20211110_Prática com Metatrader.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Código criado para demonstrar como utilizar o Metatrader para extrair dados de ativos brasileiros"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import MetaTrader5 as mt5\n",
    "import time\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mt5.initialize()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "winfut= mt5.symbol_info_tick"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pytz"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "from datetime import datetime"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "timezone = pytz.timezone(\"Etc/GMT-3\")\n",
    "\n",
    "inicio = datetime(2021, 10, 18, hour = 15, tzinfo = timezone)\n",
    "fim = datetime(2021, 9, 27, hour = 17, tzinfo = timezone)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='time'>"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dados = mt5.copy_ticks_from(\"WINZ21\",inicio,500000, mt5.COPY_TICKS_ALL)\n",
    "\n",
    "# a partir dos dados recebidos criamos o DataFrame\n",
    "dados_frame = pd.DataFrame(dados)\n",
    "\n",
    "# convertemos o tempo em segundos no formato datetime\n",
    "dados_frame['time']=pd.to_datetime(dados_frame['time'], unit='s')\n",
    "\n",
    "dados_frame.index = dados_frame['time']\n",
    "dados_frame['last'].plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Vamos extrair 500 barras do WINZ21"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([(1634169600, 116100., 116120., 115375., 115650.,      16, 5,       36),\n",
       "       (1634256000, 116300., 117170., 116300., 116985.,      10, 5,       15),\n",
       "       (1634515200, 116315., 117290., 115250., 116750.,      44, 5,       51),\n",
       "       (1634601600, 116810., 116810., 112410., 113575.,     112, 5,      224),\n",
       "       (1634688000, 113015., 114500., 111400., 111505.,      88, 5,      157),\n",
       "       (1634774400, 110500., 111800., 108465., 110250.,      87, 5,      191),\n",
       "       (1634860800, 109250., 110000., 105515., 108485.,      93, 5,      190),\n",
       "       (1635120000, 109585., 111500., 108860., 111090.,      39, 5,       76),\n",
       "       (1635206400, 110200., 110200., 108735., 109150.,      32, 5,       88),\n",
       "       (1635292800, 109000., 110600., 108810., 109405.,      28, 5,       63),\n",
       "       (1635379200, 109120., 109435., 106965., 106965.,      13, 5,       22),\n",
       "       (1635465600, 107500., 108600., 106000., 106065.,      16, 5,       28),\n",
       "       (1635724800, 106600., 108265., 106600., 107615.,      17, 5,       26),\n",
       "       (1635897600, 106985., 109500., 106600., 108650.,      26, 5,       36),\n",
       "       (1635984000, 108700., 108700., 105350., 105700.,      31, 5,      105),\n",
       "       (1636070400, 106700., 107695., 106700., 107150.,      12, 5,       20),\n",
       "       (1636329600, 106215., 107745., 106215., 107255.,      50, 5,       78),\n",
       "       (1636416000, 107215., 108500., 107215., 107390.,      17, 5,       35),\n",
       "       (1636502400, 106885., 109630., 106885., 108400.,     145, 5,      187),\n",
       "       (1636588800, 109000., 110785., 109000., 110400.,      32, 5,       59),\n",
       "       (1636675200, 109910., 110145., 108000., 108575.,      36, 5,      206),\n",
       "       (1637020800, 108900., 109055., 106490., 106650.,      30, 5,       78),\n",
       "       (1637107200, 107220., 107725., 104710., 105400.,      36, 5,       59),\n",
       "       (1637193600, 105280., 105385., 104200., 104710.,      25, 5,       72),\n",
       "       (1637280000, 104500., 106000., 104500., 105035.,       9, 5,       16),\n",
       "       (1637539200, 105470., 106465., 104000., 104000.,      43, 5,      191),\n",
       "       (1637625600, 104565., 106025., 103790., 105950.,      90, 5,      377),\n",
       "       (1637712000, 105635., 106910., 104260., 106585.,      85, 5,      275),\n",
       "       (1637798400, 106345., 108445., 106345., 107965.,      71, 5,      251),\n",
       "       (1637884800, 105000., 105425., 103530., 104280.,      94, 5,      253),\n",
       "       (1638144000, 105300., 106000., 104540., 104860.,      40, 5,       67),\n",
       "       (1638230400, 103985., 104685., 102090., 104230.,      94, 5,      387),\n",
       "       (1638316800, 104980., 106000., 102420., 102420.,     195, 5,     1081),\n",
       "       (1638403200, 103330., 106840., 103330., 106840.,     132, 5,      516),\n",
       "       (1638489600, 106000., 108500., 105595., 107090.,     226, 5,      775),\n",
       "       (1638748800, 107490., 109390., 107350., 108925.,     153, 5,      508),\n",
       "       (1638835200, 110045., 110400., 108860., 109510.,     123, 5,      559),\n",
       "       (1638921600, 109985., 110250., 109040., 109995.,     123, 5,      476),\n",
       "       (1639008000, 109005., 109095., 107525., 107800.,     182, 5,      604),\n",
       "       (1639094400, 108600., 109950., 108600., 109550.,     379, 5,      797),\n",
       "       (1639353600, 109900., 111145., 108830., 109295.,   27767, 5,    46803),\n",
       "       (1639440000, 109100., 110765., 108000., 108160.,  139760, 5,   344204),\n",
       "       (1639526400, 108400., 109145., 107175., 109075., 5747854, 5, 19259075),\n",
       "       (1639612800, 109830., 110535., 109140., 109965., 5482260, 5, 18670154),\n",
       "       (1639699200, 109470., 109500., 107910., 108495., 5499659, 5, 18817623),\n",
       "       (1639958400, 107200., 107420., 105685., 106550., 5588653, 5, 18497332),\n",
       "       (1640044800, 107405., 107580., 106335., 106640., 4667303, 5, 16589166),\n",
       "       (1640131200, 106550., 107070., 105645., 106835., 4347066, 5, 15387560),\n",
       "       (1640217600, 107080., 107245., 105600., 105600., 3485855, 5, 13574050),\n",
       "       (1640563200, 106100., 106960., 105935., 106900., 3503806, 5, 13215801),\n",
       "       (1640649600, 107100., 107165., 105625., 105960., 3667839, 5, 13534152),\n",
       "       (1640736000, 106100., 106445., 104905., 104995., 4135051, 5, 13634552),\n",
       "       (1640822400, 105200., 106490., 105180., 105865., 4101090, 5, 12849042),\n",
       "       (1641168000, 106395., 107245., 104360., 104760., 4876010, 5, 16558852),\n",
       "       (1641254400, 105440., 105785., 104040., 104435., 5299069, 5, 17711170),\n",
       "       (1641340800, 104570., 104695., 101580., 101580., 5872625, 5, 20679806),\n",
       "       (1641427200, 101975., 103180., 101645., 102600., 6019648, 5, 19816776),\n",
       "       (1641513600, 102385., 103720., 101855., 103410., 5308818, 5, 18728267),\n",
       "       (1641772800, 102900., 103405., 101750., 103315., 5657825, 5, 20817377),\n",
       "       (1641859200, 103400., 104875., 102565., 104775., 4979772, 5, 19154744),\n",
       "       (1641945600, 104800., 106740., 104375., 106740., 5064136, 5, 19387371),\n",
       "       (1642032000, 106300., 107015., 105650., 106300., 5829582, 5, 21190305),\n",
       "       (1642118400, 106135., 107985., 105700., 107985., 5674912, 5, 20485106),\n",
       "       (1642377600, 107660., 107855., 106715., 107000., 3843326, 5, 14107960),\n",
       "       (1642464000, 106300., 107745., 106155., 107530., 5777585, 5, 22539010),\n",
       "       (1642550400, 107530., 109315., 107510., 108850., 5355526, 5, 19929823),\n",
       "       (1642636800, 109400., 110515., 108800., 109850., 5000271, 5, 18510736),\n",
       "       (1642723200, 109500., 110430., 108890., 109550., 6856994, 5, 23576438),\n",
       "       (1642982400, 108955., 109350., 107135., 109015., 8194163, 5, 27186985),\n",
       "       (1643068800, 108475., 111340., 107625., 110805., 7029434, 5, 24670212),\n",
       "       (1643155200, 111570., 113270., 111425., 112080., 7532199, 5, 25278224),\n",
       "       (1643241600, 112110., 113580., 112100., 112900., 7206036, 5, 24713337),\n",
       "       (1643328000, 112640., 113480., 112170., 112380.,  776418, 0, 10731822)],\n",
       "      dtype=[('time', '<i8'), ('open', '<f8'), ('high', '<f8'), ('low', '<f8'), ('close', '<f8'), ('tick_volume', '<u8'), ('spread', '<i4'), ('real_volume', '<u8')])"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mt5.copy_rates_from_pos('WING22',mt5.TIMEFRAME_D1, 0, 500)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "ativo = 'WINZ21'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "winfut(ativo)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "ativo = mt5.symbol_info_tick(\"WINZ21\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "115865.0"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ativo.last"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "115830.0\n",
      "115835.0\n",
      "115830.0\n",
      "115835.0\n",
      "115830.0\n",
      "115830.0\n",
      "115830.0\n",
      "115830.0\n",
      "115835.0\n",
      "115830.0\n",
      "115835.0\n",
      "115840.0\n",
      "115835.0\n"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-52-3d4f98eac95c>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      4\u001b[0m     \u001b[0msys\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mstdout\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mflush\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 6\u001b[1;33m     \u001b[0mtime\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msleep\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m0.5\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "while(True):\n",
    "    ativo = mt5.symbol_info_tick(\"WINZ21\")\n",
    "    print(\"\\r\" + str(ativo.last))\n",
    "    sys.stdout.flush()\n",
    "    \n",
    "    time.sleep(0.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "107730.0"
     ]
    }
   ],
   "source": [
    "import sys\n",
    "import MetaTrader5 as mt5\n",
    "import time\n",
    "\n",
    "mt5.initialize()\n",
    "\n",
    "while(True):\n",
    "    ativo = mt5.symbol_info_tick(\"WINZ21\")\n",
    "    sys.stdout.write(\"\\r\" + str(ativo.last))\n",
    "    sys.stdout.flush()\n",
    "    \n",
    "    time.sleep(0.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "import MetaTrader5 as mt5\n",
    "import time\n",
    "import streamlit as st"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "mt5.initialize()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "115735.0"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-53-ce5636c87f0d>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      4\u001b[0m     \u001b[0msys\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mstdout\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mflush\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 6\u001b[1;33m     \u001b[0mtime\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msleep\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m0.5\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "while(True):\n",
    "    ativo = mt5.symbol_info_tick(\"WINZ21\")\n",
    "    sys.stdout.write(\"\\r\" + str(ativo.last))\n",
    "    sys.stdout.flush()\n",
    "    \n",
    "    time.sleep(0.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "999"
     ]
    }
   ],
   "source": [
    "import time\n",
    "import sys\n",
    "\n",
    "for i in range(1000):\n",
    "    #print(i)\n",
    "    sys.stdout.write('\\r' + str(i))\n",
    "    #sys.stdout.flush()\n",
    "    time.sleep(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2. Abrindo bibliotecas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "from datetime import datetime\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "from pandas.plotting import register_matplotlib_converters\n",
    "register_matplotlib_converters()\n",
    "import MetaTrader5 as mt5\n",
    "import pytz"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 3. Primeiros passos"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Se a sua conta estiver OK junto à corretora, login será automático ao acionar o Metatrader pelo método abaixo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 269,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 269,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mt5.initialize()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Uma outra opção é pedir que ele exiba uma mensagem caso a inicialização não funcione"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "# conecte-se ao MetaTrader 5\n",
    "if not mt5.initialize():\n",
    "    print(\"initialize() failed\")\n",
    "    mt5.shutdown()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Você também pode fazer o login pelo Python, embora não preciso aqui pois o software já possui minhas informações de login"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "mt5.login(\n",
    "   login,                    # número da conta\n",
    "   password=\"PASSWORD\",      # senha\n",
    "   server=\"SERVER\",          # nome do servidor como definido no terminal\n",
    "   timeout=TIMEOUT           # tempo de espera esgotado (opcional)\n",
    "   )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(500, 2981, '21 Jun 2021')"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# obtemos informações sobre a versão do MetaTrader 5\n",
    "mt5.version()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "TerminalInfo(community_account=False, community_connection=False, connected=True, dlls_allowed=False, trade_allowed=False, tradeapi_disabled=False, email_enabled=False, ftp_enabled=False, notifications_enabled=False, mqid=False, build=2981, maxbars=100000, codepage=1252, ping_last=6156, community_balance=0.0, retransmission=0.0, company='MetaQuotes Software Corp.', name='MetaTrader 5', language='Portuguese (Brazil)', path='C:\\\\Program Files\\\\MetaTrader 5', data_path='C:\\\\Users\\\\victo\\\\AppData\\\\Roaming\\\\MetaQuotes\\\\Terminal\\\\D0E8209F77C8CF37AD8BF550E51FF075', commondata_path='C:\\\\Users\\\\victo\\\\AppData\\\\Roaming\\\\MetaQuotes\\\\Terminal\\\\Common')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# consultamos o estado e os parâmetros de conexão\n",
