introduction.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "33c6cb91",
   "metadata": {
    "execute": {
     "shell": {
      "execute_reply": "2022-02-03T11:12:36.270550+00:00"
     }
    },
    "iopub": {
     "execute_input": "2022-02-03T11:12:36.263550+00:00",
     "status": {
      "busy": "2022-02-03T11:12:36.263144+00:00",
      "idle": "2021-12-17T08:24:16.475079+00:00"
     }
    },
    "jupyter": {
     "source_hidden": true
    },
    "tags": []
   },
   "source": [
    "# euporie\n",
    "\n",
    "Welcome to `euporie`, a terminal based interactive development environment for Jupyter notebooks.\n",
    "\n",
    "- Use `Up` and `Down` to navigate, `Enter` to edit a cell, and `Esc` to stop editing a cell\n",
    "- Use `Ctrl+Enter` to run or render a cell, or `Shift+Enter` to additionally select the next cell.\n",
    "- You can view all keyboard shortcuts in the `Help` menu\n",
    "- The online documentation is available at [https://euporie.readthedocs.io](https://euporie.readthedocs.io)\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1e737449",
   "metadata": {},
   "source": [
    "## Markdown Cells\n",
    "\n",
    "`euporie` will render markdown cells in notebooks, including elements such as:\n",
    "\n",
    "> Quote blocks\n",
    "\n",
    "1. Ordered lists\n",
    "    - Unordered lists\n",
    "    - (Another list item)\n",
    "2. **Bold**, *Italic*, ~~strikethrough~~, `code`\n",
    "\n",
    "```python\n",
    "def code_blocks():\n",
    "    return True\n",
    "```\n",
    "\n",
    "| Tables       | *with* | ~~formatting~~ |\n",
    "|-------------:|:------:|:---------------|\n",
    "| **and**      | cell   | alignment      |\n",
    "\n",
    "Inline maths: $x =\\frac{-b \\pm \\sqrt{\\frac{1}{2} a b^2}}{2a}$ and maths blocks:\n",
    "\n",
    "$$\n",
    "f = \\sum_{i = 0}^{\\infty} \\frac{f^{(i)}(0)}{i!} x^i\n",
    "$$\n",
    "\n",
    "Links: [https://euporie.readthedocs.io](https://euporie.readthedocs.io)\n",
    "\n",
    "Inline images ![](https://user-images.githubusercontent.com/12154190/160242688-440c67ca-fdba-4ca4-a941-a35e200f9813.svg) in paragraphs.\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "39eae66d",
   "metadata": {},
   "source": [
    "## Cell Output\n",
    "\n",
    "`Euporie` will also render the output of code cells.\n",
    "\n",
    "This includes displaying Markdown, LaTeX, Images, HTML, SVG, JSON, and ANSI text:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "aa1d9c37",
   "metadata": {
    "execute": {
     "shell": {
      "execute_reply": "2022-02-16T11:08:19.149766+00:00"
     }
    },
    "iopub": {
     "execute_input": "2022-02-16T11:08:19.137229+00:00",
     "status": {
      "busy": "2022-02-16T11:08:19.135967+00:00",
      "idle": "2022-02-16T11:08:19.150514+00:00"
     }
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<b>Bold</b> <u>Underlined</u> <i>Italic</i>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display({\"text/html\": \"<b>Bold</b> <u>Underlined</u> <i>Italic</i>\"}, raw=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "583a8b24",
   "metadata": {
    "execute": {
     "shell": {
      "execute_reply": "2022-02-16T11:08:19.156306+00:00"
     }
    },
    "iopub": {
     "execute_input": "2022-02-16T11:08:19.152478+00:00",
     "status": {
      "busy": "2022-02-16T11:08:19.152175+00:00",
      "idle": "2022-02-16T11:08:19.156885+00:00"
     }
    }
   },
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$x =\\frac{-b \\pm \\sqrt{\\frac{1}{2} a b^2}}{2a}$"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display({\"text/latex\": r\"$x =\\frac{-b \\pm \\sqrt{\\frac{1}{2} a b^2}}{2a}$\"}, raw=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "97e10f0f",
   "metadata": {
    "execute": {
     "shell": {
      "execute_reply": "2022-02-16T11:08:19.526395+00:00"
     }
    },
    "iopub": {
     "execute_input": "2022-02-16T11:08:19.157955+00:00",
     "status": {
      "busy": "2022-02-16T11:08:19.157765+00:00",
      "idle": "2022-02-16T11:08:19.527257+00:00"
     }
    }
   },
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import *\n",
    "import urllib.request\n",
