 #### GitHub Codespaces
 
 This tutorial is available to run within [GitHub Codespaces](https://github.com/features/codespaces) - a preconfigured development environment running in Microsoft Azure.
@@ -39,13 +39,28 @@ You can choose from a selection of virtual machine types: 2 cores - 8 GB RAM sho
 Additionally, you are able to chose from various configurations for specific workshops (such as Scipy2024).
 GitHub currently gives every user [120 vCPU hours per month for free](https://docs.github.com/en/billing/managing-billing-for-github-codespaces/about-billing-for-github-codespaces#monthly-included-storage-and-core-hours-for-personal-accounts), beyond that you must pay. **So be sure to explicitly stop your codespace when you are done by going to this page (https://github.com/codespaces).** You can also chose to fully delete your codespace when you're done exploring tutorial content.
 
+```{tip}
+By default Codespaces open VSCode in a browser window. But you can also launch a JupyterLab interface. Once you've launched a codespace, use the auto-generated name in the following URL: `https://github.com/codespaces/CODESPACE-NAME?editor=jupyter`
+```
+
+Using the GitHub CLI is another very convenient way to start a codespace:
+
+```bash
+gh codespace create -R xarray-contrib/xarray-tutorial
+```
+
+```bash
+# Wait a few minutes for `gh codespace create` to finish, then run:
+gh codespace jupyter
+```
+
 ### On your computer
 
 Running tutorials on your computer requires some setup:
 
 We recommend using [`pixi`](https://pixi.sh/latest/) to ensure a fully reproducible Python environment
 
-```
+```bash
 git clone https://github.com/xarray-contrib/xarray-tutorial.git
 cd xarray-tutorial
 pixi run tutorial