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import pandas as pd
from urllib.request import Request, urlopen
import json
from pandas.io.json import json_normalize




Prefix = "https://api.iextrading.com/1.0/tops?symbols="
#Suffix = input()
Suffix1 = "IBM"
Suffix2 = "AAPL"
linke1 = Prefix + Suffix1
linke2 = Prefix + Suffix2

#print (linke1)
#print (linke2)

def return_valid_securities():
    """
    Return a list of valid securities
    :param securities: list of securities
    :return: list of valid securities
    """


    valid_securities = _url_to_dataframe(linke1)['symbol']
    valid_securities = _url_to_dataframe(linke2)['symbo2']

    return [x for x in securities if x in set(valid_securities)]


def _url_to_dataframe(url, nest=None):

    """
    Takes a url and returns the response in a pandas dataframe
    :param url: str url
    :param nest: column with nested data
    :return: pandas dataframe containing data from url
    """

    request = Request(url)
    response = urlopen(request)
    elevations = response.read()
    data = json.loads(elevations)

    if nest:
        data = json_normalize(data[nest])
    else:
        data = json_normalize(data)

    return pd.DataFrame(data)



while (Suffix1 == "IBM" and Suffix2 == "AAPL"):
    def get_latest_quote_and_trade1():

        """
        Gets latest quote and trade data
        :param securities: list of securities
        :return: pandas dataframe containing data for valid securities
        """

        df = _url_to_dataframe(linke1)
        df['lastSaleTime'] = pd.to_datetime(df['lastSaleTime'], unit='ms')
        df['lastUpdated'] = pd.to_datetime(df['lastUpdated'], unit='ms')
        df.set_index(['symbol'], inplace=True)
        return df.to_string()
        #return df.to_excel('exceloutput.xlsx', sheet_name='sheet1', index=False,)





    def get_latest_quote_and_trade2():
        """
        Gets latest quote and trade data
        :param securities: list of securities
        :return: pandas dataframe containing data for valid securities
        """

        df = _url_to_dataframe(linke2)
        df['lastSaleTime'] = pd.to_datetime(df['lastSaleTime'], unit='ms')
        df['lastUpdated'] = pd.to_datetime(df['lastUpdated'], unit='ms')
        df.set_index(['symbol'], inplace=True)
        return df.to_string()






    print(get_latest_quote_and_trade1())
    print(get_latest_quote_and_trade2())



    print(linke1)
    print(linke2)

    f = open('1530', 'a')
    #output1 = get_latest_quote_and_trade1()
    output2 = get_latest_quote_and_trade2()
    f.write (output2)



#to_excel('test.xlsx', sheet_name='sheet1', index=False,)