{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "f72144fd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Flask==3.1.3\n",
      "pandas==3.0.2\n",
      "xgboost==3.2.0\n",
      "joblib==1.5.3\n",
      "scikit-learn==1.8.0\n",
      "gunicorn==23.0.0\n"
     ]
    }
   ],
   "source": [
    "import importlib.metadata\n",
    "\n",
    "name = ['flask', 'pandas', 'xgboost', 'joblib', 'scikit-learn']\n",
    "\n",
    "for p_name in name:\n",
    "    try:\n",
    "        version = importlib.metadata.version(p_name)\n",
    "        if p_name == 'flask':\n",
    "            p_name = 'Flask'\n",
    "        elif p_name == 'scikit-learn':\n",
    "            p_name = 'scikit-learn'\n",
    "        print(f\"{p_name}=={version}\")\n",
    "    except importlib.metadata.PackageNotFoundError:\n",
    "        pass\n",
    "\n",
    "print(\"gunicorn==23.0.0\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d0798960",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "ml (3.13.9)",
   "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": "3.13.9"
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