Moved examples to separate repo, added new notebook for testing purpo…

…ses.
JanPalasek · Jul 10, 2022 · 15de24e · 15de24e
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diff --git a/README.md b/README.md
@@ -32,7 +32,7 @@ To unlock the full potential of Pretty Jupyter, see [the customization section](
 ## Documentation
 
 - [Documentation for Pretty Jupyter](https://github.com/JanPalasek/pretty-jupyter/wiki).
-- Examples on GitHub: Can be found in the directory `examples`.
+- [Examples](https://github.com/JanPalasek/pretty-jupyter-examples).
 
 ## Dev Installation
 ```sh

diff --git a/examples/demo.html b/examples/demo.html
diff --git a/examples/demo.ipynb b/examples/demo.ipynb
diff --git a/tests/fixture/basic.ipynb b/tests/fixture/basic.ipynb
diff --git a/tests/fixture/notebook.ipynb b/tests/fixture/notebook.ipynb
@@ -0,0 +1,354 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%load_ext pretty_jupyter"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/markdown": [
+       "\n",
+       "# Introduction\n",
+       "\n",
+       "The purpose of this notebook is only to test functionality of the Pretty Jupyter.\n",
+       "\n",
+       "# Chapter 1: Tabs\n",
+       "<span class='pretty-jupyter-token tabset tabset-pills' style='display: none;'></span>\n",
+       "\n",
+       "First we will test tabsets together with maths. We can clearly see that no math symbol is leaking.\n",
+       "\n",
+       "## Tab 1\n",
+       "\n",
+       "First tab.\n",
+       "\n",
+       "## Tab 2\n",
+       "\n",
+       "Second tab. This tab contains some math symbols, such as inline math: $a = 5$.\n",
+       "\n",
+       "Another symbol:\n",
+       "\n",
+       "$$a \\cdot a^2 = \\frac{a^5}{a^2} = a^3 = 125$$\n",
+       "\n",
+       "## Tab 3\n",
+       "\n",
+       "Tab 3."
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "execution_count": 65,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%%jinja markdown\n",
+    "\n",
+    "# Introduction\n",
+    "\n",
+    "The purpose of this notebook is only to test functionality of the Pretty Jupyter.\n",
+    "\n",
+    "# Chapter 1: Tabs\n",
+    "[//]: <> (-.- tabset tabset-pills)\n",
+    "\n",
+    "First we will test tabsets together with maths. We can clearly see that no math symbol is leaking.\n",
+    "\n",
+    "## Tab 1\n",
+    "\n",
+    "First tab.\n",
+    "\n",
+    "## Tab 2\n",
+    "\n",
+    "Second tab. This tab contains some math symbols, such as inline math: $a = 5$.\n",
+    "\n",
+    "Another symbol:\n",
+    "\n",
+    "$$a \\cdot a^2 = \\frac{a^5}{a^2} = a^3 = 125$$\n",
+    "\n",
+    "## Tab 3\n",
+    "\n",
+    "Tab 3."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/markdown": [
+       "\n",
+       "# Chapter 2: Jinja Markdown\n",
+       "\n",
+       "Jinja Markdown is a great way how to combine variables together with Markdown."
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%%jinja markdown\n",
+    "\n",
+    "# Chapter 2: Jinja Markdown\n",
+    "\n",
+    "Jinja Markdown is a great way how to combine variables together with Markdown."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "data = pd.DataFrame({\n",
+    "    \"A\": [1, 2, 3, 4],\n",
+    "    \"B\": [\"One\", \"Two\", \"Three\", \"Four\"]\n",
+    "})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/markdown": [
+       "\n",
+       "Using Jinja Markdown, we can show the table as part of our markdown text:\n",
+       "\n",
+       "<details>\n",
+       "\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>A</th>\n",
+       "      <th>B</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>One</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>Two</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>Three</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>Four</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "\n",
