{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Create a Trove OCR corrections ticker"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Run this cell first to set things up\n",
    "import requests\n",
    "import time\n",
    "from IPython.display import display, HTML, clear_output\n",
    "params = {\n",
    "    'q': 'has:corrections',\n",
    "    'zone': 'newspaper',\n",
    "    'encoding': 'json',\n",
    "    'n': '0',\n",
    "    'key': 'ju3rgk0jp354ikmh'\n",
    "}\n",
    "\n",
    "def update_corrections():\n",
    "    try:\n",
    "        while True:\n",
    "            clear_output(wait=True)\n",
    "            response = requests.get('http://api.trove.nla.gov.au/v2/result', params=params)\n",
    "            data = response.json()\n",
    "            total = int(data['response']['zone'][0]['records']['total'])\n",
    "            display(HTML('<p style=\"line-height: 15rem;\">Trove users have made corrections to <span style=\"font-size: 10rem;\">{:,}</span> newspaper articles.</p>'.format(total)))\n",
    "            time.sleep(5)\n",
    "    except KeyboardInterrupt:\n",
    "        pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<p style=\"line-height: 15rem;\">Trove users have made corrections to <span style=\"font-size: 10rem;\">11,998,162</span> newspaper articles.</p>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Run this cell to start the ticker\n",
    "# To stop, click the stop button or select Kernel > Interrupt from the menu\n",
    "update_corrections()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "----\n",
    "\n",
    "Created by [Tim Sherratt](https://timsherratt.org/) for the [GLAM Workbench](https://glam-workbench.github.io/)."
   ]
  }
 ],
 "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": "3.7.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}