Stock market data presentation.ipynb

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   "cell_type": "code",
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   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "{\n    \"Stock Name\": \"reliance\",\n    \"Latest Price\": \"1,959.00\",\n    \"Open\": \"1,958.50\",\n    \"close\": \"1,958.15\",\n    \"Day High\": \"1,962.00\",\n    \"Day Low\": \"1,935.00\",\n    \"Quantity Traded(volume)\": \"1,02,40,168\",\n    \"Delivery Quantity\": \"38,85,070\",\n    \"Delivery Percentage\": \"37.94%\"\n}\n"
     ]
    }
   ],
   "source": [
    "import requests\n",
    "from bs4 import BeautifulSoup\n",
    "import pandas\n",
    "import json\n",
    "\n",
    "# Problem statement 1\n",
    "# please write the input separated by commas(,) without spaces, even if the input is give with spaces after commas\n",
    "# the code will print first stock the will allow the user to inputs remaining stock one by one\n",
    "# the code automatically converts lower case in uppercase\n",
    "# if a number is entered as a input, the code allows user to input a correct value\n",
    "\n",
    "# both pandas and json module is used in the code for preferred presentation of output\n",
    "# code can be modified quickly to switch between pandas method (Tabular presentation)\n",
    "# json format for as a whole presentation( personally prefer json)\n",
    "# the written code take data from live stock market of nseindia.com to give the required output\n",
    "# the site mention in the document of instruction new nseindia.com is not use, as I was not able to perform Webscraping\n",
    "# due to no response from the site to request module\n",
    "\n",
    "try:\n",
    "    def func(stockname):\n",
    "        while True:                  # to check for input if entered any number\n",
    "            if stockname.isalpha():\n",
    "                break\n",
    "            else:\n",
    "                stockname = (input(\"Enter a valid stock name: \")).upper()\n",
    "        # stock url to be use\n",
    "        stock_url = 'https://www.nseindia.com/live_market/dynaContent/live_watch/get_quote/GetQuote.jsp?symbol=' + str(\n",
    "            stockname)\n",
    "        # print(stock_url)\n",
    "        headers = {\n",
    "            'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/79.0.3945.117 Safari/537.36'}\n",
    "\n",
    "        # request module for gaining access to the content of the website\n",
    "        response = requests.get(stock_url, headers=headers)\n",
    "        soup = BeautifulSoup(response.text, 'html.parser')\n",
    "\n",
    "        # fetch required section of the array\n",
    "        data_array = soup.find(id='responseDiv').getText().strip().split(\":\")\n",
    "        type(data_array)\n",
    "\n",
    "        # following function contain the data needed\n",
    "        # Some names of data may be change as per site showcase\n",
    "        def data_required():\n",
    "\n",
    "            def Lastest_Price():\n",
    "                for item in data_array:\n",
    "                    if 'lastPrice' in item:          # find the mention(in this case lastprice) data from the arrays\n",
    "                        index = data_array.index(item) + 1   # stores the data\n",
    "                        # print(\"Index -> \"+ str(index))\n",
    "                        latestPrice = data_array[index].split('\"')[1]  # to get to the the data\n",
    "                        return latestPrice\n",
    "                        # print(\"Lastest Price: \" + latestPrice)\n",
    "\n",
    "            def Open_price():\n",
    "                for item in data_array:\n",
    "                    if 'open' in item:\n",
    "                        index = data_array.index(item) + 1\n",
    "                        # print(\"Index -> \"+ str(index))\n",
    "                        open = data_array[index].split('\"')[1]\n",
    "                        return open\n",
    "\n",
    "            def Close_price():\n",
    "                for item in data_array:\n",
    "                    if 'close' in item:\n",
    "                        index = data_array.index(item) + 1\n",
    "                        # print(\"Index -> \"+ str(index))\n",
    "                        close = data_array[index].split('\"')[1]\n",
    "                        return close\n",
    "\n",