    "mt5.terminal_info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AccountInfo(login=1000080735, trade_mode=2, leverage=1, limit_orders=0, margin_so_mode=1, trade_allowed=True, trade_expert=True, margin_mode=0, currency_digits=2, fifo_close=False, balance=0.0, credit=0.0, profit=0.0, equity=0.0, margin=0.0, margin_free=0.0, margin_level=0.0, margin_so_call=0.0, margin_so_so=0.0, margin_initial=0.0, margin_maintenance=0.0, assets=0.0, liabilities=0.0, commission_blocked=0.0, name='VICTOR NOGUEIRA CORTEZ GOMES', server='ClearInvestimentos-CLEAR', currency='BRL', company='Clear (XP Investimentos CCTVM)')"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mt5.account_info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Quantos instrumentos financeiros?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "21961"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mt5.symbols_total()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Que ticks são esses?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(SymbolInfo(custom=False, chart_mode=1, select=False, visible=False, session_deals=0, session_buy_orders=0, session_sell_orders=0, volume=0, volumehigh=0, volumelow=0, time=0, digits=2, spread=0, spread_float=True, ticks_bookdepth=32, trade_calc_mode=32, trade_mode=4, start_time=0, expiration_time=0, trade_stops_level=0, trade_freeze_level=0, trade_exemode=3, swap_mode=0, swap_rollover3days=3, margin_hedged_use_leg=False, expiration_mode=2, filling_mode=3, order_mode=127, order_gtc_mode=0, option_mode=0, option_right=0, bid=0.0, bidhigh=0.0, bidlow=0.0, ask=0.0, askhigh=0.0, asklow=0.0, last=0.0, lasthigh=0.0, lastlow=0.0, volume_real=0.0, volumehigh_real=0.0, volumelow_real=0.0, option_strike=0.0, point=0.01, trade_tick_value=0.01, trade_tick_value_profit=0.01, trade_tick_value_loss=0.01, trade_tick_size=0.01, trade_contract_size=1.0, trade_accrued_interest=0.0, trade_face_value=0.0, trade_liquidity_rate=0.0, volume_min=1.0, volume_max=1653017000.0, volume_step=1.0, volume_limit=0.0, swap_long=0.0, swap_short=0.0, margin_initial=0.0, margin_maintenance=0.0, session_volume=0.0, session_turnover=0.0, session_interest=0.0, session_buy_orders_volume=0.0, session_sell_orders_volume=0.0, session_open=0.0, session_close=0.0, session_aw=0.0, session_price_settlement=0.0, session_price_limit_min=0.0, session_price_limit_max=0.0, margin_hedged=0.0, price_change=0.0, price_volatility=0.0, price_theoretical=0.0, price_greeks_delta=0.0, price_greeks_theta=0.0, price_greeks_gamma=0.0, price_greeks_vega=0.0, price_greeks_rho=0.0, price_greeks_omega=0.0, price_sensitivity=0.0, basis='', category='', currency_base='BRL', currency_profit='BRL', currency_margin='BRL', bank='', description='APPLE       DRN', exchange='', formula='', isin='BRAAPLBDR004', name='AAPL34', page='', path='BOVESPA\\\\A VISTA\\\\AAPL34'),)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mt5.symbols_get('AAPL')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "dict_weg = mt5.symbols_get('WEGE')[0]._asdict()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'BOVESPA\\\\A VISTA\\\\WEGE3'"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dict_weg['path']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SymbolInfo(custom=False, chart_mode=1, select=True, visible=True, session_deals=9760, session_buy_orders=0, session_sell_orders=0, volume=100, volumehigh=23200, volumelow=100, time=1632748956, digits=2, spread=1, spread_float=True, ticks_bookdepth=32, trade_calc_mode=32, trade_mode=4, start_time=0, expiration_time=0, trade_stops_level=0, trade_freeze_level=0, trade_exemode=3, swap_mode=0, swap_rollover3days=3, margin_hedged_use_leg=False, expiration_mode=2, filling_mode=3, order_mode=127, order_gtc_mode=0, option_mode=0, option_right=0, bid=40.96, bidhigh=41.14, bidlow=40.42, ask=40.97, askhigh=41.16, asklow=40.45, last=40.97, lasthigh=41.16, lastlow=40.42, volume_real=100.0, volumehigh_real=23200.0, volumelow_real=100.0, option_strike=0.0, point=0.01, trade_tick_value=0.01, trade_tick_value_profit=0.01, trade_tick_value_loss=0.01, trade_tick_size=0.01, trade_contract_size=1.0, trade_accrued_interest=0.0, trade_face_value=0.0, trade_liquidity_rate=0.0, volume_min=100.0, volume_max=41973180.0, volume_step=100.0, volume_limit=0.0, swap_long=0.0, swap_short=0.0, margin_initial=0.0, margin_maintenance=0.0, session_volume=2510900.0, session_turnover=0.0, session_interest=0.0, session_buy_orders_volume=0.0, session_sell_orders_volume=0.0, session_open=41.06, session_close=41.32, session_aw=40.79, session_price_settlement=0.0, session_price_limit_min=0.0, session_price_limit_max=0.0, margin_hedged=0.0, price_change=-0.847, price_volatility=0.0, price_theoretical=0.0, price_greeks_delta=0.0, price_greeks_theta=0.0, price_greeks_gamma=0.0, price_greeks_vega=0.0, price_greeks_rho=0.0, price_greeks_omega=0.0, price_sensitivity=0.0, basis='', category='', currency_base='BRL', currency_profit='BRL', currency_margin='BRL', bank='', description='WEG         ON  EJ  NM', exchange='', formula='', isin='BRWEGEACNOR0', name='WEGE3', page='', path='BOVESPA\\\\A VISTA\\\\WEGE3')"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mt5.symbol_info(\"WEGE3\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Tick(time=1632748989, bid=40.97, ask=40.98, last=40.97, volume=100, time_msc=1632748989355, flags=6, volume_real=100.0)"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mt5.symbol_info_tick(\"WEGE3\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Tick(time=1632748989, bid=40.97, ask=40.98, last=40.97, volume=100, time_msc=1632748989355, flags=6, volume_real=100.0)"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mt5.symbol_info_tick(\"WEGE3\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Tick(time=1632749023, bid=40.97, ask=40.98, last=40.98, volume=100, time_msc=1632749023245, flags=0, volume_real=100.0)"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mt5.symbol_info_tick(\"WEGE3\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "import time\n",
    "\n",
    "t_end = time.time() + 60 * 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tick(time=1632749229, bid=27.39, ask=27.41, last=27.41, volume=100, time_msc=1632749229820, flags=0, volume_real=100.0)\n",
      "Tick(time=1632749232, bid=27.39, ask=27.41, last=27.39, volume=100, time_msc=1632749232268, flags=0, volume_real=100.0)\n",
      "Tick(time=1632749233, bid=27.39, ask=27.41, last=27.39, volume=200, time_msc=1632749233455, flags=88, volume_real=200.0)\n",
      "Tick(time=1632749236, bid=27.39, ask=27.41, last=27.4, volume=1000, time_msc=1632749236520, flags=0, volume_real=1000.0)\n",
      "Tick(time=1632749238, bid=27.39, ask=27.41, last=27.41, volume=100, time_msc=1632749238599, flags=0, volume_real=100.0)\n",
      "Tick(time=1632749240, bid=27.38, ask=27.4, last=27.4, volume=300, time_msc=1632749240596, flags=56, volume_real=300.0)\n",
      "Tick(time=1632749241, bid=27.38, ask=27.4, last=27.38, volume=100, time_msc=1632749241017, flags=0, volume_real=100.0)\n",
      "Tick(time=1632749244, bid=27.38, ask=27.4, last=27.38, volume=400, time_msc=1632749244673, flags=88, volume_real=400.0)\n",
      "Tick(time=1632749246, bid=27.38, ask=27.4, last=27.4, volume=100, time_msc=1632749246397, flags=0, volume_real=100.0)\n",
      "Tick(time=1632749247, bid=27.38, ask=27.4, last=27.4, volume=100, time_msc=1632749247214, flags=56, volume_real=100.0)\n",
      "Tick(time=1632749250, bid=27.38, ask=27.4, last=27.4, volume=200, time_msc=1632749250224, flags=4, volume_real=200.0)\n",
      "Tick(time=1632749252, bid=27.38, ask=27.39, last=27.38, volume=2000, time_msc=1632749252836, flags=0, volume_real=2000.0)\n",
      "Tick(time=1632749254, bid=27.39, ask=27.4, last=27.4, volume=100, time_msc=1632749254316, flags=2, volume_real=100.0)\n",
      "Tick(time=1632749256, bid=27.39, ask=27.4, last=27.39, volume=200, time_msc=1632749256872, flags=0, volume_real=200.0)\n",
      "Tick(time=1632749258, bid=27.38, ask=27.4, last=27.38, volume=100, time_msc=1632749258734, flags=0, volume_real=100.0)\n",
      "Tick(time=1632749260, bid=27.39, ask=27.4, last=27.4, volume=200, time_msc=1632749260807, flags=0, volume_real=200.0)\n",
      "Tick(time=1632749262, bid=27.39, ask=27.41, last=27.39, volume=100, time_msc=1632749262827, flags=0, volume_real=100.0)\n",
      "Tick(time=1632749264, bid=27.39, ask=27.41, last=27.4, volume=1000, time_msc=1632749264781, flags=0, volume_real=1000.0)\n",
      "Tick(time=1632749266, bid=27.39, ask=27.41, last=27.39, volume=100, time_msc=1632749266842, flags=0, volume_real=100.0)\n",
      "Tick(time=1632749268, bid=27.39, ask=27.41, last=27.4, volume=1000, time_msc=1632749268831, flags=0, volume_real=1000.0)\n",
      "Tick(time=1632749270, bid=27.39, ask=27.41, last=27.39, volume=100, time_msc=1632749270873, flags=0, volume_real=100.0)\n",
      "Tick(time=1632749272, bid=27.39, ask=27.41, last=27.4, volume=100, time_msc=1632749272857, flags=0, volume_real=100.0)\n",
      "Tick(time=1632749274, bid=27.39, ask=27.41, last=27.4, volume=1000, time_msc=1632749274840, flags=0, volume_real=1000.0)\n",
      "Tick(time=1632749276, bid=27.39, ask=27.41, last=27.4, volume=1000, time_msc=1632749276761, flags=0, volume_real=1000.0)\n",
      "Tick(time=1632749278, bid=27.4, ask=27.41, last=27.4, volume=500, time_msc=1632749278274, flags=0, volume_real=500.0)\n",
      "Tick(time=1632749280, bid=27.4, ask=27.41, last=27.41, volume=100, time_msc=1632749280979, flags=0, volume_real=100.0)\n",
      "Tick(time=1632749282, bid=27.4, ask=27.41, last=27.41, volume=100, time_msc=1632749282981, flags=0, volume_real=100.0)\n",
      "Tick(time=1632749284, bid=27.4, ask=27.41, last=27.4, volume=200, time_msc=1632749284511, flags=0, volume_real=200.0)\n",
      "Tick(time=1632749286, bid=27.4, ask=27.41, last=27.4, volume=200, time_msc=1632749286016, flags=0, volume_real=200.0)\n",
      "Tick(time=1632749288, bid=27.4, ask=27.41, last=27.4, volume=100, time_msc=1632749288973, flags=0, volume_real=100.0)\n"
     ]
    }
   ],
   "source": [
    "import time\n",
    "\n",
    "t_end = time.time() + 60 * 1\n",
    "\n",
    "while time.time() < t_end:\n",
    "\n",
    "    x = mt5.symbol_info_tick(\"PETR4\")\n",
    "    \n",
    "    print(x)\n",
    "\n",
    "    time.sleep(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Quando terminarmos as nossas tarefas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# concluímos a conexão ao terminal MetaTrader 5\n",
    "mt5.shutdown()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "ativo = 'ITUB4'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Pesquisando por símbolos"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(SymbolInfo(custom=False, chart_mode=1, select=False, visible=False, session_deals=0, session_buy_orders=0, session_sell_orders=0, volume=0, volumehigh=0, volumelow=0, time=0, digits=0, spread=0, spread_float=True, ticks_bookdepth=32, trade_calc_mode=33, trade_mode=0, start_time=0, expiration_time=0, trade_stops_level=0, trade_freeze_level=0, trade_exemode=3, swap_mode=0, swap_rollover3days=3, margin_hedged_use_leg=False, expiration_mode=2, filling_mode=3, order_mode=127, order_gtc_mode=2, option_mode=0, option_right=0, bid=0.0, bidhigh=0.0, bidlow=0.0, ask=0.0, askhigh=0.0, asklow=0.0, last=0.0, lasthigh=0.0, lastlow=0.0, volume_real=0.0, volumehigh_real=0.0, volumelow_real=0.0, option_strike=0.0, point=1.0, trade_tick_value=0.2, trade_tick_value_profit=0.2, trade_tick_value_loss=0.2, trade_tick_size=1.0, trade_contract_size=1.0, trade_accrued_interest=0.0, trade_face_value=0.0, trade_liquidity_rate=0.0, volume_min=1.0, volume_max=10000.0, volume_step=1.0, volume_limit=0.0, swap_long=0.0, swap_short=0.0, margin_initial=0.0, margin_maintenance=0.0, session_volume=0.0, session_turnover=0.0, session_interest=0.0, session_buy_orders_volume=0.0, session_sell_orders_volume=0.0, session_open=0.0, session_close=0.0, session_aw=0.0, session_price_settlement=0.0, session_price_limit_min=0.0, session_price_limit_max=0.0, margin_hedged=0.0, price_change=0.0, price_volatility=0.0, price_theoretical=0.0, price_greeks_delta=0.0, price_greeks_theta=0.0, price_greeks_gamma=0.0, price_greeks_vega=0.0, price_greeks_rho=0.0, price_greeks_omega=0.0, price_sensitivity=0.0, basis='', category='', currency_base='BRL', currency_profit='BRL', currency_margin='BRL', bank='', description='IBOVESPA MINI - Por Liquidez (WINZ21) - Ajuste Proporcional', exchange='', formula='', isin='BRBMEFWIN2V0', name='WIN$', page='', path='BMF\\\\SERIES CONTINUAS\\\\WIN$'),\n",
       " SymbolInfo(custom=False, chart_mode=1, select=False, visible=False, session_deals=0, session_buy_orders=0, session_sell_orders=0, volume=0, volumehigh=0, volumelow=0, time=0, digits=0, spread=0, spread_float=True, ticks_bookdepth=32, trade_calc_mode=33, trade_mode=0, start_time=0, expiration_time=0, trade_stops_level=0, trade_freeze_level=0, trade_exemode=3, swap_mode=0, swap_rollover3days=3, margin_hedged_use_leg=False, expiration_mode=2, filling_mode=3, order_mode=127, order_gtc_mode=2, option_mode=0, option_right=0, bid=0.0, bidhigh=0.0, bidlow=0.0, ask=0.0, askhigh=0.0, asklow=0.0, last=0.0, lasthigh=0.0, lastlow=0.0, volume_real=0.0, volumehigh_real=0.0, volumelow_real=0.0, option_strike=0.0, point=1.0, trade_tick_value=1.0, trade_tick_value_profit=1.0, trade_tick_value_loss=1.0, trade_tick_size=5.0, trade_contract_size=1.0, trade_accrued_interest=0.0, trade_face_value=0.0, trade_liquidity_rate=0.0, volume_min=1.0, volume_max=10000.0, volume_step=1.0, volume_limit=0.0, swap_long=0.0, swap_short=0.0, margin_initial=0.0, margin_maintenance=0.0, session_volume=0.0, session_turnover=0.0, session_interest=0.0, session_buy_orders_volume=0.0, session_sell_orders_volume=0.0, session_open=0.0, session_close=0.0, session_aw=0.0, session_price_settlement=0.0, session_price_limit_min=0.0, session_price_limit_max=0.0, margin_hedged=0.0, price_change=0.0, price_volatility=0.0, price_theoretical=0.0, price_greeks_delta=0.0, price_greeks_theta=0.0, price_greeks_gamma=0.0, price_greeks_vega=0.0, price_greeks_rho=0.0, price_greeks_omega=0.0, price_sensitivity=0.0, basis='', category='', currency_base='BRL', currency_profit='BRL', currency_margin='BRL', bank='', description='IBOVESPA MINI - Por Liquidez (WINZ21) - Ajuste por Diferença', exchange='', formula='', isin='BRBMEFWIN2V0', name='WIN$D', page='', path='BMF\\\\SERIES CONTINUAS\\\\WIN$D'),\n",
       " SymbolInfo(custom=False, chart_mode=1, select=False, visible=False, session_deals=0, session_buy_orders=0, session_sell_orders=0, volume=0, volumehigh=0, volumelow=0, time=0, digits=0, spread=0, spread_float=True, ticks_bookdepth=32, trade_calc_mode=33, trade_mode=0, start_time=0, expiration_time=0, trade_stops_level=0, trade_freeze_level=0, trade_exemode=3, swap_mode=0, swap_rollover3days=3, margin_hedged_use_leg=False, expiration_mode=2, filling_mode=3, order_mode=127, order_gtc_mode=2, option_mode=0, option_right=0, bid=0.0, bidhigh=0.0, bidlow=0.0, ask=0.0, askhigh=0.0, asklow=0.0, last=0.0, lasthigh=0.0, lastlow=0.0, volume_real=0.0, volumehigh_real=0.0, volumelow_real=0.0, option_strike=0.0, point=1.0, trade_tick_value=1.0, trade_tick_value_profit=1.0, trade_tick_value_loss=1.0, trade_tick_size=5.0, trade_contract_size=1.0, trade_accrued_interest=0.0, trade_face_value=0.0, trade_liquidity_rate=0.0, volume_min=1.0, volume_max=10000.0, volume_step=1.0, volume_limit=0.0, swap_long=0.0, swap_short=0.0, margin_initial=0.0, margin_maintenance=0.0, session_volume=0.0, session_turnover=0.0, session_interest=0.0, session_buy_orders_volume=0.0, session_sell_orders_volume=0.0, session_open=0.0, session_close=0.0, session_aw=0.0, session_price_settlement=0.0, session_price_limit_min=0.0, session_price_limit_max=0.0, margin_hedged=0.0, price_change=0.0, price_volatility=0.0, price_theoretical=0.0, price_greeks_delta=0.0, price_greeks_theta=0.0, price_greeks_gamma=0.0, price_greeks_vega=0.0, price_greeks_rho=0.0, price_greeks_omega=0.0, price_sensitivity=0.0, basis='', category='', currency_base='BRL', currency_profit='BRL', currency_margin='BRL', bank='', description='IBOVESPA MINI - Por Liquidez (WINZ21) - Sem Ajustes', exchange='', formula='', isin='BRBMEFWIN2V0', name='WIN$N', page='', path='BMF\\\\SERIES CONTINUAS\\\\WIN$N'),\n",
       " SymbolInfo(custom=False, chart_mode=1, select=False, visible=False, session_deals=0, session_buy_orders=0, session_sell_orders=0, volume=0, volumehigh=0, volumelow=0, time=0, digits=0, spread=0, spread_float=True, ticks_bookdepth=32, trade_calc_mode=33, trade_mode=0, start_time=0, expiration_time=0, trade_stops_level=0, trade_freeze_level=0, trade_exemode=3, swap_mode=0, swap_rollover3days=3, margin_hedged_use_leg=False, expiration_mode=2, filling_mode=3, order_mode=127, order_gtc_mode=2, option_mode=0, option_right=0, bid=0.0, bidhigh=0.0, bidlow=0.0, ask=0.0, askhigh=0.0, asklow=0.0, last=0.0, lasthigh=0.0, lastlow=0.0, volume_real=0.0, volumehigh_real=0.0, volumelow_real=0.0, option_strike=0.0, point=1.0, trade_tick_value=0.2, trade_tick_value_profit=0.2, trade_tick_value_loss=0.2, trade_tick_size=1.0, trade_contract_size=1.0, trade_accrued_interest=0.0, trade_face_value=0.0, trade_liquidity_rate=0.0, volume_min=1.0, volume_max=10000.0, volume_step=1.0, volume_limit=0.0, swap_long=0.0, swap_short=0.0, margin_initial=0.0, margin_maintenance=0.0, session_volume=0.0, session_turnover=0.0, session_interest=0.0, session_buy_orders_volume=0.0, session_sell_orders_volume=0.0, session_open=0.0, session_close=0.0, session_aw=0.0, session_price_settlement=0.0, session_price_limit_min=0.0, session_price_limit_max=0.0, margin_hedged=0.0, price_change=0.0, price_volatility=0.0, price_theoretical=0.0, price_greeks_delta=0.0, price_greeks_theta=0.0, price_greeks_gamma=0.0, price_greeks_vega=0.0, price_greeks_rho=0.0, price_greeks_omega=0.0, price_sensitivity=0.0, basis='', category='', currency_base='BRL', currency_profit='BRL', currency_margin='BRL', bank='', description='IBOVESPA MINI - Por Vencimento (WINZ21) - Ajuste Proporcional', exchange='', formula='', isin='BRBMEFWIN2V0', name='WIN@', page='', path='BMF\\\\SERIES CONTINUAS\\\\WIN@'),\n",
