mirror of
https://github.com/OpenBB-finance/OpenBB.git
synced 2026-10-27 12:40:35 +00:00
Extract main key metrics from overview data
This commit is contained in:
didier
@@ -39,8 +39,6 @@ def print_help(s_ticker, s_start, s_interval, b_is_market_open):
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""" Print help
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"""
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print("What do you want to do?")
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print("\nMenu:")
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print(" gainers show latest top gainers")
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print(" sectors show sectors performance")
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print(" view view and load a specific stock ticker for technical analysis")
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@@ -50,55 +48,21 @@ def print_help(s_ticker, s_start, s_interval, b_is_market_open):
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print(" quit to abandon the program")
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s_intraday = (f'Intraday {s_interval}', 'Daily')[s_interval == "1440min"]
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if s_ticker and s_start:
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print(f"\n{s_intraday} Stock: {s_ticker} (from {s_start.strftime('%Y-%m-%d')})")
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elif s_ticker:
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print(f"\n{s_intraday} Stock: {s_ticker}")
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else:
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print("\nStock: ?")
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print(f"Market {('CLOSED', 'OPEN')[b_is_market_open]}.")
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if s_ticker:
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print("\nFundamental Analysis:") # https://github.com/JerBouma/FundamentalAnalysis
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print(" info provides information on main key metrics of company")
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print("details:")
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print(" profile profile of the company [FMP]")
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print(" rating rating of the company from strong sell to strong buy [FMP]")
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print(" quote quote of the company [FMP]")
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print(" enterprise enterprise value of the company over time [FMP]")
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print(" dcf discounted cash flow of the company over time [FMP]")
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print(" overview overview of the company [AV]")
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print(" earnings earnings dates and reported EPS [AV]")
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print("financial statement:")
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print(" income income statements of the company [default: AV, FMP]")
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print(" balance balance sheet of the company [default: AV, FMP]")
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print(" cash cash flow of the company [default: AV, FMP]")
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print("ratios:")
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print(" metrics key metrics of the company [FMP]")
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print(" ratios financial ratios of the company [FMP]")
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print(" growth financial statement growth of the company [FMP]")
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print("\nMenus:")
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print(" fa fundamental analysis")
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print(" ta technical analysis")
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print(" pred prediction techniques")
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print("\nTechnical Analysis:") # https://github.com/twopirllc/pandas-ta
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print("overlap:")
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print(" ema exponential moving average")
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print(" sma simple moving average")
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if s_interval != "1440min":
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print(" vwap volume weighted average price")
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print("momentum:")
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print(" cci commodity channel index")
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print(" macd moving average convergence/divergence")
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print(" rsi relative strength index")
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print(" stoch stochastic oscillator")
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print("trend:")
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print(" adx average directional movement index")
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print(" aroon aroon indicator")
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print("volatility:")
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print(" bbands bollinger bands")
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print("volume:")
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print(" ad chaikin accumulation/distribution line values")
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print(" obv on balance volume")
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'''
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'''
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print("\nPrediction:")
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print(" ma")
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print(" ema")
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@@ -108,9 +72,79 @@ def print_help(s_ticker, s_start, s_interval, b_is_market_open):
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print(" rnn")
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print(" lstm")
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print(" prophet")
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'''
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print(f"\nMarket {('CLOSED', 'OPEN')[b_is_market_open]}.")
