YHT_1.5_paisa_17_10_2020_version.ipynb

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      "0yld9m8WfmP6wDixi9z16BcOprzCeBcz\n"
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    "#####################\n",
    "# AUTO LOGIN-1 of 1 #\n",
    "#####################\n",
    "\n",
    "import login\n",
    "from login import *\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
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   "source": [
    "#######################\n",
    "# OPTIONAL RUN-1 of 4 #\n",
    "#######################\n",
    "\n",
    "myorder = kite.orders()\n",
    "\n",
    "myorder\n",
    "\n",
    "pending_orders = []\n",
    "\n",
    "for i  in range(len(myorder)):\n",
    "    if(myorder[i]['status']=='AMO REQ RECEIVED'):\n",
    "        pending_orders.append(myorder[i])\n",
    "        kite.cancel_order(myorder[i]['variety'], myorder[i]['order_id'], parent_order_id=None)\n",
    "\n",
    "pending_orders"
   ]
  },
  {
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    "#######################\n",
    "# OPTIONAL RUN-2 of 4 #\n",
    "#######################\n",
    "\n",
    "#kite.positions()['net']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "outputs": [],
   "source": [
    "#######################\n",
    "# OPTIONAL RUN-3 of 4 #\n",
    "#######################\n",
    "\n",
    "#kite.holdings()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#######################\n",
    "# OPTIONAL RUN-4 of 4 #\n",
    "#######################\n",
    "\n",
    "#kite.margins(segment = 'equity')['available']['live_balance']"
   ]
  },
  {
   "cell_type": "code",
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    "#####################\n",
    "# NORMAL RUN-1 of 3 #\n",
    "#####################\n",
    "#############################################################################################################################\n",
    "#########################\n",
    "# Update this part only #\n",
    "#########################\n",
    "\n",
    "one_dollar_margin = 1100     # (USD-MIS=984/NRML=1967)(GBP-MIS=1948/NRML=3895)(EUR-MIS=1313/NRML=2625)(JPY-MIS=1333/NRML=2667)\n",
    "per_order_quant = 25\n",
    "initial_difference = 0.0000\n",
    "\n",
    "order_type = 'MIS'           # MIS / NRML\n",
    "symbol_ip = 'USDINR20OCTFUT' # USDINR20OCTFUT / GBPINR20OCTFUT / EURINR20OCTFUT / JPYINR20OCTFUT\n",
    "inst_token = 690691          # 690691(USD) / 490755(GBP) / 278019(EUR) / 690435(JPY)\n",
    "moving_pivot_on = False      # True / False\n",
    "\n",
    "stoploss_on = False          # True / False\n",
    "\n",
    "hl_range = 0.23              # (Default=0.00)(USD=0.23)(GBP=?)(EUR=?)(JPY=?)\n",
    "\n",
    "#############################################################################################################################\n",
    "\n",
    "import datetime\n",
    "interval='day'\n",
    "todaydt=datetime.date.today()\n",
    "hud_ago=todaydt-datetime.timedelta(days=10)\n",
    "to_date=datetime.date.isoformat(todaydt)\n",
    "\n",
    "from_date=datetime.date.isoformat(hud_ago)\n",
    "data = kite.historical_data(inst_token, from_date, to_date, interval, continuous=False)\n",
    "\n",
    "import pandas as pd\n",
    "mydata = pd.DataFrame(data)\n",
    "\n",
    "last_close = 123.0\n",
    "last_high = 123.0\n",
    "last_low = 123.0\n",
    "\n",
    "from datetime import date\n",
    "\n",
    "today = date.today()\n",
    "\n",
    "print('Today Date : '+str(today))\n",
    "\n",
    "\n",
    "for i in range(len(mydata['date'])):\n",
    "    if(mydata['date'][i].date()==today-datetime.timedelta(days=1) or mydata['date'][i].date()==today-datetime.timedelta(days=2) or mydata['date'][i].date()==today-datetime.timedelta(days=3)):\n",
    "        print('Yestreday Date : '+str(mydata['date'][i].date()))\n",
    "        last_close = mydata['close'][i]\n",
    "        last_high = mydata['high'][i]\n",
    "        last_low = mydata['low'][i]\n",
    "        if(hl_range == 0):\n",
    "            hl_range = last_high - last_low\n",
    "        \n",
    "        \n",
    "print('last close : '+ str(last_close))\n",
    "print('last high : '+ str(last_high))\n",
    "print('last low : '+ str(last_low))\n",
    "print('HL Range : '+ str(round(hl_range,4)))\n",
    "\n",
    "mymargin = round(kite.margins(segment = 'equity')['available']['live_balance'],4)\n",
    "#mymargin = 185777.23\n",
    "\n",
    "pivot_price = last_close\n",
    "\n",
    "fullquantity = int(mymargin / one_dollar_margin)\n",
    "\n",
    "num_of_steps = int(fullquantity / per_order_quant)\n",
    "\n",
    "difference = round(hl_range / num_of_steps,4)\n",
