{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Shioaji Quote Api with bqplot\n",
    "![shioaji-logo](https://sinotrade.github.io/images/shioaji_spot_light-01.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [],
   "source": [
    "import json\n",
    "import datetime as dt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import bqplot as bq\n",
    "import shioaji as sj\n",
    "from ipywidgets import HBox, VBox"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## Init shioaji api and login"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "api = sj.Shioaji(simulation=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "with open('login.json', 'r') as f:\n",
    "    kw_login = json.loads(f.read())\n",
    "api.login(**kw_login)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## Init Charts dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "today = dt.date.today()\n",
    "df_min = pd.DataFrame(index=pd.date_range(start=dt.datetime(*(today.year, today.month, today.day, 8, 45)),\n",
    "                                          end=dt.datetime(*(today.year, today.month, today.day, 13, 45)),\n",
    "                                          freq='1T'),\n",
    "                      columns=['open', 'high', 'low', 'close'], dtype=float,\n",
    "                     )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "last_close = 10200\n",
    "\n",
    "tick_plot_length = 150\n",
    "x_tick_index = np.arange(tick_plot_length)\n",
    "y_price = np.zeros((tick_plot_length,)) + last_close\n",
    "y_vol = np.zeros((tick_plot_length,))\n",
    "updown_color = np.zeros((tick_plot_length,)) + 1 \n",
    "askbid_color_data = np.zeros((tick_plot_length,))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "new_index = 0\n",
    "new_deal_price = 1\n",
    "new_vol = 1\n",
    "new_updown_color = 1\n",
    "new_askbid_color_data = 1\n",
    "ask_price = 0\n",
    "bid_price = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "ask_bid_period_length = 500\n",
    "ask_bid_static = np.zeros((6, ask_bid_period_length))\n",
    "large_ask_deal_volsum = 0\n",
    "small_ask_deal_volsum = 0\n",
    "large_bid_deal_volsum = 0\n",
    "small_bid_deal_volsum = 0\n",
    "ask_deal_count = 0\n",
    "bid_deal_count = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "bid_color = '#ff0000'\n",
    "ask_color = '#03ba00'\n",
    "x_bar_data = np.zeros(10)\n",
    "y_bar_data = np.zeros(10, dtype=np.int64)\n",
    "color_bar_data = np.array(['#000000' for i in range(10)])\n",
    "y_bar_data_diff = np.zeros(10, dtype=np.int64)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "data_in = np.random.rand(2)\n",
    "data_inner = np.random.rand(2)\n",
    "data_outer = np.random.rand(4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## define init charts function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "def init_ohlc_chart():\n",
    "    global ohlc_chart\n",
    "    sc = bq.LinearScale()\n",
    "    dt_scale = bq.DateScale()\n",
    "    ax_x = bq.Axis(label='datetime', scale=dt_scale)\n",
    "    ax_y = bq.Axis(label='price', scale=sc, orientation='vertical', tick_format='0.0f')\n",
    "\n",
    "    # Construct the marks\n",
    "    ohlc_chart = bq.OHLC(x=df_min.index, y=df_min.dropna().values,#df_tick_nosim_min.values[:10], \n",
    "                   marker='candle', scales={'x': dt_scale, 'y': sc}, format='ohlc',\n",
    "                   colors=['red', 'limegreen'], stroke='gray', \n",
    "                   opacities=[0.85 for _ in df_min.index],\n",
    "                   display_legend=True, labels=['TXFD9'])\n",
    "\n",
    "    fig = bq.Figure(axes=[ax_x, ax_y], marks=[ohlc_chart])\n",
    "    return fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "def init_tickchart():\n",
    "    global line_chart, scatter_chart\n",
    "    global x_tick_index, y_price, y_vol, updown_color, askbid_color_data\n",
    "    x_sc = bq.LinearScale()\n",
    "    y_sc = bq.LinearScale()\n",
    "    sc_size = bq.LinearScale()\n",
    "    color_line = bq.ColorScale(colors=['red', 'gray', 'green'])\n",
    "    c_ord = bq.ColorScale(colors=['gray', 'HotPink', 'SeaGreen'])\n",