    "data = urllib.request.urlopen(\"https://www.python.org/static/img/python-logo.png\").read()\n",
    "Image(data)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "43a7ed60",
   "metadata": {
    "execute": {
     "shell": {
      "execute_reply": "2022-02-03T11:12:36.282953+00:00"
     }
    },
    "iopub": {
     "status": {
      "busy": "2022-02-03T11:12:36.282693+00:00",
      "idle": "2022-02-03T11:12:36.283084+00:00"
     }
    }
   },
   "source": [
    "This means you can use libraries like `pandas`, and display dataframes as you would expect:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "5dc84d78",
   "metadata": {
    "execute": {
     "shell": {
      "execute_reply": "2022-02-16T11:08:20.296522+00:00"
     }
    },
    "iopub": {
     "execute_input": "2022-02-16T11:08:19.528869+00:00",
     "status": {
      "busy": "2022-02-16T11:08:19.528528+00:00",
      "idle": "2022-02-16T11:08:20.297331+00:00"
     }
    }
   },
   "outputs": [
    {
     "data": {
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       "#T_9853a_row6_col0 {\n",
       "  background-color: #34608d;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_9853a_row6_col1 {\n",
       "  background-color: #306a8e;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_9853a_row6_col2 {\n",
       "  background-color: #2c718e;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_9853a_row6_col3 {\n",
       "  background-color: #2a768e;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_9853a_row7_col0 {\n",
       "  background-color: #453882;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_9853a_row7_col1 {\n",
       "  background-color: #f8e621;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_9853a_row7_col2 {\n",
       "  background-color: #404588;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_9853a_row7_col3 {\n",
       "  background-color: #460a5d;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_9853a_row8_col0 {\n",
       "  background-color: #375b8d;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_9853a_row8_col1 {\n",
       "  background-color: #58c765;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_9853a_row8_col3 {\n",
       "  background-color: #2db27d;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_9853a_row9_col0 {\n",
       "  background-color: #2f6c8e;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_9853a_row9_col1 {\n",
       "  background-color: #33628d;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_9853a_row9_col2 {\n",
       "  background-color: #3d4e8a;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_9853a_row10_col0 {\n",
       "  background-color: #46337f;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_9853a_row10_col1 {\n",
       "  background-color: #365c8d;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_9853a_row10_col2 {\n",
       "  background-color: #4ec36b;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_9853a_row10_col3 {\n",
       "  background-color: #25838e;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_9853a_row11_col1 {\n",
       "  background-color: #35b779;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_9853a_row11_col2 {\n",
       "  background-color: #3dbc74;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_9853a_row11_col3 {\n",
       "  background-color: #375a8c;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_9853a_row12_col0 {\n",
       "  background-color: #481b6d;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_9853a_row12_col2 {\n",
       "  background-color: #c2df23;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_9853a_row13_col0 {\n",
       "  background-color: #46327e;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_9853a_row13_col1 {\n",
       "  background-color: #26828e;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_9853a_row13_col2 {\n",
       "  background-color: #24878e;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_9853a_row13_col3 {\n",
       "  background-color: #40bd72;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_9853a_row14_col1 {\n",
       "  background-color: #3aba76;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_9853a_row14_col2 {\n",