    "\n",
    "difference = round(0.0025 * round(difference /0.0025),4)\n",
    "\n",
    "last_buy_price = round(pivot_price -  difference*num_of_steps,4)\n",
    "last_sell_price = round(pivot_price +  difference*num_of_steps,4)\n",
    "\n",
    "print('My Margin : '+str(mymargin))\n",
    "print('Pivot Price : ' + str(pivot_price))\n",
    "print('Full Quantity : '+str(fullquantity))\n",
    "print('Number of Steps : '+str(num_of_steps))\n",
    "print('Price Difference Between One Trade : ' + str(difference))\n",
    "print('Quantity Difference Between One Trade : ' + str(per_order_quant))\n",
    "print('Last Buy Pivot Price : '+str(last_buy_price))\n",
    "print('Last Sell Pivot Price : '+str(last_sell_price))\n",
    "print('Stoploss On ? : '+str(stoploss_on))\n",
    "print('Moving Pivot On ? : '+str(moving_pivot_on))\n",
    "base=0.0025\n",
    "max_no_of_order = int(fullquantity / per_order_quant)\n",
    "total_parts = 2*max_no_of_order\n",
    "\n",
    "print()\n",
    "print('pivot_price : '+str(pivot_price))\n",
    "print()\n",
    "upper_limit = 0.12\n",
    "lower_limit = 0.12\n",
    "def calc_pivots():\n",
    "    global upper_limit, lower_limit\n",
    "    for i in range(1,max_no_of_order+1):\n",
    "        globals()['p'+str(i)+'b'] = pivot_price - (initial_difference + i* difference)\n",
    "        globals()['p'+str(i)+'b'] = round(base * round(globals()['p'+str(i)+'b'] /base),4)\n",
    "        print('p'+str(i)+'b : '+str(globals()['p'+str(i)+'b']))\n",
    "\n",
    "    print()\n",
    "    for i in range(1,max_no_of_order+1):\n",
    "        globals()['p'+str(i)+'s'] = pivot_price + (initial_difference + i* difference)\n",
    "        globals()['p'+str(i)+'s'] = round(base * round(globals()['p'+str(i)+'s'] /base),4)\n",
    "        print('p'+str(i)+'s : '+str(globals()['p'+str(i)+'s']))\n",
    "\n",
    "    print()\n",
    "    for i in range(1,max_no_of_order+1):\n",
    "        globals()['p'+str(i)+'q'] = per_order_quant*i\n",
    "        print('p'+str(i)+'q : '+str(globals()['p'+str(i)+'q']))\n",
    "        \n",
    "    print()\n",
    "    upper_limit = round(((globals()['p'+str(max_no_of_order)+'s']) + hl_range*0.236),4)\n",
    "    lower_limit = round(((globals()['p'+str(max_no_of_order)+'b']) - hl_range*0.236),4)\n",
    "    print('S Limit : '+str(upper_limit))\n",
    "    print('B Limit : '+str(lower_limit))\n",
    "\n",
    "calc_pivots()"
   ]
  },
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    "#####################\n",
    "# NORMAL RUN-2 of 3 #\n",
    "#####################\n",
    "\n",
    "myquantity = 0\n",
    "def getquant():\n",
    "    global myquantity\n",
    "    global order_type\n",
    "    global symbol_ip\n",
    "    allpos = kite.positions()['net']\n",
    "    for i in range(len(allpos)):\n",
    "        if(allpos[i]['tradingsymbol']==symbol_ip and  allpos[i]['product']== order_type):\n",
    "            myquantity = allpos[i]['quantity']\n",
    "            print('My Quantity : ' + str(allpos[i]['quantity']))\n",
    "\n",
    "getquant()\n",
    "\n",
    "stopbuy = False\n",
    "stopsell = False\n",
    "\n",
    "def placeneworder(quantdiff):\n",
    "    global stopbuy\n",
    "    global stopsell\n",
    "    global order_type\n",
    "    global symbol_ip\n",
    "    if(quantdiff>0 and stopbuy == False):\n",
    "        try:\n",
    "                order_id= kite.place_order(tradingsymbol=symbol_ip,\n",
    "                            exchange=kite.EXCHANGE_CDS,\n",
    "                            transaction_type=kite.TRANSACTION_TYPE_BUY,\n",
    "                            quantity=abs(quantdiff),\n",
    "                            order_type=kite.ORDER_TYPE_MARKET,\n",
    "                            variety = kite.VARIETY_REGULAR,\n",
    "                            product=kite.PRODUCT_MIS if order_type=='MIS' else kite.PRODUCT_NRML)\n",
    "                getquant()\n",
    "                stopsell = False\n",
    "        except Exception as e:\n",
    "            stopbuy = False\n",
    "            print(e)\n",
    "            getquant()\n",
    "    if(quantdiff<0 and stopsell == False):\n",
    "        try:\n",
    "                order_id= kite.place_order(tradingsymbol=symbol_ip,\n",
    "                            exchange=kite.EXCHANGE_CDS,\n",
    "                            transaction_type=kite.TRANSACTION_TYPE_SELL,\n",
    "                            quantity=abs(quantdiff),\n",
    "                            order_type=kite.ORDER_TYPE_MARKET,\n",
    "                            variety = kite.VARIETY_REGULAR,\n",
    "                            product=kite.PRODUCT_MIS if order_type=='MIS' else kite.PRODUCT_NRML)\n",