    "\n",
    "    line_chart = bq.FlexLine(x=x_tick_index, y=y_price, color=updown_color,\n",
    "                             scales= {'x': x_sc, 'y': y_sc, 'color': color_line}, \n",
    "                             display_legend=True, labels=[\"TXFD9\"])\n",
    "\n",
    "    def_tt = bq.Tooltip(fields=['x', 'y', 'size'], formats=['', '.0f', '.0f'], \n",
    "                        lables=['tick', 'price', 'vol'])\n",
    "\n",
    "    scatter_chart = bq.Scatter(x=x_tick_index, y=y_price, size=y_vol, color=askbid_color_data, \n",
    "                               scales= {'x': x_sc, 'y': y_sc, 'size': sc_size, 'color': c_ord}, \n",
    "                               #colors=['dodgerblue',],\n",
    "                               tooltip=def_tt, lables=['tick', 'price', 'vol'],\n",
    "                               selected_style={'opacity': 1.0,}, #'fill': 'DarkOrange', 'stroke': 'Red'}, \n",
    "                               unselected_style={'opacity': 0.7})\n",
    "\n",
    "    ax_x = bq.Axis(scale=x_sc)\n",
    "    ax_y = bq.Axis(scale=y_sc, orientation='vertical', tick_format='0.0f')\n",
    "    ax_color = bq.ColorAxis(label='updown', scale=color_line, tick_format='.0f')\n",
    "\n",
    "    fig = bq.Figure(marks=[line_chart, scatter_chart], axes=[ax_x, ax_y, ax_color],\n",
    "                    #min_aspect_ratio=1, max_aspect_ratio=3,\n",
    "                    #fig_margin= {\"top\":0, \"bottom\":60, \"left\":60, \"right\":0},\n",
    "                   )\n",
    "    return fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "def bidask_bar_chart():\n",
    "    global x_bar_data, y_bar_data, color_bar_data, y_data_diff\n",
    "    global bar_bidask, bar_bidask_diff\n",
    "    x_ord = bq.OrdinalScale()\n",
    "    y_sc = bq.LinearScale()\n",
    "    stroke_color = '#000000'\n",
    "    bar_bidask = bq.Bars(x=x_bar_data, y=y_bar_data,\n",
    "                         scales={'x': x_ord, 'y': y_sc}, \n",
    "                         stroke=stroke_color, color_mode='group',\n",
    "                         padding=0, colors=color_bar_data.tolist(),\n",
    "                         type='stacked', orientation='horizontal',\n",
    "                         opacities=[0.7 for _ in x_bar_data],\n",
    "                        )\n",
    "    bar_bidask_diff = bq.Bars(x=x_bar_data, y=y_bar_data_diff,\n",
    "                         scales={'x': x_ord, 'y': y_sc}, \n",
    "                         stroke=stroke_color, color_mode='group',\n",
    "                         padding=0, colors=color_bar_data.tolist()[::-1],\n",
    "                         type='stacked', orientation='horizontal',\n",
    "                         opacities=[0.7 for _ in x_bar_data],\n",
    "                        )\n",
    "    ax_x = bq.Axis(scale=x_ord, orientation='vertical')\n",
    "    ax_y = bq.Axis(scale=y_sc, tick_format='0.0f')\n",
    "\n",
    "    fig = bq.Figure(marks=[bar_bidask, bar_bidask_diff], axes=[ax_x, ax_y],\n",
    "                    #min_aspect_ratio=1, max_aspect_ratio=1,\n",
    "                    #fig_margin= {\"top\":0, \"bottom\":60, \"left\":10, \"right\":0},\n",
    "                   )\n",
    "    return fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "def pies_chart():\n",
    "    global data_in, data_inner, data_outer\n",
    "    global pie_outer, pie_inner, pie_in\n",
    "    outer_pie_redius = [180, 150]\n",
    "    inner_pie_redius = [100, 70]\n",
    "    in_pie_redius = [50, 10]\n",
    "    pie_outer = bq.Pie(sizes=data_outer, display_labels='outside', apply_clip=False,\n",
    "              radius=outer_pie_redius[0], inner_radius=outer_pie_redius[1], \n",
    "              display_values=True, values_format='.0%', colors=['red', 'limegreen', 'red', 'limegreen'],\n",
    "              labels=['大單委賣成交', '大單委買成交', '小單委賣成交', '小單委買成交'])\n",
    "\n",
    "    pie_inner = bq.Pie(sizes=data_inner, display_labels='inside', apply_clip=False,\n",
    "                    radius=inner_pie_redius[0], inner_radius=inner_pie_redius[1], \n",
    "                    display_values=True, values_format='.0%', colors=['red', 'limegreen'],\n",
