{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "TTOOLS: Loaded env variables from file /Users/davidbrazda/Documents/Development/python/.env\n"
     ]
    }
   ],
   "source": [
    "from ttools.external_loaders import load_history_bars\n",
    "from ttools.config import zoneNY\n",
    "from datetime import datetime, time\n",
    "from alpaca.data.timeframe import TimeFrame, TimeFrameUnit\n",
    "\n",
    "symbol = \"AAPL\"\n",
    "start_date = zoneNY.localize(datetime(2023, 2, 27, 18, 51, 38))\n",
    "end_date = zoneNY.localize(datetime(2023, 4, 27, 21, 51, 39))\n",
    "timeframe = TimeFrame(amount=1,unit=TimeFrameUnit.Minute)\n",
    "\n",
    "df = load_history_bars(symbol, start_date, end_date, timeframe, True)\n",
    "df.loc[('AAPL',)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
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       "      <th>2023-02-28 09:30:00-05:00</th>\n",
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       "      <th>2023-02-28 09:31:00-05:00</th>\n",
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       "      <td>6855.0</td>\n",
       "      <td>147.252171</td>\n",
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       "    <tr>\n",
       "      <th>2023-02-28 09:32:00-05:00</th>\n",
       "      <td>147.305</td>\n",
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       "      <th>2023-02-28 09:33:00-05:00</th>\n",
       "      <td>147.140</td>\n",
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       "      <td>147.1500</td>\n",
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       "      <td>7235.0</td>\n",
       "      <td>147.154832</td>\n",
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       "    <tr>\n",
       "      <th>2023-02-28 09:34:00-05:00</th>\n",
       "      <td>147.160</td>\n",
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       "      <th>2023-04-27 15:26:00-04:00</th>\n",
       "      <td>168.400</td>\n",
       "      <td>168.415</td>\n",
       "      <td>168.340</td>\n",
       "      <td>168.3601</td>\n",
       "      <td>163973.0</td>\n",
       "      <td>1398.0</td>\n",
       "      <td>168.368809</td>\n",
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       "    <tr>\n",
       "      <th>2023-04-27 15:27:00-04:00</th>\n",
       "      <td>168.360</td>\n",
       "      <td>168.400</td>\n",
       "      <td>168.330</td>\n",
       "      <td>168.3800</td>\n",
       "      <td>130968.0</td>\n",
       "      <td>1420.0</td>\n",
       "      <td>168.364799</td>\n",
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       "    <tr>\n",
       "      <th>2023-04-27 15:28:00-04:00</th>\n",
       "      <td>168.380</td>\n",
       "      <td>168.430</td>\n",
       "      <td>168.320</td>\n",
       "      <td>168.3285</td>\n",
       "      <td>152193.0</td>\n",
       "      <td>1361.0</td>\n",
       "      <td>168.372671</td>\n",
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       "      <th>2023-04-27 15:29:00-04:00</th>\n",
       "      <td>168.325</td>\n",
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       "      <td>1736.0</td>\n",
       "      <td>168.297379</td>\n",
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       "    <tr>\n",
       "      <th>2023-04-27 15:30:00-04:00</th>\n",
       "      <td>168.280</td>\n",
       "      <td>168.350</td>\n",
       "      <td>168.255</td>\n",
       "      <td>168.3450</td>\n",
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       "      <td>1694.0</td>\n",
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       "                              open     high      low     close     volume  \\\n",
       "timestamp                                                                   \n",
       "2023-02-28 09:30:00-05:00  147.050  147.380  146.830  147.2700  1554100.0   \n",
       "2023-02-28 09:31:00-05:00  147.250  147.320  147.180  147.2942   159387.0   \n",
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       "...                            ...      ...      ...       ...        ...   \n",
       "2023-04-27 15:26:00-04:00  168.400  168.415  168.340  168.3601   163973.0   \n",
       "2023-04-27 15:27:00-04:00  168.360  168.400  168.330  168.3800   130968.0   \n",
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       "2023-04-27 15:29:00-04:00  168.325  168.330  168.260  168.2850   208426.0   \n",
       "2023-04-27 15:30:00-04:00  168.280  168.350  168.255  168.3450   218077.0   \n",
       "\n",
       "                           trade_count        vwap  \n",
       "timestamp                                           \n",
       "2023-02-28 09:30:00-05:00       6447.0  146.914560  \n",
       "2023-02-28 09:31:00-05:00       6855.0  147.252171  \n",
       "2023-02-28 09:32:00-05:00       7435.0  147.210128  \n",
       "2023-02-28 09:33:00-05:00       7235.0  147.154832  \n",
       "2023-02-28 09:34:00-05:00       4965.0  147.001762  \n",
       "...                                ...         ...  \n",
       "2023-04-27 15:26:00-04:00       1398.0  168.368809  \n",
       "2023-04-27 15:27:00-04:00       1420.0  168.364799  \n",
       "2023-04-27 15:28:00-04:00       1361.0  168.372671  \n",
       "2023-04-27 15:29:00-04:00       1736.0  168.297379  \n",
       "2023-04-27 15:30:00-04:00       1694.0  168.308873  \n",
       "\n",
       "[15162 rows x 7 columns]"
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     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[('AAPL',)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th rowspan=\"11\" valign=\"top\">AAPL</th>\n",
       "      <th>2023-02-27 18:52:00-05:00</th>\n",
       "      <td>148.0200</td>\n",
       "      <td>148.02</td>\n",