    "                getquant()\n",
    "                stopbuy = False\n",
    "        except Exception as e:\n",
    "            stopsell = True\n",
    "            print(e)\n",
    "            getquant()\n",
    "\n",
    "\n",
    "def ckqnt (orderprice,orderquant):\n",
    "    global myquantity\n",
    "    quantdiff = orderquant - myquantity\n",
    "    placeneworder(quantdiff)\n",
    "    return myquantity\n",
    "\n",
    "\n",
    "last_price = pivot_price\n",
    "\n",
    "def checkpivot(ltps):\n",
    "    global last_price, upper_limit, lower_limit\n",
    "    trade_quant = 0\n",
    "    \n",
    "    if((ltps > upper_limit or ltps < lower_limit) and stoploss_on ):\n",
    "        ckqnt(pivot_price,0)\n",
    "    \n",
    "    elif ((ltps>=(pivot_price-0.0025)) and (ltps<=(pivot_price+0.0025))):\n",
    "        ckqnt(pivot_price,0)\n",
    "        print('in pivot range')\n",
    "        \n",
    "    elif(upper_limit>ltps>(globals()['p'+str(max_no_of_order)+'s'])):\n",
    "        ckqnt(globals()['p'+str(max_no_of_order)+'s'],-globals()['p'+str(max_no_of_order)+'q'])\n",
    "        \n",
    "    elif(lower_limit<ltps<(globals()['p'+str(max_no_of_order)+'b'])):\n",
    "        ckqnt(globals()['p'+str(max_no_of_order)+'b'],globals()['p'+str(max_no_of_order)+'q'])\n",
    "        \n",
    "    else:\n",
    "        for i in range(1,int(total_parts/2)+1):\n",
    "\n",
    "            if(ltps<pivot_price):\n",
    "                trade_quant = globals()['p'+str(i)+'q']\n",
    "            elif(ltps>pivot_price):\n",
    "                trade_quant = -globals()['p'+str(i)+'q']\n",
    "\n",
    "            if ((ltps == globals()['p'+str(i)+'b'] or ltps == globals()['p'+str(i)+'s']) and ltps < last_price):\n",
    "                ckqnt(globals()['p'+str(i)+'b'],trade_quant)\n",
    "                print('==========' +'p'+str(i)+'b @ ' +str(ltps) + '==============' )\n",
    "                last_price=ltps\n",
    "\n",
    "            if ((ltps == globals()['p'+str(i)+'b'] or ltps == globals()['p'+str(i)+'s']) and ltps > last_price):\n",
    "                ckqnt(globals()['p'+str(i)+'s'],trade_quant)\n",
    "                print('==========' +'p'+str(i)+'s @ ' +str(ltps) + '==============' )\n",
    "                last_price=ltps"
   ]
  },
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    "#####################\n",
    "# NORMAL RUN-3 of 3 #\n",
    "#####################\n",
    "#################\n",
    "# START TRADING #\n",
    "#################\n",
    "\n",
    "import logging\n",
    "from kiteconnect import KiteTicker\n",
    "logging.basicConfig(level=logging.DEBUG)\n",
    "# kws = KiteTicker(\"w19o0chuo929jxkp\", \"eA5B5OJQNOtZ0OYihkBmYw7Ke3B9pmCC\")\n",
    "\n",
    "def on_ticks(ws, ticks):\n",
    "    global pivot_price, moving_pivot_on\n",
    "    checkpivot(ticks[0]['last_price'])\n",
    "\n",
    "    if(moving_pivot_on):\n",
    "        pivot_price =round(base * round(ticks[0]['average_price']/base),4) # Moving Trade Average Line : 1\n",
    "        calc_pivots();                                                     # Moving Trade Average Line : 2\n",
    "        \n",
    "    #print(hjhj)\n",
    "    #print('===========================')\n",
    "    #print()\n",
    "\n",
    "        \n",
    "    \n",
    "#     print(ticks[0]['last_trade_time'].second)\n",
    "#     print('==========================')\n",
    "#     print( 'LTP : ' + str(ticks[0]['last_price']))\n",
    "    #print('==========================')\n",
    "    #print()\n",
    "\n",
    "def on_connect(ws, response):\n",
    "    global inst_token\n",
    "    ws.subscribe([inst_token])\n",
    "    ws.set_mode(ws.MODE_FULL, [inst_token])\n",
    "\n",
    "def on_close(ws, code, reason):\n",
    "    ws.stop()\n",
    "    \n",
    "def on_error(ws, code, reason):\n",
    "    logging.error(\"closed connection on error: {} {}\".format(code, reason))\n",
    "\n",
    "def on_noreconnect(ws):\n",
    "    logging.error(\"Reconnecting the websocket failed\")\n",
    "\n",
    "def on_reconnect(ws, attempt_count):\n",
    "    logging.debug(\"Reconnecting the websocket: {}\".format(attempt_count))\n",
    "\n",
    "#def on_order_update(ws, data):\n",
    "#    print(\"order update: \", data)\n",
    "\n",
    "kws.on_error = on_error\n",
    "kws.on_noreconnect = on_noreconnect\n",
    "kws.on_reconnect = on_reconnect\n",
    "#kws.on_order_update = on_order_update\n",
    "\n",
    "kws.on_ticks = on_ticks\n",
    "kws.on_connect = on_connect\n",
    "kws.on_close = on_close\n",
    "\n",
    "kws.connect()"
   ]
  },