       " SymbolInfo(custom=False, chart_mode=1, select=False, visible=False, session_deals=0, session_buy_orders=0, session_sell_orders=0, volume=0, volumehigh=0, volumelow=0, time=0, digits=0, spread=0, spread_float=True, ticks_bookdepth=32, trade_calc_mode=33, trade_mode=0, start_time=0, expiration_time=0, trade_stops_level=0, trade_freeze_level=0, trade_exemode=3, swap_mode=0, swap_rollover3days=3, margin_hedged_use_leg=False, expiration_mode=2, filling_mode=3, order_mode=127, order_gtc_mode=2, option_mode=0, option_right=0, bid=0.0, bidhigh=0.0, bidlow=0.0, ask=0.0, askhigh=0.0, asklow=0.0, last=0.0, lasthigh=0.0, lastlow=0.0, volume_real=0.0, volumehigh_real=0.0, volumelow_real=0.0, option_strike=0.0, point=1.0, trade_tick_value=1.0, trade_tick_value_profit=1.0, trade_tick_value_loss=1.0, trade_tick_size=5.0, trade_contract_size=1.0, trade_accrued_interest=0.0, trade_face_value=0.0, trade_liquidity_rate=0.0, volume_min=1.0, volume_max=10000.0, volume_step=1.0, volume_limit=0.0, swap_long=0.0, swap_short=0.0, margin_initial=0.0, margin_maintenance=0.0, session_volume=0.0, session_turnover=0.0, session_interest=0.0, session_buy_orders_volume=0.0, session_sell_orders_volume=0.0, session_open=0.0, session_close=0.0, session_aw=0.0, session_price_settlement=0.0, session_price_limit_min=0.0, session_price_limit_max=0.0, margin_hedged=0.0, price_change=0.0, price_volatility=0.0, price_theoretical=0.0, price_greeks_delta=0.0, price_greeks_theta=0.0, price_greeks_gamma=0.0, price_greeks_vega=0.0, price_greeks_rho=0.0, price_greeks_omega=0.0, price_sensitivity=0.0, basis='', category='', currency_base='BRL', currency_profit='BRL', currency_margin='BRL', bank='', description='IBOVESPA MINI - Por Vencimento (WINZ21) - Ajuste por Diferença', exchange='', formula='', isin='BRBMEFWIN2V0', name='WIN@D', page='', path='BMF\\\\SERIES CONTINUAS\\\\WIN@D'),\n",
       " SymbolInfo(custom=False, chart_mode=1, select=False, visible=False, session_deals=0, session_buy_orders=0, session_sell_orders=0, volume=0, volumehigh=0, volumelow=0, time=0, digits=0, spread=0, spread_float=True, ticks_bookdepth=32, trade_calc_mode=33, trade_mode=0, start_time=0, expiration_time=0, trade_stops_level=0, trade_freeze_level=0, trade_exemode=3, swap_mode=0, swap_rollover3days=3, margin_hedged_use_leg=False, expiration_mode=2, filling_mode=3, order_mode=127, order_gtc_mode=2, option_mode=0, option_right=0, bid=0.0, bidhigh=0.0, bidlow=0.0, ask=0.0, askhigh=0.0, asklow=0.0, last=0.0, lasthigh=0.0, lastlow=0.0, volume_real=0.0, volumehigh_real=0.0, volumelow_real=0.0, option_strike=0.0, point=1.0, trade_tick_value=1.0, trade_tick_value_profit=1.0, trade_tick_value_loss=1.0, trade_tick_size=5.0, trade_contract_size=1.0, trade_accrued_interest=0.0, trade_face_value=0.0, trade_liquidity_rate=0.0, volume_min=1.0, volume_max=10000.0, volume_step=1.0, volume_limit=0.0, swap_long=0.0, swap_short=0.0, margin_initial=0.0, margin_maintenance=0.0, session_volume=0.0, session_turnover=0.0, session_interest=0.0, session_buy_orders_volume=0.0, session_sell_orders_volume=0.0, session_open=0.0, session_close=0.0, session_aw=0.0, session_price_settlement=0.0, session_price_limit_min=0.0, session_price_limit_max=0.0, margin_hedged=0.0, price_change=0.0, price_volatility=0.0, price_theoretical=0.0, price_greeks_delta=0.0, price_greeks_theta=0.0, price_greeks_gamma=0.0, price_greeks_vega=0.0, price_greeks_rho=0.0, price_greeks_omega=0.0, price_sensitivity=0.0, basis='', category='', currency_base='BRL', currency_profit='BRL', currency_margin='BRL', bank='', description='IBOVESPA MINI - Por Vencimento (WINZ21) - Sem Ajustes', exchange='', formula='', isin='BRBMEFWIN2V0', name='WIN@N', page='', path='BMF\\\\SERIES CONTINUAS\\\\WIN@N'),\n",
       " SymbolInfo(custom=False, chart_mode=1, select=False, visible=False, session_deals=0, session_buy_orders=0, session_sell_orders=0, volume=0, volumehigh=0, volumelow=0, time=0, digits=0, spread=0, spread_float=True, ticks_bookdepth=32, trade_calc_mode=33, trade_mode=4, start_time=0, expiration_time=1645038900, trade_stops_level=0, trade_freeze_level=0, trade_exemode=3, swap_mode=0, swap_rollover3days=3, margin_hedged_use_leg=False, expiration_mode=2, filling_mode=3, order_mode=127, order_gtc_mode=2, option_mode=0, option_right=0, bid=0.0, bidhigh=0.0, bidlow=0.0, ask=0.0, askhigh=0.0, asklow=0.0, last=0.0, lasthigh=0.0, lastlow=0.0, volume_real=0.0, volumehigh_real=0.0, volumelow_real=0.0, option_strike=0.0, point=1.0, trade_tick_value=1.0, trade_tick_value_profit=1.0, trade_tick_value_loss=1.0, trade_tick_size=5.0, trade_contract_size=1.0, trade_accrued_interest=0.0, trade_face_value=0.0, trade_liquidity_rate=0.0, volume_min=1.0, volume_max=10000.0, volume_step=1.0, volume_limit=0.0, swap_long=0.0, swap_short=0.0, margin_initial=0.0, margin_maintenance=0.0, session_volume=0.0, session_turnover=0.0, session_interest=0.0, session_buy_orders_volume=0.0, session_sell_orders_volume=0.0, session_open=0.0, session_close=0.0, session_aw=0.0, session_price_settlement=0.0, session_price_limit_min=0.0, session_price_limit_max=0.0, margin_hedged=0.0, price_change=0.0, price_volatility=0.0, price_theoretical=0.0, price_greeks_delta=0.0, price_greeks_theta=0.0, price_greeks_gamma=0.0, price_greeks_vega=0.0, price_greeks_rho=0.0, price_greeks_omega=0.0, price_sensitivity=0.0, basis='', category='', currency_base='BRL', currency_profit='BRL', currency_margin='BRL', bank='', description='IBOVESPA MINI', exchange='', formula='', isin='BRBMEFWIN2W8', name='WING22', page='', path='BMF\\\\WING22'),\n",
       " SymbolInfo(custom=False, chart_mode=1, select=False, visible=False, session_deals=0, session_buy_orders=0, session_sell_orders=0, volume=0, volumehigh=0, volumelow=0, time=0, digits=0, spread=0, spread_float=True, ticks_bookdepth=32, trade_calc_mode=33, trade_mode=4, start_time=0, expiration_time=1676488500, trade_stops_level=0, trade_freeze_level=0, trade_exemode=3, swap_mode=0, swap_rollover3days=3, margin_hedged_use_leg=False, expiration_mode=2, filling_mode=3, order_mode=127, order_gtc_mode=2, option_mode=0, option_right=0, bid=0.0, bidhigh=0.0, bidlow=0.0, ask=0.0, askhigh=0.0, asklow=0.0, last=0.0, lasthigh=0.0, lastlow=0.0, volume_real=0.0, volumehigh_real=0.0, volumelow_real=0.0, option_strike=0.0, point=1.0, trade_tick_value=1.0, trade_tick_value_profit=1.0, trade_tick_value_loss=1.0, trade_tick_size=5.0, trade_contract_size=1.0, trade_accrued_interest=0.0, trade_face_value=0.0, trade_liquidity_rate=0.0, volume_min=1.0, volume_max=400.0, volume_step=1.0, volume_limit=0.0, swap_long=0.0, swap_short=0.0, margin_initial=0.0, margin_maintenance=0.0, session_volume=0.0, session_turnover=0.0, session_interest=0.0, session_buy_orders_volume=0.0, session_sell_orders_volume=0.0, session_open=0.0, session_close=0.0, session_aw=0.0, session_price_settlement=0.0, session_price_limit_min=0.0, session_price_limit_max=0.0, margin_hedged=0.0, price_change=0.0, price_volatility=0.0, price_theoretical=0.0, price_greeks_delta=0.0, price_greeks_theta=0.0, price_greeks_gamma=0.0, price_greeks_vega=0.0, price_greeks_rho=0.0, price_greeks_omega=0.0, price_sensitivity=0.0, basis='', category='', currency_base='BRL', currency_profit='BRL', currency_margin='BRL', bank='', description='IBOVESPA MINI', exchange='', formula='', isin='BRBMEFWIN320', name='WING23', page='', path='BMF\\\\WING23'),\n",
       " SymbolInfo(custom=False, chart_mode=1, select=False, visible=False, session_deals=0, session_buy_orders=0, session_sell_orders=0, volume=0, volumehigh=0, volumelow=0, time=0, digits=0, spread=0, spread_float=True, ticks_bookdepth=32, trade_calc_mode=33, trade_mode=4, start_time=0, expiration_time=1649877300, trade_stops_level=0, trade_freeze_level=0, trade_exemode=3, swap_mode=0, swap_rollover3days=3, margin_hedged_use_leg=False, expiration_mode=2, filling_mode=3, order_mode=127, order_gtc_mode=2, option_mode=0, option_right=0, bid=0.0, bidhigh=0.0, bidlow=0.0, ask=0.0, askhigh=0.0, asklow=0.0, last=0.0, lasthigh=0.0, lastlow=0.0, volume_real=0.0, volumehigh_real=0.0, volumelow_real=0.0, option_strike=0.0, point=1.0, trade_tick_value=1.0, trade_tick_value_profit=1.0, trade_tick_value_loss=1.0, trade_tick_size=5.0, trade_contract_size=1.0, trade_accrued_interest=0.0, trade_face_value=0.0, trade_liquidity_rate=0.0, volume_min=1.0, volume_max=400.0, volume_step=1.0, volume_limit=0.0, swap_long=0.0, swap_short=0.0, margin_initial=0.0, margin_maintenance=0.0, session_volume=0.0, session_turnover=0.0, session_interest=0.0, session_buy_orders_volume=0.0, session_sell_orders_volume=0.0, session_open=0.0, session_close=0.0, session_aw=0.0, session_price_settlement=0.0, session_price_limit_min=0.0, session_price_limit_max=0.0, margin_hedged=0.0, price_change=0.0, price_volatility=0.0, price_theoretical=0.0, price_greeks_delta=0.0, price_greeks_theta=0.0, price_greeks_gamma=0.0, price_greeks_vega=0.0, price_greeks_rho=0.0, price_greeks_omega=0.0, price_sensitivity=0.0, basis='', category='', currency_base='BRL', currency_profit='BRL', currency_margin='BRL', bank='', description='IBOVESPA MINI', exchange='', formula='', isin='BRBMEFWIN2X6', name='WINJ22', page='', path='BMF\\\\WINJ22'),\n",
       " SymbolInfo(custom=False, chart_mode=1, select=False, visible=False, session_deals=0, session_buy_orders=0, session_sell_orders=0, volume=0, volumehigh=0, volumelow=0, time=0, digits=0, spread=0, spread_float=True, ticks_bookdepth=32, trade_calc_mode=33, trade_mode=4, start_time=0, expiration_time=1681326900, trade_stops_level=0, trade_freeze_level=0, trade_exemode=3, swap_mode=0, swap_rollover3days=3, margin_hedged_use_leg=False, expiration_mode=2, filling_mode=3, order_mode=127, order_gtc_mode=2, option_mode=0, option_right=0, bid=0.0, bidhigh=0.0, bidlow=0.0, ask=0.0, askhigh=0.0, asklow=0.0, last=0.0, lasthigh=0.0, lastlow=0.0, volume_real=0.0, volumehigh_real=0.0, volumelow_real=0.0, option_strike=0.0, point=1.0, trade_tick_value=1.0, trade_tick_value_profit=1.0, trade_tick_value_loss=1.0, trade_tick_size=5.0, trade_contract_size=1.0, trade_accrued_interest=0.0, trade_face_value=0.0, trade_liquidity_rate=0.0, volume_min=1.0, volume_max=400.0, volume_step=1.0, volume_limit=0.0, swap_long=0.0, swap_short=0.0, margin_initial=0.0, margin_maintenance=0.0, session_volume=0.0, session_turnover=0.0, session_interest=0.0, session_buy_orders_volume=0.0, session_sell_orders_volume=0.0, session_open=0.0, session_close=0.0, session_aw=0.0, session_price_settlement=0.0, session_price_limit_min=0.0, session_price_limit_max=0.0, margin_hedged=0.0, price_change=0.0, price_volatility=0.0, price_theoretical=0.0, price_greeks_delta=0.0, price_greeks_theta=0.0, price_greeks_gamma=0.0, price_greeks_vega=0.0, price_greeks_rho=0.0, price_greeks_omega=0.0, price_sensitivity=0.0, basis='', category='', currency_base='BRL', currency_profit='BRL', currency_margin='BRL', bank='', description='IBOVESPA MINI', exchange='', formula='', isin='BRBMEFWIN338', name='WINJ23', page='', path='BMF\\\\WINJ23'),\n",
       " SymbolInfo(custom=False, chart_mode=1, select=False, visible=False, session_deals=0, session_buy_orders=0, session_sell_orders=0, volume=0, volumehigh=0, volumelow=0, time=0, digits=0, spread=0, spread_float=True, ticks_bookdepth=32, trade_calc_mode=33, trade_mode=4, start_time=0, expiration_time=1655320500, trade_stops_level=0, trade_freeze_level=0, trade_exemode=3, swap_mode=0, swap_rollover3days=3, margin_hedged_use_leg=False, expiration_mode=2, filling_mode=3, order_mode=127, order_gtc_mode=2, option_mode=0, option_right=0, bid=0.0, bidhigh=0.0, bidlow=0.0, ask=0.0, askhigh=0.0, asklow=0.0, last=0.0, lasthigh=0.0, lastlow=0.0, volume_real=0.0, volumehigh_real=0.0, volumelow_real=0.0, option_strike=0.0, point=1.0, trade_tick_value=1.0, trade_tick_value_profit=1.0, trade_tick_value_loss=1.0, trade_tick_size=5.0, trade_contract_size=1.0, trade_accrued_interest=0.0, trade_face_value=0.0, trade_liquidity_rate=0.0, volume_min=1.0, volume_max=400.0, volume_step=1.0, volume_limit=0.0, swap_long=0.0, swap_short=0.0, margin_initial=0.0, margin_maintenance=0.0, session_volume=0.0, session_turnover=0.0, session_interest=0.0, session_buy_orders_volume=0.0, session_sell_orders_volume=0.0, session_open=0.0, session_close=0.0, session_aw=0.0, session_price_settlement=0.0, session_price_limit_min=0.0, session_price_limit_max=0.0, margin_hedged=0.0, price_change=0.0, price_volatility=0.0, price_theoretical=0.0, price_greeks_delta=0.0, price_greeks_theta=0.0, price_greeks_gamma=0.0, price_greeks_vega=0.0, price_greeks_rho=0.0, price_greeks_omega=0.0, price_sensitivity=0.0, basis='', category='', currency_base='BRL', currency_profit='BRL', currency_margin='BRL', bank='', description='IBOVESPA MINI', exchange='', formula='', isin='BRBMEFWIN2Y4', name='WINM22', page='', path='BMF\\\\WINM22'),\n",
       " SymbolInfo(custom=False, chart_mode=1, select=False, visible=False, session_deals=0, session_buy_orders=0, session_sell_orders=0, volume=0, volumehigh=0, volumelow=0, time=0, digits=0, spread=0, spread_float=True, ticks_bookdepth=32, trade_calc_mode=33, trade_mode=4, start_time=0, expiration_time=1686770100, trade_stops_level=0, trade_freeze_level=0, trade_exemode=3, swap_mode=0, swap_rollover3days=3, margin_hedged_use_leg=False, expiration_mode=2, filling_mode=3, order_mode=127, order_gtc_mode=2, option_mode=0, option_right=0, bid=0.0, bidhigh=0.0, bidlow=0.0, ask=0.0, askhigh=0.0, asklow=0.0, last=0.0, lasthigh=0.0, lastlow=0.0, volume_real=0.0, volumehigh_real=0.0, volumelow_real=0.0, option_strike=0.0, point=1.0, trade_tick_value=1.0, trade_tick_value_profit=1.0, trade_tick_value_loss=1.0, trade_tick_size=5.0, trade_contract_size=1.0, trade_accrued_interest=0.0, trade_face_value=0.0, trade_liquidity_rate=0.0, volume_min=1.0, volume_max=400.0, volume_step=1.0, volume_limit=0.0, swap_long=0.0, swap_short=0.0, margin_initial=0.0, margin_maintenance=0.0, session_volume=0.0, session_turnover=0.0, session_interest=0.0, session_buy_orders_volume=0.0, session_sell_orders_volume=0.0, session_open=0.0, session_close=0.0, session_aw=0.0, session_price_settlement=0.0, session_price_limit_min=0.0, session_price_limit_max=0.0, margin_hedged=0.0, price_change=0.0, price_volatility=0.0, price_theoretical=0.0, price_greeks_delta=0.0, price_greeks_theta=0.0, price_greeks_gamma=0.0, price_greeks_vega=0.0, price_greeks_rho=0.0, price_greeks_omega=0.0, price_sensitivity=0.0, basis='', category='', currency_base='BRL', currency_profit='BRL', currency_margin='BRL', bank='', description='IBOVESPA MINI', exchange='', formula='', isin='BRBMEFWIN346', name='WINM23', page='', path='BMF\\\\WINM23'),\n",
       " SymbolInfo(custom=False, chart_mode=1, select=False, visible=False, session_deals=0, session_buy_orders=0, session_sell_orders=0, volume=0, volumehigh=0, volumelow=0, time=0, digits=0, spread=0, spread_float=True, ticks_bookdepth=32, trade_calc_mode=33, trade_mode=4, start_time=0, expiration_time=1660763700, trade_stops_level=0, trade_freeze_level=0, trade_exemode=3, swap_mode=0, swap_rollover3days=3, margin_hedged_use_leg=False, expiration_mode=2, filling_mode=3, order_mode=127, order_gtc_mode=2, option_mode=0, option_right=0, bid=0.0, bidhigh=0.0, bidlow=0.0, ask=0.0, askhigh=0.0, asklow=0.0, last=0.0, lasthigh=0.0, lastlow=0.0, volume_real=0.0, volumehigh_real=0.0, volumelow_real=0.0, option_strike=0.0, point=1.0, trade_tick_value=1.0, trade_tick_value_profit=1.0, trade_tick_value_loss=1.0, trade_tick_size=5.0, trade_contract_size=1.0, trade_accrued_interest=0.0, trade_face_value=0.0, trade_liquidity_rate=0.0, volume_min=1.0, volume_max=400.0, volume_step=1.0, volume_limit=0.0, swap_long=0.0, swap_short=0.0, margin_initial=0.0, margin_maintenance=0.0, session_volume=0.0, session_turnover=0.0, session_interest=0.0, session_buy_orders_volume=0.0, session_sell_orders_volume=0.0, session_open=0.0, session_close=0.0, session_aw=0.0, session_price_settlement=0.0, session_price_limit_min=0.0, session_price_limit_max=0.0, margin_hedged=0.0, price_change=0.0, price_volatility=0.0, price_theoretical=0.0, price_greeks_delta=0.0, price_greeks_theta=0.0, price_greeks_gamma=0.0, price_greeks_vega=0.0, price_greeks_rho=0.0, price_greeks_omega=0.0, price_sensitivity=0.0, basis='', category='', currency_base='BRL', currency_profit='BRL', currency_margin='BRL', bank='', description='IBOVESPA MINI', exchange='', formula='', isin='BRBMEFWIN2Z1', name='WINQ22', page='', path='BMF\\\\WINQ22'),\n",