    "                    labels=['賣成筆', '買成筆'])\n",
    "\n",
    "    pie_in = bq.Pie(sizes=data_in, display_labels='inside', #apply_clip=False,\n",
    "                    radius=in_pie_redius[0], inner_radius=in_pie_redius[1], \n",
    "                    display_values=True, values_format='.0%', colors=['limegreen', 'red'],\n",
    "                    labels=['賣成口', '買成口'])\n",
    "\n",
    "    fig = bq.Figure(marks=[pie_outer, pie_inner, pie_in], animation_duration=1000,\n",
    "                    #min_aspect_ratio=1, max_aspect_ratio=1.5,\n",
    "                    #fig_margin= {\"top\":0, \"bottom\":60, \"left\":60, \"right\":0},\n",
    "                   )\n",
    "    return fig"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## define processing data function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "def proc_ohlc_data(quote_msg, new_deal_price):\n",
    "    global df_min\n",
    "    ts = pd.Timestamp(\"{Date} {Time}\" .format(**quote_msg)).replace(second=0, microsecond=0)\n",
    "    df_min.loc[ts, 'open'] = new_deal_price if np.isnan(df_min.loc[ts, 'open']) else df_min.loc[ts, 'open'] \n",
    "    df_min.loc[ts, 'high'] = new_deal_price if np.isnan(df_min.loc[ts, 'high']) or new_deal_price > df_min.loc[ts, 'high'] else df_min.loc[ts, 'high'] \n",
    "    df_min.loc[ts, 'low'] = new_deal_price if np.isnan(df_min.loc[ts, 'low']) or new_deal_price < df_min.loc[ts, 'low'] else df_min.loc[ts, 'low']\n",
    "    df_min.loc[ts, 'close'] = new_deal_price"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "def proc_ask_bid_bardata(topic, quote_msg):\n",
    "    global x_bar_data, y_bar_data, color_bar_data, y_data_diff\n",
    "    ask_price = quote_msg.get('AskPrice', [0])[0]\n",
    "    bid_price = quote_msg.get('BidPrice', [0])[0]\n",
    "\n",
    "    x_bar_data[:5] = quote_msg['BidPrice'][::-1]\n",
    "    x_bar_data[5:] = quote_msg['AskPrice']\n",
    "    y_bar_data[:5] = quote_msg['BidVolume'][::-1]\n",
    "    y_bar_data[5:] = quote_msg['AskVolume']\n",
    "    y_bar_data[5:] *= -1\n",
    "    y_bar_data_diff[5:] = quote_msg[\"DiffAskVol\"]\n",
    "    y_bar_data_diff[:5] = quote_msg['DiffBidVol'][::-1]\n",
    "    color_bar_data[:5] = bid_color\n",
    "    color_bar_data[5:] = ask_color"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "def proc_tick_chartdata(topic, quote_msg):\n",
    "    global new_index, new_deal_price, new_vol, new_updown_color, new_askbid_color_data\n",
    "    global x_tick_index, y_price, y_vol, updown_color, askbid_color_data\n",
    "    new_index += 1\n",
    "    new_deal_price = quote_msg.get('Close', [0,])[-1]\n",
    "    new_vol = quote_msg.get('Volume', [0,])[-1]\n",
    "    ask_volsum = quote_msg.get('TradeAskVolSum', 0)\n",
    "    bid_volsum = quote_msg.get('TradeBidVolSum', 0)\n",
    "    new_askbid_color_data = quote_msg.get('TickType', [0,])[-1]# 0: -, 1: ask, 2, bid\n",
    "    if new_deal_price > y_price[-1]:\n",
    "        new_updown_color = 0\n",
    "    elif new_deal_price < y_price[-1]:\n",
    "        new_updown_color = 2\n",
    "    else:\n",
    "        new_updown_color = 1\n",
    "        \n",
    "    x_tick_index[:-1] = x_tick_index[1:]\n",
    "    x_tick_index[-1] = new_index\n",
    "    y_price[:-1] = y_price[1:]\n",
    "    y_price[-1] = new_deal_price\n",
    "    y_vol[:-1] = y_vol[1:]\n",
    "    y_vol[-1] = new_vol\n",
    "    updown_color[:-1] = updown_color[1:]\n",
    "    updown_color[-2] = new_updown_color\n",
    "    askbid_color_data[:-1] = askbid_color_data[1:]\n",
    "    askbid_color_data[-1] = new_askbid_color_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "def proc_ask_bid_staticdata(topic, quote_msg, vol_threshold):\n",
    "    global ask_bid_static\n",
    "    global small_bid_deal_volsum, ask_deal_count, bid_deal_count\n",
    "    ask_volsum = quote_msg.get('TradeAskVolSum', 0)\n",
    "    bid_volsum = quote_msg.get('TradeBidVolSum', 0)\n",
    "    ask_bid_static[:, :-1] = ask_bid_static[:, 1:]\n",
    "    if new_askbid_color_data == 1:\n",
    "        ask_deal_count += 1\n",
