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README.html

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<meta charset="utf-8" />
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<meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="viewport" content="width=device-width, initial-scale=1" />
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<title>Kerchunk Cookbook &#8212; Kerchunk Cookbook</title>
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<title>Virtual Zarr Cookbook (Kerchunk and VirtualiZarr) &#8212; Kerchunk Cookbook</title>
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<meta name="viewport" content="width=device-width, initial-scale=1"/>
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<meta name="docsearch:language" content="en"/>
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<meta name="docsearch:version" content="" />
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<meta name="docbuild:last-update" content="11 November 2024"/>
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<meta name="docbuild:last-update" content="2 December 2024"/>
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</head>
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<ul class="nav bd-sidenav bd-sidenav__home-link">
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<li class="toctree-l1 current active">
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<a class="reference internal" href="#">
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Kerchunk Cookbook
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Virtual Zarr Cookbook (Kerchunk and VirtualiZarr)
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</a>
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</li>
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</ul>
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</ul>
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<p aria-level="2" class="caption" role="heading"><span class="caption-text">Foundations</span></p>
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<ul class="nav bd-sidenav">
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<li class="toctree-l1"><a class="reference internal" href="notebooks/foundations/01_kerchunk_basics.html">Kerchunk Basics</a></li>
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<li class="toctree-l1"><a class="reference internal" href="notebooks/foundations/02_kerchunk_multi_file.html">Multi-File Datasets with Kerchunk</a></li>
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<li class="toctree-l1"><a class="reference internal" href="notebooks/foundations/03_kerchunk_dask.html">Kerchunk and Dask</a></li>
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<li class="toctree-l1"><a class="reference internal" href="notebooks/foundations/01_kerchunk_basics.html">Basics of virtual Zarr stores</a></li>
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<li class="toctree-l1"><a class="reference internal" href="notebooks/foundations/02_kerchunk_multi_file.html">Multi-file virtual datasets with VirtualiZarr</a></li>
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<li class="toctree-l1"><a class="reference internal" href="notebooks/foundations/03_kerchunk_dask.html">Parallel virtual dataset creation with VirtualiZarr, Kerchunk, and Dask</a></li>
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</ul>
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<p aria-level="2" class="caption" role="heading"><span class="caption-text">Advanced</span></p>
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<ul class="nav bd-sidenav">
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<li class="toctree-l1"><a class="reference internal" href="notebooks/advanced/Parquet_Reference_Storage.html">Store Kerchunk Reference Files as Parquet</a></li>
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<li class="toctree-l1"><a class="reference internal" href="notebooks/advanced/Parquet_Reference_Storage.html">Store virtual datasets as Kerchunk Parquet references</a></li>
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<li class="toctree-l1"><a class="reference internal" href="notebooks/advanced/appending.html">Appending to Kerchunk references</a></li>
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<article class="bd-article">
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<a class="reference internal image-reference" href="_images/thumbnail.png"><img alt="thumbnail" src="_images/thumbnail.png" style="width: 300px;" /></a>
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<section class="tex2jax_ignore mathjax_ignore" id="kerchunk-cookbook">
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<h1>Kerchunk Cookbook<a class="headerlink" href="#kerchunk-cookbook" title="Link to this heading"><i class="fas fa-link"></i></a></h1>
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<section class="tex2jax_ignore mathjax_ignore" id="virtual-zarr-cookbook-kerchunk-and-virtualizarr">
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<h1>Virtual Zarr Cookbook (Kerchunk and VirtualiZarr)<a class="headerlink" href="#virtual-zarr-cookbook-kerchunk-and-virtualizarr" title="Link to this heading"><i class="fas fa-link"></i></a></h1>
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<p><a class="reference external" href="https://github.com/ProjectPythia/kerchunk-cookbook/actions/workflows/nightly-build.yaml"><img alt="nightly-build" src="https://github.com/ProjectPythia/kerchunk-cookbook/actions/workflows/nightly-build.yaml/badge.svg" /></a>
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<a class="reference external" href="https://binder.projectpythia.org/v2/gh/ProjectPythia/kerchunk-cookbook/main?labpath=notebooks"><img alt="Binder" src="https://binder.projectpythia.org/badge_logo.svg" /></a>
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<a class="reference external" href="https://zenodo.org/badge/latestdoi/588661659"><img alt="DOI" src="https://zenodo.org/badge/588661659.svg" /></a></p>
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<p>This Project Pythia Cookbook covers using the <a class="reference external" href="https://fsspec.github.io/kerchunk/">Kerchunk</a>
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library to access archival data formats as if they were
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ARCO (Analysis-Ready-Cloud-Optimized) data.</p>
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<p>This Project Pythia Cookbook covers using the <a class="reference external" href="https://fsspec.github.io/kerchunk/">Kerchunk</a>, <a class="reference external" href="https://virtualizarr.readthedocs.io/en/latest/index.html">VirtualiZarr</a>, and <a class="reference external" href="https://zarr.readthedocs.io/en/stable/">Zarr-Python</a> libraries to access archival data formats as if they were ARCO (Analysis-Ready-Cloud-Optimized) data.</p>
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<section id="motivation">
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<h2>Motivation<a class="headerlink" href="#motivation" title="Link to this heading"><i class="fas fa-link"></i></a></h2>
