{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Default widgets for modules\n",
    "\n",
    "Define an `_ipython_display_` function that takes no arguments to show a default display for the module.\n",
    "\n",
    "![image](https://user-images.githubusercontent.com/4236275/45131612-bca6fa00-b15b-11e8-9b0b-76c80d4cbce5.png)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "%reload_ext deathbeds.__Custom_display_formatting\n",
    "from deathbeds.__Custom_display_formatting import Row, Column\n",
    "from pandas import *\n",
    "from poser import *\n",
    "import os"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this example we'll explore the [Flowers datasets on Kaggle](https://www.kaggle.com/alxmamaev/flowers-recognition/version/2#)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "flowers = λ.Path('data/flowers/').Path.glob('*').map(λ.Path.glob('*')).concat().list().pandas.Series()()\n",
    "flowers = flowers.apply(str).str.lstrip('data'+os.sep).str.split(os.sep, expand=True).set_index(flowers).rename(columns={\n",
    "    0:'label', 1: 'type', 2: 'file'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "from IPython.display import display"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "def _ipython_display_():\n",
    "    from ipywidgets import interact\n",
    "    @interact\n",
    "    def _(type=list(flowers.type.unique()), rows=3, columns=4):\n",
    "        display(Column([Row([str(x) for x in flowers[flowers.type.eq(type)].sample(columns).index])\n",
    "                        for row in range(rows)])) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "4817bf7b6ef048b58bb95790686906aa",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(Dropdown(description='type', options=('daisy', 'dandelion', 'rose', 'sunflower', 'tulip'…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "__import__(__name__)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "            "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.6.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}