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Upgrade environment for scipy2025 (#327)
* upgrade packages * updated codespace and instructions * add missing dockerfile * separate startup commands * add rich * better codespace instructions
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‎.binder/environment.yml

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- geoviews-core >=1.14.0,<2
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- gsw >=3.6.19,<4
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- hvplot >=0.11.3,<0.12
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- h5netcdf >=1.6.2,<2
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- h5netcdf >=1.6.3,<2
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- ipykernel >=6.29.5,<7
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- matplotlib-base >=3.10.3,<4
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- netcdf4 >=1.7.2,<2
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- sphinx-notfound-page >=1.1.0,<2
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- sphinxext-rediraffe >=0.2.7,<0.3
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- s3fs >=2025.5.1,<2026
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- xarray >=2025.6.1,<2026
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- zarr >=3.0.8,<4
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- xarray >=2025.7.0,<2026
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- zarr >=3.0.10,<4
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- flox >=0.10.4,<0.11
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- numbagg >=0.9.0,<0.10
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- rich >=14.0.0,<15
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- python >=3.10

‎.devcontainer/Dockerfile

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FROM mcr.microsoft.com/devcontainers/base:noble
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ARG PIXI_VERSION=v0.49.0
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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" \
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&& chmod +x /usr/local/bin/pixi \
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&& pixi info
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# set some user and workdir settings to work nicely with vscode
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USER vscode
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WORKDIR /home/vscode
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RUN echo 'eval "$(pixi completion -s bash)"' >> /home/vscode/.bashrc

‎.devcontainer/devcontainer.json

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// https://pixi.sh/latest/integration/editor/vscode/#devcontainer-extension
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{
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"image": "quay.io/pangeo/pangeo-notebook:latest",
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"postCreateCommand": {
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"vscode": "mkdir ${containerWorkspaceFolder}/.vscode && cp ${containerWorkspaceFolder}/.devcontainer/tasks.json ${containerWorkspaceFolder}/.vscode/tasks.json"
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},
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"hostRequirements": {
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"cpus": 2
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"name": "xarray-tutorial",
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"build": {
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"dockerfile": "Dockerfile",
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"context": ".."
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},
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"customizations": {
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"codespaces": {
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"openFiles": ["README.md"]
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},
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"vscode": {
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"extensions": ["ms-toolsai.jupyter", "ms-python.python"]
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"settings": {},
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"extensions": [
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"ms-toolsai.jupyter",
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"ms-python.python",
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"executablebookproject.myst-highlight"
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]
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}
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},
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"features": {
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// ensure GitHub Codespace 'Open with JupyterLab' works
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// TODO: figure out why it doesn't work w/ jupyterlab in the pixi environment
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"ghcr.io/devcontainers/features/python:1": {
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"version": "3.12",
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"installTools": false,
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// NOTE: not working, so install with pip in postCreateCommand
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// "toolsToInstall":"jupyterlab_myst,pixi-kernel",
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"installJupyterlab": true
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}
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},
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"mounts": [
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"source=${localWorkspaceFolderBasename}-pixi,target=${containerWorkspaceFolder}/.pixi,type=volume"
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],
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// These should execute in order below
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"onCreateCommand": {
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"configure_jupyterlab": "pip install jupyterlab_myst pixi-kernel"
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},
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"postCreateCommand": {
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"set_pixi_permissions": "sudo chown vscode .pixi"
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},
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"postStartCommand": {
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"configure_jupyterlab": "pixi install"
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}
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}

‎.devcontainer/scipy2025/Dockerfile

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FROM mcr.microsoft.com/devcontainers/base:noble
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ARG PIXI_VERSION=v0.49.0
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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" \
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&& chmod +x /usr/local/bin/pixi \
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&& pixi info
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# set some user and workdir settings to work nicely with vscode
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USER vscode
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WORKDIR /home/vscode
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RUN echo 'eval "$(pixi completion -s bash)"' >> /home/vscode/.bashrc

‎.devcontainer/scipy2025/devcontainer.json

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

‎.devcontainer/tasks.json

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‎README.md

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# Xarray Tutorial
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[![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)
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[![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)
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[![Jupyter Book Badge](https://jupyterbook.org/badge.svg)](https://tutorial.xarray.dev)
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[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/xarray-contrib/xarray-tutorial/HEAD?labpath=workshops/scipy2024/index.ipynb)
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[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/xarray-contrib/xarray-tutorial/HEAD?labpath=overview/xarray-in-45-min.ipynb)
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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!_
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@@ -24,12 +24,14 @@ This tutorial is available to run within [Github Codespaces](https://github.com/
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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 or shut down your codespace when you are done by going to this page (https://github.com/codespaces).**
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Once your codespace is launched, the following happens:
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You can also use the GitHub CLI to launch a codespace
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- [Visual Studio Code](https://code.visualstudio.com/) Interface will open up within your browser.
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- A built in terminal will open and it will execute `jupyter lab` automatically.
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- Once you see a url to click within the terminal, simply `cmd + click` the given url.
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- This will open up another tab in your browser, leading to a [Jupyter Lab](https://jupyterlab.readthedocs.io/en/latest/) Interface.
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```
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# This will output a URL to use VSCode in the browser
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gh codespace create --repo xarray-contrib/xarray-tutorial
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# Optionally launch JupyterLab instead of vscode (after codespace has been created)
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gh codespace jupyter
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```
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#### Locally
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‎overview/get-started.md

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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)
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```{warning}
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Be patient, it can take a few minutes for a server to become available on the Cloud!
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```
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#### Mybinder.org
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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.
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```{warning}
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Be patient, it can take a few minutes for a server to become available on the Cloud (Mybinder.org)!
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```
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#### GitHub Codespaces
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This tutorial is available to run within [GitHub Codespaces](https://github.com/features/codespaces) - a preconfigured development environment running in Microsoft Azure.
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Additionally, you are able to chose from various configurations for specific workshops (such as Scipy2024).
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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.
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```{tip}
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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`
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```
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Using the GitHub CLI is another very convenient way to start a codespace:
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```bash
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gh codespace create -R xarray-contrib/xarray-tutorial
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```
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```bash
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# Wait a few minutes for `gh codespace create` to finish, then run:
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gh codespace jupyter
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```
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### On your computer
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Running tutorials on your computer requires some setup:
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We recommend using [`pixi`](https://pixi.sh/latest/) to ensure a fully reproducible Python environment
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```
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```bash
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git clone https://github.com/xarray-contrib/xarray-tutorial.git
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cd xarray-tutorial
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pixi run tutorial

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