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<p>The <code class="docutils literal notranslate"><span class="pre">Kerchunk</span></code> library allows you to access chunked and compressed
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<p>The <code class="docutils literal notranslate"><span class="pre">Kerchunk</span></code> library pioneered the access of chunked and compressed
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data formats (such as NetCDF3. HDF5, GRIB2, TIFF &amp; FITS), many of
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which are the primary data formats for many data archives, as if
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they were in ARCO formats such as Zarr which allows for parallel,
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chunk-specific access. Instead of creating a new copy of the dataset
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in the Zarr spec/format, <code class="docutils literal notranslate"><span class="pre">Kerchunk</span></code> reads through the data archive
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and extracts the byte range and compression information of each
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chunk, then writes that information to a .json file (or alternate
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backends in future releases). For more details on how this process
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works please see this page on the
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<a class="reference external" href="https://fsspec.github.io/kerchunk/detail.html">Kerchunk docs</a>).
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These summary files can then be combined to generated a <code class="docutils literal notranslate"><span class="pre">Kerchunk</span></code>
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reference for that dataset, which can be read via
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<a class="reference external" href="https://zarr.readthedocs.io">Zarr</a> and
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chunk, then writes that information to a “virtual Zarr store” using a
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JSON or Parquet “reference file”. The <code class="docutils literal notranslate"><span class="pre">VirtualiZarr</span></code>
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library provides a simple way to create these “virtual stores” using familiary
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<code class="docutils literal notranslate"><span class="pre">xarray</span></code> syntax. Lastly, the <code class="docutils literal notranslate"><span class="pre">icechunk</span></code> provides a new way to store and re-use these references.</p>
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<p>These virtual Zarr stores can be re-used and read via <a class="reference external" href="https://zarr.readthedocs.io">Zarr</a> and
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<a class="reference external" href="https://docs.xarray.dev/en/stable/">Xarray</a>.</p>
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<p>For more details on how this process works please see this page on the
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<a class="reference external" href="https://fsspec.github.io/kerchunk/detail.html">Kerchunk docs</a>).</p>
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</section>
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<section id="authors">
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<h2>Authors<a class="headerlink" href="#authors" title="Link to this heading"><i class="fas fa-link"></i></a></h2>
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<p>This cookbook is broken up into two sections,
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Foundations and Example Notebooks.</p>
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<section id="section-1-foundations">
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<h3>Section 1 Foundations<a class="headerlink" href="#section-1-foundations" title="Link to this heading"><i class="fas fa-link"></i></a></h3>
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<h3>Section 1 - Foundations<a class="headerlink" href="#section-1-foundations" title="Link to this heading"><i class="fas fa-link"></i></a></h3>
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<p>In the <code class="docutils literal notranslate"><span class="pre">Foundations</span></code> section we will demonstrate
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how to use <code class="docutils literal notranslate"><span class="pre">Kerchunk</span></code> to create reference sets
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how to use <code class="docutils literal notranslate"><span class="pre">Kerchunk</span></code> and <code class="docutils literal notranslate"><span class="pre">VirtualiZarr</span></code> to create reference files
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from single file sources, as well as to create
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multi-file virtual datasets from collections of files.</p>
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multi-file virtual Zarr stores from collections of files.</p>
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</section>
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<section id="section-2-generating-reference-files">
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<h3>Section 2 Generating Reference Files<a class="headerlink" href="#section-2-generating-reference-files" title="Link to this heading"><i class="fas fa-link"></i></a></h3>
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<p>The notebooks in the <code class="docutils literal notranslate"><span class="pre">Generating</span> <span class="pre">Reference</span> <span class="pre">Files</span></code> section
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demonstrate how to use <code class="docutils literal notranslate"><span class="pre">Kerchunk</span></code> to create
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<section id="section-2-generating-virtual-zarr-stores">
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<h3>Section 2 - Generating Virtual Zarr Stores<a class="headerlink" href="#section-2-generating-virtual-zarr-stores" title="Link to this heading"><i class="fas fa-link"></i></a></h3>
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<p>The notebooks in the <code class="docutils literal notranslate"><span class="pre">Generating</span> <span class="pre">Virtual</span> <span class="pre">Zarr</span> <span class="pre">Stores</span></code> section
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demonstrates how to use <code class="docutils literal notranslate"><span class="pre">Kerchunk</span></code> and <code class="docutils literal notranslate"><span class="pre">VirtualiZarr</span></code> to create
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datasets for all the supported file formats.