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       "    OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
       "      /* Is output safe? */\n",
       "      safe: true,\n",
       "      /* Index of renderer in `output_area.display_order` */\n",
       "      index: 0\n",
       "    });\n",
       "  }\n",
       "\n",
       "  // register the mime type if in Jupyter Notebook environment and previously unregistered\n",
       "  if (root.Jupyter !== undefined) {\n",
       "    var events = require('base/js/events');\n",
       "    var OutputArea = require('notebook/js/outputarea').OutputArea;\n",
       "\n",
       "    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
       "      register_renderer(events, OutputArea);\n",
       "    }\n",
       "  }\n",
       "\n",
       "  \n",
       "  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "    root._bokeh_timeout = Date.now() + 5000;\n",
       "    root._bokeh_failed_load = false;\n",
       "  }\n",
       "\n",
       "  var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "     \"<div style='background-color: #fdd'>\\n\"+\n",
       "     \"<p>\\n\"+\n",
       "     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "     \"</p>\\n\"+\n",
       "     \"<ul>\\n\"+\n",
       "     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "     \"</ul>\\n\"+\n",
       "     \"<code>\\n\"+\n",
       "     \"from bokeh.resources import INLINE\\n\"+\n",
       "     \"output_notebook(resources=INLINE)\\n\"+\n",
       "     \"</code>\\n\"+\n",
       "     \"</div>\"}};\n",
       "\n",
       "  function display_loaded() {\n",
       "    var el = document.getElementById(\"1001\");\n",
       "    if (el != null) {\n",
       "      el.textContent = \"BokehJS is loading...\";\n",
       "    }\n",
       "    if (root.Bokeh !== undefined) {\n",
       "      if (el != null) {\n",
       "        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n",
       "      }\n",
       "    } else if (Date.now() < root._bokeh_timeout) {\n",
       "      setTimeout(display_loaded, 100)\n",
       "    }\n",
       "  }\n",
       "\n",
       "\n",
       "  function run_callbacks() {\n",
       "    try {\n",
       "      root._bokeh_onload_callbacks.forEach(function(callback) {\n",
       "        if (callback != null)\n",
       "          callback();\n",
       "      });\n",
       "    } finally {\n",
       "      delete root._bokeh_onload_callbacks\n",
       "    }\n",
       "    console.debug(\"Bokeh: all callbacks have finished\");\n",
       "  }\n",
       "\n",
       "  function load_libs(css_urls, js_urls, callback) {\n",
       "    if (css_urls == null) css_urls = [];\n",
       "    if (js_urls == null) js_urls = [];\n",
       "\n",
       "    root._bokeh_onload_callbacks.push(callback);\n",
       "    if (root._bokeh_is_loading > 0) {\n",
       "      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "      return null;\n",
       "    }\n",
       "    if (js_urls == null || js_urls.length === 0) {\n",
       "      run_callbacks();\n",
       "      return null;\n",
       "    }\n",
       "    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "    root._bokeh_is_loading = css_urls.length + js_urls.length;\n",
       "\n",
       "    function on_load() {\n",
       "      root._bokeh_is_loading--;\n",
       "      if (root._bokeh_is_loading === 0) {\n",
       "        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n",
       "        run_callbacks()\n",
       "      }\n",
       "    }\n",
       "\n",
       "    function on_error() {\n",
       "      console.error(\"failed to load \" + url);\n",
       "    }\n",
       "\n",
       "    for (var i = 0; i < css_urls.length; i++) {\n",
       "      var url = css_urls[i];\n",
       "      const element = document.createElement(\"link\");\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error;\n",
       "      element.rel = \"stylesheet\";\n",
       "      element.type = \"text/css\";\n",
       "      element.href = url;\n",
       "      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
       "      document.body.appendChild(element);\n",
       "    }\n",
       "\n",
       "    const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.2.3.min.js\": \"T2yuo9Oe71Cz/I4X9Ac5+gpEa5a8PpJCDlqKYO0CfAuEszu1JrXLl8YugMqYe3sM\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.2.3.min.js\": \"98GDGJ0kOMCUMUePhksaQ/GYgB3+NH9h996V88sh3aOiUNX3N+fLXAtry6xctSZ6\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.2.3.min.js\": \"89bArO+nlbP3sgakeHjCo1JYxYR5wufVgA3IbUvDY+K7w4zyxJqssu7wVnfeKCq8\"};\n",
       "\n",
       "    for (var i = 0; i < js_urls.length; i++) {\n",
