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{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "5912ba94-833f-4662-8b8c-f201b5dde892",
   "metadata": {},
   "outputs": [],
   "source": [
    "# # Function to process \"double\" followed by a number\n",
    "# def process_doubles(sentence):\n",
    "#     tokens = sentence.split()\n",
    "#     result = []\n",
    "#     i = 0\n",
    "#     while i < len(tokens):\n",
    "#         if tokens[i] == \"डबल\":\n",
    "#             if i + 1 < len(tokens):\n",
    "#                 result.append(tokens[i + 1])\n",
    "#                 result.append(tokens[i + 1])\n",
    "#                 i += 2\n",
    "#             else:\n",
    "#                 result.append(tokens[i])\n",
    "#                 i += 1\n",
    "#         else:\n",
    "#             result.append(tokens[i])\n",
    "#             i += 1\n",
    "#     return ' '.join(result)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7d7065ce-94c9-4cda-a398-71dac90a67ba",
   "metadata": {},
   "outputs": [],
   "source": [
    "import re\n",
    "\n",
    "def process_doubles(sentence):\n",
    "    # Use regex to split 'डबल' followed by numbers/words without space (e.g., \"डबलवन\" -> \"डबल वन\")\n",
    "    sentence = re.sub(r'(डबल)(\\S+)', r'\\1 \\2', sentence)\n",
    "    \n",
    "    tokens = sentence.split()\n",
    "    result = []\n",
    "    i = 0\n",
    "    \n",
    "    while i < len(tokens):\n",
    "        if tokens[i] == \"डबल\":\n",
    "            if i + 1 < len(tokens):\n",
    "                result.append(tokens[i + 1])  # Append the next word/number\n",
    "                result.append(tokens[i + 1])  # Append the next word/number again to duplicate\n",
    "                i += 2  # Skip over the next word since it's already processed\n",
    "            else:\n",
    "                result.append(tokens[i])\n",
    "                i += 1\n",
    "        else:\n",
    "            result.append(tokens[i])\n",
    "            i += 1\n",
    "\n",
    "    return ' '.join(result)\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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