{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Create a Trove OCR corrections ticker"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Run this cell first to set things up\n",
    "import time\n",
    "\n",
    "import requests\n",
    "from IPython.display import HTML, clear_output, display\n",
    "\n",
    "params = {\n",
    "    \"q\": \"has:corrections\",\n",
    "    \"zone\": \"newspaper\",\n",
    "    \"encoding\": \"json\",\n",
    "    \"n\": \"0\",\n",
    "    \"key\": \"ju3rgk0jp354ikmh\",\n",
    "}\n",
    "\n",
    "\n",
    "def update_corrections():\n",
    "    try:\n",
    "        while True:\n",
    "            clear_output(wait=True)\n",
    "            response = requests.get(\n",
    "                \"http://api.trove.nla.gov.au/v2/result\", params=params\n",
    "            )\n",
    "            data = response.json()\n",
    "            total = int(data[\"response\"][\"zone\"][0][\"records\"][\"total\"])\n",
    "            display(\n",
    "                HTML(\n",
    "                    '<p style=\"line-height: 15rem;\">Trove users have made corrections to <span style=\"font-size: 10rem;\">{:,}</span> newspaper articles.</p>'.format(\n",
    "                        total\n",
    "                    )\n",
    "                )\n",
    "            )\n",
    "            time.sleep(5)\n",
    "    except KeyboardInterrupt:\n",
    "        pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "tags": [
     "nbval-skip"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<p style=\"line-height: 15rem;\">Trove users have made corrections to <span style=\"font-size: 10rem;\">13,590,152</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/).  \n",
    "Support this project by becoming a [GitHub sponsor](https://github.com/sponsors/wragge?o=esb)."
   ]
  }
 ],
 "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": "3.8.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}