       " SymbolInfo(custom=False, chart_mode=1, select=False, visible=False, session_deals=0, session_buy_orders=0, session_sell_orders=0, volume=0, volumehigh=0, volumelow=0, time=0, digits=0, spread=0, spread_float=True, ticks_bookdepth=32, trade_calc_mode=33, trade_mode=4, start_time=0, expiration_time=1692213300, trade_stops_level=0, trade_freeze_level=0, trade_exemode=3, swap_mode=0, swap_rollover3days=3, margin_hedged_use_leg=False, expiration_mode=2, filling_mode=3, order_mode=127, order_gtc_mode=2, option_mode=0, option_right=0, bid=0.0, bidhigh=0.0, bidlow=0.0, ask=0.0, askhigh=0.0, asklow=0.0, last=0.0, lasthigh=0.0, lastlow=0.0, volume_real=0.0, volumehigh_real=0.0, volumelow_real=0.0, option_strike=0.0, point=1.0, trade_tick_value=1.0, trade_tick_value_profit=1.0, trade_tick_value_loss=1.0, trade_tick_size=5.0, trade_contract_size=1.0, trade_accrued_interest=0.0, trade_face_value=0.0, trade_liquidity_rate=0.0, volume_min=1.0, volume_max=400.0, volume_step=1.0, volume_limit=0.0, swap_long=0.0, swap_short=0.0, margin_initial=0.0, margin_maintenance=0.0, session_volume=0.0, session_turnover=0.0, session_interest=0.0, session_buy_orders_volume=0.0, session_sell_orders_volume=0.0, session_open=0.0, session_close=0.0, session_aw=0.0, session_price_settlement=0.0, session_price_limit_min=0.0, session_price_limit_max=0.0, margin_hedged=0.0, price_change=0.0, price_volatility=0.0, price_theoretical=0.0, price_greeks_delta=0.0, price_greeks_theta=0.0, price_greeks_gamma=0.0, price_greeks_vega=0.0, price_greeks_rho=0.0, price_greeks_omega=0.0, price_sensitivity=0.0, basis='', category='', currency_base='BRL', currency_profit='BRL', currency_margin='BRL', bank='', description='IBOVESPA MINI', exchange='', formula='', isin='BRBMEFWIN353', name='WINQ23', page='', path='BMF\\\\WINQ23'),\n",
       " SymbolInfo(custom=False, chart_mode=1, select=False, visible=False, session_deals=0, session_buy_orders=0, session_sell_orders=0, volume=0, volumehigh=0, volumelow=0, time=0, digits=0, spread=0, spread_float=True, ticks_bookdepth=32, trade_calc_mode=33, trade_mode=4, start_time=0, expiration_time=1665688500, trade_stops_level=0, trade_freeze_level=0, trade_exemode=3, swap_mode=0, swap_rollover3days=3, margin_hedged_use_leg=False, expiration_mode=2, filling_mode=3, order_mode=127, order_gtc_mode=2, option_mode=0, option_right=0, bid=0.0, bidhigh=0.0, bidlow=0.0, ask=0.0, askhigh=0.0, asklow=0.0, last=0.0, lasthigh=0.0, lastlow=0.0, volume_real=0.0, volumehigh_real=0.0, volumelow_real=0.0, option_strike=0.0, point=1.0, trade_tick_value=1.0, trade_tick_value_profit=1.0, trade_tick_value_loss=1.0, trade_tick_size=5.0, trade_contract_size=1.0, trade_accrued_interest=0.0, trade_face_value=0.0, trade_liquidity_rate=0.0, volume_min=1.0, volume_max=400.0, volume_step=1.0, volume_limit=0.0, swap_long=0.0, swap_short=0.0, margin_initial=0.0, margin_maintenance=0.0, session_volume=0.0, session_turnover=0.0, session_interest=0.0, session_buy_orders_volume=0.0, session_sell_orders_volume=0.0, session_open=0.0, session_close=0.0, session_aw=0.0, session_price_settlement=0.0, session_price_limit_min=0.0, session_price_limit_max=0.0, margin_hedged=0.0, price_change=0.0, price_volatility=0.0, price_theoretical=0.0, price_greeks_delta=0.0, price_greeks_theta=0.0, price_greeks_gamma=0.0, price_greeks_vega=0.0, price_greeks_rho=0.0, price_greeks_omega=0.0, price_sensitivity=0.0, basis='', category='', currency_base='BRL', currency_profit='BRL', currency_margin='BRL', bank='', description='IBOVESPA MINI', exchange='', formula='', isin='BRBMEFWIN304', name='WINV22', page='', path='BMF\\\\WINV22'),\n",
       " SymbolInfo(custom=False, chart_mode=1, select=False, visible=False, session_deals=0, session_buy_orders=0, session_sell_orders=0, volume=0, volumehigh=0, volumelow=0, time=0, digits=0, spread=0, spread_float=True, ticks_bookdepth=32, trade_calc_mode=33, trade_mode=4, start_time=0, expiration_time=1697656500, trade_stops_level=0, trade_freeze_level=0, trade_exemode=3, swap_mode=0, swap_rollover3days=3, margin_hedged_use_leg=False, expiration_mode=2, filling_mode=3, order_mode=127, order_gtc_mode=2, option_mode=0, option_right=0, bid=0.0, bidhigh=0.0, bidlow=0.0, ask=0.0, askhigh=0.0, asklow=0.0, last=0.0, lasthigh=0.0, lastlow=0.0, volume_real=0.0, volumehigh_real=0.0, volumelow_real=0.0, option_strike=0.0, point=1.0, trade_tick_value=1.0, trade_tick_value_profit=1.0, trade_tick_value_loss=1.0, trade_tick_size=5.0, trade_contract_size=1.0, trade_accrued_interest=0.0, trade_face_value=0.0, trade_liquidity_rate=0.0, volume_min=1.0, volume_max=400.0, volume_step=1.0, volume_limit=0.0, swap_long=0.0, swap_short=0.0, margin_initial=0.0, margin_maintenance=0.0, session_volume=0.0, session_turnover=0.0, session_interest=0.0, session_buy_orders_volume=0.0, session_sell_orders_volume=0.0, session_open=0.0, session_close=0.0, session_aw=0.0, session_price_settlement=0.0, session_price_limit_min=0.0, session_price_limit_max=0.0, margin_hedged=0.0, price_change=0.0, price_volatility=0.0, price_theoretical=0.0, price_greeks_delta=0.0, price_greeks_theta=0.0, price_greeks_gamma=0.0, price_greeks_vega=0.0, price_greeks_rho=0.0, price_greeks_omega=0.0, price_sensitivity=0.0, basis='', category='', currency_base='BRL', currency_profit='BRL', currency_margin='BRL', bank='', description='IBOVESPA MINI', exchange='', formula='', isin='BRBMEFWIN361', name='WINV23', page='', path='BMF\\\\WINV23'),\n",
       " SymbolInfo(custom=False, chart_mode=1, select=False, visible=False, session_deals=0, session_buy_orders=0, session_sell_orders=0, volume=0, volumehigh=0, volumelow=0, time=0, digits=0, spread=0, spread_float=True, ticks_bookdepth=32, trade_calc_mode=33, trade_mode=4, start_time=0, expiration_time=1639595700, trade_stops_level=0, trade_freeze_level=0, trade_exemode=3, swap_mode=0, swap_rollover3days=3, margin_hedged_use_leg=False, expiration_mode=2, filling_mode=3, order_mode=127, order_gtc_mode=2, option_mode=0, option_right=0, bid=0.0, bidhigh=0.0, bidlow=0.0, ask=0.0, askhigh=0.0, asklow=0.0, last=0.0, lasthigh=0.0, lastlow=0.0, volume_real=0.0, volumehigh_real=0.0, volumelow_real=0.0, option_strike=0.0, point=1.0, trade_tick_value=1.0, trade_tick_value_profit=1.0, trade_tick_value_loss=1.0, trade_tick_size=5.0, trade_contract_size=1.0, trade_accrued_interest=0.0, trade_face_value=0.0, trade_liquidity_rate=0.0, volume_min=1.0, volume_max=10000.0, volume_step=1.0, volume_limit=0.0, swap_long=0.0, swap_short=0.0, margin_initial=0.0, margin_maintenance=0.0, session_volume=0.0, session_turnover=0.0, session_interest=0.0, session_buy_orders_volume=0.0, session_sell_orders_volume=0.0, session_open=0.0, session_close=0.0, session_aw=0.0, session_price_settlement=0.0, session_price_limit_min=0.0, session_price_limit_max=0.0, margin_hedged=0.0, price_change=0.0, price_volatility=0.0, price_theoretical=0.0, price_greeks_delta=0.0, price_greeks_theta=0.0, price_greeks_gamma=0.0, price_greeks_vega=0.0, price_greeks_rho=0.0, price_greeks_omega=0.0, price_sensitivity=0.0, basis='', category='', currency_base='BRL', currency_profit='BRL', currency_margin='BRL', bank='', description='IBOVESPA MINI', exchange='', formula='', isin='BRBMEFWIN2V0', name='WINZ21', page='', path='BMF\\\\WINZ21'),\n",
       " SymbolInfo(custom=False, chart_mode=1, select=False, visible=False, session_deals=0, session_buy_orders=0, session_sell_orders=0, volume=0, volumehigh=0, volumelow=0, time=0, digits=0, spread=0, spread_float=True, ticks_bookdepth=32, trade_calc_mode=33, trade_mode=4, start_time=0, expiration_time=1671045300, trade_stops_level=0, trade_freeze_level=0, trade_exemode=3, swap_mode=0, swap_rollover3days=3, margin_hedged_use_leg=False, expiration_mode=2, filling_mode=3, order_mode=127, order_gtc_mode=2, option_mode=0, option_right=0, bid=0.0, bidhigh=0.0, bidlow=0.0, ask=0.0, askhigh=0.0, asklow=0.0, last=0.0, lasthigh=0.0, lastlow=0.0, volume_real=0.0, volumehigh_real=0.0, volumelow_real=0.0, option_strike=0.0, point=1.0, trade_tick_value=1.0, trade_tick_value_profit=1.0, trade_tick_value_loss=1.0, trade_tick_size=5.0, trade_contract_size=1.0, trade_accrued_interest=0.0, trade_face_value=0.0, trade_liquidity_rate=0.0, volume_min=1.0, volume_max=400.0, volume_step=1.0, volume_limit=0.0, swap_long=0.0, swap_short=0.0, margin_initial=0.0, margin_maintenance=0.0, session_volume=0.0, session_turnover=0.0, session_interest=0.0, session_buy_orders_volume=0.0, session_sell_orders_volume=0.0, session_open=0.0, session_close=0.0, session_aw=0.0, session_price_settlement=0.0, session_price_limit_min=0.0, session_price_limit_max=0.0, margin_hedged=0.0, price_change=0.0, price_volatility=0.0, price_theoretical=0.0, price_greeks_delta=0.0, price_greeks_theta=0.0, price_greeks_gamma=0.0, price_greeks_vega=0.0, price_greeks_rho=0.0, price_greeks_omega=0.0, price_sensitivity=0.0, basis='', category='', currency_base='BRL', currency_profit='BRL', currency_margin='BRL', bank='', description='IBOVESPA MINI', exchange='', formula='', isin='BRBMEFWIN312', name='WINZ22', page='', path='BMF\\\\WINZ22'))"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mt5.symbols_get(group=\"WIN\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Link de referencia: https://www.mql5.com/pt/docs/integration/python_metatrader5/mt5copyratesfrompos_py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mt5.market_book_add('PATI3')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(BookInfo(type=1, price=75.0, volume=200, volume_dbl=200.0),\n",
       " BookInfo(type=1, price=74.7, volume=300, volume_dbl=300.0))"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mt5.market_book_get('PATI3')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 4. Obtendo dados propriamente ditos"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4.1 Função copy_rates_from_pos"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ativo = mt5.copy_rates_from_pos('WIN$',mt5.TIMEFRAME_D1, 0, 5000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "ativo = pd.DataFrame(ativo)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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>time</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>tick_volume</th>\n",
       "      <th>spread</th>\n",
       "      <th>real_volume</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1473120000</td>\n",
       "      <td>78713.0</td>\n",
       "      <td>79169.0</td>\n",
       "      <td>77894.0</td>\n",
       "      <td>79136.0</td>\n",
       "      <td>211517</td>\n",
       "      <td>1</td>\n",
       "      <td>569070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1473292800</td>\n",
       "      <td>78778.0</td>\n",
       "      <td>79429.0</td>\n",
       "      <td>78590.0</td>\n",
       "      <td>79038.0</td>\n",
       "      <td>204705</td>\n",
       "      <td>1</td>\n",
       "      <td>552981</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1473379200</td>\n",
       "      <td>78778.0</td>\n",
       "      <td>78778.0</td>\n",
       "      <td>75649.0</td>\n",
       "      <td>75721.0</td>\n",
       "      <td>263492</td>\n",
       "      <td>1</td>\n",
       "      <td>767040</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1473638400</td>\n",
       "      <td>75226.0</td>\n",
       "      <td>77100.0</td>\n",
       "      <td>75226.0</td>\n",
       "      <td>76918.0</td>\n",
       "      <td>291905</td>\n",
       "      <td>1</td>\n",
       "      <td>785707</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1473724800</td>\n",
       "      <td>76436.0</td>\n",
       "      <td>76501.0</td>\n",
       "      <td>74166.0</td>\n",
       "      <td>74706.0</td>\n",
       "      <td>315588</td>\n",
       "      <td>1</td>\n",
       "      <td>851984</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1232</th>\n",
       "      <td>1630454400</td>\n",
       "      <td>119400.0</td>\n",
       "      <td>120615.0</td>\n",
       "      <td>118625.0</td>\n",
       "      <td>119180.0</td>\n",
       "      <td>5144525</td>\n",
       "      <td>1</td>\n",
       "      <td>20338473</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1233</th>\n",
       "      <td>1630540800</td>\n",
       "      <td>119595.0</td>\n",
       "      <td>119735.0</td>\n",
       "      <td>116920.0</td>\n",
       "      <td>117160.0</td>\n",
       "      <td>5751495</td>\n",
       "      <td>1</td>\n",
       "      <td>22396328</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1234</th>\n",
       "      <td>1630627200</td>\n",
       "      <td>117665.0</td>\n",
       "      <td>118350.0</td>\n",
       "      <td>116085.0</td>\n",
       "      <td>116855.0</td>\n",
       "      <td>5236082</td>\n",
       "      <td>1</td>\n",
       "      <td>19873990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1235</th>\n",
       "      <td>1630886400</td>\n",
       "      <td>117200.0</td>\n",
       "      <td>118585.0</td>\n",
       "      <td>116530.0</td>\n",
       "      <td>118370.0</td>\n",
       "      <td>3748279</td>\n",
       "      <td>1</td>\n",
       "      <td>14006225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1236</th>\n",
       "      <td>1631059200</td>\n",
       "      <td>117150.0</td>\n",
       "      <td>117980.0</td>\n",
       "      <td>113570.0</td>\n",
       "      <td>113875.0</td>\n",
       "      <td>1622952</td>\n",
       "      <td>0</td>\n",
       "      <td>23824170</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1237 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            time      open      high       low     close  tick_volume  spread  \\\n",
       "0     1473120000   78713.0   79169.0   77894.0   79136.0       211517       1   \n",
       "1     1473292800   78778.0   79429.0   78590.0   79038.0       204705       1   \n",
       "2     1473379200   78778.0   78778.0   75649.0   75721.0       263492       1   \n",
       "3     1473638400   75226.0   77100.0   75226.0   76918.0       291905       1   \n",
       "4     1473724800   76436.0   76501.0   74166.0   74706.0       315588       1   \n",
       "...          ...       ...       ...       ...       ...          ...     ...   \n",
       "1232  1630454400  119400.0  120615.0  118625.0  119180.0      5144525       1   \n",
       "1233  1630540800  119595.0  119735.0  116920.0  117160.0      5751495       1   \n",
       "1234  1630627200  117665.0  118350.0  116085.0  116855.0      5236082       1   \n",
       "1235  1630886400  117200.0  118585.0  116530.0  118370.0      3748279       1   \n",
       "1236  1631059200  117150.0  117980.0  113570.0  113875.0      1622952       0   \n",
       "\n",
       "      real_volume  \n",
       "0          569070  \n",
       "1          552981  \n",
       "2          767040  \n",
       "3          785707  \n",
       "4          851984  \n",
       "...           ...  \n",
       "1232     20338473  \n",
       "1233     22396328  \n",
       "1234     19873990  \n",
       "1235     14006225  \n",
       "1236     23824170  \n",
       "\n",
       "[1237 rows x 8 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ativo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "ativo['time'] = pd.to_datetime(ativo['time'], unit='s')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>low</th>\n",
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       "      <th>0</th>\n",
       "      <td>2016-09-06</td>\n",
       "      <td>78713.0</td>\n",
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       "      <td>77894.0</td>\n",
       "      <td>79136.0</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2016-09-08</td>\n",
       "      <td>78778.0</td>\n",
       "      <td>79429.0</td>\n",
       "      <td>78590.0</td>\n",
       "      <td>79038.0</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2016-09-09</td>\n",
       "      <td>78778.0</td>\n",
       "      <td>78778.0</td>\n",
       "      <td>75649.0</td>\n",
       "      <td>75721.0</td>\n",
       "      <td>263492</td>\n",
       "      <td>1</td>\n",
       "      <td>767040</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2016-09-12</td>\n",
       "      <td>75226.0</td>\n",
       "      <td>77100.0</td>\n",
       "      <td>75226.0</td>\n",
       "      <td>76918.0</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2016-09-13</td>\n",
       "      <td>76436.0</td>\n",
       "      <td>76501.0</td>\n",
       "      <td>74166.0</td>\n",
       "      <td>74706.0</td>\n",
       "      <td>315588</td>\n",
       "      <td>1</td>\n",
       "      <td>851984</td>\n",
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      ],
      "text/plain": [
       "        time     open     high      low    close  tick_volume  spread  \\\n",
       "0 2016-09-06  78713.0  79169.0  77894.0  79136.0       211517       1   \n",
       "1 2016-09-08  78778.0  79429.0  78590.0  79038.0       204705       1   \n",
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       "3 2016-09-12  75226.0  77100.0  75226.0  76918.0       291905       1   \n",
       "4 2016-09-13  76436.0  76501.0  74166.0  74706.0       315588       1   \n",
       "\n",
       "   real_volume  \n",
       "0       569070  \n",
       "1       552981  \n",
       "2       767040  \n",
       "3       785707  \n",
       "4       851984  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ativo.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>low</th>\n",