       "  background-color: #63cb5f;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_9853a_row14_col3 {\n",
       "  background-color: #b5de2b;\n",
       "  color: #000000;\n",
       "}\n",
       "</style>\n",
       "<table id=\"T_9853a\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_9853a_level0_col0\" class=\"col_heading level0 col0\" >a</th>\n",
       "      <th id=\"T_9853a_level0_col1\" class=\"col_heading level0 col1\" >b</th>\n",
       "      <th id=\"T_9853a_level0_col2\" class=\"col_heading level0 col2\" >c</th>\n",
       "      <th id=\"T_9853a_level0_col3\" class=\"col_heading level0 col3\" >d</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_9853a_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
       "      <td id=\"T_9853a_row0_col0\" class=\"data row0 col0\" >0.003259</td>\n",
       "      <td id=\"T_9853a_row0_col1\" class=\"data row0 col1\" >0.774210</td>\n",
       "      <td id=\"T_9853a_row0_col2\" class=\"data row0 col2\" >0.896454</td>\n",
       "      <td id=\"T_9853a_row0_col3\" class=\"data row0 col3\" >0.780203</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_9853a_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "      <td id=\"T_9853a_row1_col0\" class=\"data row1 col0\" >0.004151</td>\n",
       "      <td id=\"T_9853a_row1_col1\" class=\"data row1 col1\" >0.442622</td>\n",
       "      <td id=\"T_9853a_row1_col2\" class=\"data row1 col2\" >0.847817</td>\n",
       "      <td id=\"T_9853a_row1_col3\" class=\"data row1 col3\" >0.637673</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_9853a_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
       "      <td id=\"T_9853a_row2_col0\" class=\"data row2 col0\" >0.001761</td>\n",
       "      <td id=\"T_9853a_row2_col1\" class=\"data row2 col1\" >0.229524</td>\n",
       "      <td id=\"T_9853a_row2_col2\" class=\"data row2 col2\" >0.757974</td>\n",
       "      <td id=\"T_9853a_row2_col3\" class=\"data row2 col3\" >0.890007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_9853a_level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
       "      <td id=\"T_9853a_row3_col0\" class=\"data row3 col0\" >0.269210</td>\n",
       "      <td id=\"T_9853a_row3_col1\" class=\"data row3 col1\" >0.794629</td>\n",
       "      <td id=\"T_9853a_row3_col2\" class=\"data row3 col2\" >0.863608</td>\n",
       "      <td id=\"T_9853a_row3_col3\" class=\"data row3 col3\" >0.874150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_9853a_level0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
       "      <td id=\"T_9853a_row4_col0\" class=\"data row4 col0\" >0.047546</td>\n",
       "      <td id=\"T_9853a_row4_col1\" class=\"data row4 col1\" >0.850900</td>\n",
       "      <td id=\"T_9853a_row4_col2\" class=\"data row4 col2\" >0.797513</td>\n",
       "      <td id=\"T_9853a_row4_col3\" class=\"data row4 col3\" >0.807209</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_9853a_level0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
       "      <td id=\"T_9853a_row5_col0\" class=\"data row5 col0\" >0.055865</td>\n",
       "      <td id=\"T_9853a_row5_col1\" class=\"data row5 col1\" >0.431414</td>\n",
       "      <td id=\"T_9853a_row5_col2\" class=\"data row5 col2\" >0.560731</td>\n",
       "      <td id=\"T_9853a_row5_col3\" class=\"data row5 col3\" >0.574832</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_9853a_level0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
       "      <td id=\"T_9853a_row6_col0\" class=\"data row6 col0\" >0.146059</td>\n",
       "      <td id=\"T_9853a_row6_col1\" class=\"data row6 col1\" >0.382183</td>\n",
       "      <td id=\"T_9853a_row6_col2\" class=\"data row6 col2\" >0.598058</td>\n",
       "      <td id=\"T_9853a_row6_col3\" class=\"data row6 col3\" >0.698844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_9853a_level0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
       "      <td id=\"T_9853a_row7_col0\" class=\"data row7 col0\" >0.079312</td>\n",
       "      <td id=\"T_9853a_row7_col1\" class=\"data row7 col1\" >0.843316</td>\n",
       "      <td id=\"T_9853a_row7_col2\" class=\"data row7 col2\" >0.518904</td>\n",
