{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import json\n",
    "with open(\"data/nebuloss.json\", \"r\") as f:\n",
    "    data = json.load(f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def split_dict(d, n):\n",
    "    \"\"\"\n",
    "    Splits a dictionary into n dictionaries with almost equal number of items.\n",
    "\n",
    "    Parameters:\n",
    "    - d (dict): The input dictionary.\n",
    "    - n (int): The number of dictionaries to split into.\n",
    "\n",
    "    Returns:\n",
    "    - list of dict: A list of n dictionaries.\n",
    "    \"\"\"\n",
    "    items = list(d.items())\n",
    "    length = len(items)\n",
    "    \n",
    "    # Calculate the size of each chunk\n",
    "    chunk_size = length // n\n",
    "    remainder = length % n\n",
    "\n",
    "    # Split the items into chunks\n",
    "    chunks = []\n",
    "    start = 0\n",
    "\n",
    "    for i in range(n):\n",
    "        if remainder:\n",
    "            end = start + chunk_size + 1\n",
    "            remainder -= 1\n",
    "        else:\n",
    "            end = start + chunk_size\n",
    "        chunks.append(dict(items[start:end]))\n",
    "        start = end\n",
    "\n",
    "    return chunks\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "chunk_1, chunk_2, chunk_3, chunk_4 = split_dict(data, n=4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(\"data/nebuloss_1.json\", \"w\") as f:\n",
    "    json.dump(chunk_1, f, indent=4)\n",
    "with open(\"data/nebuloss_2.json\", \"w\") as f:\n",
    "    json.dump(chunk_2, f, indent=4)\n",
    "with open(\"data/nebuloss_3.json\", \"w\") as f:\n",
    "    json.dump(chunk_3, f, indent=4)\n",
    "with open(\"data/nebuloss_4.json\", \"w\") as f:\n",
    "    json.dump(chunk_4, f, indent=4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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   "display_name": "hackenv",
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  "language_info": {
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