deploy: 439af83

_preview/451/_sources/cookbook-tasklist.md

@@ -41,7 +41,9 @@ This can be seen in individual Pull Requests as green checkmarks ✅ for importa
     - Code errors in your notebooks themselves
 - [ ] **Identify a Maintainer team via GitHub handle(s) in this thread.**
 This can be one or more people with availability to check in on this Cookbook, issue fixes to broken content, or with a vision for the future development of the Cookbook. This is typically (but not necessarily) one of the primary authors of the Cookbook.
-- [ ] **Finally, release your Cookbook!**
+- [ ] **Link your Cookbook repo to Zenodo for DOI generation**
+Follow steps 1-4 under [Generate a DOI](https://projectpythia.org/cookbook-guide.html#generate-a-doi) in the Cookbook Guide. Return here for instructions on step 5, and your final step:
+- [ ] **Release your Cookbook!**
     - On the right-hand sidebar for your Cookbook repository, click “Create a new release”. If you don’t see this button, you may need to click on the “Releases” header first and “Create” or “Draft” a new release.
     ![GitHub Repository sidebar section titled "Releases"](https://raw.githubusercontent.com/ProjectPythia/projectpythia.github.io/main/portal/_static/images/4-releases.png "Releases")
     - “Choose a tag”, enter a new tag name. This will be the git reference of the snapshot of code that represents this particular release of your Cookbook! We recommend using a name fitting the [CalVer](https://calver.org/) scheme, so something like v2024.06.13 for the date of the release, then choose “+ Create new tag: <your tag name> on publish” and make its Target main (unless you have the knowledge and desire to release from another branch!)

