{
 "cells": [
  {
   "cell_type": "raw",
   "id": "de773fab",
   "metadata": {},
   "source": [
    "---\n",
    "execute:\n",
    "  echo: false\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d3df6e7b",
   "metadata": {},
   "source": [
    "# a title\n",
    "> A description\n",
    "- key1: value1\n",
    "- key2: value2\n",
    "- categories: [c1, c2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "79d87f7d-9b49-4618-a254-98a04c566138",
   "metadata": {},
   "outputs": [],
   "source": [
    "#| hide\n",
    "#| default_exp foobar"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7746fc7d",
   "metadata": {},
   "source": [
    "some md"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "65751e43",
   "metadata": {},
   "outputs": [],
   "source": [
    "#| export\n",
    "import re"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fcebc8c3",
   "metadata": {},
   "outputs": [],
   "source": [
    "from nbdev.showdoc import show_doc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f791a06e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[94mhello\n"
     ]
    }
   ],
   "source": [
    "print('\\033[94mhello')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "54fe0b87",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "1+1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a744e0b7",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fb865f17",
   "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>a</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   a\n",
       "0  1\n",
       "1  2"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.DataFrame(dict(a=[1,2]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7181bbfc",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "933fef8f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 144x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#| notest\n",
    "plt.figure(figsize=(2,1))\n",
    "plt.plot([1,2]);"
   ]
  },
  {
   "attachments": {
    "image-2.png": {
     "image/png": "iVBORw0KGgoAAAANSUhEUgAAAEkAAABeCAYAAABvoDn/AAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAAFiUAABYlAUlSJPAAAARXSURBVHhe7ZxNKHxRFMAP2fgYJcqCfBQhRMpXQ1Hjo6woCx9JPsqGLCgbJUtl5aMkCyGJspkNWViQUqRmo5QpZDWUBWLh/eccd/z5x/xPM/fNNOP86vbOO/fV8Ht37jtv5r6JMNyA4JVItRW8IJIYiCQGIomBSGIgkhiIJAYiiYFIYiCSGHi9LYmIiFDR7+E7HV4lPT09qej3EBMTo6K/yNuNgUhiIJIYiCQGIomBSGIgkhiIJAYiiYFIYiCSGIgkBlolXVxcQEVFBcTGxlLDGHOBBO/X5+bmYGhoCJ6fn1XWP7RJOjo6guLiYnA4HCoDFGMO+wLFwcEBzM7Oqj09aJGEZ2x9fZ3i3t5ecLlc1DBGsE/XWf0JHEF4MkZHR+Hq6kpl9aBF0s3NDRwfH1NstVohOjqaGsYI9uExZvH4+Eijp7W1FVJTU6GwsFD16EGLpNPT04+3WVpaGm0RT4x9eIxZ2O12GBsbg56eHpienobk5GTVowctkpxOJ23xDCYlJVGMYOw5q55jzCAuLo5ETUxMgMViUVl9aJu4g0lTUxPU1tZCZKQ5/05YSDIbkcRAJDHQIikzM5O2eBXD+sgDxp6rnueYUESLpM+X/c+FnCfGK1xJSQnFoYgWSXjr4amuDw8PqbrGhjFSVlZGRV6ookUSVtdtbW0ULy0tUX2EDWME+/CYUEXbxF1ZWQnX19dgs9lU5v1tdnZ2Rn2hjKwF+AdZC+AjIomBSGIgkhiIJAYiiYFIYiCSGIgkBiKJgUhiIJIYiCQGIomB149KhHdkJDEQSQxEEgORxEAkMRBJDEQSA5HEQCQxEEkMRBIDkcTAFEl3d3fQ2NhIP76wtramsuaBy3yWl5ehpqaGXjMxMRHa29tpWbSO+3dTJM3Pz8POzo7aMxdc6D4yMgKDg4O0imV3dxcWFhbg/v4e6urqYGtrSx3pB/hRiU5WV1fx1H003DcTu91uWCwWY2VlxXh7e1NZw3h4eDC6uroMm81m3N7eqqxvaBtJOOQHBgags7NTZQIDPgWVm5sLpaWlX35bJT4+Hurr62Fvbw8uLy9V1je0SMI5qLm5mYZ5oBkeHqZnV3JyclRGP9rnpMnJSXqcKti8vLyQvKKioi+PcviCNkkJCQlwfn4O4+PjKhNccFHr5uYmLU/MyMhQWR9Rc5NW3CMpYBP3dzgcDqO8vNywWq2G0+lUWd8xpQQIJicnJ9DX10fx4uKi/6PITdhIcp9w2N/fh46ODoiKiqLl0Xl5earXP8JCEgra3t6G7u5uyMrKoio/Pz9f9fpPyEtCQRsbG9Df309PHmAZkp6ernr1EPKS8AEfLDuqq6thZmYGUlJSVI8+TPkGFy+/VVVVFLuvbjRPmMHr6yuVHFNTU1TpFxQUqJ6vtLS0QHZ2ttrzAZSkm0CVAC6Xy2hoaPh4rZ8a/j3+IGsBGIRdnWQGIomBSGIgkhiIJAYiiYFIYiCSGIgkBiLpvwD8AY69Z2/Cx/FwAAAAAElFTkSuQmCC"
    }
   },
   "cell_type": "markdown",
   "id": "5fd8b07a",
   "metadata": {},
   "source": [
    "My pic:\n",
    "![image-2.png](attachment:image-2.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "14481872",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "you will not be able to see this cell at all\n"