    "        ask_bid_static[4][-1] = 1\n",
    "        ask_bid_static[5][-1] = 0\n",
    "        if new_vol >= vol_threshold:\n",
    "            ask_bid_static[0][-1] = new_vol\n",
    "        else:\n",
    "            ask_bid_static[1][-1] = new_vol\n",
    "    elif new_askbid_color_data == 2:\n",
    "        bid_deal_count += 1\n",
    "        ask_bid_static[5][-1] = 1\n",
    "        ask_bid_static[4][-1] = 0\n",
    "        if new_vol >= vol_threshold:\n",
    "            ask_bid_static[2][-1] = new_vol\n",
    "        else:\n",
    "            ask_bid_static[3][-1] = new_vol\n",
    "    \n",
    "    ask_bid_static_sum = ask_bid_static.sum(axis=1)\n",
    "    data_outer = ask_bid_static_sum[:4]\n",
    "    data_inner = ask_bid_static_sum[4:]\n",
    "    data_in = np.array([ask_volsum, bid_volsum])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## define update chart function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "def update_ohlc_chart():\n",
    "    global ohlc_chart\n",
    "    with ohlc_chart.hold_sync():\n",
    "        ohlc_chart.x = df_min.dropna().index\n",
    "        ohlc_chart.y = df_min.dropna().values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "def update_barchart(x_bar_data, y_bar_data, \n",
    "                    color_bar_data, y_bar_data_diff):\n",
    "    global bar_bidask, bar_bidask_diff\n",
    "    with bar_bidask.hold_sync() and bar_bidask_diff.hold_sync():\n",
    "        bar_bidask.x = x_bar_data.copy()\n",
    "        bar_bidask.y = y_bar_data.copy()\n",
    "        bar_bidask.colors = color_bar_data.tolist()\n",
    "        bar_bidask_diff.x = x_bar_data.copy()\n",
    "        bar_bidask_diff.y = y_bar_data_diff.copy()\n",
    "        bar_bidask_diff.colors = color_bar_data.tolist()[::-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "def update_tickandpie_chart(update_freq):\n",
    "    global line_chart, scatter_chart\n",
    "    global pie_outer, pie_inner, pie_in\n",
    "    \n",
    "    if (new_index % update_freq) == 0 and new_index >= tick_plot_length:\n",
    "        with line_chart.hold_sync() and scatter_chart.hold_sync():\n",
    "            line_chart.x = x_tick_index.copy()\n",
    "            line_chart.y = y_price.copy()\n",
    "            line_chart.color = updown_color.copy()\n",
    "            scatter_chart.x = x_tick_index.copy()\n",
    "            scatter_chart.y = y_price.copy()\n",
    "            scatter_chart.size = y_vol.copy() * 10\n",
    "            scatter_chart.color = askbid_color_data.copy()\n",
    "        with pie_outer.hold_sync() and pie_inner.hold_sync() and pie_in.hold_sync():\n",
    "            pie_outer.sizes = data_outer / data_outer.sum()\n",
    "            pie_inner.sizes = data_inner / data_inner.sum()\n",
    "            pie_in.sizes = data_in / data_in.sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## define on quote callback"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "@sj.on_quote\n",
    "def quote_callback(topic, quote_msg):\n",
    "    global tick_plot_length\n",
    "    global line_chart, scatter_chart\n",
    "    global pie_outer, pie_inner, pie_in\n",
    "    global x_tick_index, y_price, y_vol, updown_color, askbid_color_data\n",
    "    global new_index, new_deal_price, new_vol, new_updown_color, new_askbid_color_data\n",
    "    global ask_price, bid_price\n",
    "    global large_ask_deal_volsum, small_ask_deal_volsum, large_bid_deal_volsum\n",
    "    global small_bid_deal_volsum, ask_deal_count, bid_deal_count\n",
    "    global ask_bid_static\n",
    "    global bar_bidask, bar_bidask_diff\n",
    "    global x_bar_data, y_bar_data, color_bar_data, y_data_diff\n",
    "    global ohlc_chart, df_min\n",
    "    vol_threshold = 10\n",
    "    print(topic, quote_msg)\n",
    "    if topic.startswith('Q') and 'TXFD9' in topic:\n",
    "        proc_ask_bid_bardata(topic, quote_msg)\n",
    "        update_barchart(x_bar_data, y_bar_data, \n",
    "                        color_bar_data, y_bar_data_diff)\n",
    "        \n",
    "    elif topic.startswith('L') and 'TXFD9' in topic:\n",
