{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "895a5bb2",
   "metadata": {},
   "source": [
    "![brainome logo](./images/brainome_logo.png)\n",
    "# 303 Predictor Validation Measurements in JSON\n",
    "The predictor can output validation measurements in json rather than human-readable text.\n",
    "\n",
    "* Validation measurements in json format."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "431b880e",
   "metadata": {},
   "source": [
    "## Prerequisites\n",
    "This notebook assumes brainome is installed as per notebook [brainome_101_Quick_Start](brainome_101_Quick_Start.ipynb)\n",
    "\n",
    "The data sets are:\n",
    "* [titanic_train.csv](https://download.brainome.ai/data/public/titanic_train.csv) for training data\n",
    "* [titanic_validate.csv](https://download.brainome.ai/data/public/titanic_validate.csv) for validation\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "!python3 -m pip install brainome --quiet\n",
    "!brainome --version\n",
    "\n",
    "import urllib.request as request\n",
    "response2 = request.urlretrieve('https://download.brainome.ai/data/public/titanic_validate.csv', 'titanic_validate.csv')\n",
    "%ls -lh titanic_validate.csv"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "markdown",
   "id": "540b27d9",
   "metadata": {},
   "source": [
    "## Generate a predictor\n",
    "The predictor filename is `predictor_303.py`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "57882e55",
   "metadata": {
    "tags": [
     "output_scroll"
    ]
   },
   "outputs": [],
   "source": [
    "!brainome https://download.brainome.ai/data/public/titanic_train.csv -y -o predictor_303.py -modelonly -q\n",
    "print('\\nCreated predictor_303.py')\n",
    "!ls -lh predictor_303.py"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c65d5739",
   "metadata": {},
   "source": [
    "## Validation measurements in json format.\n",
    "The same measurements as all previous exercises can be generated in JSON format for further system integration\n",
    "Use `-validate -json` to trigger the predictor to output json validation measurements."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "781a9407",
   "metadata": {},
   "outputs": [],
   "source": [
    "!python3 predictor_303.py -validate titanic_validate.csv -json > validation_measurements_303.json\n",
    "import json\n",
    "with open('validation_measurements_303.json', 'r') as measurement_file:\n",
    "    validation_measurements = json.load(measurement_file)\n",
    "    print(json.dumps(validation_measurements, indent=4))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "83c337d6",
   "metadata": {},
   "source": [
    "## Next Steps\n",
    "- Check out [300 Put your model to work](./brainome_300_Integrating_Predictors.ipynb)\n",
    "> TODO next..."
   ]
  }
 ],
 "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": "3.9.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}