From 2af73b3d7e97c57e0f8401e1b2e3c2e4b1cdf8a1 Mon Sep 17 00:00:00 2001
From: Xin <xin@imfing.com>
Date: Sat, 14 Sep 2024 14:29:55 +0100
Subject: [PATCH] feat: shortcode for Jupyter Notebook (#337)

* feat: shortcode for Jupyter Notebook

* chore: update generated CSS files

* chore: add example Jupyter Notebook file

* chore: update doc

* chore: enhance jupyter notebook styling

- use raw markdown for contents like code block and markdown text

* feat: support load notebook from assets and remote

- update docs accordingly
- add example notebook file

* chore: rename example file
---
 assets/css/compiled/main.css                  |  12 +-
 assets/css/components/jupyter.css             |  29 +++
 assets/css/components/scrollbar.css           |   2 +-
 data/icons.yaml                               |   2 +
 exampleSite/assets/example.ipynb              | 224 ++++++++++++++++++
 .../content/docs/guide/shortcodes/_index.md   |   1 +
 .../content/docs/guide/shortcodes/jupyter.md  |  79 ++++++
 exampleSite/hugo_stats.json                   |   4 +
 layouts/partials/scripts.html                 |   6 +
 layouts/shortcodes/jupyter.html               |  81 +++++++
 10 files changed, 433 insertions(+), 7 deletions(-)
 create mode 100644 assets/css/components/jupyter.css
 create mode 100644 exampleSite/assets/example.ipynb
 create mode 100644 exampleSite/content/docs/guide/shortcodes/jupyter.md
 create mode 100644 layouts/shortcodes/jupyter.html

diff --git a/assets/css/compiled/main.css b/assets/css/compiled/main.css
index 1a63ece0..76d980eb 100644
--- a/assets/css/compiled/main.css
+++ b/assets/css/compiled/main.css
@@ -2532,30 +2532,30 @@ nav .search-wrapper {
 .hamburger-menu svg.open > g:nth-of-type(2) path {
         transform: translate3d(0, -4px, 0);
       }
-.hextra-scrollbar {
+.hextra-scrollbar, .hextra-scrollbar * {
   scrollbar-width: thin; /* Firefox */
   scrollbar-color: oklch(55.55% 0 0 / 40%) transparent; /* Firefox */
 
   scrollbar-gutter: stable;
 }
-.hextra-scrollbar::-webkit-scrollbar {
+.hextra-scrollbar::-webkit-scrollbar, .hextra-scrollbar *::-webkit-scrollbar {
   height: 0.75rem;
   width: 0.75rem;
 }
-.hextra-scrollbar::-webkit-scrollbar-track {
+.hextra-scrollbar::-webkit-scrollbar-track, .hextra-scrollbar *::-webkit-scrollbar-track {
   background-color: transparent;
 }
-.hextra-scrollbar::-webkit-scrollbar-thumb {
+.hextra-scrollbar::-webkit-scrollbar-thumb, .hextra-scrollbar *::-webkit-scrollbar-thumb {
   border-radius: 10px;
 }
-.hextra-scrollbar:hover::-webkit-scrollbar-thumb {
+.hextra-scrollbar:hover::-webkit-scrollbar-thumb, .hextra-scrollbar *:hover::-webkit-scrollbar-thumb {
     border: 3px solid transparent;
     background-color: var(--tw-shadow-color);
     background-clip: content-box;
     --tw-shadow-color: rgb(115 115 115 / 0.2);
     --tw-shadow: var(--tw-shadow-colored);
   }
-.hextra-scrollbar:hover::-webkit-scrollbar-thumb:hover {
+.hextra-scrollbar:hover::-webkit-scrollbar-thumb:hover, .hextra-scrollbar *:hover::-webkit-scrollbar-thumb:hover {
   --tw-shadow-color: rgb(115 115 115 / 0.4);
   --tw-shadow: var(--tw-shadow-colored);
 }
diff --git a/assets/css/components/jupyter.css b/assets/css/components/jupyter.css
new file mode 100644
index 00000000..4a21fb24
--- /dev/null
+++ b/assets/css/components/jupyter.css
@@ -0,0 +1,29 @@
+.hextra-jupyter-code-cell {
+  scrollbar-gutter: auto;
+
+  @apply hx-mt-6;
+
+  .hextra-jupyter-code-cell-source {
+    @apply hx-text-sm;
+    .chroma,
+    pre {
+      @apply hx-m-0;
+    }
+  }
+
+  .hextra-jupyter-code-cell-outputs-container {
+    @apply hx-text-xs hx-overflow-hidden hx-border hx-border-t-0 hx-rounded-b-xl dark:hx-border-neutral-800;
+
+    .hextra-jupyter-code-cell-outputs {
+      @apply hx-overflow-auto hx-max-h-[50vh];
+
+      pre {
+        @apply hx-p-4;
+      }
+    }
+  }
+}
+
+.hextra-jupyter-code-cell:has(.hextra-jupyter-code-cell-outputs) .hextra-jupyter-code-cell-source .chroma {
+  @apply hx-rounded-b-none;
+}
diff --git a/assets/css/components/scrollbar.css b/assets/css/components/scrollbar.css
index 7dc75e90..6699375e 100644
--- a/assets/css/components/scrollbar.css
+++ b/assets/css/components/scrollbar.css
@@ -1,4 +1,4 @@
-.hextra-scrollbar {
+.hextra-scrollbar, .hextra-scrollbar * {
   scrollbar-width: thin; /* Firefox */
   scrollbar-color: oklch(55.55% 0 0 / 40%) transparent; /* Firefox */
 