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<code class="docutils literal notranslate"><span class="pre">Kerchunk</span></code> currently supports NetCDF3,
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NetCDF4/HDF5, GRIB2, TIFF (including CoG).</p>
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These libraries currently support virtualizing NetCDF3,
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NetCDF4/HDF5, GRIB2, TIFF (including COG).</p>
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</section>
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<section id="section-3-using-pre-generated-references">
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<h3>Section 3 Using Pre-Generated References<a class="headerlink" href="#section-3-using-pre-generated-references" title="Link to this heading"><i class="fas fa-link"></i></a></h3>
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<p>The <code class="docutils literal notranslate"><span class="pre">Pre-Generated</span> <span class="pre">References</span></code> section contains notebooks demonstrating how to load existing references into <code class="docutils literal notranslate"><span class="pre">Xarray</span></code> and <code class="docutils literal notranslate"><span class="pre">Xarray-Datatree</span></code>, generated coordinates for GeoTiffs using <code class="docutils literal notranslate"><span class="pre">xrefcoord</span></code> and plotting using <code class="docutils literal notranslate"><span class="pre">Hvplot</span> <span class="pre">Datashader</span></code>.</p>
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<section id="section-3-using-virtual-zarr-stores">
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<h3>Section 3 - Using Virtual Zarr Stores<a class="headerlink" href="#section-3-using-virtual-zarr-stores" title="Link to this heading"><i class="fas fa-link"></i></a></h3>
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<p>The <code class="docutils literal notranslate"><span class="pre">Using</span> <span class="pre">Virtual</span> <span class="pre">Zarr</span> <span class="pre">Stores</span></code> section contains notebooks demonstrating how to load existing references into <code class="docutils literal notranslate"><span class="pre">Xarray</span></code>, generating coordinates for GeoTiffs using <code class="docutils literal notranslate"><span class="pre">xrefcoord</span></code>, and plotting using <code class="docutils literal notranslate"><span class="pre">Hvplot</span> <span class="pre">Datashader</span></code>.</p>
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</section>
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<section id="running-the-notebooks">
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</ul>
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<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#structure">Structure</a><ul class="nav section-nav flex-column">
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<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#section-1-foundations">Section 1 Foundations</a></li>
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<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#section-2-generating-reference-files">Section 2 Generating Reference Files</a></li>
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<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#section-3-using-pre-generated-references">Section 3 Using Pre-Generated References</a></li>
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<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#section-1-foundations">Section 1 - Foundations</a></li>
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<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#section-2-generating-virtual-zarr-stores">Section 2 - Generating Virtual Zarr Stores</a></li>
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<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#section-3-using-virtual-zarr-stores">Section 3 - Using Virtual Zarr Stores</a></li>
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</ul>
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</li>
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<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#running-the-notebooks">Running the Notebooks</a><ul class="nav section-nav flex-column">
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<div class="footer-item">
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<p class="last-updated">
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Last updated on 11 November 2024.
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Last updated on 2 December 2024.
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<br/>
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</p>
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</div>
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By Norland Raphael Hagen.
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Last updated on 11 November 2024.
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Last updated on 2 December 2024.