       "      <td>148.0200</td>\n",
       "      <td>148.02</td>\n",
       "      <td>112.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>148.020000</td>\n",
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       "    <tr>\n",
       "      <th>2023-02-27 18:56:00-05:00</th>\n",
       "      <td>148.0200</td>\n",
       "      <td>148.02</td>\n",
       "      <td>148.0200</td>\n",
       "      <td>148.02</td>\n",
       "      <td>175.0</td>\n",
       "      <td>10.0</td>\n",
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       "    <tr>\n",
       "      <th>2023-02-27 19:00:00-05:00</th>\n",
       "      <td>148.0299</td>\n",
       "      <td>148.03</td>\n",
       "      <td>148.0299</td>\n",
       "      <td>148.03</td>\n",
       "      <td>1957.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>148.029993</td>\n",
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       "      <th>2023-02-27 19:06:00-05:00</th>\n",
       "      <td>148.0600</td>\n",
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       "      <td>148.0600</td>\n",
       "      <td>148.06</td>\n",
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       "      <td>7.0</td>\n",
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       "    <tr>\n",
       "      <th>2023-02-27 19:09:00-05:00</th>\n",
       "      <td>148.0500</td>\n",
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       "      <td>148.0500</td>\n",
       "      <td>148.10</td>\n",
       "      <td>1604.0</td>\n",
       "      <td>33.0</td>\n",
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       "    <tr>\n",
       "      <th>2023-04-27 19:54:00-04:00</th>\n",
       "      <td>167.8000</td>\n",
       "      <td>167.80</td>\n",
       "      <td>167.8000</td>\n",
       "      <td>167.80</td>\n",
       "      <td>534.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>167.800000</td>\n",
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       "    <tr>\n",
       "      <th>2023-04-27 19:56:00-04:00</th>\n",
       "      <td>167.8800</td>\n",
       "      <td>167.88</td>\n",
       "      <td>167.8800</td>\n",
       "      <td>167.88</td>\n",
       "      <td>1386.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>167.880000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-04-27 19:57:00-04:00</th>\n",
       "      <td>167.8000</td>\n",
       "      <td>167.80</td>\n",
       "      <td>167.8000</td>\n",
       "      <td>167.80</td>\n",
       "      <td>912.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>167.800000</td>\n",
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       "      <th>2023-04-27 19:58:00-04:00</th>\n",
       "      <td>167.8000</td>\n",
       "      <td>167.88</td>\n",
       "      <td>167.8000</td>\n",
       "      <td>167.88</td>\n",
       "      <td>3311.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>167.877333</td>\n",
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       "    <tr>\n",
       "      <th>2023-04-27 19:59:00-04:00</th>\n",
       "      <td>167.9000</td>\n",
       "      <td>167.94</td>\n",
       "      <td>167.9000</td>\n",
       "      <td>167.94</td>\n",
       "      <td>1969.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>167.918150</td>\n",
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       "<p>31217 rows × 7 columns</p>\n",
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      ],
      "text/plain": [
       "                                      open    high       low   close  volume  \\\n",
       "symbol timestamp                                                               \n",
       "AAPL   2023-02-27 18:52:00-05:00  148.0200  148.02  148.0200  148.02   112.0   \n",
       "       2023-02-27 18:56:00-05:00  148.0200  148.02  148.0200  148.02   175.0   \n",
       "       2023-02-27 19:00:00-05:00  148.0299  148.03  148.0299  148.03  1957.0   \n",
       "       2023-02-27 19:06:00-05:00  148.0600  148.06  148.0600  148.06   122.0   \n",
       "       2023-02-27 19:09:00-05:00  148.0500  148.10  148.0500  148.10  1604.0   \n",
       "...                                    ...     ...       ...     ...     ...   \n",
       "       2023-04-27 19:54:00-04:00  167.8000  167.80  167.8000  167.80   534.0   \n",
       "       2023-04-27 19:56:00-04:00  167.8800  167.88  167.8800  167.88  1386.0   \n",
       "       2023-04-27 19:57:00-04:00  167.8000  167.80  167.8000  167.80   912.0   \n",
       "       2023-04-27 19:58:00-04:00  167.8000  167.88  167.8000  167.88  3311.0   \n",
       "       2023-04-27 19:59:00-04:00  167.9000  167.94  167.9000  167.94  1969.0   \n",
       "\n",
       "                                  trade_count        vwap  \n",
       "symbol timestamp                                           \n",
       "AAPL   2023-02-27 18:52:00-05:00          7.0  148.020000  \n",
       "       2023-02-27 18:56:00-05:00         10.0  148.020000  \n",
       "       2023-02-27 19:00:00-05:00         10.0  148.029993  \n",
       "       2023-02-27 19:06:00-05:00          7.0  148.060000  \n",
       "       2023-02-27 19:09:00-05:00         33.0  148.075109  \n",
       "...                                       ...         ...  \n",
       "       2023-04-27 19:54:00-04:00         15.0  167.800000  \n",
       "       2023-04-27 19:56:00-04:00         28.0  167.880000  \n",
       "       2023-04-27 19:57:00-04:00         60.0  167.800000  \n",
       "       2023-04-27 19:58:00-04:00         22.0  167.877333  \n",
       "       2023-04-27 19:59:00-04:00         64.0  167.918150  \n",
       "\n",
       "[31217 rows x 7 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  }
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