diff --git a/data/icons.yaml b/data/icons.yaml
index 841ac0ed..3138d480 100644
--- a/data/icons.yaml
+++ b/data/icons.yaml
@@ -36,6 +36,8 @@ hugo-full: >
     <path fill="#fff" d="M1320.72 89.15c58.79 0 106.52 47.73 106.52 106.51 0 58.8-47.73 106.52-106.52 106.52-58.78 0-106.52-47.73-106.52-106.52 0-58.78 47.74-106.51 106.52-106.51zm0 39.57c36.95 0 66.94 30 66.94 66.94a66.97 66.97 0 0 1-66.94 66.94c-36.95 0-66.94-29.99-66.94-66.94a66.97 66.97 0 0 1 66.93-66.94h.01zm-283.8 65.31c0 47.18-8.94 60.93-26.81 80.58-17.87 19.65-41.57 27.57-71.1 27.57-27 0-48.75-9.58-67.61-26.23-20.88-18.45-36.08-47.04-36.08-78.95 0-31.37 11.72-58.48 32.49-78.67 18.22-17.67 45.34-29.18 73.3-29.18 33.77 0 68.83 15.98 90.44 47.53l-31.73 26.82c-13.45-25.03-32.94-33.46-60.82-34.26-30.83-.88-64.77 28.53-62.25 67.75 1.4 21.94 11.65 59.65 60.96 66.57 25.9 3.63 55.36-24.02 55.36-39.04H944.4v-37.5h92.5V194l.02.03zm-562.6-94.65h42.29v112.17c0 17.8.49 29.33 1.47 34.61 1.69 8.48 4.81 14.37 11.17 19.5 6.37 5.13 13.8 6.59 24.84 6.59 11.2 0 14.96-1.74 20.66-6.6 5.69-4.85 9.12-9.46 10.28-16.53 1.15-7.07 3.07-18.8 3.07-35.18V99.38h42.28v108.78c0 24.86-1.07 42.43-3.21 52.69-2.14 10.27-6.08 18.93-11.82 26-5.74 7.06-13.42 12.69-23.03 16.88-9.62 4.19-22.16 6.28-37.65 6.28-18.7 0-32.87-2.28-42.52-6.85-9.66-4.57-17.3-10.5-22.9-17.8-5.61-7.3-9.3-14.95-11.08-22.96-2.58-11.86-3.88-29.38-3.88-52.55V99.38h.03zM93.91 299.92V92.7h43.35v75.48h71.92V92.7h43.48v207.22h-43.48v-90.61h-71.92v90.61z"/>
   </svg>
 
