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Add codespace config for scipy 2023 (#184)
* Initial setup for codespaces * Change build context * Add apt.txt * Add jupyter and python extensions for vscode * Modify cpu requirement to 2 * Remove apt.txt, don't need it * Open README.md by default on vscode * Move codespaces to scipy 2023 and add apt txt for git and vim * Move all to .binder and add jupyterlab config * Fix context * Remove jupyter lab config default url settings * Remove jb config.. doesn't quite work * Move configs to conda/binder * Moving out of binder folder in conda * Move config and try postCreateCommand * Add create .jupyter folder * Change to post create and copy lab config only * Add small readme * Remove unecessary jupyter lab config * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Fix misspelling of jupyterlab * Try to use tasks and predefined vars * Modify the paths to directories * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Remove comments in tasks.json * Update readme to reflect recent changes * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Update README * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Remove leading / * Add dependabot to auto update dockerfile image version * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Point to specific jupyter in conda * Allow all origins to avoid CORS * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Update .devcontainer/scipy2023/tasks.json Co-authored-by: Scott Henderson <scottyhq@gmail.com> --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Scott Henderson <scottyhq@gmail.com>
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‎.devcontainer/Dockerfile

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FROM pangeo/base-image:2023.06.20

‎.devcontainer/scipy2023/devcontainer.json

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{
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"build": {
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"dockerfile": "../Dockerfile",
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"context": "../../conda"
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},
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"postCreateCommand": {
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"jupyterlab": "mkdir /home/jovyan/.jupyter && cp ${containerWorkspaceFolder}/.devcontainer/scipy2023/jupyter_lab_config.py /home/jovyan/.jupyter/jupyter_lab_config.py",
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"vscode": "mkdir ${containerWorkspaceFolder}/.vscode && cp ${containerWorkspaceFolder}/.devcontainer/scipy2023/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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},
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"customizations": {
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"codespaces": {
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"openFiles": ["workshops/scipy2023/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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}
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}
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}

‎.devcontainer/scipy2023/jupyter_lab_config.py

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# Configuration file for lab.
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c = get_config() # noqa
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## The default URL to redirect to from `/`
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# Default: '/lab'
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c.LabApp.default_url = '/lab/tree/workshops/scipy2023/index.ipynb'
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## Set the Access-Control-Allow-Origin header
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#
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# Use '*' to allow any origin to access your server.
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#
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# Takes precedence over allow_origin_pat.
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# Default: ''
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c.ServerApp.allow_origin = '*'

‎.devcontainer/scipy2023/tasks.json

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{
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"version": "2.0.0",
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"tasks": [
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{
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"label": "jupyterlab",
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"type": "shell",
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"command": "/srv/conda/envs/notebook/bin/jupyter lab --no-browser",
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"presentation": {
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"reveal": "always"
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},
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"runOptions": {
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"runOn": "folderOpen"
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}
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}
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]
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}

‎.github/dependabot.yml

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version: 2
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updates:
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- package-ecosystem: 'docker'
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directory: '/.devcontainer'
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schedule:
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interval: 'daily'

‎conda/apt.txt

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git
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vim

‎workshops/scipy2023/README.md

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For the live tutorial, we will be using the SciPy 2023 Nebari JupyterHub. Instructions for the live
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tutorial will be added soon.
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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 development environment that's hosted in the cloud" - with the conda environment specification in the [`conda-lock.yml`](../../conda/conda-lock.yml) file.
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[![Open in GitHub Codespaces](https://github.com/codespaces/badge.svg)](https://github.com/codespaces/new/xarray-contrib/xarray-tutorial/tree/main?devcontainer_path=.devcontainer%2Fscipy2023%2Fdevcontainer.json)
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☝️ Click the button above to go to options window to launch a Github codespace.
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A codespace is a development environment that's hosted in the cloud.
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You can choose from a selection of virtual machine types: 2 cores - 4 GB RAM - 32 GB storage, and 4 cores - 8 GB RAM - 32GB storage.
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Additionally, you are able to chose from various Dev container configuration, for this specific workshop, please ensure that `Scipy2023` is selected.
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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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- [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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## Outline
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**🏗️ Outline coming soon! Please check back later**

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