       "      var url = js_urls[i];\n",
       "      var element = document.createElement('script');\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error;\n",
       "      element.async = false;\n",
       "      element.src = url;\n",
       "      if (url in hashes) {\n",
       "        element.crossOrigin = \"anonymous\";\n",
       "        element.integrity = \"sha384-\" + hashes[url];\n",
       "      }\n",
       "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      document.head.appendChild(element);\n",
       "    }\n",
       "  };\n",
       "\n",
       "  function inject_raw_css(css) {\n",
       "    const element = document.createElement(\"style\");\n",
       "    element.appendChild(document.createTextNode(css));\n",
       "    document.body.appendChild(element);\n",
       "  }\n",
       "\n",
       "  \n",
       "  var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.2.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.2.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.2.3.min.js\"];\n",
       "  var css_urls = [];\n",
       "  \n",
       "\n",
       "  var inline_js = [\n",
       "    function(Bokeh) {\n",
       "      Bokeh.set_log_level(\"info\");\n",
       "    },\n",
       "    function(Bokeh) {\n",
       "    \n",
       "    \n",
       "    }\n",
       "  ];\n",
       "\n",
       "  function run_inline_js() {\n",
       "    \n",
       "    if (root.Bokeh !== undefined || force === true) {\n",
       "      \n",
       "    for (var i = 0; i < inline_js.length; i++) {\n",
       "      inline_js[i].call(root, root.Bokeh);\n",
       "    }\n",
       "    if (force === true) {\n",
       "        display_loaded();\n",
       "      }} else if (Date.now() < root._bokeh_timeout) {\n",
       "      setTimeout(run_inline_js, 100);\n",
       "    } else if (!root._bokeh_failed_load) {\n",
       "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "      root._bokeh_failed_load = true;\n",
       "    } else if (force !== true) {\n",
       "      var cell = $(document.getElementById(\"1001\")).parents('.cell').data().cell;\n",
       "      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "    }\n",
       "\n",
       "  }\n",
       "\n",
       "  if (root._bokeh_is_loading === 0) {\n",
       "    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "    run_inline_js();\n",
       "  } else {\n",
       "    load_libs(css_urls, js_urls, function() {\n",
       "      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "      run_inline_js();\n",
       "    });\n",
       "  }\n",
       "}(window));"
      ],
      "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  var force = true;\n\n  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n    root._bokeh_onload_callbacks = [];\n    root._bokeh_is_loading = undefined;\n  }\n\n  \n\n  \n  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  var NB_LOAD_WARNING = {'data': {'text/html':\n     \"<div style='background-color: #fdd'>\\n\"+\n     \"<p>\\n\"+\n     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n     \"</p>\\n\"+\n     \"<ul>\\n\"+\n     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n     \"</ul>\\n\"+\n     \"<code>\\n\"+\n     \"from bokeh.resources import INLINE\\n\"+\n     \"output_notebook(resources=INLINE)\\n\"+\n     \"</code>\\n\"+\n     \"</div>\"}};\n\n  function display_loaded() {\n    var el = document.getElementById(\"1001\");\n    if (el != null) {\n      el.textContent = \"BokehJS is loading...\";\n    }\n    if (root.Bokeh !== undefined) {\n      if (el != null) {\n        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n      }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(display_loaded, 100)\n    }\n  }\n\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n\n    root._bokeh_onload_callbacks.push(callback);\n    if (root._bokeh_is_loading > 0) {\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    }\n    if (js_urls == null || js_urls.length === 0) {\n      run_callbacks();\n      return null;\n    }\n    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n    root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n\n    function on_error() {\n      console.error(\"failed to load \" + url);\n    }\n\n    for (var i = 0; i < css_urls.length; i++) {\n      var url = css_urls[i];\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }\n\n    const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.2.3.min.js\": \"T2yuo9Oe71Cz/I4X9Ac5+gpEa5a8PpJCDlqKYO0CfAuEszu1JrXLl8YugMqYe3sM\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.2.3.min.js\": \"98GDGJ0kOMCUMUePhksaQ/GYgB3+NH9h996V88sh3aOiUNX3N+fLXAtry6xctSZ6\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.2.3.min.js\": \"89bArO+nlbP3sgakeHjCo1JYxYR5wufVgA3IbUvDY+K7w4zyxJqssu7wVnfeKCq8\"};\n\n    for (var i = 0; i < js_urls.length; i++) {\n      var url = js_urls[i];\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      if (url in hashes) {\n        element.crossOrigin = \"anonymous\";\n        element.integrity = \"sha384-\" + hashes[url];\n      }\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n  };\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  \n  var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.2.