       "      <td id=\"T_9853a_row7_col3\" class=\"data row7 col3\" >0.542317</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_9853a_level0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
       "      <td id=\"T_9853a_row8_col0\" class=\"data row8 col0\" >0.137434</td>\n",
       "      <td id=\"T_9853a_row8_col1\" class=\"data row8 col1\" >0.664604</td>\n",
       "      <td id=\"T_9853a_row8_col2\" class=\"data row8 col2\" >0.420789</td>\n",
       "      <td id=\"T_9853a_row8_col3\" class=\"data row8 col3\" >0.805205</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_9853a_level0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
       "      <td id=\"T_9853a_row9_col0\" class=\"data row9 col0\" >0.168505</td>\n",
       "      <td id=\"T_9853a_row9_col1\" class=\"data row9 col1\" >0.358604</td>\n",
       "      <td id=\"T_9853a_row9_col2\" class=\"data row9 col2\" >0.532415</td>\n",
       "      <td id=\"T_9853a_row9_col3\" class=\"data row9 col3\" >0.957759</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_9853a_level0_row10\" class=\"row_heading level0 row10\" >10</th>\n",
       "      <td id=\"T_9853a_row10_col0\" class=\"data row10 col0\" >0.071780</td>\n",
       "      <td id=\"T_9853a_row10_col1\" class=\"data row10 col1\" >0.342045</td>\n",
       "      <td id=\"T_9853a_row10_col2\" class=\"data row10 col2\" >0.763512</td>\n",
       "      <td id=\"T_9853a_row10_col3\" class=\"data row10 col3\" >0.722953</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_9853a_level0_row11\" class=\"row_heading level0 row11\" >11</th>\n",
       "      <td id=\"T_9853a_row11_col0\" class=\"data row11 col0\" >0.479252</td>\n",
       "      <td id=\"T_9853a_row11_col1\" class=\"data row11 col1\" >0.614191</td>\n",
       "      <td id=\"T_9853a_row11_col2\" class=\"data row11 col2\" >0.746985</td>\n",
       "      <td id=\"T_9853a_row11_col3\" class=\"data row11 col3\" >0.650710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_9853a_level0_row12\" class=\"row_heading level0 row12\" >12</th>\n",
       "      <td id=\"T_9853a_row12_col0\" class=\"data row12 col0\" >0.036609</td>\n",
       "      <td id=\"T_9853a_row12_col1\" class=\"data row12 col1\" >0.138304</td>\n",
       "      <td id=\"T_9853a_row12_col2\" class=\"data row12 col2\" >0.852930</td>\n",
       "      <td id=\"T_9853a_row12_col3\" class=\"data row12 col3\" >0.531633</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_9853a_level0_row13\" class=\"row_heading level0 row13\" >13</th>\n",
       "      <td id=\"T_9853a_row13_col0\" class=\"data row13 col0\" >0.068955</td>\n",
       "      <td id=\"T_9853a_row13_col1\" class=\"data row13 col1\" >0.454261</td>\n",
       "      <td id=\"T_9853a_row13_col2\" class=\"data row13 col2\" >0.641144</td>\n",
       "      <td id=\"T_9853a_row13_col3\" class=\"data row13 col3\" >0.827327</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_9853a_level0_row14\" class=\"row_heading level0 row14\" >14</th>\n",
       "      <td id=\"T_9853a_row14_col0\" class=\"data row14 col0\" >0.142360</td>\n",
       "      <td id=\"T_9853a_row14_col1\" class=\"data row14 col1\" >0.620112</td>\n",
       "      <td id=\"T_9853a_row14_col2\" class=\"data row14 col2\" >0.781901</td>\n",
       "      <td id=\"T_9853a_row14_col3\" class=\"data row14 col3\" >0.910570</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7ff8f32ca8f0>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "x = np.arange(20_000)\n",
    "\n",
    "df = pd.DataFrame(\n",
    "    {\n",
    "        col: np.random.beta(i+1, 3, x.shape)\n",
    "        for col, i in zip(\"abcd\", [0, 2, 4, 6])\n",
    "    },\n",
    "    index = x,\n",
    ")\n",
    "df.head(15).style.background_gradient(cmap=\"viridis\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "10690823",
   "metadata": {
    "execute": {
     "shell": {
      "execute_reply": "2022-02-03T11:12:36.286420+00:00"
     }
    },
    "iopub": {
     "status": {
      "busy": "2022-02-03T11:12:36.286194+00:00",
      "idle": "2022-02-03T11:12:36.286552+00:00"
     }
    }
   },
   "source": [