    "        proc_tick_chartdata(topic, quote_msg)\n",
    "        proc_ask_bid_staticdata(topic, quote_msg, vol_threshold)\n",
    "        proc_ohlc_data(quote_msg, new_deal_price)\n",
    "        update_ohlc_chart()\n",
    "        update_tickandpie_chart(update_freq=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## define event callback"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "@sj.on_event\n",
    "def event_callback(resp_code, event_code, event):\n",
    "    print(\"Respone Code: {} | Event Code: {} | Event: {}\".format(resp_code, event_code, event))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## set callback function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "api.quote.set_callback(quote_callback)\n",
    "api.quote.set_event_callback(event_callback)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "pie_in.label_color = '#fff'\n",
    "pie_inner.label_color = '#fff'\n",
    "pie_outer.label_color = '#fff'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Chart"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "2deef03e26864984bf35462333257e58",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(HBox(children=(Figure(axes=[Axis(label='datetime', scale=DateScale()), Axis(label='price', orie…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "VBox([HBox([init_ohlc_chart(), init_tickchart(),]),\n",
    "      HBox([pies_chart(), bidask_bar_chart(), ])\n",
    "     ])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "![gif](https://raw.githubusercontent.com/Sinotrade/Sinotrade.github.io/master/images/quote_visualize.gif)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## Subscribe Quote"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "TXFR1 = api.Contracts.Futures.TXF.TXF201904\n",
    "TSE2330 = api.Contracts.Stocks.TSE.TSE2330"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Respone Code: 200 | Event Code: 16 | Event: Subscribe or Unsubscribe ok\n",
      "Respone Code: 200 | Event Code: 16 | Event: Subscribe or Unsubscribe ok\n",
      "Respone Code: 200 | Event Code: 16 | Event: Subscribe or Unsubscribe ok\n",
      "Respone Code: 200 | Event Code: 16 | Event: Subscribe or Unsubscribe ok\n",
      "Q/TFE/TXFD9 {'AskPrice': [10580.0, 10581.0, 10582.0, 10583.0, 10584.0], 'AskVolSum': 356, 'AskVolume': [25, 44, 64, 75, 148], 'BidPrice': [10579.0, 10578.0, 10577.0, 10576.0, 10575.0], 'BidVolSum': 240, 'BidVolume': [12, 42, 59, 66, 61], 'Code': 'TXFD9', 'Date': '2019/03/29', 'DiffAskVol': [0, 0, 0, -1, 0], 'DiffAskVolSum': -1, 'DiffBidVol': [0, 0, 0, 0, 0], 'DiffBidVolSum': 0, 'FirstDerivedAskPrice': 10581.0, 'FirstDerivedAskVolume': 6, 'FirstDerivedBidPrice': 10577.0, 'FirstDerivedBidVolume': 1, 'TargetKindPrice': 10620.7, 'Time': '13:12:35.328000'}\n",
      "Q/TFE/TXFD9 {'AskPrice': [10580.0, 10581.0, 10582.0, 10583.0, 10584.0], 'AskVolSum': 356, 'AskVolume': [25, 44, 64, 75, 148], 'BidPrice': [10579.0, 10578.0, 10577.0, 10576.0, 10575.0], 'BidVolSum': 239, 'BidVolume': [11, 42, 59, 66, 61], 'Code': 'TXFD9', 'Date': '2019/03/29', 'DiffAskVol': [0, 0, 0, 0, 0], 'DiffAskVolSum': 0, 'DiffBidVol': [-1, 0, 0, 0, 0], 'DiffBidVolSum': -1, 'FirstDerivedAskPrice': 10581.0, 'FirstDerivedAskVolume': 6, 'FirstDerivedBidPrice': 10577.0, 'FirstDerivedBidVolume': 1, 'TargetKindPrice': 10620.7, 'Time': '13:12:35.453000'}\n",
      "Q/TFE/TXFD9 {'AskPrice': [10580.0, 10581.0, 10582.0, 10583.0, 10584.0], 'AskVolSum': 341, 'AskVolume': [25, 44, 64, 65, 143], 'BidPrice': [10579.0, 10578.0, 10577.0, 10576.0, 10575.0], 'BidVolSum': 239, 'BidVolume': [11, 42, 59, 66, 61], 'Code': 'TXFD9', 'Date': '2019/03/29', 'DiffAskVol': [0, 0, 0, -10, -5], 'DiffAskVolSum': -15, 'DiffBidVol': [0, 0, 0, 0, 0], 'DiffBidVolSum': 0, 'FirstDerivedAskPrice': 10581.0, 'FirstDerivedAskVolume': 6, 'FirstDerivedBidPrice': 10577.0, 'FirstDerivedBidVolume': 1, 'TargetKindPrice': 10620.7, 'Time': '13:12:35.703000'}\n",