    "            def Day_high():\n",
    "                for item in data_array:\n",
    "                    if 'dayHigh' in item:\n",
    "                        index = data_array.index(item) + 1\n",
    "                        # print(\"Index -> \"+ str(index))\n",
    "                        dayHigh = data_array[index].split('\"')[1]\n",
    "                        return dayHigh\n",
    "\n",
    "            def Day_low():\n",
    "                for item in data_array:\n",
    "                    if 'dayLow' in item:\n",
    "                        index = data_array.index(item) + 1\n",
    "                        # print(\"Index -> \"+ str(index))\n",
    "                        dayLow = data_array[index].split('\"')[1]\n",
    "                        return dayLow\n",
    "\n",
    "            def Volume():\n",
    "                for item in data_array:\n",
    "                    if 'totalTradedVolume' in item:\n",
    "                        index = data_array.index(item) + 1\n",
    "                        # print(\"Index -> \"+ str(index))\n",
    "                        totalTradedVolume = data_array[index].split('\"')[1]\n",
    "                        return totalTradedVolume\n",
    "\n",
    "            def Delivery_quantity():\n",
    "                for item in data_array:\n",
    "                    if 'deliveryQuantity' in item:\n",
    "                        index = data_array.index(item) + 1\n",
    "                        # print(\"Index -> \"+ str(index))\n",
    "                        deliveryQuantity = data_array[index].split('\"')[1]\n",
    "                        return deliveryQuantity\n",
    "\n",
    "            def Percent_deliver_quantity():\n",
    "                for item in data_array:\n",
    "                    if 'deliveryToTradedQuantity' in item:\n",
    "                        index = data_array.index(item) + 1\n",
    "                        # print(\"Index -> \"+ str(index))\n",
    "                        deliveryToTradedQuantity = data_array[index].split('\"')[1]\n",
    "                        return deliveryToTradedQuantity\n",
    "            def required():\n",
    "                l = []\n",
    "                i = 2\n",
    "                for i in range(1, 2):\n",
    "                    d={}\n",
    "                    d[\"Stock Name\"] = stockname\n",
    "                    d[\"Latest Price\"] = Lastest_Price()\n",
    "                    d[\"Open\"] = Open_price()\n",
    "                    d[\"close\"] = Close_price()\n",
    "                    d[\"Day High\"] = Day_high()\n",
    "                    d[\"Day Low\"] = Day_low()\n",
    "                    d[\"Quantity Traded(volume)\"] = Volume()\n",
    "                    d[\"Delivery Quantity\"] = Delivery_quantity()\n",
    "                    d[\"Delivery Percentage\"] = Percent_deliver_quantity() + '%'\n",
    "                    l.append(d)\n",
    "                    # pandas.set_option('display.max_rows', None)\n",
    "                    # pandas.set_option('display.max_columns', None)\n",
    "                    # pandas.set_option('display.width', 2000)\n",
    "                    # pandas.set_option('display.float_format', '{:20,.2f}'.format)\n",
    "                    # pandas.set_option('display.max_colwidth', None)\n",
    "                    # pandas.get_option('display.max_columns')\n",
    "                    # pandas.set_option('display.max_columns',None)\n",
    "                    #df = pandas.DataFrame(l)\n",
    "                    json_object = json.dumps(d, indent= 4 )\n",
    "                    print(json_object)\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "                # print(df)\n",
    "\n",
    "            return required()\n",
    "        return data_required()\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "        func(stockname)\n",
    "\n",
    "except TypeError:\n",
    "    print(\"Invalid Name\")\n",
    "\n",
    "Stock_name = list(map(str, input(\"Enter the name of stock or stocks, seperate the stocks by comma(,) without spaces\"\n",
    "                                 \"\\n (Example:RELIANCE,HDFCBANK,ADANIPORTS,ITC,SBIN,IOC,RBLBANK)   : \").split(\",\")))\n",
    "\n",
    "e=0\n",
    "for e in range(len(Stock_name)):\n",
    "    stockname = Stock_name[e]\n",
    "    e = e + 1\n",
    "    func(stockname)"
   ]
  }
 ]
}