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</p>
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_sources/README.md

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<img src="thumbnail.png" alt="thumbnail" width="300"/>
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# Kerchunk Cookbook
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# Virtual Zarr Cookbook (Kerchunk and VirtualiZarr)
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[![nightly-build](https://github.com/ProjectPythia/kerchunk-cookbook/actions/workflows/nightly-build.yaml/badge.svg)](https://github.com/ProjectPythia/kerchunk-cookbook/actions/workflows/nightly-build.yaml)
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[![Binder](https://binder.projectpythia.org/badge_logo.svg)](https://binder.projectpythia.org/v2/gh/ProjectPythia/kerchunk-cookbook/main?labpath=notebooks)
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[![DOI](https://zenodo.org/badge/588661659.svg)](https://zenodo.org/badge/latestdoi/588661659)
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This Project Pythia Cookbook covers using the [Kerchunk](https://fsspec.github.io/kerchunk/)
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library to access archival data formats as if they were
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ARCO (Analysis-Ready-Cloud-Optimized) data.
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This Project Pythia Cookbook covers using the [Kerchunk](https://fsspec.github.io/kerchunk/), [VirtualiZarr](https://virtualizarr.readthedocs.io/en/latest/index.html), and [Zarr-Python](https://zarr.readthedocs.io/en/stable/) libraries to access archival data formats as if they were ARCO (Analysis-Ready-Cloud-Optimized) data.
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## Motivation
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The `Kerchunk` library allows you to access chunked and compressed
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The `Kerchunk` library pioneered the access of chunked and compressed
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data formats (such as NetCDF3. HDF5, GRIB2, TIFF & FITS), many of
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which are the primary data formats for many data archives, as if
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they were in ARCO formats such as Zarr which allows for parallel,
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chunk-specific access. Instead of creating a new copy of the dataset
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in the Zarr spec/format, `Kerchunk` reads through the data archive
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and extracts the byte range and compression information of each
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chunk, then writes that information to a .json file (or alternate
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backends in future releases). For more details on how this process
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works please see this page on the
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[Kerchunk docs](https://fsspec.github.io/kerchunk/detail.html)).
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These summary files can then be combined to generated a `Kerchunk`
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reference for that dataset, which can be read via
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[Zarr](https://zarr.readthedocs.io) and
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chunk, then writes that information to a "virtual Zarr store" using a
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JSON or Parquet "reference file". The `VirtualiZarr`
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library provides a simple way to create these "virtual stores" using familiary
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`xarray` syntax. Lastly, the `icechunk` provides a new way to store and re-use these references.
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These virtual Zarr stores can be re-used and read via [Zarr](https://zarr.readthedocs.io) and
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[Xarray](https://docs.xarray.dev/en/stable/).
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For more details on how this process works please see this page on the
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[Kerchunk docs](https://fsspec.github.io/kerchunk/detail.html)).
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## Authors
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[Raphael Hagen](https://github.com/norlandrhagen)
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This cookbook is broken up into two sections,
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Foundations and Example Notebooks.
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### Section 1 Foundations
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### Section 1 - Foundations
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In the `Foundations` section we will demonstrate
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how to use `Kerchunk` to create reference sets
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how to use `Kerchunk` and `VirtualiZarr` to create reference files
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from single file sources, as well as to create
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multi-file virtual datasets from collections of files.
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multi-file virtual Zarr stores from collections of files.
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### Section 2 Generating Reference Files
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### Section 2 - Generating Virtual Zarr Stores
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The notebooks in the `Generating Reference Files` section
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demonstrate how to use `Kerchunk` to create
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The notebooks in the `Generating Virtual Zarr Stores` section
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demonstrates how to use `Kerchunk` and `VirtualiZarr` to create
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datasets for all the supported file formats.
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`Kerchunk` currently supports NetCDF3,
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NetCDF4/HDF5, GRIB2, TIFF (including CoG).
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These libraries currently support virtualizing NetCDF3,
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NetCDF4/HDF5, GRIB2, TIFF (including COG).
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### Section 3 Using Pre-Generated References
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### Section 3 - Using Virtual Zarr Stores
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The `Pre-Generated References` section contains notebooks demonstrating how to load existing references into `Xarray` and `Xarray-Datatree`, generated coordinates for GeoTiffs using `xrefcoord` and plotting using `Hvplot Datashader`.
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The `Using Virtual Zarr Stores` section contains notebooks demonstrating how to load existing references into `Xarray`, generating coordinates for GeoTiffs using `xrefcoord`, and plotting using `Hvplot Datashader`.
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## Running the Notebooks
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