+       "</details>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "execution_count": 49,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%%jinja markdown\n",
+    "\n",
+    "Using Jinja Markdown, we can show the table as part of our markdown text:\n",
+    "\n",
+    "<details>\n",
+    "\n",
+    "{{ data.to_html() }}\n",
+    "\n",
+    "</details>"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "a = 10"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/markdown": [
+       "\n",
+       "We can also combine variables and math symbols thanks to Jinja Markdown and create more complex expressions, such as the following:\n",
+       "\n",
+       "\n",
+       "<details>\n",
+       "\n",
+       "$$\n",
+       "\n",
+       "\\begin{align}\n",
+       "\n",
+       "a &= 10 \\\\\n",
+       "\\frac{a^{10}}{a^8} &= \\frac{ 10^{10} }{ 10^8 } \\\\\n",
+       "\\frac{ 10^{10} }{ 10^8 } &= 10^{2} \\\\\n",
+       "10^{2} &= 100 \\\\\n",
+       "\n",
+       "\\end{align}\n",
+       "$$\n",
+       "\n",
+       "</details>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "execution_count": 66,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%%jinja markdown\n",
+    "\n",
+    "We can also combine variables and math symbols thanks to Jinja Markdown and create more complex expressions, such as the following:\n",
+    "\n",
+    "\n",
+    "<details>\n",
+    "\n",
+    "$$\n",
+    "\n",
+    "\\begin{align}\n",
+    "\n",
+    "a &= {{a}} \\\\\n",
+    "\\frac{a^{10}}{a^8} &= \\frac{ {{a}}^{10} }{ {{a}}^8 } \\\\\n",
+    "\\frac{ {{a}}^{10} }{ {{a}}^8 } &= {{a}}^{2} \\\\\n",
+    "{{a}}^{2} &= {{ a ** 2 }} \\\\\n",
+    "\n",
+    "\\end{align}\n",
+    "$$\n",
+    "\n",
+    "</details>"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns\n",
+    "sns.set_theme()\n",
+    "\n",
+    "import base64\n",
+    "from io import BytesIO\n",
+    "\n",
+    "IMG_FORMAT = r\"<img src='data:image/png;base64,{encoded}'>'\"\n",
+    "\n",
+    "tmpfile = BytesIO()\n",
+    "\n",
+    "fig, ax = plt.subplots()\n",
+    "sns.countplot(x=data[\"A\"], ax=ax).set(title=\"Example Figure\")\n",
+    "fig.savefig(tmpfile, format=\"png\")\n",
+    "plt.close()\n",
+    "\n",
+    "encoded = IMG_FORMAT.format(encoded=base64.b64encode(tmpfile.getvalue()).decode('utf-8'))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 64,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/markdown": [
+       "\n",
+       "We can even include matplotlib figures in-between our markdown, although this is a bit hardcore.\n",
+       "\n",
+       "**Watch this:**\n",
+       "\n",
+       "<img src='data:image/png;base64,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'>'"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "execution_count": 64,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%%jinja markdown\n",
+    "\n",
+    "We can even include matplotlib figures in-between our markdown, although this is a bit hardcore.\n",
+    "\n",
+    "**Watch this:**\n",
+    "\n",
+    "{{ encoded }}\n",
+    "\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "code_folding": "show",
+  "kernelspec": {
+   "display_name": "Python 3.9.13 ('venv': 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": "3.9.13"
+  },
+  "orig_nbformat": 4,
+  "vscode": {
+   "interpreter": {
+    "hash": "bcd7e97cf71e998a93ec80db15725ed4a4806c1de3630361ecb7124b538cb899"
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/tests/test_cli.py b/tests/test_cli.py
@@ -5,7 +5,7 @@
 
 @pytest.fixture
 def input_path():
-    return "tests/fixture/basic.ipynb"
+    return "tests/fixture/notebook.ipynb"
 
 
 def test_nbconvert(input_path, tmpdir):