tools/tests/Confined Output.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#  Test notebook for overflowing content"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "markdown image:\n",
    "\n",
    "<img src=\"http://placehold.it/800x200.png\">\n",
    "\n",
    "unconfined markdown image:\n",
    "\n",
    "<img src=\"http://placehold.it/800x200.png\" class=\"unconfined\">"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from IPython.display import Image, IFrame"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Overflow image in HTML (non-embedded)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<img src=\"http://placehold.it/800x200.png\"   />"
      ],
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Image(url=\"http://placehold.it/800x200.png\", embed=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Overflow image:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAyAAAADIBAMAAADioZgpAAAAG1BMVEXMzMyWlpbFxcWxsbGjo6Oc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\nLzkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Image(url=\"http://placehold.it/800x200.png\", embed=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Overflow, unconfined"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAyAAAADIBAMAAADioZgpAAAAG1BMVEXMzMyWlpbFxcWxsbGjo6Oc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\nLzkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 4,
     "metadata": {
      "image/png": {
       "unconfined": true
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Image(url=\"http://placehold.it/800x200.png\", embed=True, unconfined=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Overflow with explicit height, width (retina):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 5,
     "metadata": {
      "image/jpeg": {
       "height": 100,
       "width": 900
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Image(url=\"http://placehold.it/1800x200.jpg\", embed=True, retina=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Overflowing IFrame:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "        <iframe\n",
       "            width=\"900\"\n",
       "            height=\"400\"\n",
       "            src=\"https://ipython.org\"\n",
       "            frameborder=\"0\"\n",
       "            allowfullscreen\n",
       "        ></iframe>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.lib.display.IFrame at 0x105239dd8>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "IFrame(src=\"https://ipython.org\", width=900, height=400)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Overflowing table:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>10</th>\n",
       "      <th>11</th>\n",
       "      <th>12</th>\n",
       "      <th>13</th>\n",
       "      <th>14</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td> column</td>\n",
       "      <td> column</td>\n",
       "      <td> column</td>\n",
       "      <td> column</td>\n",
       "      <td> column</td>\n",
       "      <td> column</td>\n",
       "      <td> column</td>\n",
       "      <td> column</td>\n",
       "      <td> column</td>\n",
       "      <td> column</td>\n",
       "      <td> column</td>\n",
       "      <td> column</td>\n",
       "      <td> column</td>\n",
       "      <td> column</td>\n",
       "      <td> column</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       0       1       2       3       4       5       6       7       8   \\\n",
       "0  column  column  column  column  column  column  column  column  column   \n",
       "\n",
       "       9       10      11      12      13      14  \n",
       "0  column  column  column  column  column  column  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "pd.DataFrame([['column'] * 15])"
   ]
  }
 ],
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