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       "      <th>1232</th>\n",
       "      <td>2021-09-01</td>\n",
       "      <td>119400.0</td>\n",
       "      <td>120615.0</td>\n",
       "      <td>118625.0</td>\n",
       "      <td>119180.0</td>\n",
       "      <td>5144525</td>\n",
       "      <td>1</td>\n",
       "      <td>20338473</td>\n",
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       "    <tr>\n",
       "      <th>1233</th>\n",
       "      <td>2021-09-02</td>\n",
       "      <td>119595.0</td>\n",
       "      <td>119735.0</td>\n",
       "      <td>116920.0</td>\n",
       "      <td>117160.0</td>\n",
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       "      <td>1</td>\n",
       "      <td>22396328</td>\n",
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       "    <tr>\n",
       "      <th>1234</th>\n",
       "      <td>2021-09-03</td>\n",
       "      <td>117665.0</td>\n",
       "      <td>118350.0</td>\n",
       "      <td>116085.0</td>\n",
       "      <td>116855.0</td>\n",
       "      <td>5236082</td>\n",
       "      <td>1</td>\n",
       "      <td>19873990</td>\n",
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       "    <tr>\n",
       "      <th>1235</th>\n",
       "      <td>2021-09-06</td>\n",
       "      <td>117200.0</td>\n",
       "      <td>118585.0</td>\n",
       "      <td>116530.0</td>\n",
       "      <td>118370.0</td>\n",
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       "      <td>14006225</td>\n",
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       "    <tr>\n",
       "      <th>1236</th>\n",
       "      <td>2021-09-08</td>\n",
       "      <td>117150.0</td>\n",
       "      <td>117980.0</td>\n",
       "      <td>113570.0</td>\n",
       "      <td>113875.0</td>\n",
       "      <td>1622952</td>\n",
       "      <td>0</td>\n",
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      ],
      "text/plain": [
       "           time      open      high       low     close  tick_volume  spread  \\\n",
       "1232 2021-09-01  119400.0  120615.0  118625.0  119180.0      5144525       1   \n",
       "1233 2021-09-02  119595.0  119735.0  116920.0  117160.0      5751495       1   \n",
       "1234 2021-09-03  117665.0  118350.0  116085.0  116855.0      5236082       1   \n",
       "1235 2021-09-06  117200.0  118585.0  116530.0  118370.0      3748279       1   \n",
       "1236 2021-09-08  117150.0  117980.0  113570.0  113875.0      1622952       0   \n",
       "\n",
       "      real_volume  \n",
       "1232     20338473  \n",
       "1233     22396328  \n",
       "1234     19873990  \n",
       "1235     14006225  \n",
       "1236     23824170  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ativo.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [],
   "source": [
    "mt5.initialize()\n",
    "\n",
    "# importamos o módulo pytz para trabalhar com o fuso horário\n",
    "import pytz"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [],
   "source": [
    "# definimos o fuso horário como UTC\n",
    "timezone = pytz.timezone(\"Etc/UTC\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "# criamos o objeto datetime no fuso horário UTC para que não seja aplicado o deslocamento do fuso horário local\n",
    "#utc_from = datetime(2021, 9, 3, tzinfo=timezone)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [],
   "source": [
    "from datetime import datetime\n",
    "today= datetime.today()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [],
   "source": [
    "# recebemos 10 barras de EURUSD H4 a partir de 01/10/2019 no fuso horário UTC\n",
    "rates = mt5.copy_rates_from(\"PETR4\", mt5.TIMEFRAME_D1, today,3000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {},
   "outputs": [],
   "source": [
    "ativo = pd.DataFrame(rates)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>15.21</td>\n",
       "      <td>14.73</td>\n",
       "      <td>14.73</td>\n",
       "      <td>30689</td>\n",
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       "      <td>23649000</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
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       "      <td>15.03</td>\n",
       "      <td>15.15</td>\n",
       "      <td>14.68</td>\n",
       "      <td>14.69</td>\n",
       "      <td>22964</td>\n",
       "      <td>1</td>\n",
       "      <td>17195200</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1314057600</td>\n",
       "      <td>14.80</td>\n",
       "      <td>15.18</td>\n",
       "      <td>14.59</td>\n",
       "      <td>15.07</td>\n",
       "      <td>23128</td>\n",
       "      <td>1</td>\n",
       "      <td>21910500</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
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       "      <th>2480</th>\n",
       "      <td>1630022400</td>\n",
       "      <td>27.70</td>\n",
       "      <td>28.49</td>\n",
       "      <td>27.67</td>\n",
       "      <td>28.49</td>\n",
       "      <td>74976</td>\n",
       "      <td>1</td>\n",
       "      <td>76095600</td>\n",
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       "    <tr>\n",
       "      <th>2481</th>\n",
       "      <td>1630281600</td>\n",
       "      <td>28.40</td>\n",
       "      <td>28.71</td>\n",
       "      <td>28.26</td>\n",
       "      <td>28.30</td>\n",
       "      <td>77793</td>\n",
       "      <td>1</td>\n",
       "      <td>60857400</td>\n",
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       "    <tr>\n",
       "      <th>2482</th>\n",
       "      <td>1630368000</td>\n",
       "      <td>28.20</td>\n",
       "      <td>28.23</td>\n",
       "      <td>26.99</td>\n",
       "      <td>27.19</td>\n",
       "      <td>138678</td>\n",
       "      <td>1</td>\n",
       "      <td>109914400</td>\n",
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       "    <tr>\n",
       "      <th>2483</th>\n",
       "      <td>1630454400</td>\n",
       "      <td>27.32</td>\n",
       "      <td>27.34</td>\n",
       "      <td>26.33</td>\n",
       "      <td>27.04</td>\n",
       "      <td>135235</td>\n",
       "      <td>1</td>\n",
       "      <td>69059900</td>\n",
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       "    <tr>\n",
       "      <th>2484</th>\n",
       "      <td>1630540800</td>\n",
       "      <td>27.00</td>\n",
       "      <td>27.35</td>\n",
       "      <td>26.46</td>\n",
       "      <td>26.60</td>\n",
       "      <td>93447</td>\n",
       "      <td>1</td>\n",
       "      <td>55501400</td>\n",
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       "</table>\n",
       "<p>2485 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            time   open   high    low  close  tick_volume  spread  real_volume\n",
       "0     1313539200  15.55  15.67  15.36  15.60        25850       1     18831300\n",
       "1     1313625600  15.21  15.23  14.78  15.18        30147       1     25674000\n",
       "2     1313712000  14.90  15.21  14.73  14.73        30689       1     23649000\n",
       "3     1313971200  15.03  15.15  14.68  14.69        22964       1     17195200\n",
       "4     1314057600  14.80  15.18  14.59  15.07        23128       1     21910500\n",
       "...          ...    ...    ...    ...    ...          ...     ...          ...\n",
       "2480  1630022400  27.70  28.49  27.67  28.49        74976       1     76095600\n",
       "2481  1630281600  28.40  28.71  28.26  28.30        77793       1     60857400\n",
       "2482  1630368000  28.20  28.23  26.99  27.19       138678       1    109914400\n",
       "2483  1630454400  27.32  27.34  26.33  27.04       135235       1     69059900\n",
       "2484  1630540800  27.00  27.35  26.46  26.60        93447       1     55501400\n",
       "\n",
       "[2485 rows x 8 columns]"
      ]
     },
     "execution_count": 126,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ativo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {},
   "outputs": [],
   "source": [
    "ativo['time']=pd.to_datetime(ativo['time'], unit='s')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {},
   "outputs": [],
   "source": [
    "ativo['time']=pd.to_datetime(ativo['time'], unit='s')\n",
    "ativo.index = ativo['time']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>time</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>tick_volume</th>\n",
       "      <th>spread</th>\n",
       "      <th>real_volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>time</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2011-08-17</th>\n",
       "      <td>2011-08-17</td>\n",
       "      <td>15.55</td>\n",
       "      <td>15.67</td>\n",
       "      <td>15.36</td>\n",
       "      <td>15.60</td>\n",
       "      <td>25850</td>\n",
       "      <td>1</td>\n",
       "      <td>18831300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-08-18</th>\n",
       "      <td>2011-08-18</td>\n",
       "      <td>15.21</td>\n",
       "      <td>15.23</td>\n",
       "      <td>14.78</td>\n",
       "      <td>15.18</td>\n",
       "      <td>30147</td>\n",
       "      <td>1</td>\n",
       "      <td>25674000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-08-19</th>\n",
       "      <td>2011-08-19</td>\n",
       "      <td>14.90</td>\n",
       "      <td>15.21</td>\n",
       "      <td>14.73</td>\n",
       "      <td>14.73</td>\n",
       "      <td>30689</td>\n",
       "      <td>1</td>\n",
       "      <td>23649000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-08-22</th>\n",
       "      <td>2011-08-22</td>\n",
       "      <td>15.03</td>\n",
       "      <td>15.15</td>\n",
       "      <td>14.68</td>\n",
       "      <td>14.69</td>\n",
       "      <td>22964</td>\n",
       "      <td>1</td>\n",
       "      <td>17195200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-08-23</th>\n",
       "      <td>2011-08-23</td>\n",
       "      <td>14.80</td>\n",
       "      <td>15.18</td>\n",
       "      <td>14.59</td>\n",
       "      <td>15.07</td>\n",
       "      <td>23128</td>\n",
       "      <td>1</td>\n",
       "      <td>21910500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-08-27</th>\n",
       "      <td>2021-08-27</td>\n",
       "      <td>27.70</td>\n",
       "      <td>28.49</td>\n",
       "      <td>27.67</td>\n",
       "      <td>28.49</td>\n",
       "      <td>74976</td>\n",
       "      <td>1</td>\n",
       "      <td>76095600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-08-30</th>\n",
       "      <td>2021-08-30</td>\n",
       "      <td>28.40</td>\n",
       "      <td>28.71</td>\n",
       "      <td>28.26</td>\n",
       "      <td>28.30</td>\n",
       "      <td>77793</td>\n",
       "      <td>1</td>\n",
       "      <td>60857400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-08-31</th>\n",
       "      <td>2021-08-31</td>\n",
       "      <td>28.20</td>\n",
       "      <td>28.23</td>\n",
       "      <td>26.99</td>\n",
       "      <td>27.19</td>\n",
       "      <td>138678</td>\n",
       "      <td>1</td>\n",
       "      <td>109914400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-01</th>\n",
       "      <td>2021-09-01</td>\n",
       "      <td>27.32</td>\n",
       "      <td>27.34</td>\n",
       "      <td>26.33</td>\n",
       "      <td>27.04</td>\n",
       "      <td>135235</td>\n",
       "      <td>1</td>\n",
       "      <td>69059900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-02</th>\n",
       "      <td>2021-09-02</td>\n",
       "      <td>27.00</td>\n",
       "      <td>27.35</td>\n",
       "      <td>26.46</td>\n",
       "      <td>26.60</td>\n",
       "      <td>93447</td>\n",
       "      <td>1</td>\n",
       "      <td>55501400</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2485 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 time   open   high    low  close  tick_volume  spread  \\\n",
       "time                                                                     \n",
       "2011-08-17 2011-08-17  15.55  15.67  15.36  15.60        25850       1   \n",
       "2011-08-18 2011-08-18  15.21  15.23  14.78  15.18        30147       1   \n",
       "2011-08-19 2011-08-19  14.90  15.21  14.73  14.73        30689       1   \n",
       "2011-08-22 2011-08-22  15.03  15.15  14.68  14.69        22964       1   \n",
       "2011-08-23 2011-08-23  14.80  15.18  14.59  15.07        23128       1   \n",
       "...               ...    ...    ...    ...    ...          ...     ...   \n",
       "2021-08-27 2021-08-27  27.70  28.49  27.67  28.49        74976       1   \n",
       "2021-08-30 2021-08-30  28.40  28.71  28.26  28.30        77793       1   \n",
       "2021-08-31 2021-08-31  28.20  28.23  26.99  27.19       138678       1   \n",
       "2021-09-01 2021-09-01  27.32  27.34  26.33  27.04       135235       1   \n",
       "2021-09-02 2021-09-02  27.00  27.35  26.46  26.60        93447       1   \n",
       "\n",
       "            real_volume  \n",
       "time                     \n",
       "2011-08-17     18831300  \n",
       "2011-08-18     25674000  \n",
       "2011-08-19     23649000  \n",
       "2011-08-22     17195200  \n",
       "2011-08-23     21910500  \n",
       "...                 ...  \n",
       "2021-08-27     76095600  \n",
       "2021-08-30     60857400  \n",
       "2021-08-31    109914400  \n",
       "2021-09-01     69059900  \n",
       "2021-09-02     55501400  \n",
       "\n",
       "[2485 rows x 8 columns]"
      ]
     },
     "execution_count": 130,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ativo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='time'>"
      ]
     },
     "execution_count": 132,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ativo.close.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Criando função que retorna plot da função escolhida"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "unsupported operand type(s) for -: 'datetime.datetime' and 'int'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-133-0c94c9cd23d8>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mtoday\u001b[0m\u001b[1;33m-\u001b[0m\u001b[1;36m300\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mTypeError\u001b[0m: unsupported operand type(s) for -: 'datetime.datetime' and 'int'"
     ]
    }
   ],
   "source": [
    "today-300"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os, time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "metadata": {},
   "outputs": [],
   "source": [
    "s = time.strftime('%m/%d/%Y', time.gmtime(time.time()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "str"
      ]
     },
     "execution_count": 137,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(s)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {},
   "outputs": [],
   "source": [
    "from datetime import datetime, timedelta"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "metadata": {},
   "outputs": [
    {
     "ename": "AttributeError",
     "evalue": "type object 'datetime.datetime' has no attribute 'timedelta'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-150-ec5e5de71afd>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0ms\u001b[0m \u001b[1;33m-\u001b[0m \u001b[0mdatetime\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtimedelta\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdays\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m10\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mAttributeError\u001b[0m: type object 'datetime.datetime' has no attribute 'timedelta'"
     ]
    }
   ],
   "source": [
    "s - datetime.timedelta(days=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "metadata": {},
   "outputs": [],
   "source": [
    "today= datetime.today()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "datetime.datetime(2018, 12, 8, 9, 55, 7, 131455)"
      ]
     },
     "execution_count": 156,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "today-timedelta(days=1000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3006"
      ]
     },
     "execution_count": 162,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(today - start).days"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from datetime import datetime, timedelta\n",
    "\n",
    "print (start,end )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "s - datetime.timedelta(days=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3006"