    "`euporie` can render images using Sixel graphics if your terminal supports it. Otherwise it will fall back to using character-based terminal graphics.\n",
    "\n",
    "This means you can produce plots with `matplotlib` and `euporie` will display them in the best way it can:"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3adda7cd",
   "metadata": {
    "execute": {
     "shell": {
      "execute_reply": "2022-02-03T11:12:36.292730+00:00"
     }
    },
    "iopub": {
     "status": {
      "busy": "2022-02-03T11:12:36.292507+00:00",
      "idle": "2022-02-03T11:12:36.292880+00:00"
     }
    }
   },
   "source": [
    "It can also display SVG output:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "600da1a5",
   "metadata": {
    "execute": {
     "shell": {
      "execute_reply": "2022-02-16T11:08:21.852100+00:00"
     }
    },
    "iopub": {
     "execute_input": "2022-02-16T11:08:20.300070+00:00",
     "status": {
      "busy": "2022-02-16T11:08:20.299711+00:00",
      "idle": "2022-02-16T11:08:21.852873+00:00"
     }
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(8,2), facecolor=\"#FFF\")\n",
    "df.plot.hist(ax=ax, bins=80, alpha=0.75)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "02fe9798",
   "metadata": {
    "execute": {
     "shell": {
      "execute_reply": "2022-02-16T11:08:22.063910+00:00"
     }
    },
    "iopub": {
     "execute_input": "2022-02-16T11:08:22.058466+00:00",
     "status": {
      "busy": "2022-02-16T11:08:22.058214+00:00",
      "idle": "2022-02-16T11:08:22.064507+00:00"
     }
    }
   },
   "outputs": [
    {
     "data": {
      "image/svg+xml": [
       "<svg width=\"200\" height=\"200\"><polygon points=\"105,5 45,185 195,65 5,65 165,185\" fill=\"yellow\"/></svg>"
      ],
      "text/plain": [
       "<IPython.core.display.SVG object>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import SVG\n",
    "\n",
    "SVG(\n",
    "    '<svg width=\"200\" height=\"200\"><polygon points=\"105,5 45,185 195,65 5,65 165,185\" fill=\"yellow\" /></svg>'\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1bd9c919",
   "metadata": {},
   "source": [
    "Euporie can display JSON output interactively. Try clicking to expand and collapse items in the output:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "28fae044",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/json": {
       "bool": true,
       "dict": {
        "bool": true,
        "list": [
         "First",
         "Second",
         "Third",
         "Fourth"
        ],
        "number": 123.456,
        "string": "This is a string"
       },
       "list": [
        "First",
        "Second",
        "Third",
        "Fourth"
       ],
       "number": 123.456,
       "string": "This is a string"
      },
      "text/plain": [
       "<IPython.core.display.JSON object>"
      ]
     },
     "execution_count": 7,
     "metadata": {
      "application/json": {
       "expanded": true,
       "root": "My JSON document"
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import JSON\n",
    "\n",
    "JSON(\n",
    "    {\n",
    "        \"number\": 123.456,\n",
    "        \"bool\": True,\n",
    "        \"string\": \"This is a string\",\n",
    "        \"list\": [\"First\", \"Second\", \"Third\", \"Fourth\"],\n",
    "        \"dict\": {\n",
    "            \"number\": 123.456,\n",
    "            \"bool\": True,\n",
    "            \"string\": \"This is a string\",\n",
    "            \"list\": [\"First\", \"Second\", \"Third\", \"Fourth\"],\n",
    "        },\n",
    "    },\n",
    "    expanded=True,\n",
    "    root=\"My JSON document\",\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "930e6d01",
   "metadata": {
    "execute": {
     "shell": {
      "execute_reply": "2022-02-03T11:12:36.299041+00:00"
     }
    },
    "iopub": {
     "execute_input": "2022-02-03T11:10:23.378289+00:00",
     "status": {
      "busy": "2022-02-03T11:12:36.298716+00:00",
      "idle": "2022-02-03T11:12:36.299174+00:00"
     }
    }
   },
   "source": [
    "`euporie` supporst ANSI output, so  works with libraries like `tqdm` and `rich`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "831136cb-3feb-4dc1-867c-cd35af15bdd1",