+jupyter: <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path fill="currentColor" d="M7.157 22.201A1.784 1.799 0 0 1 5.374 24a1.784 1.799 0 0 1-1.784-1.799a1.784 1.799 0 0 1 1.784-1.799a1.784 1.799 0 0 1 1.783 1.799M20.582 1.427a1.415 1.427 0 0 1-1.415 1.428a1.415 1.427 0 0 1-1.416-1.428A1.415 1.427 0 0 1 19.167 0a1.415 1.427 0 0 1 1.415 1.427M4.992 3.336A1.047 1.056 0 0 1 3.946 4.39a1.047 1.056 0 0 1-1.047-1.055A1.047 1.056 0 0 1 3.946 2.28a1.047 1.056 0 0 1 1.046 1.056m7.336 1.517c3.769 0 7.06 1.38 8.768 3.424a9.36 9.36 0 0 0-3.393-4.547a9.24 9.24 0 0 0-5.377-1.728A9.24 9.24 0 0 0 6.95 3.73a9.36 9.36 0 0 0-3.394 4.547c1.713-2.04 5.004-3.424 8.772-3.424m.001 13.295c-3.768 0-7.06-1.381-8.768-3.425a9.36 9.36 0 0 0 3.394 4.547A9.24 9.24 0 0 0 12.33 21a9.24 9.24 0 0 0 5.377-1.729a9.36 9.36 0 0 0 3.393-4.547c-1.712 2.044-5.003 3.425-8.772 3.425Z" /></svg>
+
 warning: <svg xmlns="http://www.w3.org/2000/svg" fill="none" stroke="currentColor" stroke-width="1.5" viewBox="0 0 24 24"><path stroke-linecap="round" stroke-linejoin="round" d="M12 9v3.75m-9.303 3.376c-.866 1.5.217 3.374 1.948 3.374h14.71c1.73 0 2.813-1.874 1.948-3.374L13.949 3.378c-.866-1.5-3.032-1.5-3.898 0L2.697 16.126zM12 15.75h.007v.008H12v-.008z"></path></svg>
 one: <svg xmlns="http://www.w3.org/2000/svg" fill="currentColor" viewBox="-1 0 19 19"><path d="M16.417 9.6A7.917 7.917 0 1 1 8.5 1.683 7.917 7.917 0 0 1 16.417 9.6zM9.666 6.508H8.248L6.09 8.09l.806 1.103 1.222-.945v4.816h1.547z"></path></svg>
 cards: <svg xmlns="http://www.w3.org/2000/svg" fill="none" stroke="currentColor" stroke-width="1.5" viewBox="0 0 24 24"><path stroke-linecap="round" stroke-linejoin="round" d="M6 6.878V6a2.25 2.25 0 0 1 2.25-2.25h7.5A2.25 2.25 0 0 1 18 6v.878m-12 0c.235-.083.487-.128.75-.128h10.5c.263 0 .515.045.75.128m-12 0A2.25 2.25 0 0 0 4.5 9v.878m13.5-3A2.25 2.25 0 0 1 19.5 9v.878m0 0a2.246 2.246 0 0 0-.75-.128H5.25c-.263 0-.515.045-.75.128m15 0A2.25 2.25 0 0 1 21 12v6a2.25 2.25 0 0 1-2.25 2.25H5.25A2.25 2.25 0 0 1 3 18v-6c0-.98.626-1.813 1.5-2.122"></path></svg>
diff --git a/exampleSite/assets/example.ipynb b/exampleSite/assets/example.ipynb
new file mode 100644
index 00000000..b196ee55
--- /dev/null
+++ b/exampleSite/assets/example.ipynb
@@ -0,0 +1,224 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### What is the Jupyter Notebook?\n",
+    "\n",
+    "The Jupyter Notebook is an **interactive computing environment** that enables users to author notebook documents that include:\n",
+    "- Live code\n",
+    "- Interactive widgets\n",
+    "- Plots\n",
+    "- Narrative text\n",
+    "- Equations\n",
+    "- Images\n",
+    "- Video\n",
+    "\n",
+    "These documents provide a **complete and self-contained record of a computation** that can be converted to various formats and shared with others using email, version control systems (like Git/[GitHub](https://github.com)) or [nbviewer.jupyter.org](https://nbviewer.jupyter.org)."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Data Visualization\n",
+    "\n",