      ]
     },
     "execution_count": 164,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "end = datetime.today()\n",
    "(end - start).days"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "janela = mt5.TIMEFRAME_D1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def retorna_plot(ativo, inicio, timeframe):\n",
    "    mt5.initialize()\n",
    "    from datetime import datetime\n",
    "    start = inicio\n",
    "    start = datetime.strptime(start, \"%m/%d/%Y\") #string to date\n",
    "    end = datetime.today()\n",
    "    dias = (end - start).days\n",
    "    \n",
    "    rates = mt5.copy_rates_from(ativo, timeframe, end,dias)\n",
    "    ativo = pd.DataFrame(rates)\n",
    "    \n",
    "    ativo['time']=pd.to_datetime(ativo['time'], unit='s')\n",
    "    ativo.index = ativo['time']\n",
    "    mt5.shutdown()\n",
    "    \n",
    "    return ativo.close.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='time'>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "retorna_plot('WEGE3', '01/01/2019', janela)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='time'>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "mt5.initialize()\n",
    "from datetime import datetime\n",
    "today= datetime.today()\n",
    "# recebemos 10 barras de EURUSD H4 a partir de 01/10/2019 no fuso horário UTC\n",
    "rates = mt5.copy_rates_from(\"GOLL4\", mt5.TIMEFRAME_M1, today,300)\n",
    "ativo = pd.DataFrame(rates)\n",
    "ativo['time']=pd.to_datetime(ativo['time'], unit='s')\n",
    "ativo.index = ativo['time']\n",
    "ativo.close.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "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>time</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>tick_volume</th>\n",
       "      <th>spread</th>\n",
       "      <th>real_volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>time</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2021-09-06 16:00:00</th>\n",
       "      <td>2021-09-06 16:00:00</td>\n",
       "      <td>19.32</td>\n",
       "      <td>19.32</td>\n",
       "      <td>19.32</td>\n",
       "      <td>19.32</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-06 16:01:00</th>\n",
       "      <td>2021-09-06 16:01:00</td>\n",
       "      <td>19.31</td>\n",
       "      <td>19.31</td>\n",
       "      <td>19.30</td>\n",
       "      <td>19.30</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-06 16:02:00</th>\n",
       "      <td>2021-09-06 16:02:00</td>\n",
       "      <td>19.31</td>\n",
       "      <td>19.31</td>\n",
       "      <td>19.30</td>\n",
       "      <td>19.30</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>3200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-06 16:03:00</th>\n",
       "      <td>2021-09-06 16:03:00</td>\n",
       "      <td>19.29</td>\n",
       "      <td>19.32</td>\n",
       "      <td>19.28</td>\n",
       "      <td>19.32</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>1300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-06 16:04:00</th>\n",
       "      <td>2021-09-06 16:04:00</td>\n",
       "      <td>19.31</td>\n",
       "      <td>19.31</td>\n",
       "      <td>19.30</td>\n",
       "      <td>19.30</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   time   open   high    low  close  \\\n",
       "time                                                                  \n",
       "2021-09-06 16:00:00 2021-09-06 16:00:00  19.32  19.32  19.32  19.32   \n",
       "2021-09-06 16:01:00 2021-09-06 16:01:00  19.31  19.31  19.30  19.30   \n",
       "2021-09-06 16:02:00 2021-09-06 16:02:00  19.31  19.31  19.30  19.30   \n",
       "2021-09-06 16:03:00 2021-09-06 16:03:00  19.29  19.32  19.28  19.32   \n",
       "2021-09-06 16:04:00 2021-09-06 16:04:00  19.31  19.31  19.30  19.30   \n",
       "\n",
       "                     tick_volume  spread  real_volume  \n",
       "time                                                   \n",
       "2021-09-06 16:00:00            3       1          300  \n",
       "2021-09-06 16:01:00            2       1         1400  \n",
       "2021-09-06 16:02:00            4       1         3200  \n",
       "2021-09-06 16:03:00            8       1         1300  \n",
       "2021-09-06 16:04:00            2       2          200  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ativo.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Utilizando a CopyRatesfrom pos"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 209,
   "metadata": {},
   "outputs": [],
   "source": [
    "# estabelecemos a conexão ao MetaTrader 5\n",
    "if not mt5.initialize():\n",
    "    print(\"initialize() failed, error code =\",mt5.last_error())\n",
    "    quit()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 210,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "# solicitamos 10 barras de GBPUSD D1 do dia atual\n",
    "rates = mt5.copy_rates_from_pos(\"EMBR3\", mt5.TIMEFRAME_D1, 0, 300)\n",
    " "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 211,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 211,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# concluímos a conexão ao terminal MetaTrader 5\n",
    "mt5.shutdown()\n",
    " "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 212,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Exibimos os dados recebidos como estão\n",
      "(1592870400, 8.59, 8.64, 8.37, 8.52, 16295, 1, 9311100)\n",
      "(1592956800, 8.49, 8.73, 8.08, 8.09, 25804, 1, 13845400)\n",
      "(1593043200, 8.1, 8.22, 7.9, 8.15, 20598, 1, 12510100)\n",
      "(1593129600, 8.15, 8.26, 7.8, 7.83, 16735, 1, 10071200)\n",
      "(1593388800, 7.94, 8.42, 7.84, 8.42, 25804, 1, 17457400)\n",
      "(1593475200, 8.35, 8.36, 8.04, 8.09, 23700, 1, 14838600)\n",
      "(1593561600, 8.27, 8.44, 8.08, 8.1, 22427, 1, 14158200)\n",
      "(1593648000, 8.3, 8.66, 8.07, 8.17, 34097, 1, 19559200)\n",
      "(1593734400, 8.16, 8.26, 8.02, 8.19, 8044, 1, 5181000)\n",
      "(1593993600, 8.4, 8.51, 8.18, 8.47, 19933, 1, 12590400)\n",
      "(1594080000, 8.34, 8.42, 8.18, 8.2, 16966, 1, 10032300)\n",
      "(1594166400, 8.27, 8.3, 8.13, 8.18, 16922, 1, 9169700)\n",
      "(1594252800, 8.19, 8.2, 7.96, 7.99, 18339, 1, 11094400)\n",
      "(1594339200, 8., 8.09, 7.86, 8.06, 17365, 1, 9376200)\n",
      "(1594598400, 8.12, 8.3, 8.06, 8.16, 21152, 1, 15040000)\n",
      "(1594684800, 8.16, 8.17, 7.97, 8.01, 17757, 1, 12564300)\n",
      "(1594771200, 8.16, 8.8, 8.11, 8.8, 39682, 1, 28614000)\n",
      "(1594857600, 8.67, 8.86, 8.21, 8.26, 33580, 1, 23118900)\n",
      "(1594944000, 8.34, 8.48, 8.22, 8.38, 24038, 1, 12376000)\n",
      "(1595203200, 8.4, 8.46, 8.21, 8.32, 17653, 1, 10202700)\n",
      "(1595289600, 8.42, 8.67, 8.37, 8.5, 23719, 1, 15049000)\n",
      "(1595376000, 8.46, 8.48, 8.26, 8.31, 13614, 1, 9041200)\n",
      "(1595462400, 8.35, 8.42, 8.16, 8.22, 17295, 1, 11049800)\n",
      "(1595548800, 8.15, 8.18, 7.93, 8.02, 17895, 1, 11869500)\n",
      "(1595808000, 8.06, 8.09, 7.93, 8.02, 11426, 1, 8013300)\n",
      "(1595894400, 8.02, 8.25, 7.89, 8.17, 13655, 1, 9890200)\n",
      "(1595980800, 8.19, 8.24, 8.05, 8.18, 11683, 1, 7437600)\n",
      "(1596067200, 8.05, 8.11, 7.92, 7.95, 16614, 1, 12198400)\n",
      "(1596153600, 7.98, 8., 7.58, 7.61, 30390, 1, 21464500)\n",
      "(1596412800, 7.68, 7.77, 7.37, 7.66, 26982, 1, 15937700)\n",
      "(1596499200, 7.57, 7.71, 7.46, 7.47, 15530, 1, 7413300)\n",
      "(1596585600, 7.41, 7.68, 7.29, 7.66, 25635, 1, 13771900)\n",
      "(1596672000, 7.74, 7.74, 7.39, 7.58, 16642, 1, 9519200)\n",
      "(1596758400, 7.5, 7.61, 7.44, 7.5, 16537, 1, 8394800)\n",
      "(1597017600, 7.51, 7.95, 7.4, 7.93, 22788, 1, 14461800)\n",
      "(1597104000, 7.9, 8.32, 7.84, 8.02, 25598, 1, 17082300)\n",
      "(1597190400, 8.1, 8.17, 7.68, 7.8, 22011, 1, 11745200)\n",
      "(1597276800, 7.84, 7.9, 7.55, 7.6, 17844, 1, 8343700)\n",
      "(1597363200, 7.6, 7.74, 7.47, 7.68, 17342, 1, 8041200)\n",
      "(1597622400, 7.68, 7.74, 7.35, 7.39, 17924, 1, 10512700)\n",
      "(1597708800, 7.49, 7.5, 7.31, 7.39, 13975, 1, 7471100)\n",
      "(1597795200, 7.41, 7.43, 7.15, 7.16, 16805, 1, 11004400)\n",
      "(1597881600, 7.07, 7.22, 6.97, 7.16, 20944, 1, 13672600)\n",
      "(1597968000, 7.16, 7.33, 7.12, 7.24, 14606, 1, 8077700)\n",
      "(1598227200, 7.34, 7.73, 7.28, 7.64, 22556, 1, 14846100)\n",
      "(1598313600, 7.63, 7.72, 7.49, 7.66, 13194, 1, 9021600)\n",
      "(1598400000, 7.64, 7.77, 7.29, 7.31, 19500, 1, 10660800)\n",
      "(1598486400, 7.32, 7.53, 7.26, 7.33, 14129, 1, 9959100)\n",
      "(1598572800, 7.37, 7.62, 7.27, 7.56, 15396, 1, 10477400)\n",
      "(1598832000, 7.49, 7.57, 7.27, 7.34, 14626, 1, 9497600)\n",
      "(1598918400, 7.44, 7.8, 7.32, 7.67, 34242, 1, 16154800)\n",
      "(1599004800, 7.73, 7.86, 7.47, 7.57, 17665, 1, 10461800)\n",
      "(1599091200, 7.56, 7.94, 7.34, 7.44, 27574, 1, 19372800)\n",
      "(1599177600, 7.43, 7.44, 7.18, 7.41, 15606, 1, 12913700)\n",
      "(1599523200, 7.3, 7.39, 7.26, 7.36, 15038, 1, 9763000)\n",
      "(1599609600, 7.4, 7.66, 7.14, 7.19, 22124, 1, 20580500)\n",
      "(1599696000, 7.2, 7.26, 6.99, 7.01, 17292, 1, 16256000)\n",
      "(1599782400, 7.06, 7.07, 6.72, 6.81, 19168, 1, 13236300)\n",
      "(1600041600, 6.9, 6.95, 6.73, 6.9, 12536, 1, 9815400)\n",
      "(1600128000, 6.97, 7., 6.79, 6.87, 10861, 1, 6702100)\n",
      "(1600214400, 6.85, 7., 6.78, 6.92, 11952, 1, 7744600)\n",
      "(1600300800, 6.85, 7.02, 6.76, 6.97, 10821, 1, 8244900)\n",
      "(1600387200, 6.92, 6.93, 6.62, 6.68, 21827, 1, 16739400)\n",
      "(1600646400, 6.56, 6.6, 6.33, 6.36, 17729, 1, 14530000)\n",
      "(1600732800, 6.37, 6.41, 6.16, 6.18, 18554, 1, 18839800)\n",
      "(1600819200, 6.2, 6.36, 6.03, 6.04, 19708, 1, 14154200)\n",
      "(1600905600, 6.09, 6.29, 5.98, 6.18, 20536, 1, 19673600)\n",
      "(1600992000, 6.15, 6.22, 6.07, 6.12, 11808, 1, 10506200)\n",
      "(1601251200, 6.23, 6.66, 6.21, 6.36, 33385, 1, 33001000)\n",
      "(1601337600, 6.41, 6.56, 6.1, 6.1, 19942, 1, 17719100)\n",
      "(1601424000, 6.15, 6.35, 6.14, 6.24, 13440, 1, 13135300)\n",
      "(1601510400, 6.29, 6.48, 6.24, 6.47, 14532, 1, 11926300)\n",
      "(1601596800, 6.39, 6.55, 6.34, 6.49, 16761, 1, 12250100)\n",
      "(1601856000, 6.52, 6.64, 6.4, 6.42, 15931, 1, 10375900)\n",
      "(1601942400, 6.65, 6.92, 6.57, 6.62, 24952, 1, 23855100)\n",
      "(1602028800, 6.66, 6.73, 6.35, 6.37, 17631, 1, 14278700)\n",
      "(1602115200, 6.41, 6.69, 6.35, 6.69, 13215, 1, 10352100)\n",
      "(1602201600, 6.67, 6.82, 6.56, 6.69, 13174, 1, 10112200)\n",
      "(1602547200, 6.69, 6.71, 6.45, 6.49, 13704, 1, 10006800)\n",
      "(1602633600, 6.5, 6.68, 6.5, 6.57, 14255, 1, 10610300)\n",
      "(1602720000, 6.49, 6.63, 6.41, 6.6, 16585, 1, 8834000)\n",
      "(1602806400, 6.58, 6.66, 6.42, 6.47, 15912, 1, 9795900)\n",
      "(1603065600, 6.48, 6.69, 6.37, 6.4, 12964, 1, 10619800)\n",
      "(1603152000, 6.51, 6.63, 6.4, 6.59, 10940, 1, 10773300)\n",
      "(1603238400, 6.59, 6.86, 6.53, 6.79, 16042, 1, 15661800)\n",
      "(1603324800, 6.82, 6.95, 6.68, 6.82, 21087, 1, 16937700)\n",
      "(1603411200, 6.85, 7.17, 6.79, 7.09, 24204, 1, 23368000)\n",
      "(1603670400, 7.04, 7.08, 6.83, 6.88, 16036, 1, 15093100)\n",
      "(1603756800, 6.89, 6.94, 6.43, 6.45, 18828, 1, 23087100)\n",
      "(1603843200, 6.3, 6.3, 6.05, 6.05, 18899, 1, 20628000)\n",
      "(1603929600, 6.04, 6.11, 5.77, 6.11, 23377, 1, 23502100)\n",
      "(1604016000, 6.02, 6.08, 5.85, 6.03, 19632, 1, 18797600)\n",
      "(1604361600, 6.17, 6.21, 5.98, 6.03, 19424, 1, 14542900)\n",
      "(1604448000, 6.11, 6.29, 5.98, 6.24, 17068, 1, 14671100)\n",
      "(1604534400, 6.34, 6.63, 6.27, 6.61, 18040, 1, 15426800)\n",
      "(1604620800, 6.53, 6.68, 6.45, 6.55, 12318, 1, 11239900)\n",
      "(1604880000, 7., 7.53, 6.97, 7.41, 42012, 1, 44199300)\n",
      "(1604966400, 7.3, 7.48, 6.91, 7.32, 36677, 1, 33217300)\n",
      "(1605052800, 7.32, 7.59, 7.08, 7.18, 23471, 1, 19619800)\n",
      "(1605139200, 7.18, 7.32, 6.94, 7.02, 15453, 1, 14724800)\n",
      "(1605225600, 7.13, 7.53, 7.05, 7.45, 23206, 1, 21272300)\n",
      "(1605484800, 7.68, 8.1, 7.5, 8.05, 33302, 1, 28955100)\n",
      "(1605571200, 7.91, 8.18, 7.74, 8.1, 24939, 1, 21074200)\n",
      "(1605657600, 8.15, 8.5, 8., 8.05, 32925, 1, 26941700)\n",
      "(1605744000, 8.05, 8.14, 7.83, 8.08, 23994, 1, 17577500)\n",
      "(1605830400, 8.13, 8.15, 7.83, 7.9, 15341, 1, 12655000)\n",
      "(1606089600, 8.03, 8.39, 7.98, 8.21, 20312, 1, 16750700)\n",
      "(1606176000, 8.31, 8.67, 8.13, 8.41, 25582, 1, 22776900)\n",
      "(1606262400, 8.37, 8.5, 8.18, 8.31, 15591, 1, 12922000)\n",
      "(1606348800, 8.31, 8.4, 8.14, 8.27, 7567, 1, 6760600)\n",
      "(1606435200, 8.33, 8.54, 8.25, 8.25, 14185, 1, 10549200)\n",
      "(1606694400, 8.24, 8.45, 8.05, 8.1, 16561, 1, 15508900)\n",
      "(1606780800, 8.23, 8.44, 8.15, 8.21, 19117, 1, 13823800)\n",
      "(1606867200, 8.25, 8.44, 8.07, 8.42, 14153, 1, 11727400)\n",
      "(1606953600, 8.43, 9.7, 8.4, 9.35, 58442, 1, 58068300)\n",
      "(1607040000, 9.6, 9.92, 9.1, 9.37, 39409, 1, 33474800)\n",
      "(1607299200, 9.39, 9.57, 9.23, 9.37, 22535, 1, 18074300)\n",
      "(1607385600, 9.34, 9.42, 9.08, 9.18, 19886, 1, 14696800)\n",
      "(1607472000, 9.22, 9.29, 8.9, 8.97, 25115, 1, 19204600)\n",
      "(1607558400, 9.02, 9.06, 8.72, 8.89, 17032, 1, 12366600)\n",
      "(1607644800, 8.77, 9.12, 8.65, 9.05, 23143, 1, 16155700)\n",
      "(1607904000, 9.2, 9.32, 8.97, 9.01, 18778, 1, 14373100)\n",
      "(1607990400, 9.12, 9.38, 8.94, 9.27, 19195, 1, 15532700)\n",
      "(1608076800, 9.3, 9.33, 9.08, 9.22, 20499, 1, 12496300)\n",
      "(1608163200, 9.22, 9.4, 9.05, 9.11, 15342, 1, 13087000)\n",
      "(1608249600, 9.16, 9.21, 8.92, 8.95, 15782, 1, 15034600)\n",
      "(1608508800, 8.6, 8.8, 8.39, 8.54, 23110, 1, 21451300)\n",
      "(1608595200, 8.58, 8.67, 8.16, 8.22, 19366, 1, 13200500)\n",
      "(1608681600, 8.24, 8.57, 8.24, 8.56, 14687, 1, 13045000)\n",
      "(1609113600, 8.64, 8.69, 8.51, 8.67, 14932, 1, 11250800)\n",
      "(1609200000, 8.7, 8.78, 8.58, 8.63, 14529, 1, 8791200)\n",
      "(1609286400, 8.63, 8.9, 8.58, 8.85, 13711, 1, 10953200)\n",
      "(1609718400, 8.94, 9., 8.31, 8.37, 20537, 1, 17114300)\n",
      "(1609804800, 8.34, 8.68, 8.21, 8.57, 17695, 1, 12580900)\n",
      "(1609891200, 8.58, 9.15, 8.51, 8.91, 24952, 1, 21813900)\n",
      "(1609977600, 8.93, 9.14, 8.82, 8.88, 17430, 1, 12826600)\n",
      "(1610064000, 8.92, 9.01, 8.66, 8.81, 15476, 1, 11694800)\n",
      "(1610323200, 8.71, 8.85, 8.54, 8.61, 15861, 1, 10674400)\n",
      "(1610409600, 8.71, 9.33, 8.68, 9.29, 28694, 1, 27161800)\n",
      "(1610496000, 9.29, 9.4, 9.03, 9.2, 19962, 1, 13906900)\n",
      "(1610582400, 9.3, 10.09, 9.22, 9.98, 40891, 1, 35630400)\n",
      "(1610668800, 9.82, 9.96, 9.5, 9.52, 24600, 1, 19587300)\n",
      "(1610928000, 9.65, 9.95, 9.31, 9.38, 16464, 1, 15640200)\n",
      "(1611014400, 9.51, 9.55, 9.25, 9.47, 15999, 1, 15766400)\n",
      "(1611100800, 9.38, 9.62, 9., 9.16, 28928, 1, 23370100)\n",
      "(1611187200, 9.03, 9.07, 8.79, 8.88, 23615, 1, 18663900)\n",
      "(1611273600, 8.59, 8.74, 8.45, 8.66, 24504, 1, 18285000)\n",
      "(1611619200, 8.76, 8.96, 8.6, 8.65, 19791, 1, 12184600)\n",
      "(1611705600, 8.63, 9.09, 8.47, 8.84, 23093, 1, 16744100)\n",
      "(1611792000, 8.84, 9.27, 8.84, 9.13, 19478, 1, 15782000)\n",
      "(1611878400, 9., 9.22, 8.73, 8.79, 15623, 1, 11819800)\n",
      "(1612137600, 8.93, 8.99, 8.77, 8.93, 14455, 1, 10035300)\n",
      "(1612224000, 9.05, 9.54, 9.05, 9.53, 24541, 1, 16198400)\n",
      "(1612310400, 9.54, 9.82, 9.42, 9.64, 21688, 1, 15124400)\n",
      "(1612396800, 9.66, 9.85, 9.43, 9.45, 12795, 1, 8865100)\n",
      "(1612483200, 9.55, 9.62, 9.39, 9.47, 10358, 1, 7112500)\n",
      "(1612742400, 9.44, 9.75, 9.32, 9.63, 13840, 1, 9757300)\n",
      "(1612828800, 9.54, 9.67, 9.41, 9.63, 12071, 1, 7257700)\n",
      "(1612915200, 9.63, 9.94, 9.59, 9.67, 18976, 1, 14265200)\n",
      "(1613001600, 9.7, 10.46, 9.68, 10.02, 28639, 1, 25036500)\n",
      "(1613088000, 10.1, 10.25, 9.89, 10.08, 17897, 1, 15297700)\n",
      "(1613520000, 11.01, 11.58, 10.74, 11.5, 42256, 1, 37144800)\n",
      "(1613606400, 11.59, 12.37, 11.17, 11.3, 50280, 1, 33704500)\n",
      "(1613692800, 11.28, 11.73, 10.99, 11.62, 23435, 1, 15216400)\n",
      "(1613952000, 11.2, 12.77, 11.11, 12.48, 52775, 1, 36289800)\n",
