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workshops/scipy2025/index.ipynb

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"# SciPy 2025\n",
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"\n",
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"## Welcome to the Xarray SciPy 2025 Tutorial! \n",
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"\n",
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"<img src=\"https://images.squarespace-cdn.com/content/v1/6743676bb9f2e109f0ddba96/055e9b3f-965f-42c7-b496-2ba3870e216e/Logo_color-black.png?format=1500w\" align=\"right\" width=\"20%\">\n",
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"\n",
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"**Xarray**: *Friendly, Interactive, and Scalable Scientific Data Analysis*\n",
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"\n",
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"July 8, 13:30–17:30 (US/Pacific), Tacoma Convention Center Room 315\n",
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"\n",
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"This *4-hour* workshop will explore content from [the Xarray tutorial](https://tutorial.xarray.dev), which contains a comprehensive collection of hands-on tutorial Jupyter Notebooks. We will review a curated set of examples that will prepare you for increasingly complex real-world data analysis tasks!\n",
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"\n",
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":::{admonition} Learning Goals\n",
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"- Understand xarray’s core data structures\n",
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"- Understand how to map typical xarray computations and workflows over hierarchical data\n",
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"- Understand how common storage formats correspond to the DataTree model\n",
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"- Open a public Zarr store in the cloud and manipulate the contents\n",
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":::"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"## Schedule \n",
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"\n",
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"*Times in US/Pacific Timezone (Tacoma, WA)\n",
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"\n",
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"Use the links to navigate to the right notebooks.\n",
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"\n",
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"| Topic | Time | Notebook Links | \n",
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"| :- | - | - | \n",
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"| Introduction and Setup | 1:30 (10 min) | | \n",
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"| The Xarray Data Model | 1:40 (50 min) | [Data structures](../../fundamentals/01_data_structures.md) | \n",
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"| *10 minute Break* \n",
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"| Computational Patterns | 2:30 (50 min) | [Computational Patterns](../../intermediate/01-high-level-computation-patterns.ipynb) <br> | \n",
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"| *10 minute Break* | \n",
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"| Storage formats | 3:30 (50 min) | [Storage formats](../../intermediate/storage_formats.ipynb) | \n",
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"| *10 minute Break* | \n",
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"| Zarr & the cloud | 4:30 (50 min) | [Intro to Zarr](../../intermediate/intro-to-zarr.ipynb) |\n",
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"| | End 5:30 | |"
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]
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{
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"### Tutorial Setup\n",
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"\n",
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"We recommend using a preconfigured GitHub Codespace for this tutorial. This section describes how to access and manage a GitHub Codespace.\n",
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"\n",
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":::{note}\n",
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"If you prefer to work on your own computer, refer to instructions in the [Getting Started Section](../../overview/get-started.md)\n",
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":::\n",
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"\n",
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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\".\n",
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"\n",
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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%2Fscipy2024%2Fdevcontainer.json)\n",
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"\n",
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"☝️ Click the button above to go to options window to launch a Github Codespace.\n",
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"\n",
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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).**\n",
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"\n",
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"Once your Codespace is launched, the following happens:\n",
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"\n",
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"- [Visual Studio Code](https://code.visualstudio.com/) Interface will open up within your browser.\n",
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"- A built in terminal will open and it will execute `jupyter lab` automatically.\n",
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"- Once you see a url to click within the terminal, simply `cmd + click` the given url.\n",
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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.\n",
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"\n",
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":::{warning}\n",
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"Consider Codespaces as ephemeral environments. You may lose your connection and any edits you make.\n",
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":::"
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]
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}
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