      "Q/TFE/TXFD9 {'AskPrice': [10580.0, 10581.0, 10582.0, 10583.0, 10584.0], 'AskVolSum': 341, 'AskVolume': [25, 44, 64, 65, 143], 'BidPrice': [10579.0, 10578.0, 10577.0, 10576.0, 10575.0], 'BidVolSum': 239, 'BidVolume': [11, 42, 59, 66, 61], 'Code': 'TXFD9', 'Date': '2019/03/29', 'DiffAskVol': [0, 0, 0, 0, 0], 'DiffAskVolSum': 0, 'DiffBidVol': [0, 0, 0, 0, 0], 'DiffBidVolSum': 0, 'FirstDerivedAskPrice': 10581.0, 'FirstDerivedAskVolume': 6, 'FirstDerivedBidPrice': 10577.0, 'FirstDerivedBidVolume': 1, 'TargetKindPrice': 10620.7, 'Time': '13:12:35.828000'}\n",
      "Q/TFE/TXFD9 {'AskPrice': [10580.0, 10581.0, 10582.0, 10583.0, 10584.0], 'AskVolSum': 341, 'AskVolume': [25, 44, 64, 65, 143], 'BidPrice': [10579.0, 10578.0, 10577.0, 10576.0, 10575.0], 'BidVolSum': 241, 'BidVolume': [12, 42, 59, 66, 62], 'Code': 'TXFD9', 'Date': '2019/03/29', 'DiffAskVol': [0, 0, 0, 0, 0], 'DiffAskVolSum': 0, 'DiffBidVol': [1, 0, 0, 0, 1], 'DiffBidVolSum': 2, 'FirstDerivedAskPrice': 10581.0, 'FirstDerivedAskVolume': 6, 'FirstDerivedBidPrice': 10577.0, 'FirstDerivedBidVolume': 1, 'TargetKindPrice': 10620.7, 'Time': '13:12:36.203000'}\n",
      "Q/TFE/TXFD9 {'AskPrice': [10580.0, 10581.0, 10582.0, 10583.0, 10584.0], 'AskVolSum': 341, 'AskVolume': [25, 44, 64, 65, 143], 'BidPrice': [10579.0, 10578.0, 10577.0, 10576.0, 10575.0], 'BidVolSum': 244, 'BidVolume': [15, 42, 59, 66, 62], 'Code': 'TXFD9', 'Date': '2019/03/29', 'DiffAskVol': [0, 0, 0, 0, 0], 'DiffAskVolSum': 0, 'DiffBidVol': [3, 0, 0, 0, 0], 'DiffBidVolSum': 3, 'FirstDerivedAskPrice': 10581.0, 'FirstDerivedAskVolume': 6, 'FirstDerivedBidPrice': 10577.0, 'FirstDerivedBidVolume': 1, 'TargetKindPrice': 10620.7, 'Time': '13:12:36.328000'}\n",
      "Q/TFE/TXFD9 {'AskPrice': [10580.0, 10581.0, 10582.0, 10583.0, 10584.0], 'AskVolSum': 342, 'AskVolume': [25, 45, 64, 65, 143], 'BidPrice': [10579.0, 10578.0, 10577.0, 10576.0, 10575.0], 'BidVolSum': 244, 'BidVolume': [14, 44, 58, 65, 63], 'Code': 'TXFD9', 'Date': '2019/03/29', 'DiffAskVol': [0, 1, 0, 0, 0], 'DiffAskVolSum': 1, 'DiffBidVol': [-1, 2, -1, -1, 1], 'DiffBidVolSum': 0, 'FirstDerivedAskPrice': 10581.0, 'FirstDerivedAskVolume': 6, 'FirstDerivedBidPrice': 10577.0, 'FirstDerivedBidVolume': 1, 'TargetKindPrice': 10620.7, 'Time': '13:12:36.453000'}\n",
      "Q/TFE/TXFD9 {'AskPrice': [10580.0, 10581.0, 10582.0, 10583.0, 10584.0], 'AskVolSum': 342, 'AskVolume': [25, 45, 64, 65, 143], 'BidPrice': [10579.0, 10578.0, 10577.0, 10576.0, 10575.0], 'BidVolSum': 247, 'BidVolume': [16, 43, 58, 66, 64], 'Code': 'TXFD9', 'Date': '2019/03/29', 'DiffAskVol': [0, 0, 0, 0, 0], 'DiffAskVolSum': 0, 'DiffBidVol': [2, -1, 0, 1, 1], 'DiffBidVolSum': 3, 'FirstDerivedAskPrice': 10581.0, 'FirstDerivedAskVolume': 6, 'FirstDerivedBidPrice': 10577.0, 'FirstDerivedBidVolume': 1, 'TargetKindPrice': 10620.7, 'Time': '13:12:36.578000'}\n",
      "Q/TFE/TXFD9 {'AskPrice': [10580.0, 10581.0, 10582.0, 10583.0, 10584.0], 'AskVolSum': 342, 'AskVolume': [25, 45, 64, 65, 143], 'BidPrice': [10579.0, 10578.0, 10577.0, 10576.0, 10575.0], 'BidVolSum': 248, 'BidVolume': [17, 44, 58, 65, 64], 'Code': 'TXFD9', 'Date': '2019/03/29', 'DiffAskVol': [0, 0, 0, 0, 0], 'DiffAskVolSum': 0, 'DiffBidVol': [1, 1, 0, -1, 0], 'DiffBidVolSum': 1, 'FirstDerivedAskPrice': 10581.0, 'FirstDerivedAskVolume': 6, 'FirstDerivedBidPrice': 10577.0, 'FirstDerivedBidVolume': 1, 'TargetKindPrice': 10620.7, 'Time': '13:12:36.703000'}\n",
      "Q/TFE/TXFD9 {'AskPrice': [10580.0, 10581.0, 10582.0, 10583.0, 10584.0], 'AskVolSum': 342, 'AskVolume': [25, 45, 64, 65, 143], 'BidPrice': [10579.0, 10578.0, 10577.0, 10576.0, 10575.0], 'BidVolSum': 247, 'BidVolume': [16, 44, 58, 65, 64], 'Code': 'TXFD9', 'Date': '2019/03/29', 'DiffAskVol': [0, 0, 0, 0, 0], 'DiffAskVolSum': 0, 'DiffBidVol': [-1, 0, 0, 0, 0], 'DiffBidVolSum': -1, 'FirstDerivedAskPrice': 10581.0, 'FirstDerivedAskVolume': 6, 'FirstDerivedBidPrice': 10577.0, 'FirstDerivedBidVolume': 1, 'TargetKindPrice': 10620.7, 'Time': '13:12:36.828000'}\n",
      "MKT/idcdmzpcr01/TSE/2330 {'Close': [244.5], 'Time': '13:12:37.754742', 'VolSum': [15915], 'Volume': [1]}\n",
      "QUT/idcdmzpcr01/TSE/2330 {'AskPrice': [245.0, 245.5, 246.0, 246.5, 247.0], 'AskVolume': [1148, 377, 501, 182, 218], 'BidPrice': [244.5, 244.0, 243.5, 243.0, 242.5], 'BidVolume': [456, 373, 1529, 1670, 280], 'Date': '2019/03/29', 'Time': '13:12:37.754742'}\n",