      "(1614038400, 12.68, 12.68, 11.67, 12.35, 37445, 1, 21373800)\n",
      "(1614124800, 12.44, 13.33, 12.2, 13.1, 38110, 1, 25174200)\n",
      "(1614211200, 13.07, 13.22, 12.21, 12.27, 39087, 1, 21108300)\n",
      "(1614297600, 12.31, 12.42, 11.79, 12.23, 30534, 1, 17922400)\n",
      "(1614556800, 12.53, 12.7, 12.15, 12.21, 27387, 1, 14282400)\n",
      "(1614643200, 12.13, 12.56, 11.49, 12.42, 36223, 1, 16942600)\n",
      "(1614729600, 12.35, 12.56, 11.96, 12.43, 37672, 1, 18422000)\n",
      "(1614816000, 12.5, 12.94, 12.15, 12.4, 34331, 1, 18129600)\n",
      "(1614902400, 12.45, 12.89, 11.94, 12.82, 31292, 1, 17275100)\n",
      "(1615161600, 12.59, 13.1, 12.14, 12.23, 30990, 1, 15305200)\n",
      "(1615248000, 12.21, 12.53, 12., 12.34, 25661, 1, 12879700)\n",
      "(1615334400, 12.38, 13.82, 12.24, 13.82, 36574, 1, 22790700)\n",
      "(1615420800, 13.84, 13.93, 13.4, 13.74, 32901, 1, 17259300)\n",
      "(1615507200, 13.69, 14.52, 13.67, 14.4, 32812, 1, 20211700)\n",
      "(1615766400, 14.25, 15.04, 14.13, 14.69, 33704, 1, 17997800)\n",
      "(1615852800, 14.7, 14.82, 13.73, 13.99, 29887, 1, 15945200)\n",
      "(1615939200, 13.99, 14.45, 13.85, 14.42, 27577, 1, 12468800)\n",
      "(1616025600, 14.44, 14.64, 13.81, 13.95, 23316, 1, 11640600)\n",
      "(1616112000, 14.08, 14.78, 13.21, 14.51, 42838, 1, 31426600)\n",
      "(1616371200, 14.39, 14.45, 13.25, 13.43, 41036, 1, 26341900)\n",
      "(1616457600, 13.43, 14.25, 13.24, 13.35, 35705, 1, 20400800)\n",
      "(1616544000, 13.41, 13.9, 13.06, 13.1, 29754, 1, 15243700)\n",
      "(1616630400, 13.15, 13.43, 12.69, 13.19, 35530, 1, 17566100)\n",
      "(1616716800, 13.23, 13.6, 12.99, 13.2, 26663, 1, 15215500)\n",
      "(1616976000, 13.02, 13.46, 13.02, 13.12, 26495, 1, 12691500)\n",
      "(1617062400, 13.05, 14.4, 13.05, 14.34, 39057, 1, 22613700)\n",
      "(1617148800, 14.29, 14.33, 13.92, 14.01, 23935, 1, 11090300)\n",
      "(1617235200, 14.18, 14.63, 13.86, 13.9, 21210, 1, 12495300)\n",
      "(1617580800, 14.09, 14.8, 14.04, 14.66, 28707, 1, 16037100)\n",
      "(1617667200, 14.66, 14.83, 14.41, 14.46, 17421, 1, 8719800)\n",
      "(1617753600, 14.46, 14.8, 14.32, 14.78, 21998, 1, 11031400)\n",
      "(1617840000, 14.8, 16.08, 14.7, 16.08, 42175, 1, 24972000)\n",
      "(1617926400, 15.89, 16.05, 15.61, 15.96, 29433, 1, 14442500)\n",
      "(1618185600, 16.05, 16.2, 15.69, 16.05, 31185, 1, 12827700)\n",
      "(1618272000, 16., 16.17, 15.52, 15.76, 22604, 1, 12278800)\n",
      "(1618358400, 15.77, 16.55, 15.77, 16.14, 25256, 1, 12553300)\n",
      "(1618444800, 16.29, 16.4, 15.78, 15.96, 22951, 1, 11009500)\n",
      "(1618531200, 15.98, 16.04, 15.69, 15.81, 14766, 1, 6713700)\n",
      "(1618790400, 15.83, 15.87, 15.41, 15.43, 20384, 1, 9130700)\n",
      "(1618876800, 15.42, 15.61, 14.6, 15.08, 35418, 1, 22750700)\n",
      "(1619049600, 15.24, 15.45, 15.01, 15.19, 24102, 1, 9131400)\n",
      "(1619136000, 15.28, 15.65, 15.22, 15.51, 24098, 1, 8007100)\n",
      "(1619395200, 15.74, 16.1, 15.59, 16.09, 18956, 1, 9146800)\n",
      "(1619481600, 16.19, 16.48, 15.63, 15.93, 19904, 1, 9511600)\n",
      "(1619568000, 15.96, 16.02, 15.68, 15.78, 13341, 1, 5342800)\n",
      "(1619654400, 15.58, 15.89, 15.03, 15.1, 20664, 1, 9124000)\n",
      "(1619740800, 15.12, 15.43, 14.9, 15.4, 18987, 1, 8842600)\n",
      "(1620000000, 15.22, 15.96, 15.14, 15.96, 24852, 1, 9563700)\n",
      "(1620086400, 15.92, 16.16, 15.62, 15.91, 21077, 1, 9960800)\n",
      "(1620172800, 16.07, 16.09, 15.62, 15.71, 13783, 1, 5835600)\n",
      "(1620259200, 15.79, 16.17, 15.43, 15.82, 20585, 1, 9024000)\n",
      "(1620345600, 15.83, 16.99, 15.79, 16.99, 25745, 1, 13021200)\n",
      "(1620604800, 16.98, 17.18, 16.48, 16.57, 23598, 1, 8527700)\n",
      "(1620691200, 16.41, 16.69, 15.92, 16.44, 22098, 1, 9895500)\n",
      "(1620777600, 16.46, 16.5, 15.34, 15.57, 39040, 1, 19340900)\n",
      "(1620864000, 15.69, 16.01, 15.26, 15.53, 32760, 1, 13724000)\n",
      "(1620950400, 15.8, 16.22, 15.66, 15.99, 18475, 1, 7096200)\n",
      "(1621209600, 15.95, 16.1, 15.68, 16.1, 15093, 1, 5714900)\n",
      "(1621296000, 16.08, 16.64, 15.88, 16.42, 20659, 1, 9084400)\n",
      "(1621382400, 16.17, 16.17, 15.6, 15.89, 23166, 1, 12152800)\n",
      "(1621468800, 15.92, 16.17, 15.67, 16.15, 15859, 1, 7952500)\n",
      "(1621555200, 16.2, 16.76, 15.91, 16.66, 24397, 1, 11497400)\n",
      "(1621814400, 16.74, 17.09, 16.51, 17.05, 16915, 1, 7534900)\n",
      "(1621900800, 17.14, 17.79, 17.1, 17.27, 26940, 1, 13293700)\n",
      "(1621987200, 17.4, 17.65, 16.76, 16.85, 18315, 1, 10202000)\n",
      "(1622073600, 17.05, 18., 17.05, 17.87, 41020, 1, 19360600)\n",
      "(1622160000, 17.91, 18.03, 17.08, 17.43, 18652, 1, 9533400)\n",
      "(1622419200, 17.4, 17.43, 17.15, 17.28, 6455, 1, 2870500)\n",
      "(1622505600, 17.79, 18.55, 17.77, 17.98, 34990, 1, 14659600)\n",
      "(1622592000, 18.05, 18.15, 17.66, 17.82, 18534, 1, 7200200)\n",
      "(1622764800, 17.82, 17.84, 17.25, 17.26, 19661, 1, 8246600)\n",
      "(1623024000, 17.33, 17.5, 17.15, 17.48, 17813, 1, 7557900)\n",
      "(1623110400, 17.57, 18.1, 17.4, 17.55, 18168, 1, 8021300)\n",
      "(1623196800, 17.61, 17.67, 17.23, 17.3, 14292, 1, 5943000)\n",
      "(1623283200, 19.6, 20., 19.15, 20., 66232, 1, 38439200)\n",
      "(1623369600, 20.47, 21.29, 20.28, 21.02, 54826, 1, 27538000)\n",
      "(1623628800, 21.15, 21.5, 20.86, 21.07, 27951, 1, 13645800)\n",
      "(1623715200, 21.06, 21.56, 20.71, 21.38, 24624, 1, 11609300)\n",
      "(1623801600, 21.3, 21.3, 20.16, 20.44, 35399, 1, 15821000)\n",
      "(1623888000, 20.34, 20.63, 19.97, 20.23, 20836, 1, 8779100)\n",
      "(1623974400, 20.2, 20.48, 19.65, 20., 25054, 1, 11775500)\n",
      "(1624233600, 20.05, 20.35, 19.83, 20.35, 14106, 1, 5096600)\n",
      "(1624320000, 20.35, 20.45, 19.66, 20.08, 21813, 1, 8302100)\n",
      "(1624406400, 20.17, 20.44, 19.55, 19.66, 19495, 1, 9356900)\n",
      "(1624492800, 19.76, 20.02, 19.48, 19.61, 18285, 1, 8660500)\n",
      "(1624579200, 19.8, 19.85, 18.83, 19.1, 22368, 1, 9646400)\n",
      "(1624838400, 19.06, 19.21, 18.71, 18.99, 12916, 1, 5925400)\n",
      "(1624924800, 18.98, 19.06, 18.4, 18.61, 19059, 1, 7442600)\n",
      "(1625011200, 18.55, 19.02, 18.36, 18.87, 15727, 1, 6054300)\n",
      "(1625097600, 18.99, 19.1, 18.56, 18.74, 14067, 1, 4894900)\n",
      "(1625184000, 18.84, 19.21, 18.6, 18.95, 10298, 1, 5207400)\n",
      "(1625443200, 18.8, 19.45, 18.74, 18.98, 8642, 1, 4949700)\n",
      "(1625529600, 18.95, 19.09, 18.61, 18.69, 13094, 1, 4164200)\n",
      "(1625616000, 18.82, 19.11, 18.38, 18.69, 19441, 1, 6970000)\n",
      "(1625702400, 18.27, 18.58, 18., 18.21, 14091, 1, 5746800)\n",
      "(1626048000, 18.57, 19.72, 18.38, 19.7, 28085, 1, 17533500)\n",
      "(1626134400, 19.73, 19.92, 19.06, 19.12, 15595, 1, 10021700)\n",
      "(1626220800, 19.25, 19.36, 18.51, 18.63, 18121, 1, 10325400)\n",
      "(1626307200, 18.7, 18.78, 18.05, 18.27, 11976, 1, 6409400)\n",
      "(1626393600, 18.4, 18.47, 17.44, 17.54, 17695, 1, 10316900)\n",
      "(1626652800, 17.32, 17.32, 16.72, 17.3, 28411, 1, 14570400)\n",
      "(1626739200, 17.44, 18.43, 17.31, 18.32, 15530, 1, 11254500)\n",
      "(1626825600, 18.37, 19.17, 18.26, 18.87, 17129, 1, 10788000)\n",
      "(1626912000, 18.87, 19.24, 18.49, 18.7, 16711, 1, 7039900)\n",
      "(1626998400, 18.7, 19., 18.5, 18.51, 10007, 1, 5957800)\n",
      "(1627257600, 18.48, 19.42, 18.35, 19.16, 16543, 1, 10260800)\n",
      "(1627344000, 19.09, 19.3, 18.58, 18.92, 15349, 1, 10605000)\n",
      "(1627430400, 19.09, 19.39, 18.86, 19.37, 18587, 1, 11330300)\n",
      "(1627516800, 19.37, 19.63, 19.15, 19.42, 15594, 1, 10088100)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1627603200, 19.25, 19.46, 18.42, 18.59, 14472, 1, 10319500)\n",
      "(1627862400, 18.79, 19.68, 18.6, 18.89, 19570, 1, 12336100)\n",
      "(1627948800, 18.86, 19.03, 17.96, 18.92, 18806, 1, 11457100)\n",
      "(1628035200, 18.91, 19.1, 18.26, 18.32, 13535, 1, 8066600)\n",
      "(1628121600, 18.5, 18.94, 18.45, 18.62, 13861, 1, 7682400)\n",
      "(1628208000, 18.55, 19.37, 18.55, 19.23, 12169, 1, 6959500)\n",
      "(1628467200, 19.06, 19.2, 18.69, 18.98, 10432, 1, 5293400)\n",
      "(1628553600, 19.2, 19.84, 19.08, 19.6, 32466, 1, 16262400)\n",
      "(1628640000, 19.59, 19.97, 19.18, 19.93, 17565, 1, 11121800)\n",
      "(1628726400, 19.94, 20.17, 19.3, 19.38, 14526, 1, 7477600)\n",
      "(1628812800, 19.93, 20.85, 19.84, 20.79, 35756, 1, 20326400)\n",
      "(1629072000, 20.76, 20.9, 19.34, 19.45, 30845, 1, 15163900)\n",
      "(1629158400, 19.27, 19.27, 17.84, 18.16, 37309, 1, 21163500)\n",
      "(1629244800, 18.31, 19.38, 18.08, 18.83, 32289, 1, 21417500)\n",
      "(1629331200, 18.45, 19.72, 18.28, 19.56, 22892, 1, 13352300)\n",
      "(1629417600, 19.27, 19.95, 19.14, 19.87, 17160, 1, 9725800)\n",
      "(1629676800, 19.88, 21.15, 19.76, 20.92, 27964, 1, 15404600)\n",
      "(1629763200, 20.86, 22.74, 20.86, 22.62, 37075, 1, 20384800)\n",
      "(1629849600, 22.57, 23.46, 22.24, 23.34, 31966, 1, 20744300)\n",
      "(1629936000, 23.2, 23.85, 23.06, 23.12, 22782, 1, 12239700)\n",
      "(1630022400, 23.12, 23.79, 22.9, 23.68, 16781, 1, 9704500)\n",
      "(1630281600, 23.6, 23.83, 22.86, 23.15, 17242, 1, 7931300)\n",
      "(1630368000, 23.07, 23.72, 22.89, 23.42, 26691, 1, 12278400)\n",
      "(1630454400, 23.6, 24.03, 22.82, 22.93, 21692, 1, 9545300)\n",
      "(1630540800, 22.86, 23.62, 22.72, 22.78, 25924, 1, 12371600)\n",
      "(1630627200, 22.81, 23.2, 22.03, 22.17, 5136, 0, 3852800)\n"
     ]
    }
   ],
   "source": [
    "# exibimos cada elemento de dados recebidos numa nova linha\n",
    "print(\"Exibimos os dados recebidos como estão\")\n",
    "for rate in rates:\n",
    "    print(rate)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 213,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "# a partir dos dados recebidos criamos o DataFrame\n",
    "rates_frame = pd.DataFrame(rates)\n",
    "# convertemos o tempo em segundos no formato datetime\n",
    "rates_frame['time']=pd.to_datetime(rates_frame['time'], unit='s')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 214,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(300, 8)"
      ]
     },
     "execution_count": 214,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rates_frame.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 215,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 215,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "rates_frame.close.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Função copy_rates_range"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "from datetime import datetime"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Rodar essa função para ver todos os fusos disponíveis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "pytz.all_timezones"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [],
   "source": [
    "timezone = pytz.timezone(\"Etc/GMT-3\")\n",
    "\n",
    "inicio = datetime(2021, 9, 27, hour = 9, tzinfo = timezone)\n",
    "fim = datetime(2021, 9, 27, hour = 17, tzinfo = timezone)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [],
   "source": [
    "# obtemos as barras com USDJPY M5 no intervalo 2020.01.10 00:00 - 2020.01.11 13:00 no fuso horário UTC\n",
    "rates = mt5.copy_rates_range(\"WEGE3\", mt5.TIMEFRAME_M1, inicio, fim)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [],
   "source": [
    "# a partir dos dados recebidos criamos o DataFrame\n",
    "rates_frame = pd.DataFrame(rates)\n",
    "# convertemos o tempo em segundos no formato datetime\n",
    "rates_frame['time']=pd.to_datetime(rates_frame['time'], unit='s')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "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>time</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>tick_volume</th>\n",
       "      <th>spread</th>\n",
       "      <th>real_volume</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2021-09-27 10:07:00</td>\n",
       "      <td>41.06</td>\n",
       "      <td>41.08</td>\n",
       "      <td>40.88</td>\n",
       "      <td>40.95</td>\n",
       "      <td>78</td>\n",
       "      <td>0</td>\n",
       "      <td>61200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2021-09-27 10:08:00</td>\n",
       "      <td>40.95</td>\n",
       "      <td>40.95</td>\n",
       "      <td>40.79</td>\n",
       "      <td>40.79</td>\n",
       "      <td>71</td>\n",
       "      <td>1</td>\n",
       "      <td>41300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2021-09-27 10:09:00</td>\n",
       "      <td>40.83</td>\n",
       "      <td>40.84</td>\n",
       "      <td>40.71</td>\n",
       "      <td>40.73</td>\n",
       "      <td>57</td>\n",
       "      <td>1</td>\n",
       "      <td>38100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021-09-27 10:10:00</td>\n",
       "      <td>40.75</td>\n",
       "      <td>40.95</td>\n",
       "      <td>40.75</td>\n",
       "      <td>40.91</td>\n",
       "      <td>59</td>\n",
       "      <td>1</td>\n",
       "      <td>46000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2021-09-27 10:11:00</td>\n",
       "      <td>40.90</td>\n",
       "      <td>40.90</td>\n",
       "      <td>40.75</td>\n",
       "      <td>40.89</td>\n",
       "      <td>52</td>\n",
       "      <td>2</td>\n",
       "      <td>25600</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 time   open   high    low  close  tick_volume  spread  \\\n",
       "0 2021-09-27 10:07:00  41.06  41.08  40.88  40.95           78       0   \n",
       "1 2021-09-27 10:08:00  40.95  40.95  40.79  40.79           71       1   \n",
       "2 2021-09-27 10:09:00  40.83  40.84  40.71  40.73           57       1   \n",
       "3 2021-09-27 10:10:00  40.75  40.95  40.75  40.91           59       1   \n",
       "4 2021-09-27 10:11:00  40.90  40.90  40.75  40.89           52       2   \n",
       "\n",
       "   real_volume  \n",
       "0        61200  \n",
       "1        41300  \n",
       "2        38100  \n",
       "3        46000  \n",
       "4        25600  "
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rates_frame.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='time'>"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "rates_frame.index = rates_frame['time']\n",
    "rates_frame.close.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(223, 8)"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rates_frame.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Função copy_ticks_from"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "COPY_TICKS_INFO - apenas as alterações no Bid & ASk\n",
    "\n",
    "COPY_TICKS_TRADE - apenas alterações no volume\n",
    "\n",
    "COPY_TICKS_ALL - todos os ticks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='time'>"
      ]
     },
     "execution_count": 117,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dados = mt5.copy_ticks_from(\"WEGE3\",inicio,100000, mt5.COPY_TICKS_ALL)\n",
    "\n",
    "# a partir dos dados recebidos criamos o DataFrame\n",
    "dados_frame = pd.DataFrame(dados)\n",
    "\n",
    "# convertemos o tempo em segundos no formato datetime\n",
    "dados_frame['time']=pd.to_datetime(dados_frame['time'], unit='s')\n",
    "\n",
    "dados_frame.index = dados_frame['time']\n",
    "dados_frame['last'].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "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>time</th>\n",
       "      <th>bid</th>\n",
       "      <th>ask</th>\n",
       "      <th>last</th>\n",
       "      <th>volume</th>\n",
       "      <th>time_msc</th>\n",
       "      <th>flags</th>\n",
       "      <th>volume_real</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>time</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2021-09-27 10:07:31</th>\n",
       "      <td>2021-09-27 10:07:31</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>41.06</td>\n",
       "      <td>3300</td>\n",
       "      <td>1632737251706</td>\n",
       "      <td>56</td>\n",
       "      <td>3300.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-27 10:07:31</th>\n",
       "      <td>2021-09-27 10:07:31</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>41.06</td>\n",
       "      <td>2900</td>\n",
       "      <td>1632737251706</td>\n",
       "      <td>56</td>\n",
       "      <td>2900.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-27 10:07:31</th>\n",