_preview/451/_sources/resource-gallery.md

@@ -91,7 +91,7 @@ Resource Gallery
 <img src="_static/thumbnails/earth_env_data_science.png" class="gallery-thumbnail" />
 <div class="container">
 <a href="https://earth-env-data-science.github.io/intro" class="text-decoration-none"><h4 class="display-4 p-0">An Introduction to Earth and Environmental Data Science</h4></a>
-<p class="card-subtitle"><strong>Author:</strong> Kerry Key, Ryan Abernathey<br/><strong>Affiliation:</strong> Lamont-Doherty Earth Observatory</p>
+<p class="card-subtitle"><strong>Author:</strong> Ryan Abernathey, Kerry Key<br/><strong>Affiliation:</strong> Lamont-Doherty Earth Observatory</p>
 <p class="my-2">This book grew out of a course developed at Columbia University called Research Computing in Earth Science. It was written mostly by Ryan Abernathey, with significant contributions from Kerry Key. By separating the book from the class, we hope to create an open-source community resource for python education<a class="modal-btn"> ... more</a> </p>
 </div>
 </div>
@@ -100,7 +100,7 @@ Resource Gallery
 <div class="content">
 <img src="_static/thumbnails/earth_env_data_science.png" class="modal-img" />
 <h3 class="display-3">An Introduction to Earth and Environmental Data Science</h3>
-<strong>Author:</strong> Kerry Key, Ryan Abernathey
+<strong>Author:</strong> Ryan Abernathey, Kerry Key
 <br/>
 <strong>Affiliation:</strong> Lamont-Doherty Earth Observatory
 <p class="my-2">This book grew out of a course developed at Columbia University called Research Computing in Earth Science. It was written mostly by Ryan Abernathey, with significant contributions from Kerry Key. By separating the book from the class, we hope to create an open-source community resource for python education in the Earth and Environmental Sciences.
@@ -1389,7 +1389,7 @@ Xarray is inspired by and borrows heavily from pandas, the popular data analysis
 <img src="_static/images/ebp-logo.png" class="gallery-thumbnail" />
 <div class="container">
 <a href="https://nbviewer.jupyter.org/github/ltauxe/Python-for-Earth-Science-Students/tree/master/" class="text-decoration-none"><h4 class="display-4 p-0">Python Programming for Earth Science Students</h4></a>
-<p class="card-subtitle"><strong>Author:</strong> <a href="mailto:hasefaw@ucsd.edu">Hanna Asefaw</a>, <a href="mailto:bcych@ucsd.edu">Brendan Cych</a>, <a href="mailto:[email protected]">Lisa Tauxe</a><br/><strong>Affiliation:</strong> <a href="https://scripps.ucsd.edu/">Scripps Institution of Oceanography</a></p>
+<p class="card-subtitle"><strong>Author:</strong> <a href="mailto:bcych@ucsd.edu">Brendan Cych</a>, <a href="mailto:hasefaw@ucsd.edu">Hanna Asefaw</a>, <a href="mailto:[email protected]">Lisa Tauxe</a><br/><strong>Affiliation:</strong> <a href="https://scripps.ucsd.edu/">Scripps Institution of Oceanography</a></p>
 <p class="my-2">Python Programming for Earth Science Students </p>
 </div>
 </div>
@@ -1722,7 +1722,7 @@ Xarray is inspired by and borrows heavily from pandas, the popular data analysis
 <img src="_static/thumbnails/ptss-jupyter.jpeg" class="gallery-thumbnail" />
 <div class="container">
 <a href="https://youtu.be/xSzXvwzFsDU" class="text-decoration-none"><h4 class="display-4 p-0">Python Tutorial Seminar Series - Jupyter Notebooks</h4></a>
-<p class="card-subtitle"><strong>Author:</strong> Project Pythia, Kevin Paul<br/><strong>Affiliation:</strong> <a href="https://ncar.ucar.edu/">NSF NCAR</a></p>
+<p class="card-subtitle"><strong>Author:</strong> Kevin Paul, Project Pythia<br/><strong>Affiliation:</strong> <a href="https://ncar.ucar.edu/">NSF NCAR</a></p>
 <p class="my-2">Recording from the Python Tutorial Seminar Series introducing JupyterLab and Jupyter Notebooks.
 </p>
 </div>
@@ -1834,7 +1834,7 @@ Xarray is inspired by and borrows heavily from pandas, the popular data analysis
 <img src="_static/thumbnails/ptss-cartopy.jpeg" class="gallery-thumbnail" />
 <div class="container">
 <a href="https://youtu.be/ivmd3RluMiw" class="text-decoration-none"><h4 class="display-4 p-0">Python Tutorial Seminar Series - Cartopy</h4></a>
-<p class="card-subtitle"><strong>Author:</strong> Project Pythia, Michaela Sizemore<br/><strong>Affiliation:</strong> <a href="https://ncar.ucar.edu/">NSF NCAR</a></p>
+<p class="card-subtitle"><strong>Author:</strong> Michaela Sizemore, Project Pythia<br/><strong>Affiliation:</strong> <a href="https://ncar.ucar.edu/">NSF NCAR</a></p>
 <p class="my-2">Recording from the Python Tutorial Seminar Series introducing the Python Package `cartopy`. The content to follow along with this video is hosted in this <A href="https://github.com/michaelavs/cartopy_tutorial">Cartopy Tutorial GitHub Repository</A>.
 </p>
 </div>
@@ -1864,7 +1864,7 @@ Xarray is inspired by and borrows heavily from pandas, the popular data analysis
 <img src="_static/thumbnails/ptss-git.png" class="gallery-thumbnail" />
 <div class="container">
 <a href="https://youtu.be/fYkPn0Nttlg" class="text-decoration-none"><h4 class="display-4 p-0">Python Tutorial Seminar Series - Git and GitHub</h4></a>
-<p class="card-subtitle"><strong>Author:</strong> Project Pythia, Kevin Paul<br/><strong>Affiliation:</strong> <a href="https://ncar.ucar.edu/">NSF NCAR</a></p>
+<p class="card-subtitle"><strong>Author:</strong> Kevin Paul, Project Pythia<br/><strong>Affiliation:</strong> <a href="https://ncar.ucar.edu/">NSF NCAR</a></p>
 <p class="my-2">Recording from the Python Tutorial Seminar Series introducing the tools Git and GitHub. The content to follow along with this tutorial is hosted in this <A href="https://github.com/NCAR/git-github-demo">Git and GitHub Demo GitHub Repository</A>.
 </p>
 </div>
@@ -1920,7 +1920,7 @@ Xarray is inspired by and borrows heavily from pandas, the popular data analysis
 <img src="_static/thumbnails/ptss-xarray1.jpeg" class="gallery-thumbnail" />
 <div class="container">
 <a href="https://youtu.be/Ss4ryKukhi4" class="text-decoration-none"><h4 class="display-4 p-0">Python Tutorial Seminar Series - Xarray Part 1</h4></a>
-<p class="card-subtitle"><strong>Author:</strong> Project Pythia, Anderson Banihirwe<br/><strong>Affiliation:</strong> <a href="https://ncar.ucar.edu/">NSF NCAR</a></p>
+<p class="card-subtitle"><strong>Author:</strong> Anderson Banihirwe, Project Pythia<br/><strong>Affiliation:</strong> <a href="https://ncar.ucar.edu/">NSF NCAR</a></p>
 <p class="my-2">Recording from the Python Tutorial Seminar Series introducing the Python Package `xarray`. This is the first lesson of a two part series. The content to follow along with this video is hosted in this <A href="https://github.com/andersy005/xarray-tutorial">Xarray Tutorial GitHub Repository</A>.
 </p>
 </div>
@@ -1948,7 +1948,7 @@ Xarray is inspired by and borrows heavily from pandas, the popular data analysis
 <img src="_static/thumbnails/ptss-xarray2.jpeg" class="gallery-thumbnail" />
 <div class="container">
 <a href="https://youtu.be/2H_4drBwORY" class="text-decoration-none"><h4 class="display-4 p-0">Python Tutorial Seminar Series - Xarray Part 2</h4></a>
-<p class="card-subtitle"><strong>Author:</strong> Project Pythia, Anderson Banihirwe<br/><strong>Affiliation:</strong> <a href="https://ncar.ucar.edu/">NSF NCAR</a></p>
+<p class="card-subtitle"><strong>Author:</strong> Anderson Banihirwe, Project Pythia<br/><strong>Affiliation:</strong> <a href="https://ncar.ucar.edu/">NSF NCAR</a></p>
 <p class="my-2">Recording from the Python Tutorial Seminar Series introducing the Python Package `xarray`. This is the second lesson of a two part series. The content to follow along with this video is hosted in this <A href="https://github.com/andersy005/xarray-tutorial">Xarray Tutorial GitHub Repository</A>.
 </p>
 </div>
@@ -1976,7 +1976,7 @@ Xarray is inspired by and borrows heavily from pandas, the popular data analysis
 <img src="_static/thumbnails/ptss-dask1.jpeg" class="gallery-thumbnail" />
 <div class="container">
 <a href="https://youtu.be/wn-QM6QUB_U" class="text-decoration-none"><h4 class="display-4 p-0">Python Tutorial Seminar Series - Dask Part 1</h4></a>
-<p class="card-subtitle"><strong>Author:</strong> Project Pythia, Anderson Banihirwe<br/><strong>Affiliation:</strong> <a href="https://ncar.ucar.edu/">NSF NCAR</a></p>
+<p class="card-subtitle"><strong>Author:</strong> Anderson Banihirwe, Project Pythia<br/><strong>Affiliation:</strong> <a href="https://ncar.ucar.edu/">NSF NCAR</a></p>
 <p class="my-2">Recording from the Python Tutorial Seminar Series introducing the Python Package `dask`. This is the first lesson of a two part series. The content to follow along with this video is hosted in this <A href="https://github.com/andersy005/xarray-tutorial">Xarray Tutorial GitHub Repository</A>.
 </p>
 </div>
@@ -2004,7 +2004,7 @@ Xarray is inspired by and borrows heavily from pandas, the popular data analysis
 <img src="_static/thumbnails/ptss-dask2.jpeg" class="gallery-thumbnail" />
 <div class="container">
 <a href="https://youtu.be/yn4_-1pHC5k" class="text-decoration-none"><h4 class="display-4 p-0">Python Tutorial Seminar Series - Dask Part 2</h4></a>
-<p class="card-subtitle"><strong>Author:</strong> Project Pythia, Anderson Banihirwe<br/><strong>Affiliation:</strong> <a href="https://ncar.ucar.edu/">NSF NCAR</a></p>
+<p class="card-subtitle"><strong>Author:</strong> Anderson Banihirwe, Project Pythia<br/><strong>Affiliation:</strong> <a href="https://ncar.ucar.edu/">NSF NCAR</a></p>
 <p class="my-2">Recording from the Python Tutorial Seminar Series introducing the Python Package `dask`. This is the second lesson of a two part series. The content to follow along with this video is hosted in this <A href="https://github.com/andersy005/xarray-tutorial">Xarray Tutorial GitHub Repository</A>.
 </p>
 </div>