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print("Stonks and things")
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'''
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# -----------------------------------------------------------------------------------------------------------------------
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def print_fundamental_analysis(s_ticker, s_start, s_interval):
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""" Print help """
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s_intraday = (f'Intraday {s_interval}', 'Daily')[s_interval == "1440min"]
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if s_start:
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print(f"\n{s_intraday} Stock: {s_ticker} (from {s_start.strftime('%Y-%m-%d')})")
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else:
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print(f"\n{s_intraday} Stock: {s_ticker}")
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print("\nFundamental Analysis:") # https://github.com/JerBouma/FundamentalAnalysis
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print(" info provides information on main key metrics of company")
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print(" help show this fundamental analysis menu again")
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print(" q quit this menu, and shows back to main menu")
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print(" quit quit to abandon program")
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print("details:")
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print(" overview overview of the company [AV]")
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print(" key main key metrics of the company [AV]")
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print(" profile profile of the company [FMP]")
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print(" rating rating of the company from strong sell to strong buy [FMP]")
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print(" quote quote of the company [FMP]")
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print(" enterprise enterprise value of the company over time [FMP]")
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print(" dcf discounted cash flow of the company over time [FMP]")
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print("financial statement:")
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print(" income income statements of the company [default: AV, FMP]")
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print(" balance balance sheet of the company [default: AV, FMP]")
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print(" cash cash flow of the company [default: AV, FMP]")
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print(" earnings earnings dates and reported EPS [AV]")
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print("ratios:")
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print(" metrics key metrics of the company [FMP]")
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print(" ratios financial ratios of the company [FMP]")
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print(" growth financial statement growth of the company [FMP]")
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print("")
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# -----------------------------------------------------------------------------------------------------------------------
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def print_technical_analysis(s_ticker, s_start, s_interval):
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""" Print help """
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s_intraday = (f'Intraday {s_interval}', 'Daily')[s_interval == "1440min"]
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if s_start:
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print(f"\n{s_intraday} Stock: {s_ticker} (from {s_start.strftime('%Y-%m-%d')})")
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else:
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print(f"\n{s_intraday} Stock: {s_ticker}")
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print("\nTechnical Analysis:") # https://github.com/twopirllc/pandas-ta
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print(" help show this technical analysis menu again")
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print(" q quit this menu, and shows back to main menu")
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print(" quit quit to abandon program")
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print("overlap:")
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print(" ema exponential moving average")
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print(" sma simple moving average")
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if s_interval != "1440min":
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print(" vwap volume weighted average price")
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print("momentum:")
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print(" cci commodity channel index")
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print(" macd moving average convergence/divergence")
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print(" rsi relative strength index")
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print(" stoch stochastic oscillator")
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print("trend:")
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print(" adx average directional movement index")
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print(" aroon aroon indicator")
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print("volatility:")
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print(" bbands bollinger bands")
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print("volume:")
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print(" ad chaikin accumulation/distribution line values")
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print(" obv on balance volume")
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print("")
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# -----------------------------------------------------------------------------------------------------------------------
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@@ -132,14 +166,28 @@ def main():
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df_stock = df_stock[s_start:]
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# Delete above in the future
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main_parser = argparse.ArgumentParser(prog='stock_market_bot', add_help=False)
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# Add list of arguments that the main parser accepts
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main_parser.add_argument('cmd', choices=['quit', 'help', 'gainers', 'sectors', 'view', 'load', 'clear',
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'sma', 'ema', 'macd', 'vwap', 'stoch', 'rsi', 'adx', 'quote',
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'cci', 'aroon', 'bbands', 'ad', 'obv', 'rating', 'profile',
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'income', 'balance', 'cash', 'metrics', 'ratios', 'growth',
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'enterprise', 'dcf', 'overview', 'earnings', 'info'])
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menu_parser = argparse.ArgumentParser(prog='stock_market_bot', add_help=False)
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menu_parser.add_argument('cmd', choices=['gainers', 'sectors', 'view', 'clear', 'load',
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'fa', 'ta', 'help', 'quit'])