+    "Below is an example of a simple data visualization using the Seaborn library."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Matplotlib is building the font cache; this may take a moment.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<seaborn.axisgrid.FacetGrid at 0x12830caa0>"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1105.12x500 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Import seaborn\n",
+    "import seaborn as sns\n",
+    "\n",
+    "# Apply the default theme\n",
+    "sns.set_theme()\n",
+    "\n",
+    "# Load an example dataset\n",
+    "tips = sns.load_dataset(\"tips\")\n",
+    "\n",
+    "# Create a visualization\n",
+    "sns.relplot(\n",
+    "    data=tips,\n",
+    "    x=\"total_bill\", y=\"tip\", col=\"time\",\n",
+    "    hue=\"smoker\", style=\"smoker\", size=\"size\",\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>total_bill</th>\n",
+       "      <th>tip</th>\n",
+       "      <th>sex</th>\n",
+       "      <th>smoker</th>\n",
+       "      <th>day</th>\n",
+       "      <th>time</th>\n",
+       "      <th>size</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>16.99</td>\n",
+       "      <td>1.01</td>\n",
+       "      <td>Female</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Dinner</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>10.34</td>\n",
+       "      <td>1.66</td>\n",
+       "      <td>Male</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Dinner</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>21.01</td>\n",
+       "      <td>3.50</td>\n",
+       "      <td>Male</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Dinner</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>23.68</td>\n",
+       "      <td>3.31</td>\n",
+       "      <td>Male</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Dinner</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>24.59</td>\n",
+       "      <td>3.61</td>\n",
+       "      <td>Female</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Dinner</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   total_bill   tip     sex smoker  day    time  size\n",
+       "0       16.99  1.01  Female     No  Sun  Dinner     2\n",
+       "1       10.34  1.66    Male     No  Sun  Dinner     3\n",
+       "2       21.01  3.50    Male     No  Sun  Dinner     3\n",
+       "3       23.68  3.31    Male     No  Sun  Dinner     2\n",
+       "4       24.59  3.61  Female     No  Sun  Dinner     4"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tips.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Equations\n",
+    "\n",
+    "The following is an example of a simple equation using LaTeX.\n",
+    "\n",
+    "$$\n",
+    "E = mc^2\n",
+    "$$"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": ".venv",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/exampleSite/content/docs/guide/shortcodes/_index.md b/exampleSite/content/docs/guide/shortcodes/_index.md
index 1ecaab97..e5945636 100644
--- a/exampleSite/content/docs/guide/shortcodes/_index.md
+++ b/exampleSite/content/docs/guide/shortcodes/_index.md
@@ -24,5 +24,6 @@ Hextra provides a collection of beautiful shortcodes to enhance your content.
 Additional shortcodes provided by Hugo and Hextra:
 
