{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import json\n",
    "from pandas.io.json import json_normalize\n",
    "\n",
    "with open('./data/freeformatter-out.json',encoding='utf-8') as json_file:\n",
    "    data = json.load(json_file)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [],
   "source": [
    "def flatten_json(nested_json, exclude=['']):\n",
    "    \"\"\"Flatten json object with nested keys into a single level.\n",
    "        Args:\n",
    "            nested_json: A nested json object.\n",
    "            exclude: Keys to exclude from output.\n",
    "        Returns:\n",
    "            The flattened json object if successful, None otherwise.\n",
    "    \"\"\"\n",
    "    out = {}\n",
    "\n",
    "    def flatten(x, name='', exclude=exclude):\n",
    "        if type(x) is dict:\n",
    "            for a in x:\n",
    "                if a not in exclude: flatten(x[a], name + a + '_')\n",
    "        elif type(x) is list:\n",
    "            i = 0\n",
    "            for a in x:\n",
    "                flatten(a, name + str(i) + '_')\n",
    "                i += 1\n",
    "        else:\n",
    "            out[name[:-1]] = x\n",
    "\n",
    "    flatten(nested_json)\n",
    "    return out\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [],
   "source": [
    "#flat_json = flatten_json(data,['postmeta'])\n",
    "flat_json = pd.DataFrame([flatten_json(x) for x in data['channel']['item']])\n",
    "flat_json.to_csv('./freeform.csv')"
   ]
  }
 ],
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