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# Add list of arguments that the fundamental analysis parser accepts
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fa_parser = argparse.ArgumentParser(prog='fundamental_analysis', add_help=False)
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fa_parser.add_argument('fa', choices=['info', 'help', 'q', 'quit',
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'overview', 'key', 'profile', 'rating', 'quote', 'enterprise', 'dcf', # details
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'income', 'balance', 'cash', 'earnings', # financial statement
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'metrics', 'ratios', 'growth']) # ratios
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# Add list of arguments that the technical analysis parser accepts
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ta_parser = argparse.ArgumentParser(prog='technical_analysis', add_help=False)
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ta_parser.add_argument('ta', choices=['help', 'q', 'quit',
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'ema', 'sma', 'vwap', # overlap
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'cci', 'macd', 'rsi', 'stoch', # momentum
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'adx', 'aroon', # trend
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'bbands', # volatility
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'ad', 'obv']) # volume
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# Print first welcome message and help
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print("\nWelcome to Didier's Stock Market Bot\n")
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@@ -153,7 +201,8 @@ def main():
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# Parse main command of the list of possible commands
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try:
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(ns_known_args, l_args) = main_parser.parse_known_args(as_input.split())
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(ns_known_args, l_args) = menu_parser.parse_known_args(as_input.split())
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except SystemExit:
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print("The command selected doesn't exist\n")
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continue
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@@ -165,12 +214,10 @@ def main():
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# --------------------------------------------------- GAINERS --------------------------------------------------
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if ns_known_args.cmd == 'gainers':
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smm.gainers(l_args)
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continue
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# --------------------------------------------------- SECTORS --------------------------------------------------
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if ns_known_args.cmd == 'sectors':
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smm.sectors(l_args)
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continue
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# --------------------------------------------------- CLEAR ----------------------------------------------------
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elif ns_known_args.cmd == 'clear':
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@@ -181,141 +228,180 @@ def main():
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# ---------------------------------------------------- LOAD ----------------------------------------------------
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elif ns_known_args.cmd == 'load':
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[s_ticker, s_start, s_interval, df_stock] = smm.load(l_args, s_ticker, s_start, s_interval, df_stock)
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continue
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# ---------------------------------------------------- VIEW ----------------------------------------------------
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elif ns_known_args.cmd == 'view':
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smm.view(l_args, s_ticker, s_start, s_interval, df_stock)
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continue
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# ---------------------------------------------------- HELP ----------------------------------------------------
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# ---------------------------------------------------- HELP ----------------------------------------------------
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elif ns_known_args.cmd == 'help':
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print_help(s_ticker, s_start, s_interval, b_is_stock_market_open())
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# ----------------------------------------------------- QUIT ----------------------------------------------------
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elif ns_known_args.cmd == 'quit':
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print("Hope you made money today. Good bye my lover, good bye my friend.\n")
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break
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return
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# --------------------------------------------------------------------------------------------------------------
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# ------------------------------------------- FUNDAMENTAL ANALYSIS ---------------------------------------------
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# --------------------------------------------------------------------------------------------------------------
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elif ns_known_args.cmd == 'fa':
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# Print fundamental analysis menun
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print_fundamental_analysis(s_ticker, s_start, s_interval)
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# -------------------------------------------------- DETAILS --------------------------------------------------
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elif ns_known_args.cmd == 'info':
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smfa.info(l_args, s_ticker)
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continue
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elif ns_known_args.cmd == 'profile':
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smfa.profile(l_args, s_ticker)
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continue
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# Loop forever and ever
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while True:
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# Get input command from user
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as_input = input('> ')
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# Parse fundamental analysis command of the list of possible commands
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try:
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(ns_known_args, l_args) = fa_parser.parse_known_args(as_input.split())
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elif ns_known_args.cmd == 'rating':
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smfa.rating(l_args, s_ticker)
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continue
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except SystemExit:
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print("The command selected doesn't exist\n")
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continue
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elif ns_known_args.cmd == 'quote':
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smfa.quote(l_args, s_ticker)
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continue
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elif ns_known_args.cmd == 'enterprise':
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smfa.enterprise(l_args, s_ticker)
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continue
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if ns_known_args.fa == 'info':
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smfa.info(l_args, s_ticker)
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elif ns_known_args.cmd == 'dcf':
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smfa.discounted_cash_flow(l_args, s_ticker)
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continue
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elif ns_known_args.fa == 'help':
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print_fundamental_analysis(s_ticker, s_start, s_interval)
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elif ns_known_args.cmd == 'overview':
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smfa.overview(l_args, s_ticker)
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continue
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elif ns_known_args.fa == 'q':
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print_help(s_ticker, s_start, s_interval, b_is_stock_market_open())
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break
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elif ns_known_args.cmd == 'earnings':
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smfa.earnings(l_args, s_ticker)
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continue
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elif ns_known_args.fa == 'quit':
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print("Hope you made money today. Good bye my lover, good bye my friend.\n")
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return
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# -------------------------------------------------- DETAILS --------------------------------------------------
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elif ns_known_args.fa == 'profile':
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smfa.profile(l_args, s_ticker)
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# --------------------------------------------- FINANCIAL STATEMENT --------------------------------------------
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elif ns_known_args.cmd == 'income':
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smfa.income_statement(l_args, s_ticker)
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continue
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elif ns_known_args.fa == 'rating':
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smfa.rating(l_args, s_ticker)
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elif ns_known_args.cmd == 'balance':
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smfa.balance_sheet(l_args, s_ticker)
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continue
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elif ns_known_args.fa == 'quote':
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smfa.quote(l_args, s_ticker)
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elif ns_known_args.fa == 'enterprise':
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smfa.enterprise(l_args, s_ticker)
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elif ns_known_args.cmd == 'cash':
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smfa.cash_flow(l_args, s_ticker)
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continue
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elif ns_known_args.fa == 'dcf':
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smfa.discounted_cash_flow(l_args, s_ticker)
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# --------------------------------------------------- RATIOS -----------------------------------------------------
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elif ns_known_args.cmd == 'metrics':
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smfa.key_metrics(l_args, s_ticker)
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continue
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elif ns_known_args.fa == 'overview':
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smfa.overview(l_args, s_ticker)
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elif ns_known_args.cmd == 'ratios':
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smfa.financial_ratios(l_args, s_ticker)
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continue
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elif ns_known_args.fa == 'key':
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smfa.key(l_args, s_ticker)
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elif ns_known_args.cmd == 'growth':
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smfa.financial_statement_growth(l_args, s_ticker)
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continue
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# --------------------------------------------- FINANCIAL STATEMENT --------------------------------------------
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elif ns_known_args.fa == 'income':
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smfa.income_statement(l_args, s_ticker)
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elif ns_known_args.fa == 'balance':
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smfa.balance_sheet(l_args, s_ticker)
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elif ns_known_args.fa == 'cash':
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smfa.cash_flow(l_args, s_ticker)
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elif ns_known_args.fa == 'earnings':
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smfa.earnings(l_args, s_ticker)
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# --------------------------------------------------- RATIOS -----------------------------------------------------
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elif ns_known_args.fa == 'metrics':
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smfa.key_metrics(l_args, s_ticker)
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elif ns_known_args.fa == 'ratios':
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smfa.financial_ratios(l_args, s_ticker)
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elif ns_known_args.fa == 'growth':
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smfa.financial_statement_growth(l_args, s_ticker)
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# ------------------------------------------------------------------------------------------------------------
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else:
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print("Command not recognized!")
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print("")
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# --------------------------------------------------------------------------------------------------------------
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# -------------------------------------------- TECHNICAL ANALYSIS ----------------------------------------------
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# --------------------------------------------------------------------------------------------------------------