      "Q/TFE/TXFD9 {'AskPrice': [10580.0, 10581.0, 10582.0, 10583.0, 10584.0], 'AskVolSum': 342, 'AskVolume': [25, 45, 64, 65, 143], 'BidPrice': [10579.0, 10578.0, 10577.0, 10576.0, 10575.0], 'BidVolSum': 247, 'BidVolume': [16, 44, 58, 65, 64], 'Code': 'TXFD9', 'Date': '2019/03/29', 'DiffAskVol': [0, 0, 0, 0, 0], 'DiffAskVolSum': 0, 'DiffBidVol': [0, 0, 0, 0, 0], 'DiffBidVolSum': 0, 'FirstDerivedAskPrice': 10581.0, 'FirstDerivedAskVolume': 6, 'FirstDerivedBidPrice': 10577.0, 'FirstDerivedBidVolume': 1, 'TargetKindPrice': 10620.7, 'Time': '13:12:37.953000'}\n",
      "Q/TFE/TXFD9 {'AskPrice': [10580.0, 10581.0, 10582.0, 10583.0, 10584.0], 'AskVolSum': 339, 'AskVolume': [25, 45, 64, 62, 143], 'BidPrice': [10579.0, 10578.0, 10577.0, 10576.0, 10575.0], 'BidVolSum': 247, 'BidVolume': [16, 44, 58, 65, 64], 'Code': 'TXFD9', 'Date': '2019/03/29', 'DiffAskVol': [0, 0, 0, -3, 0], 'DiffAskVolSum': -3, 'DiffBidVol': [0, 0, 0, 0, 0], 'DiffBidVolSum': 0, 'FirstDerivedAskPrice': 10581.0, 'FirstDerivedAskVolume': 6, 'FirstDerivedBidPrice': 10577.0, 'FirstDerivedBidVolume': 1, 'TargetKindPrice': 10620.7, 'Time': '13:12:38.078000'}\n",
      "Q/TFE/TXFD9 {'AskPrice': [10580.0, 10581.0, 10582.0, 10583.0, 10584.0], 'AskVolSum': 339, 'AskVolume': [25, 45, 64, 62, 143], 'BidPrice': [10579.0, 10578.0, 10577.0, 10576.0, 10575.0], 'BidVolSum': 248, 'BidVolume': [16, 44, 59, 65, 64], 'Code': 'TXFD9', 'Date': '2019/03/29', 'DiffAskVol': [0, 0, 0, 0, 0], 'DiffAskVolSum': 0, 'DiffBidVol': [0, 0, 1, 0, 0], 'DiffBidVolSum': 1, 'FirstDerivedAskPrice': 10581.0, 'FirstDerivedAskVolume': 6, 'FirstDerivedBidPrice': 10577.0, 'FirstDerivedBidVolume': 1, 'TargetKindPrice': 10620.7, 'Time': '13:12:38.203000'}\n",
      "Q/TFE/TXFD9 {'AskPrice': [10580.0, 10581.0, 10582.0, 10583.0, 10584.0], 'AskVolSum': 340, 'AskVolume': [26, 45, 64, 62, 143], 'BidPrice': [10579.0, 10578.0, 10577.0, 10576.0, 10575.0], 'BidVolSum': 247, 'BidVolume': [16, 44, 59, 64, 64], 'Code': 'TXFD9', 'Date': '2019/03/29', 'DiffAskVol': [1, 0, 0, 0, 0], 'DiffAskVolSum': 1, 'DiffBidVol': [0, 0, 0, -1, 0], 'DiffBidVolSum': -1, 'FirstDerivedAskPrice': 10581.0, 'FirstDerivedAskVolume': 6, 'FirstDerivedBidPrice': 10577.0, 'FirstDerivedBidVolume': 1, 'TargetKindPrice': 10620.7, 'Time': '13:12:38.703000'}\n",
      "Q/TFE/TXFD9 {'AskPrice': [10580.0, 10581.0, 10582.0, 10583.0, 10584.0], 'AskVolSum': 340, 'AskVolume': [26, 45, 64, 62, 143], 'BidPrice': [10579.0, 10578.0, 10577.0, 10576.0, 10575.0], 'BidVolSum': 247, 'BidVolume': [16, 43, 60, 64, 64], 'Code': 'TXFD9', 'Date': '2019/03/29', 'DiffAskVol': [0, 0, 0, 0, 0], 'DiffAskVolSum': 0, 'DiffBidVol': [0, -1, 1, 0, 0], 'DiffBidVolSum': 0, 'FirstDerivedAskPrice': 10581.0, 'FirstDerivedAskVolume': 6, 'FirstDerivedBidPrice': 10577.0, 'FirstDerivedBidVolume': 1, 'TargetKindPrice': 10620.7, 'Time': '13:12:38.828000'}\n",
      "Q/TFE/TXFD9 {'AskPrice': [10580.0, 10581.0, 10582.0, 10583.0, 10584.0], 'AskVolSum': 341, 'AskVolume': [26, 46, 64, 62, 143], 'BidPrice': [10579.0, 10578.0, 10577.0, 10576.0, 10575.0], 'BidVolSum': 247, 'BidVolume': [16, 43, 60, 64, 64], 'Code': 'TXFD9', 'Date': '2019/03/29', 'DiffAskVol': [0, 1, 0, 0, 0], 'DiffAskVolSum': 1, 'DiffBidVol': [0, 0, 0, 0, 0], 'DiffBidVolSum': 0, 'FirstDerivedAskPrice': 10581.0, 'FirstDerivedAskVolume': 6, 'FirstDerivedBidPrice': 10577.0, 'FirstDerivedBidVolume': 1, 'TargetKindPrice': 10620.7, 'Time': '13:12:39.078000'}\n",
      "Q/TFE/TXFD9 {'AskPrice': [10580.0, 10581.0, 10582.0, 10583.0, 10584.0], 'AskVolSum': 341, 'AskVolume': [26, 46, 64, 62, 143], 'BidPrice': [10579.0, 10578.0, 10577.0, 10576.0, 10575.0], 'BidVolSum': 247, 'BidVolume': [16, 43, 60, 64, 64], 'Code': 'TXFD9', 'Date': '2019/03/29', 'DiffAskVol': [0, 0, 0, 0, 0], 'DiffAskVolSum': 0, 'DiffBidVol': [0, 0, 0, 0, 0], 'DiffBidVolSum': 0, 'FirstDerivedAskPrice': 10581.0, 'FirstDerivedAskVolume': 6, 'FirstDerivedBidPrice': 10577.0, 'FirstDerivedBidVolume': 1, 'TargetKindPrice': 10620.7, 'Time': '13:12:39.328000'}\n",
      "Q/TFE/TXFD9 {'AskPrice': [10580.0, 10581.0, 10582.0, 10583.0, 10584.0], 'AskVolSum': 341, 'AskVolume': [26, 46, 64, 62, 143], 'BidPrice': [10579.0, 10578.0, 10577.0, 10576.0, 10575.0], 'BidVolSum': 245, 'BidVolume': [14, 43, 60, 64, 64], 'Code': 'TXFD9', 'Date': '2019/03/29', 'DiffAskVol': [0, 0, 0, 0, 0], 'DiffAskVolSum': 0, 'DiffBidVol': [-2, 0, 0, 0, 0], 'DiffBidVolSum': -2, 'FirstDerivedAskPrice': 10581.0, 'FirstDerivedAskVolume': 6, 'FirstDerivedBidPrice': 10577.0, 'FirstDerivedBidVolume': 1, 'TargetKindPrice': 10620.7, 'Time': '13:12:39.453000'}\n",
