info.py

info_list = ['averageDailyVolume10Day', 
    'averageVolume', 
    'averageVolume10days', 
    'country', 
    'currency', 
    'dayHigh', 
    'dayLow', 
    'dividendRate', 
    'earningsQuarterlyGrowth', 
    'enterpriseToEbitda', 
    'enterpriseToRevenue', 
    'enterpriseValue', 
    'exDividendDate', 
    'exchange', 
    'exchangeTimezoneName', 
    'exchangeTimezoneShortName', 
    'fiftyDayAverage', 
    'fiftyTwoWeekHigh', 
    'fiftyTwoWeekLow', 
    'fiveYearAvgDividendYield', 
    'floatShares', 
    'forwardEps', 
    'forwardPE', 
    'fullTimeEmployees',
    'industry', 
    'lastDividendDate', 
    'lastDividendValue', 
    'lastFiscalYearEnd', 
    'lastSplitDate', 
    'lastSplitFactor', 
    'market', 
    'marketCap', 
    'previousClose', 
    'priceHint', 
    'regularMarketDayHigh', 
    'regularMarketDayLow', 
    'regularMarketOpen', 
    'regularMarketPreviousClose', 
    'regularMarketPrice', 
    'regularMarketVolume', 
    'sector', 
    'sharesOutstanding', 
    'sharesPercentSharesOut', 
    'sharesShort', 
    'sharesShortPreviousMonthDate', 
    'sharesShortPriorMonth', 
    'shortName', 
    'shortPercentOfFloat', 
    'shortRatio', 
    'website'
]

news_sources = [
    "abc-news",
    "axios",
    "bbc-news",
    "bleacher-report",
    "bloomberg",
    "buzzfeed",
    "cbc-news",
    "cbs-news",
    "cnn",
    "crypto-coins-news",
    "espn",
    "financial-post",
    "focus",
    "fortune",
    "fox-news",
    "google-news",
    "hacker-news",
    "independent",
    "info-money",
    "national-geographic",
    "nbc-news",
    "news24",
    "newsweek",
    "new-york-magazine",
    "next-big-future",
    "techcrunch",
    "the-huffington-post",
    "the-wall-street-journal",
    "the-washington-post",
    "the-washington-times",
    "time",
    "usa-today",
    "wired",
]