{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```yaml\n",
    "operator: local.JupyterOperator\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This could very well be abstracted into some sort of StockHistoryOperator, with ticker(s), period, and interval parameterized, but here we will do the work in a notebook."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import yfinance as yf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "stock = yf.Ticker('SPY')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "history = stock.history(period='5y', interval='1d').reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "history.columns = history.columns.str.strip().str.lower().str.replace(' ', '_').str.replace('(', '').str.replace(')', '')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "history = history.sort_values('date', ascending = False).reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Take final table and save to the database."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from airflow.hooks.postgres_hook import PostgresHook\n",
    "\n",
    "con = PostgresHook('postgres_default').get_sqlalchemy_engine()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "history.to_sql('stock_data',\n",
    "               con,\n",
    "               schema='views',\n",
    "               if_exists=\"replace\",\n",
    "               index=False)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}