      "Q/TFE/TXFD9 {'AskPrice': [10580.0, 10581.0, 10582.0, 10583.0, 10584.0], 'AskVolSum': 341, 'AskVolume': [26, 46, 64, 62, 143], 'BidPrice': [10579.0, 10578.0, 10577.0, 10576.0, 10575.0], 'BidVolSum': 242, 'BidVolume': [12, 42, 60, 65, 63], 'Code': 'TXFD9', 'Date': '2019/03/29', 'DiffAskVol': [0, 0, 0, 0, 0], 'DiffAskVolSum': 0, 'DiffBidVol': [-2, -1, 0, 1, -1], 'DiffBidVolSum': -3, 'FirstDerivedAskPrice': 10581.0, 'FirstDerivedAskVolume': 6, 'FirstDerivedBidPrice': 10577.0, 'FirstDerivedBidVolume': 1, 'TargetKindPrice': 10620.7, 'Time': '13:12:39.578000'}\n",
      "Q/TFE/TXFD9 {'AskPrice': [10580.0, 10581.0, 10582.0, 10583.0, 10584.0], 'AskVolSum': 311, 'AskVolume': [26, 46, 64, 62, 113], 'BidPrice': [10579.0, 10578.0, 10577.0, 10576.0, 10575.0], 'BidVolSum': 242, 'BidVolume': [12, 42, 60, 65, 63], 'Code': 'TXFD9', 'Date': '2019/03/29', 'DiffAskVol': [0, 0, 0, 0, -30], 'DiffAskVolSum': -30, 'DiffBidVol': [0, 0, 0, 0, 0], 'DiffBidVolSum': 0, 'FirstDerivedAskPrice': 10581.0, 'FirstDerivedAskVolume': 6, 'FirstDerivedBidPrice': 10577.0, 'FirstDerivedBidVolume': 1, 'TargetKindPrice': 10620.7, 'Time': '13:12:39.828000'}\n",
      "Q/TFE/TXFD9 {'AskPrice': [10580.0, 10581.0, 10582.0, 10583.0, 10584.0], 'AskVolSum': 311, 'AskVolume': [26, 46, 64, 62, 113], 'BidPrice': [10579.0, 10578.0, 10577.0, 10576.0, 10575.0], 'BidVolSum': 248, 'BidVolume': [18, 42, 60, 65, 63], 'Code': 'TXFD9', 'Date': '2019/03/29', 'DiffAskVol': [0, 0, 0, 0, 0], 'DiffAskVolSum': 0, 'DiffBidVol': [6, 0, 0, 0, 0], 'DiffBidVolSum': 6, 'FirstDerivedAskPrice': 10581.0, 'FirstDerivedAskVolume': 6, 'FirstDerivedBidPrice': 10577.0, 'FirstDerivedBidVolume': 1, 'TargetKindPrice': 10620.7, 'Time': '13:12:40.078000'}\n",
      "Q/TFE/TXFD9 {'AskPrice': [10580.0, 10581.0, 10582.0, 10583.0, 10584.0], 'AskVolSum': 308, 'AskVolume': [23, 46, 64, 62, 113], 'BidPrice': [10579.0, 10578.0, 10577.0, 10576.0, 10575.0], 'BidVolSum': 249, 'BidVolume': [19, 44, 59, 64, 63], 'Code': 'TXFD9', 'Date': '2019/03/29', 'DiffAskVol': [-3, 0, 0, 0, 0], 'DiffAskVolSum': -3, 'DiffBidVol': [1, 2, -1, -1, 0], 'DiffBidVolSum': 1, 'FirstDerivedAskPrice': 10581.0, 'FirstDerivedAskVolume': 6, 'FirstDerivedBidPrice': 10577.0, 'FirstDerivedBidVolume': 1, 'TargetKindPrice': 10615.63, 'Time': '13:12:40.203000'}\n",
      "Q/TFE/TXFD9 {'AskPrice': [10580.0, 10581.0, 10582.0, 10583.0, 10584.0], 'AskVolSum': 309, 'AskVolume': [23, 47, 64, 62, 113], 'BidPrice': [10579.0, 10578.0, 10577.0, 10576.0, 10575.0], 'BidVolSum': 249, 'BidVolume': [19, 44, 59, 64, 63], 'Code': 'TXFD9', 'Date': '2019/03/29', 'DiffAskVol': [0, 1, 0, 0, 0], 'DiffAskVolSum': 1, 'DiffBidVol': [0, 0, 0, 0, 0], 'DiffBidVolSum': 0, 'FirstDerivedAskPrice': 10581.0, 'FirstDerivedAskVolume': 6, 'FirstDerivedBidPrice': 10577.0, 'FirstDerivedBidVolume': 1, 'TargetKindPrice': 10615.63, 'Time': '13:12:40.953000'}\n",
      "Q/TFE/TXFD9 {'AskPrice': [10580.0, 10581.0, 10582.0, 10583.0, 10584.0], 'AskVolSum': 310, 'AskVolume': [24, 47, 64, 62, 113], 'BidPrice': [10579.0, 10578.0, 10577.0, 10576.0, 10575.0], 'BidVolSum': 249, 'BidVolume': [19, 44, 59, 64, 63], 'Code': 'TXFD9', 'Date': '2019/03/29', 'DiffAskVol': [1, 0, 0, 0, 0], 'DiffAskVolSum': 1, 'DiffBidVol': [0, 0, 0, 0, 0], 'DiffBidVolSum': 0, 'FirstDerivedAskPrice': 10581.0, 'FirstDerivedAskVolume': 6, 'FirstDerivedBidPrice': 10577.0, 'FirstDerivedBidVolume': 1, 'TargetKindPrice': 10615.63, 'Time': '13:12:41.078000'}\n"
     ]
    }
   ],
   "source": [
    "api.quote.subscribe(TXFR1)\n",
    "api.quote.subscribe(TXFR1, quote_type='bidask')\n",
    "api.quote.subscribe(TSE2330)\n",
    "api.quote.subscribe(TSE2330, quote_type='bidask')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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   "language": "python",
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    "name": "ipython",
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