       "      <td>2021-09-27 10:07:31</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>41.06</td>\n",
       "      <td>4200</td>\n",
       "      <td>1632737251706</td>\n",
       "      <td>56</td>\n",
       "      <td>4200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-27 10:07:31</th>\n",
       "      <td>2021-09-27 10:07:31</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>41.06</td>\n",
       "      <td>3500</td>\n",
       "      <td>1632737251706</td>\n",
       "      <td>56</td>\n",
       "      <td>3500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-27 10:07:31</th>\n",
       "      <td>2021-09-27 10:07:31</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>41.06</td>\n",
       "      <td>10500</td>\n",
       "      <td>1632737251706</td>\n",
       "      <td>56</td>\n",
       "      <td>10500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-27 10:07:45</th>\n",
       "      <td>2021-09-27 10:07:45</td>\n",
       "      <td>40.9</td>\n",
       "      <td>40.95</td>\n",
       "      <td>40.91</td>\n",
       "      <td>200</td>\n",
       "      <td>1632737265582</td>\n",
       "      <td>4</td>\n",
       "      <td>200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-27 10:07:45</th>\n",
       "      <td>2021-09-27 10:07:45</td>\n",
       "      <td>40.9</td>\n",
       "      <td>40.94</td>\n",
       "      <td>40.91</td>\n",
       "      <td>200</td>\n",
       "      <td>1632737265881</td>\n",
       "      <td>4</td>\n",
       "      <td>200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-27 10:07:46</th>\n",
       "      <td>2021-09-27 10:07:46</td>\n",
       "      <td>40.9</td>\n",
       "      <td>40.94</td>\n",
       "      <td>40.90</td>\n",
       "      <td>300</td>\n",
       "      <td>1632737266146</td>\n",
       "      <td>88</td>\n",
       "      <td>300.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-27 10:07:46</th>\n",
       "      <td>2021-09-27 10:07:46</td>\n",
       "      <td>40.9</td>\n",
       "      <td>40.94</td>\n",
       "      <td>40.89</td>\n",
       "      <td>100</td>\n",
       "      <td>1632737266146</td>\n",
       "      <td>88</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-27 10:07:46</th>\n",
       "      <td>2021-09-27 10:07:46</td>\n",
       "      <td>40.9</td>\n",
       "      <td>40.94</td>\n",
       "      <td>40.88</td>\n",
       "      <td>100</td>\n",
       "      <td>1632737266146</td>\n",
       "      <td>88</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>70 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   time   bid    ask   last  volume  \\\n",
       "time                                                                  \n",
       "2021-09-27 10:07:31 2021-09-27 10:07:31   0.0   0.00  41.06    3300   \n",
       "2021-09-27 10:07:31 2021-09-27 10:07:31   0.0   0.00  41.06    2900   \n",
       "2021-09-27 10:07:31 2021-09-27 10:07:31   0.0   0.00  41.06    4200   \n",
       "2021-09-27 10:07:31 2021-09-27 10:07:31   0.0   0.00  41.06    3500   \n",
       "2021-09-27 10:07:31 2021-09-27 10:07:31   0.0   0.00  41.06   10500   \n",
       "...                                 ...   ...    ...    ...     ...   \n",
       "2021-09-27 10:07:45 2021-09-27 10:07:45  40.9  40.95  40.91     200   \n",
       "2021-09-27 10:07:45 2021-09-27 10:07:45  40.9  40.94  40.91     200   \n",
       "2021-09-27 10:07:46 2021-09-27 10:07:46  40.9  40.94  40.90     300   \n",
       "2021-09-27 10:07:46 2021-09-27 10:07:46  40.9  40.94  40.89     100   \n",
       "2021-09-27 10:07:46 2021-09-27 10:07:46  40.9  40.94  40.88     100   \n",
       "\n",
       "                          time_msc  flags  volume_real  \n",
       "time                                                    \n",
       "2021-09-27 10:07:31  1632737251706     56       3300.0  \n",
       "2021-09-27 10:07:31  1632737251706     56       2900.0  \n",
       "2021-09-27 10:07:31  1632737251706     56       4200.0  \n",
       "2021-09-27 10:07:31  1632737251706     56       3500.0  \n",
       "2021-09-27 10:07:31  1632737251706     56      10500.0  \n",
       "...                            ...    ...          ...  \n",
       "2021-09-27 10:07:45  1632737265582      4        200.0  \n",
       "2021-09-27 10:07:45  1632737265881      4        200.0  \n",
       "2021-09-27 10:07:46  1632737266146     88        300.0  \n",
       "2021-09-27 10:07:46  1632737266146     88        100.0  \n",
       "2021-09-27 10:07:46  1632737266146     88        100.0  \n",
       "\n",
       "[70 rows x 8 columns]"
      ]
     },
     "execution_count": 118,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dados_frame.head(70)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Função copy_ticks_range"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "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>time</th>\n",
       "      <th>bid</th>\n",
       "      <th>ask</th>\n",
       "      <th>last</th>\n",
       "      <th>volume</th>\n",
       "      <th>time_msc</th>\n",
       "      <th>flags</th>\n",
       "      <th>volume_real</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>time</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2021-09-27 10:07:31</th>\n",
       "      <td>2021-09-27 10:07:31</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>41.06</td>\n",
       "      <td>3300</td>\n",
       "      <td>1632737251706</td>\n",
       "      <td>56</td>\n",
       "      <td>3300.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-27 10:07:31</th>\n",
       "      <td>2021-09-27 10:07:31</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>41.06</td>\n",
       "      <td>2900</td>\n",
       "      <td>1632737251706</td>\n",
       "      <td>56</td>\n",
       "      <td>2900.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-27 10:07:31</th>\n",
       "      <td>2021-09-27 10:07:31</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>41.06</td>\n",
       "      <td>4200</td>\n",
       "      <td>1632737251706</td>\n",
       "      <td>56</td>\n",
       "      <td>4200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-27 10:07:31</th>\n",
       "      <td>2021-09-27 10:07:31</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>41.06</td>\n",
       "      <td>3500</td>\n",
       "      <td>1632737251706</td>\n",
       "      <td>56</td>\n",
       "      <td>3500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-27 10:07:31</th>\n",
       "      <td>2021-09-27 10:07:31</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>41.06</td>\n",
       "      <td>10500</td>\n",
       "      <td>1632737251706</td>\n",
       "      <td>56</td>\n",
       "      <td>10500.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   time  bid  ask   last  volume  \\\n",
       "time                                                               \n",
       "2021-09-27 10:07:31 2021-09-27 10:07:31  0.0  0.0  41.06    3300   \n",
       "2021-09-27 10:07:31 2021-09-27 10:07:31  0.0  0.0  41.06    2900   \n",
       "2021-09-27 10:07:31 2021-09-27 10:07:31  0.0  0.0  41.06    4200   \n",
       "2021-09-27 10:07:31 2021-09-27 10:07:31  0.0  0.0  41.06    3500   \n",
       "2021-09-27 10:07:31 2021-09-27 10:07:31  0.0  0.0  41.06   10500   \n",
       "\n",
       "                          time_msc  flags  volume_real  \n",
       "time                                                    \n",
       "2021-09-27 10:07:31  1632737251706     56       3300.0  \n",
       "2021-09-27 10:07:31  1632737251706     56       2900.0  \n",
       "2021-09-27 10:07:31  1632737251706     56       4200.0  \n",
       "2021-09-27 10:07:31  1632737251706     56       3500.0  \n",
       "2021-09-27 10:07:31  1632737251706     56      10500.0  "
      ]
     },
     "execution_count": 121,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# obtemos as barras com USDJPY M5 no intervalo 2020.01.10 00:00 - 2020.01.11 13:00 no fuso horário UTC\n",
    "rates = mt5.copy_ticks_range(\"WEGE3\", inicio, fim,  mt5.COPY_TICKS_ALL)\n",
    "\n",
    "# a partir dos dados recebidos criamos o DataFrame\n",
    "rates_frame = pd.DataFrame(rates)\n",
    "# convertemos o tempo em segundos no formato datetime\n",
    "rates_frame['time']=pd.to_datetime(rates_frame['time'], unit='s')\n",
    "\n",
    "rates_frame.index = rates_frame['time']\n",
    "rates_frame.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='time'>"
      ]
     },
     "execution_count": 122,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "rates_frame['last'].plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 5. Vamos mexer com as ordens"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 123,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mt5.orders_total()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "No orders on GBPUSD, error code=(-4, 'Terminal: Not found')\n",
      "\n"
     ]
    }
   ],
   "source": [
    "orders=mt5.orders_get(symbol=\"GBPUSD\")\n",
    "if orders is None:\n",
    "    print(\"No orders on GBPUSD, error code={}\".format(mt5.last_error()))\n",
    "else:\n",
    "    print(\"Total orders on GBPUSD:\",len(orders))\n",
    "    # exibimos todas as ordens ativas\n",
    "    for order in orders:\n",
    "        print(order)\n",
    "print()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {},
   "outputs": [],
   "source": [
    "symbol = 'WEGE3'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {},
   "outputs": [],
   "source": [
    "ask=mt5.symbol_info_tick(symbol).ask"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "40.9"
      ]
     },
     "execution_count": 133,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ask"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0"
      ]
     },
     "execution_count": 135,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "action=mt5.ORDER_TYPE_BUY\n",
    "\n",
    "mt5.order_calc_margin(action,symbol,10000,ask)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.01"
      ]
     },
     "execution_count": 136,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mt5.symbol_info(symbol).point"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Temos dinheiro para mandar a ordem?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 224,
   "metadata": {},
   "outputs": [],
   "source": [
    "symbol = 'OIBR3'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 225,
   "metadata": {},
   "outputs": [],
   "source": [
    "point=mt5.symbol_info(symbol).point"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 226,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.01"
      ]
     },
     "execution_count": 226,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "point"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 227,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.02"
      ]
     },
     "execution_count": 227,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mt5.symbol_info_tick(symbol).ask-1*point"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 228,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.04"
      ]
     },
     "execution_count": 228,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mt5.symbol_info_tick(symbol).ask+1*point"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "metadata": {},
   "outputs": [],
   "source": [
    "request = {\n",
    "    \"action\": mt5.TRADE_ACTION_DEAL,\n",
    "    \"symbol\": symbol,\n",
    "    \"volume\": 1.0,\n",
    "    \"type\": mt5.ORDER_TYPE_BUY,\n",
    "    \"price\": mt5.symbol_info_tick(symbol).ask,\n",
    "    \"sl\": mt5.symbol_info_tick(symbol).ask-1*point,\n",
    "    \"tp\": mt5.symbol_info_tick(symbol).ask+1*point,\n",
    "    \"deviation\": 5,\n",
    "    \"magic\": 234000,\n",
    "    \"comment\": \"python script\",\n",
    "    \"type_time\": mt5.ORDER_TIME_DAY,\n",
    "    \"type_filling\": mt5.ORDER_FILLING_RETURN,\n",
    "}\n",
    " \n",
    "# verificamos e exibimos o resultado como está\n",
    "result = mt5.order_check(request)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OrderCheckResult(retcode=10014, balance=0.0, equity=0.0, profit=0.0, margin=0.0, margin_free=0.0, margin_level=0.0, comment='Invalid volume', request=TradeRequest(action=5, magic=234000, order=0, symbol='OIBR3', volume=1.0, price=1.03, stoplimit=0.0, sl=0.030000000000000027, tp=2.0300000000000002, deviation=10, type=0, type_filling=2, type_time=1, expiration=0, comment='python script', position=0, position_by=0))\n"
     ]
    }
   ],
   "source": [
    "print(result)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Aparentemente não temos balanço, mas isso se deve mais ao fato da Clear não refletir no Metatrader as configurações da nossa conta"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 198,
   "metadata": {},
   "outputs": [],
   "source": [
    "symbol_info = mt5.symbol_info(symbol)\n",
    "\n",
    "if symbol_info is None:\n",
    "    print(symbol, \"not found, can not call order_check()\")\n",
    "    mt5.shutdown()\n",
    "    quit()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Estrutura de envio de ordens"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 236,
   "metadata": {},
   "outputs": [],
   "source": [
    "if not mt5.initialize():\n",
    "    print(\"initialize() failed, error code =\",mt5.last_error())\n",
    "    quit()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 264,
   "metadata": {},
   "outputs": [],
   "source": [
    "ordem['price'] = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 268,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'OIBR3'"
      ]
     },
     "execution_count": 268,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "symbol"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 276,
   "metadata": {},
   "outputs": [],
   "source": [
    "ordem = {\n",
    "    \"action\": mt5.TRADE_ACTION_DEAL,\n",
    "    \"symbol\": symbol,\n",
    "    \"volume\": 100.0,\n",
    "    \"type\": mt5.ORDER_TYPE_BUY,\n",
    "    \"price\": mt5.symbol_info_tick(symbol).ask-1*point,\n",
    "    \"sl\": mt5.symbol_info_tick(symbol).ask-2*point,\n",
    "    \"tp\": mt5.symbol_info_tick(symbol).ask+1*point,\n",
    "    \"deviation\": 0,\n",
    "    \"magic\": 1,\n",
    "    \"comment\": \"python script\",\n",
    "    \"type_time\": mt5.ORDER_TIME_GTC,\n",
    "    \"type_filling\": mt5.ORDER_FILLING_RETURN,\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 277,
   "metadata": {},
   "outputs": [],
   "source": [
    "result = mt5.order_send(ordem)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Abri uma ordem manualmente"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Vamos ver se o Python identifica aqui"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 279,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 279,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mt5.orders_total()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 280,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "()"
      ]
     },
     "execution_count": 280,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mt5.orders_get()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Agora que temos uma posição de OIBR3 aberta"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 287,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 287,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mt5.positions_total()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 282,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(TradePosition(ticket=2176609438, time=1632756294, time_msc=1632756294365, time_update=1632756294, time_update_msc=1632756294365, type=0, magic=1, identifier=2176609438, reason=3, volume=100.0, price_open=1.01, sl=0.99, tp=1.02, price_current=1.0, swap=0.0, profit=-1.0, symbol='OIBR3', comment='python script', external_id=''),)"
      ]
     },
     "execution_count": 282,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mt5.positions_get()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 283,
   "metadata": {},
   "outputs": [],
   "source": [
    "from_date=datetime(2020,1,1)\n",
    "to_date=datetime.now()\n",
    "history_orders=mt5.history_orders_total(from_date, datetime.now())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 285,
   "metadata": {},
   "outputs": [],
   "source": [
    "from_date=datetime(2020,1,1)\n",
    "to_date=datetime.now()\n",
    "history_orders=mt5.history_orders_get(from_date, to_date)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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