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.2.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.2.3.min.js\"];\n  var css_urls = [];\n  \n\n  var inline_js = [\n    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\n    function(Bokeh) {\n    \n    \n    }\n  ];\n\n  function run_inline_js() {\n    \n    if (root.Bokeh !== undefined || force === true) {\n      \n    for (var i = 0; i < inline_js.length; i++) {\n      inline_js[i].call(root, root.Bokeh);\n    }\n    if (force === true) {\n        display_loaded();\n      }} else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    } else if (force !== true) {\n      var cell = $(document.getElementById(\"1001\")).parents('.cell').data().cell;\n      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n    }\n\n  }\n\n  if (root._bokeh_is_loading === 0) {\n    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n    run_inline_js();\n  } else {\n    load_libs(css_urls, js_urls, function() {\n      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n      run_inline_js();\n    });\n  }\n}(window));"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "7791\n",
      "7791\n",
      "7791\n"
     ]
    }
   ],
   "source": [
    "from datetime import timedelta\n",
    "import datetime\n",
    "pd.set_option('plotting.backend', 'pandas_bokeh')\n",
    "import pandas_bokeh\n",
    "pandas_bokeh.output_notebook()\n",
    "old_lst=[]\n",
    "interval='minute'\n",
    "todaydt=datetime.date.today()\n",
    "hud_ago=todaydt-timedelta(days=59)\n",
    "to_date=datetime.date.isoformat(todaydt)\n",
    "from_date=datetime.date.isoformat(hud_ago)\n",
    "inst_token = 13734146\n",
    "for i2 in range(3):\n",
    "    new_lst = kite.historical_data(inst_token, from_date, to_date, interval,continuous=False)\n",
    "    old_lst = new_lst + old_lst\n",
    "    todaydt=todaydt-timedelta(days=60)\n",
    "    hud_ago=hud_ago-timedelta(days=60)\n",
    "    to_date=datetime.date.isoformat(todaydt)\n",
    "    from_date=datetime.date.isoformat(hud_ago)\n",
    "    print(len(old_lst))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/hemang/.local/lib/python3.8/site-packages/ta/trend.py:608: RuntimeWarning: invalid value encountered in double_scalars\n",
      "  dip[i] = 100 * (self._dip[i]/self._trs[i])\n",
      "/home/hemang/.local/lib/python3.8/site-packages/ta/trend.py:612: RuntimeWarning: invalid value encountered in double_scalars\n",
      "  din[i] = 100 * (self._din[i]/self._trs[i])\n",
      "/home/hemang/.local/lib/python3.8/site-packages/ta/trend.py:636: RuntimeWarning: invalid value encountered in double_scalars\n",
      "  dip[i+self._n] = 100 * (self._dip[i]/self._trs[i])\n",
      "/home/hemang/.local/lib/python3.8/site-packages/ta/trend.py:649: RuntimeWarning: invalid value encountered in double_scalars\n",
      "  din[i+self._n] = 100 * (self._din[i]/self._trs[i])\n"
     ]
    },
    {
     "data": {
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       "      <th>volume_fi</th>\n",
       "      <th>...</th>\n",
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       "      <th>momentum_stoch_signal</th>\n",
       "      <th>momentum_wr</th>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-09-21 15:15:00+05:30</td>\n",
       "      <td>41.50</td>\n",
       "      <td>41.50</td>\n",
       "      <td>41.50</td>\n",
       "      <td>41.50</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</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",
       "      <td>...</td>\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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7786</th>\n",
       "      <td>2020-10-26 15:25:00+05:30</td>\n",
       "      <td>16.30</td>\n",
       "      <td>16.45</td>\n",
       "      <td>15.95</td>\n",
       "      <td>16.15</td>\n",
       "      <td>82050</td>\n",
       "      <td>588090.650993</td>\n",
       "      <td>-372525</td>\n",
       "      <td>-0.072136</td>\n",
       "      <td>-1035.369088</td>\n",
       "      <td>...</td>\n",
       "      <td>21.052632</td>\n",
       "      <td>35.350877</td>\n",