     ]
    }
   ],
   "source": [
    "#| hide\n",
    "print('you will not be able to see this cell at all')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b73a3841",
   "metadata": {},
   "outputs": [],
   "source": [
    "def show():\n",
    "    a = 2\n",
    "    b = 3 #|hide_line"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "27a4a82b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "hi\n",
      "CPU times: user 1.32 ms, sys: 165 µs, total: 1.48 ms\n",
      "Wall time: 881 µs\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "print('hi')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "89fd5aca",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "hi\n"
     ]
    }
   ],
   "source": [
    "%%bash\n",
    "echo hi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b7cdf5c6",
   "metadata": {},
   "outputs": [],
   "source": [
    "#| export\n",
    "def some_func(a=1): ..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "745d66d8-1669-411c-a7b4-c10ba6b096fd",
   "metadata": {},
   "outputs": [],
   "source": [
    "#| export\n",
    "def another_func(b): \n",
    "    \"A link in a docstring: `ModuleMaker`.\"\n",
    "    pass\n",
    "def and_another(c): ..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8c751591",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "---\n",
       "\n",
       "#### another_func\n",
       "\n",
       "> **`another_func`**` (b)`\n",
       "\n",
       "A link in a docstring: `ModuleMaker`."
      ],
      "text/plain": [
       "<nbdev.showdoc.BasicMarkdownRenderer>"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "show_doc(another_func) # should only appear once"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "be043747",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "A line\n",
      "Foobar baz FutureWarning blah\n",
      "zig zagMultiIndex zoom\n",
      "Another line.\n"
     ]
    }
   ],
   "source": [
    "#| filter_stream FutureWarning MultiIndex\n",
    "print('\\n'.join(['A line', 'Foobar baz FutureWarning blah', 'zig zagMultiIndex zoom', 'Another line.']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b02ef463",
   "metadata": {},
   "outputs": [],
   "source": [
    "def cool_func(a):\n",
    "    '''This cell has \"hidden\" metadata property'''\n",
    "    pass"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e06ecf02",
   "metadata": {},
   "source": [
    "# A heading to Hide -"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ee691141-b4d3-46ce-8a87-37e536276291",
   "metadata": {},
   "source": [
    "## Another! Heading -"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "03dfb7a0-bdc6-4d16-8b22-82495f7a302f",
   "metadata": {},
   "source": [
    "some words"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6788928c-3e21-4cbf-a44e-75fc2c71edfd",
   "metadata": {},
   "source": [
    "## Yet another heading to hide. -"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "84e4bb08-ffe9-405a-9da6-606f90bb0d3b",
   "metadata": {},
   "source": [
    "This is a link to `numpy.array` and to `ModuleMaker` but not a link to `foobar`.\n",
    "And not a link to <code>dict2nb</code>."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "46c80afd",
   "metadata": {},
   "outputs": [],
   "source": [
    "#| exporti\n",
    "class a(Exception): ..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bdd3f149",
   "metadata": {},
   "outputs": [],
   "source": [
    "#| exports\n",
    "class b(a): ..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bd2f67a1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "__main__.b()"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "516a8282",
   "metadata": {},
   "outputs": [],
   "source": [
    "%%ai 0\n",
    "This is a test."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1c22aa7d",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.11.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}