{
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   "id": "b52e9a66-a8e9-4f56-91fd-8564b5b636fc",
   "metadata": {},
   "outputs": [],
   "source": [
    "# import nbimporter\n",
    "import nbimporter\n",
    "from Text2List import text_to_list\n",
    "def convert_to_list(text, text_list):\n",
    "    matched_words = []\n",
    "    unmatched_text = ''  # To accumulate unmatched characters\n",
    "\n",
    "    # Sort text_list by length in descending order to prioritize longest matches first\n",
    "    text_list_sorted = sorted(text_list, key=len, reverse=True)\n",
    "\n",
    "    while text:\n",
    "        matched = False\n",
    "        for word in text_list_sorted:\n",
    "            if text.startswith(word):\n",
    "                # Add any accumulated unmatched text before appending the matched word\n",
    "                if unmatched_text:\n",
    "                    matched_words.append(unmatched_text)\n",
    "                    unmatched_text = ''  # Reset unmatched text accumulator\n",
    "\n",
    "                matched_words.append(word)\n",
    "                text = text[len(word):]  # Remove the matched part from text\n",
    "                matched = True\n",
    "                break\n",
    "\n",
    "        if not matched:\n",
    "            # Accumulate unmatched characters\n",
    "            unmatched_text += text[0]\n",
    "            text = text[1:]\n",
    "\n",
    "    # If there's any remaining unmatched text, add it to the result\n",
    "    if unmatched_text:\n",
    "        matched_words.append(unmatched_text)\n",
    "\n",
    "    # Join matched words and unmatched text with a space\n",
    "    result = ' '.join(matched_words)\n",
    "    return result\n",
    "    \n",
    "# text = \"जीरोएकदोतीनचारपांचछहसातआठनौदसजीरोएकदोतीनचारपांच\"\n",
    "\n",
    "# if __name__==\"__main__\":\n",
    "#     converted=convert_to_list(text, text_to_list())\n",
    "#     print(converted)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "98835c96-2949-4e78-8d1e-c8623d5dcb00",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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   "language": "python",
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
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   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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