       "      <td>-78.947368</td>\n",
       "      <td>0.063529</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.308642</td>\n",
       "      <td>-0.920245</td>\n",
       "      <td>-0.924506</td>\n",
       "      <td>-61.084337</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7787</th>\n",
       "      <td>2020-10-26 15:26:00+05:30</td>\n",
       "      <td>16.10</td>\n",
       "      <td>16.30</td>\n",
       "      <td>16.05</td>\n",
       "      <td>16.20</td>\n",
       "      <td>32550</td>\n",
       "      <td>594600.650993</td>\n",
       "      <td>-339975</td>\n",
       "      <td>-0.033122</td>\n",
       "      <td>-654.959218</td>\n",
       "      <td>...</td>\n",
       "      <td>26.315789</td>\n",
       "      <td>29.122807</td>\n",
       "      <td>-73.684211</td>\n",
       "      <td>0.012500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1.219512</td>\n",
       "      <td>0.309598</td>\n",
       "      <td>0.309119</td>\n",
       "      <td>-60.963855</td>\n",
       "      <td>0.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7788</th>\n",
       "      <td>2020-10-26 15:27:00+05:30</td>\n",
       "      <td>16.20</td>\n",
       "      <td>16.30</td>\n",
       "      <td>16.00</td>\n",
       "      <td>16.00</td>\n",
       "      <td>33525</td>\n",
       "      <td>561075.650993</td>\n",
       "      <td>-373500</td>\n",
       "      <td>-0.081461</td>\n",
       "      <td>-1519.250758</td>\n",
       "      <td>...</td>\n",
       "      <td>5.263158</td>\n",
       "      <td>17.543860</td>\n",
       "      <td>-94.736842</td>\n",
       "      <td>-0.048382</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-2.439024</td>\n",
       "      <td>-1.234568</td>\n",
       "      <td>-1.242252</td>\n",
       "      <td>-61.445783</td>\n",
       "      <td>0.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7789</th>\n",
       "      <td>2020-10-26 15:28:00+05:30</td>\n",
       "      <td>16.10</td>\n",
       "      <td>16.10</td>\n",
       "      <td>15.60</td>\n",
       "      <td>15.85</td>\n",
       "      <td>52950</td>\n",
       "      <td>561075.650993</td>\n",
       "      <td>-426450</td>\n",
       "      <td>-0.042106</td>\n",
       "      <td>-2436.857793</td>\n",
       "      <td>...</td>\n",
       "      <td>19.230769</td>\n",
       "      <td>16.936572</td>\n",
       "      <td>-80.769231</td>\n",
       "      <td>-0.187794</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-2.461538</td>\n",
       "      <td>-0.937500</td>\n",
       "      <td>-0.941922</td>\n",
       "      <td>-61.807229</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7790</th>\n",
       "      <td>2020-10-26 15:29:00+05:30</td>\n",
       "      <td>15.85</td>\n",
       "      <td>16.00</td>\n",
       "      <td>15.50</td>\n",
       "      <td>15.75</td>\n",
       "      <td>88125</td>\n",
       "      <td>561075.650993</td>\n",
       "      <td>-514575</td>\n",
       "      <td>-0.035248</td>\n",
       "      <td>-3347.663823</td>\n",
       "      <td>...</td>\n",
       "      <td>17.857143</td>\n",
       "      <td>14.117023</td>\n",
       "      <td>-82.142857</td>\n",
       "      <td>-0.318382</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-3.076923</td>\n",
       "      <td>-0.630915</td>\n",
       "      <td>-0.632914</td>\n",
       "      <td>-62.048193</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7791 rows × 79 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                          date   open   high    low  close  volume  \\\n",
       "0    2020-09-21 15:11:00+05:30  41.50  41.50  41.50  41.50       0   \n",
       "1    2020-09-21 15:12:00+05:30  41.50  41.50  41.50  41.50       0   \n",
       "2    2020-09-21 15:13:00+05:30  41.50  41.50  41.50  41.50       0   \n",
       "3    2020-09-21 15:14:00+05:30  41.50  41.50  41.50  41.50       0   \n",
       "4    2020-09-21 15:15:00+05:30  41.50  41.50  41.50  41.50       0   \n",
       "...                        ...    ...    ...    ...    ...     ...   \n",
       "7786 2020-10-26 15:25:00+05:30  16.30  16.45  15.95  16.15   82050   \n",
       "7787 2020-10-26 15:26:00+05:30  16.10  16.30  16.05  16.20   32550   \n",
       "7788 2020-10-26 15:27:00+05:30  16.20  16.30  16.00  16.00   33525   \n",
       "7789 2020-10-26 15:28:00+05:30  16.10  16.10  15.60  15.85   52950   \n",
       "7790 2020-10-26 15:29:00+05:30  15.85  16.00  15.50  15.75   88125   \n",
       "\n",
       "         volume_adi  volume_obv  volume_cmf    volume_fi  ...  momentum_stoch  \\\n",
       "0          0.000000           0         NaN          NaN  ...             NaN   \n",