_preview/451/cookbook-tasklist.html

@@ -435,7 +435,9 @@ <h1>Cookbook Author Checklist Template<a class="headerlink" href="#cookbook-auth
 <span class="w">    </span><span class="k">-</span><span class="w"> </span>Code errors in your notebooks themselves
 <span class="k">- [ ]</span> <span class="gs">**Identify a Maintainer team via GitHub handle(s) in this thread.**</span>
 This can be one or more people with availability to check in on this Cookbook, issue fixes to broken content, or with a vision for the future development of the Cookbook. This is typically (but not necessarily) one of the primary authors of the Cookbook.
-<span class="k">- [ ]</span> <span class="gs">**Finally, release your Cookbook!**</span>
+<span class="k">- [ ]</span> <span class="gs">**Link your Cookbook repo to Zenodo for DOI generation**</span>
+Follow steps 1-4 under [<span class="nt">Generate a DOI</span>](<span class="na">https://projectpythia.org/cookbook-guide.html#generate-a-doi</span>) in the Cookbook Guide. Return here for instructions on step 5, and your final step:
+<span class="k">- [ ]</span> <span class="gs">**Release your Cookbook!**</span>
 <span class="w">    </span><span class="k">-</span><span class="w"> </span>On the right-hand sidebar for your Cookbook repository, click “Create a new release”. If you don’t see this button, you may need to click on the “Releases” header first and “Create” or “Draft” a new release.
     ![<span class="nt">GitHub Repository sidebar section titled &quot;Releases&quot;</span>](<span class="na">https://raw.githubusercontent.com/ProjectPythia/projectpythia.github.io/main/portal/_static/images/4-releases.png &quot;Releases&quot;</span>)
 <span class="w">    </span><span class="k">-</span><span class="w"> </span>“Choose a tag”, enter a new tag name. This will be the git reference of the snapshot of code that represents this particular release of your Cookbook! We recommend using a name fitting the [<span class="nt">CalVer</span>](<span class="na">https://calver.org/</span>) scheme, so something like v2024.06.13 for the date of the release, then choose “+ Create new tag: &lt;your tag name&gt; on publish” and make its Target main (unless you have the knowledge and desire to release from another branch!)