   "metadata": {
    "execute": {
     "shell": {
      "execute_reply": "2022-02-16T11:08:29.098413+00:00"
     }
    },
    "iopub": {
     "execute_input": "2022-02-16T11:08:25.039636+00:00",
     "status": {
      "busy": "2022-02-16T11:08:25.038767+00:00",
      "idle": "2022-02-16T11:08:29.099088+00:00"
     }
    }
   },
   "outputs": [],
   "source": [
    "import time\n",
    "from tqdm import tqdm\n",
    "\n",
    "for i in tqdm(range(20), ncols=100):\n",
    "    time.sleep(0.2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "51d035f3-6cfb-4d0e-a72d-7787b0bc537b",
   "metadata": {
    "execute": {
     "shell": {
      "execute_reply": "2022-02-16T11:08:33.187586+00:00"
     }
    },
    "iopub": {
     "execute_input": "2022-02-16T11:08:29.100639+00:00",
     "status": {
      "busy": "2022-02-16T11:08:29.100293+00:00",
      "idle": "2022-02-16T11:08:33.188270+00:00"
     }
    }
   },
   "outputs": [],
   "source": [
    "from rich.progress import track\n",
    "\n",
    "for _ in track(range(20)):\n",
    "    time.sleep(0.2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b3a7402a",
   "metadata": {},
   "source": [
    "This means it can also display colored output from external commands:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7a24ebae-fe8e-4bce-a964-b4010877c45a",
   "metadata": {
    "execute": {
     "shell": {
      "execute_reply": "2022-02-16T11:08:33.317773+00:00"
     }
    },
    "iopub": {
     "execute_input": "2022-02-16T11:08:33.189476+00:00",
     "status": {
      "busy": "2022-02-16T11:08:33.189220+00:00",
      "idle": "2022-02-16T11:08:33.320167+00:00"
     }
    }
   },
   "outputs": [],
   "source": [
    "!exa -l --icons --group-directories-first"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "025efbf2",
   "metadata": {
    "execute": {
     "shell": {
      "execute_reply": "2022-02-03T11:12:36.296087+00:00"
     }
    },
    "iopub": {
     "status": {
      "busy": "2022-02-03T11:12:36.295875+00:00",
      "idle": "2022-02-03T11:12:36.296226+00:00"
     }
    }
   },
   "source": [
    "## Requesting input\n",
    "\n",
    "`euoporie` can response to requests for user input from the kernel (press enter to send your input):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "849afa5d-dd52-4ae4-87ad-9c2ab1f33792",
   "metadata": {
    "execute": {
     "shell": {
      "execute_reply": "2022-02-16T11:08:25.034779+00:00"
     }
    },
    "iopub": {
     "execute_input": "2022-02-16T11:08:22.065738+00:00",
     "status": {
      "busy": "2022-02-16T11:08:22.065489+00:00",
      "idle": "2022-02-16T11:08:25.037180+00:00"
     }
    }
   },
   "outputs": [],
   "source": [
    "name = input(\"Enter your name:\")\n",
    "print(f\"Hello {name}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6e805611",
   "metadata": {},
   "source": [
    "## `ipywidgets`\n",
    "\n",
    "Euporie supports most of the widgets in `ipywidgets`, allowing you to build interactive applications inside your notebook in the terminal.\n",
    "\n",
    "Run the following cell to try it out:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "83c380bc-26e2-4008-9f11-f0a603e7f86d",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from matplotlib import pyplot as plt\n",
    "from ipywidgets import widgets as w\n",
    "from ipywidgets import interactive\n",
    "\n",
    "def plot(n, color):\n",
    "    x = np.arange(-20, 20, 0.1)\n",
    "    y = np.sin(n*x) / x\n",
    "    fig, ax = plt.subplots(figsize=(8,2))\n",
    "    ax.plot(x, y, c=color, lw=5)\n",
    "    plt.show()\n",
    "\n",
    "n=w.IntSlider(description=\"n\", value=2, min=-10, max=10)\n",
    "color = w.ColorPicker(value=\"red\", description=\"Colour\")\n",
    "output = w.interactive_output(plot, {'n':n, 'color': color})\n",
    "\n",
    "w.HBox([w.VBox([n, color]), output])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "84724255",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "If you like `euporie`, please [star it on GitHub](https://github.com/joouha/euporie/)\n",
    "\n",
    "⭐ https://github.com/joouha/euporie/"
   ]
  }
 ],
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