       "1          0.000000           0         NaN          NaN  ...             NaN   \n",
       "2          0.000000           0         NaN          NaN  ...             NaN   \n",
       "3          0.000000           0         NaN          NaN  ...             NaN   \n",
       "4          0.000000           0         NaN          NaN  ...             NaN   \n",
       "...             ...         ...         ...          ...  ...             ...   \n",
       "7786  588090.650993     -372525   -0.072136 -1035.369088  ...       21.052632   \n",
       "7787  594600.650993     -339975   -0.033122  -654.959218  ...       26.315789   \n",
       "7788  561075.650993     -373500   -0.081461 -1519.250758  ...        5.263158   \n",
       "7789  561075.650993     -426450   -0.042106 -2436.857793  ...       19.230769   \n",
       "7790  561075.650993     -514575   -0.035248 -3347.663823  ...       17.857143   \n",
       "\n",
       "      momentum_stoch_signal  momentum_wr  momentum_ao  momentum_kama  \\\n",
       "0                       NaN          NaN          NaN            NaN   \n",
       "1                       NaN          NaN          NaN            NaN   \n",
       "2                       NaN          NaN          NaN            NaN   \n",
       "3                       NaN          NaN          NaN            NaN   \n",
       "4                       NaN          NaN          NaN            NaN   \n",
       "...                     ...          ...          ...            ...   \n",
       "7786              35.350877   -78.947368     0.063529            NaN   \n",
       "7787              29.122807   -73.684211     0.012500            NaN   \n",
       "7788              17.543860   -94.736842    -0.048382            NaN   \n",
       "7789              16.936572   -80.769231    -0.187794            NaN   \n",
       "7790              14.117023   -82.142857    -0.318382            NaN   \n",
       "\n",
       "      momentum_roc  others_dr  others_dlr  others_cr  hl_range  \n",
       "0              NaN -34.252570         NaN   0.000000      0.00  \n",
       "1              NaN   0.000000    0.000000   0.000000      0.00  \n",
       "2              NaN   0.000000    0.000000   0.000000      0.00  \n",
       "3              NaN   0.000000    0.000000   0.000000      0.00  \n",
       "4              NaN   0.000000    0.000000   0.000000      0.00  \n",
       "...            ...        ...         ...        ...       ...  \n",
       "7786     -0.308642  -0.920245   -0.924506 -61.084337      0.50  \n",
       "7787     -1.219512   0.309598    0.309119 -60.963855      0.25  \n",
       "7788     -2.439024  -1.234568   -1.242252 -61.445783      0.30  \n",
       "7789     -2.461538  -0.937500   -0.941922 -61.807229      0.50  \n",
       "7790     -3.076923  -0.630915   -0.632914 -62.048193      0.50  \n",
       "\n",
       "[7791 rows x 79 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mydf = pd.DataFrame(old_lst) \n",
    "mydf\n",
    "import pandas as pd\n",
    "from ta import add_all_ta_features\n",
    "from ta.utils import dropna\n",
    "\n",
    "# mydf = dropna(mydf)\n",
    "mydf = add_all_ta_features(\n",
    "    mydf, open=\"open\", high=\"high\", low=\"low\", close=\"close\", volume=\"volume\")\n",
    "\n",
    "mydf['hl_range'] = mydf['high'] - mydf['low']\n",
    "mydf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "mydf[55:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# for i in list(mydf):\n",
    "#     if(i!='date'):\n",
    "#         mydf[5:][i].plot.hist(bins=500, alpha=0.8)        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#  mydf.loc[55:]['hl_range'].plot.hist(bins=250, alpha=0.9)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# pd.plotting.scatter_matrix(mydf, alpha=0.2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# # import matplotlib.pyplot as plt\n",
    "# # %matplotlib inline \n",
    "# ax = plt.figure(num=None, figsize=(100, 100), dpi=500)\n",
    "# plt.matshow(mydf.corr())\n",
    "# # plt.show(ax)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import ta\n",
    "indicator_rsi = ta.momentum.rsi(close = mydf[\"close\"], n=14, fillna=True)\n",
    "current_rsi = round(indicator_rsi[-1:].to_numpy()[0],4)\n",
    "indicator_sma = ta.trend.SMAIndicator(close = mydf[\"close\"], n=14, fillna=True)\n",
    "current_sma = round(indicator_sma.sma_indicator()[-1:].to_numpy()[0],4)\n",
    "\n",
    "print('Current RSI : '+str(current_rsi))\n",
    "print('Current SMA : '+str(current_sma))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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