{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "c452598e",
   "metadata": {},
   "source": [
    "# Pickle examples"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a1406ad8",
   "metadata": {},
   "source": [
    "## Python `pickle` module\n",
    "\n",
    "In this example we want to use the Python [pickle](https://docs.python.org/3/library/pickle.html) module to save the following dict in pickle format:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "db7ff3f7",
   "metadata": {},
   "outputs": [],
   "source": [
    "pyviz = {\n",
    "    \"Title\": \"PyViz Tutorial\",\n",
    "    \"Language\": \"de\",\n",
    "    \"Authors\": \"Veit Schiele\",\n",
    "    \"License\": \"BSD-3-Clause\",\n",
    "    \"Publication date\": \"2020-04-13\",\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "a247fb7a",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pickle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "c842fe04",
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(\"pyviz.pkl\", \"wb\") as f:\n",
    "    pickle.dump(pyviz, f, pickle.HIGHEST_PROTOCOL)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b8b2a92f",
   "metadata": {},
   "source": [
    "Now we read the pickle file again:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "25d7b260",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'Title': 'PyViz Tutorial', 'Language': 'de', 'Authors': 'Veit Schiele', 'License': 'BSD-3-Clause', 'Publication date': '2020-04-13'}\n"
     ]
    }
   ],
   "source": [
    "with open(\"pyviz.pkl\", \"rb\") as f:\n",
    "    pyviz = pickle.load(f)\n",
    "\n",
    "print(pyviz)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0590401c",
   "metadata": {},
   "source": [
    "This way we can easily store Python objects persistently.\n",
    "\n",
    "<div class=\"alert alert-warning\">\n",
    "\n",
    "**Warning:**\n",
    "\n",
    "`pickle` can only be recommended as a short-term storage format. The problem is that the format is not guaranteed to remain stable over time; an object picked today may not be unpickled with a later version of the library.\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b5d91683",
   "metadata": {},
   "source": [
    "## pandas\n",
    "\n",
    "All pandas objects have a `to_pickle` method that writes data to disk in pickle format:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "75de046d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>title</th>\n",
       "      <th>language</th>\n",
       "      <th>author</th>\n",
       "      <th>license</th>\n",
       "      <th>date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Python basics</td>\n",
       "      <td>en</td>\n",
       "      <td>Veit Schiele</td>\n",
       "      <td>BSD-3-Clause</td>\n",
       "      <td>2021-10-28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Jupyter Tutorial</td>\n",
       "      <td>en</td>\n",
       "      <td>Veit Schiele</td>\n",
       "      <td>BSD-3-Clause</td>\n",
       "      <td>2019-06-27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Jupyter Tutorial</td>\n",
       "      <td>de</td>\n",
       "      <td>Veit Schiele</td>\n",
       "      <td>BSD-3-Clause</td>\n",
       "      <td>2020-10-26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>PyViz Tutorial</td>\n",
       "      <td>en</td>\n",
       "      <td>Veit Schiele</td>\n",
       "      <td>BSD-3-Clause</td>\n",
       "      <td>2020-04-13</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id             title language        author       license        date\n",
       "0   1     Python basics       en  Veit Schiele  BSD-3-Clause  2021-10-28\n",
       "1   2  Jupyter Tutorial       en  Veit Schiele  BSD-3-Clause  2019-06-27\n",
       "2   3  Jupyter Tutorial       de  Veit Schiele  BSD-3-Clause  2020-10-26\n",
       "3   4    PyViz Tutorial       en  Veit Schiele  BSD-3-Clause  2020-04-13"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "\n",
    "books = pd.read_pickle(\"books.pkl\")\n",
    "\n",
    "books"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "29bf1b87",
   "metadata": {},
   "source": [
    "pandas objects all have a `to_pickle` method that writes the data to the hard disk in pickle format:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "70fad48e",
   "metadata": {},
   "outputs": [],
   "source": [
    "books.to_pickle(\"books.pkl\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.13 Kernel",
   "language": "python",
   "name": "python313"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.13.0"
  },
  "widgets": {
   "application/vnd.jupyter.widget-state+json": {
    "state": {},
    "version_major": 2,
    "version_minor": 0
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}