 {{< cards >}}
+  {{< card link="jupyter" title="Jupyter Notebook" icon="jupyter" tag="alpha" >}}
   {{< card link="others" title="Others" icon="view-grid" >}}
 {{< /cards >}}
diff --git a/exampleSite/content/docs/guide/shortcodes/jupyter.md b/exampleSite/content/docs/guide/shortcodes/jupyter.md
new file mode 100644
index 00000000..83487d7f
--- /dev/null
+++ b/exampleSite/content/docs/guide/shortcodes/jupyter.md
@@ -0,0 +1,79 @@
+---
+title: "Jupyter Notebook Component"
+linktitle: "Jupyter Notebook"
+math: true
+sidebar:
+  exclude: true
+---
+
+{{< callout >}}Experimental feature to include Jupyter Notebooks via a shortcode. Note that not all cell types are supported.{{< /callout >}}
+
+[Jupyter Notebook](https://jupyter.org/) is a language-agnostic HTML notebook application for [Project Jupyter](https://jupyter.org/). It allows you to create and share documents that contain live code, equations, visualizations, and narrative text.
+
+<!--more-->
+
+## How to use
+
+### Using a local notebook
+
+To use the Jupyter Notebook shortcode, you need to have a Jupyter Notebook file in your project. Similar to how you would [add images](../../organize-files#add-images) to the project, you can add Jupyter Notebooks to the `assets` folder.
+
+{{< filetree/container >}}
+  {{< filetree/folder name="assets" >}}
+    {{< filetree/file name="notebook.ipynb" >}}
+  {{< /filetree/folder >}}
+  {{< filetree/folder name="content" >}}
+    {{< filetree/folder name="docs" >}}
+        {{< filetree/file name="my-page.md" >}}
+    {{< /filetree/folder >}}
+  {{< /filetree/folder >}}
+{{< /filetree/container >}}
+
+Include the Jupyter Notebook in the page using the `jupyter` shortcode:
+
+```markdown {filename="content/docs/my-page.md"}
+---
+title: My Page
+math: true
+---
+
+{{%/* jupyter "notebook.ipynb" */%}}
+```
+
+Alternatively, you can utilize the [page bundles][page-bundles] feature of Hugo to organize the Jupyter Notebooks together with the Markdown file.
+
+{{< filetree/container >}}
+  {{< filetree/folder name="content" >}}
+    {{< filetree/folder name="docs" >}}
+        {{< filetree/folder name="my-page" >}}
+            {{< filetree/file name="index.md" >}}
+            {{< filetree/file name="notebook.ipynb" >}}
+        {{< /filetree/folder >}}
+    {{< /filetree/folder >}}
+  {{< /filetree/folder >}}
+{{< /filetree/container >}}
+
+```markdown {filename="content/docs/my-page/index.md"}
+---
+title: My Page
+math: true
+---
+
+{{%/* jupyter "notebook.ipynb" */%}}
+```
+
+### Using a remote notebook
+
+You can also use a remote notebook by providing the URL to the notebook file. For example, to include [What is the Jupyter Notebook](https://github.com/jupyter/notebook/blob/main/docs/source/examples/Notebook/What%20is%20the%20Jupyter%20Notebook.ipynb) notebook in the page, you can use the following shortcode:
+
+```
+{{%/* jupyter "https://raw.githubusercontent.com/jupyter/notebook/main/docs/source/examples/Notebook/What%20is%20the%20Jupyter%20Notebook.ipynb" */%}}
+```
+
+## Example Notebook
+
+{{< callout type="info" >}}The following is an example of a notebook file that is included in the project assets folder.{{< /callout >}}
+
+{{% jupyter "example.ipynb" %}}
+
+[page-bundles]: https://gohugo.io/content-management/page-bundles/#leaf-bundles
diff --git a/exampleSite/hugo_stats.json b/exampleSite/hugo_stats.json
index 2003dd80..c1429ece 100644
--- a/exampleSite/hugo_stats.json
+++ b/exampleSite/hugo_stats.json
@@ -191,6 +191,7 @@
       "data-[state=selected]:hx-block",
       "data-[state=selected]:hx-border-primary-500",
       "data-[state=selected]:hx-text-primary-600",
+      "dataframe",
       "filename",
       "first:hx-mt-0",
       "focus:hx-bg-white",
@@ -222,6 +223,9 @@
       "hextra-filetree",
       "hextra-filetree-folder",
       "hextra-footer",
+      "hextra-jupyter-code-cell",
+      "hextra-jupyter-code-cell-outputs",
+      "hextra-jupyter-code-cell-outputs-container",
       "hextra-pdf",
       "hextra-scrollbar",
       "hextra-sidebar-collapsible-button",
diff --git a/layouts/partials/scripts.html b/layouts/partials/scripts.html
index dbb4fe43..026b3445 100644
--- a/layouts/partials/scripts.html
+++ b/layouts/partials/scripts.html
@@ -60,12 +60,18 @@
   {{- end -}}
   <script>
     // TODO: make render options configurable
+    // Reference: https://katex.org/docs/autorender#api
     document.addEventListener("DOMContentLoaded", function () {
       renderMathInElement(document.body, {
         delimiters: [
           { left: "$$", right: "$$", display: true },
           { left: "$", right: "$", display: false },
           { left: "\\(", right: "\\)", display: false },
+          { left: "\\begin{equation}", right: "\\end{equation}", display: true },
+          {left: "\\begin{align}", right: "\\end{align}", display: true},
+          {left: "\\begin{alignat}", right: "\\end{alignat}", display: true},
+          {left: "\\begin{gather}", right: "\\end{gather}", display: true},
+          {left: "\\begin{CD}", right: "\\end{CD}", display: true},
           { left: "\\[", right: "\\]", display: true },
         ],
         throwOnError: false,
diff --git a/layouts/shortcodes/jupyter.html b/layouts/shortcodes/jupyter.html
new file mode 100644
index 00000000..a9f5209d
--- /dev/null
+++ b/layouts/shortcodes/jupyter.html
@@ -0,0 +1,81 @@
+{{/* Render Jupyter Notebook */}}
+{{- $path := .Get 0 -}}
+{{- $data := "" -}}
+{{- $page := .Page -}}
+
+{{- $isLocal := not (urls.Parse $path).Scheme -}}
+{{- $isPage := and (eq .Page.Kind "page") (not .Page.BundleType) -}}
+
+{{/* https://gohugo.io/functions/transform/unmarshal/ */}}
+{{- if (not $isLocal) -}}
+  {{- with resources.GetRemote $path -}}
+    {{- with unmarshal .Content -}}{{- $data = . -}}{{- end -}}
+  {{- else -}}
+    {{- errorf "Remote resource not found: %s" $path -}}
+  {{- end -}}
+{{- else if (not $isPage) -}}
+  {{- with .Page.Resources.Get $path -}}
+    {{- with unmarshal .Content -}}{{- $data = . -}}{{- end -}}
+  {{- else -}}
+    {{- errorf "Local resource not found: %s" $path -}}
+  {{- end -}}
+{{- else -}}
+  {{- with resources.Get $path -}}
+    {{- with unmarshal .Content -}}{{- $data = . -}}{{- end -}}
+  {{- else -}}
+    {{- errorf "Local resource not found: %s" $path -}}
+  {{- end -}}
+{{- end -}}
+
+{{- $language := index $data "metadata" "language_info" "name" | default "python" -}}
+
+{{- with index $data "cells" -}}
+  {{- range $cell := . -}}
+    {{- if eq (index $cell "cell_type") "code" -}}
+      {{- $source := index $cell "source" -}}
+      {{- $sourceContent := (cond (reflect.IsSlice $source) (delimit $source "") $source) -}}
+{{- with ($sourceContent | strings.Chomp) -}}
+{{ (printf "\n\n```%s\n%s\n```\n" $language .) | safeHTML -}}
+{{- end -}}
+
+      <div class="hextra-jupyter-code-cell hextra-scrollbar">
+        {{- $outputs := index $cell "outputs" -}}
+        {{- with $outputs -}}
+          <div class="hextra-jupyter-code-cell-outputs-container">
+            <div class="hextra-jupyter-code-cell-outputs">
+              {{- range $output := . -}}
+                {{- if eq (index $output "output_type") "display_data" -}}
+                  {{- $data := index $output "data" -}}
+                  {{- $image := index $data "image/png" -}}
+                  {{- if $image -}}
+                    <img src="data:image/png;base64,{{- $image -}}" alt="image" />
+                  {{- end -}}
+                {{- else if eq (index $output "output_type") "stream" -}}
+                  {{- $text := index $output "text" -}}
+                  {{- $textContent := (cond (reflect.IsSlice $text) (delimit $text "") $text) -}}
+                  <pre class="not-prose hx-text-sm">{{- $textContent -}}</pre>
+                {{- else if eq (index $output "output_type") "execute_result" -}}
+                  {{- $data := index $output "data" -}}
+                  {{- $text := index $data "text/plain" -}}
+                  {{- $textContent := (cond (reflect.IsSlice $text) (delimit $text "") $text) -}}
+                  <pre class="not-prose hx-text-sm">{{- $textContent -}}</pre>
+                  {{- $html := index $data "text/html" -}}
+                  {{- if $html -}}
+                    {{- $htmlText := delimit $html "" -}}
+                    <div>
+                      {{- $htmlText | safeHTML -}}
+                    </div>
+                  {{- end -}}
+                {{- end -}}
+              {{- end -}}
+            </div>
+          </div>
+        {{- end -}}
+      </div>
+    {{- else if eq (index $cell "cell_type") "markdown" -}}
+        {{- $source := index $cell "source" }}
+        {{- $sourceContent := (cond (reflect.IsSlice $source) (delimit $source "") $source) }}
+{{ (printf "\n%s\n" $sourceContent) | safeHTML }}
+    {{- end -}}
+  {{- end -}}
+{{- end -}}