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elif ns_known_args.cmd == 'ta':
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# Print technical analysis menun
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print_technical_analysis(s_ticker, s_start, s_interval)
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# -------------------------------------------------- OVERLAP --------------------------------------------------
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elif ns_known_args.cmd == 'ema':
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smta.ema(l_args, s_ticker, s_interval, df_stock)
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continue
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# Loop forever and ever
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while True:
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# Get input command from user
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as_input = input('> ')
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# Parse fundamental analysis command of the list of possible commands
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try:
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(ns_known_args, l_args) = ta_parser.parse_known_args(as_input.split())
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elif ns_known_args.cmd == 'sma':
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smta.sma(l_args, s_ticker, s_interval, df_stock)
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continue
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except SystemExit:
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print("The command selected doesn't exist\n")
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continue
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elif ns_known_args.cmd == 'vwap':
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smta.vwap(l_args, s_ticker, s_interval, df_stock)
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continue
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if ns_known_args.ta == 'help':
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print_technical_analysis(s_ticker, s_start, s_interval)
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# --------------------------------------------------- MOMENTUM ---------------------------------------------------
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elif ns_known_args.cmd == 'cci':
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smta.cci(l_args, s_ticker, s_interval, df_stock)
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continue
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elif ns_known_args.ta == 'q':
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print_help(s_ticker, s_start, s_interval, b_is_stock_market_open())
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break
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elif ns_known_args.cmd == 'macd':
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smta.macd(l_args, s_ticker, s_interval, df_stock)
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continue
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elif ns_known_args.ta == 'quit':
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print("Hope you made money today. Good bye my lover, good bye my friend.\n")
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return
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elif ns_known_args.cmd == 'rsi':
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smta.rsi(l_args, s_ticker, s_interval, df_stock)
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continue
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# -------------------------------------------------- OVERLAP --------------------------------------------------
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elif ns_known_args.ta == 'ema':
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smta.ema(l_args, s_ticker, s_interval, df_stock)
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elif ns_known_args.cmd == 'stoch':
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smta.stoch(l_args, s_ticker, s_interval, df_stock)
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continue
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# ---------------------------------------------------- TREND ----------------------------------------------------
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elif ns_known_args.cmd == 'adx':
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smta.adx(l_args, s_ticker, s_interval, df_stock)
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continue
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elif ns_known_args.ta == 'sma':
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smta.sma(l_args, s_ticker, s_interval, df_stock)
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elif ns_known_args.cmd == 'aroon':
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smta.aroon(l_args, s_ticker, s_interval, df_stock)
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continue
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elif ns_known_args.ta == 'vwap':
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smta.vwap(l_args, s_ticker, s_interval, df_stock)
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# -------------------------------------------------- VOLATILITY --------------------------------------------------
|
||||
elif ns_known_args.cmd == 'bbands':
|
||||
smta.bbands(l_args, s_ticker, s_interval, df_stock)
|
||||
continue
|
||||
# --------------------------------------------------- MOMENTUM ---------------------------------------------------
|
||||
elif ns_known_args.ta == 'cci':
|
||||
smta.cci(l_args, s_ticker, s_interval, df_stock)
|
||||
|
||||
# ---------------------------------------------------- VOLUME ----------------------------------------------------
|
||||
elif ns_known_args.cmd == 'ad':
|
||||
smta.ad(l_args, s_ticker, s_interval, df_stock)
|
||||
continue
|
||||
elif ns_known_args.ta == 'macd':
|
||||
smta.macd(l_args, s_ticker, s_interval, df_stock)
|
||||
|
||||
elif ns_known_args.cmd == 'obv':
|
||||
smta.obv(l_args, s_ticker, s_interval, df_stock)
|
||||
continue
|
||||
elif ns_known_args.ta == 'rsi':
|
||||
smta.rsi(l_args, s_ticker, s_interval, df_stock)
|
||||
|
||||
elif ns_known_args.ta == 'stoch':
|
||||
smta.stoch(l_args, s_ticker, s_interval, df_stock)
|
||||
|
||||
# ---------------------------------------------------- TREND ----------------------------------------------------
|
||||
elif ns_known_args.ta == 'adx':
|
||||
smta.adx(l_args, s_ticker, s_interval, df_stock)
|
||||
|
||||
elif ns_known_args.ta == 'aroon':
|
||||
smta.aroon(l_args, s_ticker, s_interval, df_stock)
|
||||
|
||||
# -------------------------------------------------- VOLATILITY --------------------------------------------------
|
||||
elif ns_known_args.ta == 'bbands':
|
||||
smta.bbands(l_args, s_ticker, s_interval, df_stock)
|
||||
|
||||
# ---------------------------------------------------- VOLUME ----------------------------------------------------
|
||||
elif ns_known_args.ta == 'ad':
|
||||
smta.ad(l_args, s_ticker, s_interval, df_stock)
|
||||
|
||||
elif ns_known_args.ta == 'obv':
|
||||
smta.obv(l_args, s_ticker, s_interval, df_stock)
|
||||
|
||||
# ------------------------------------------------------------------------------------------------------------
|
||||
else:
|
||||
print("Command not recognized!")
|
||||
|
||||
# --------------------------------------------------------------------------------------------------------------
|
||||
# ------------------------------------------------ PREDICTION --------------------------------------------------
|
||||
@@ -324,7 +410,7 @@ def main():
|
||||
else:
|
||||
print('Shouldnt see this command!')
|
||||
|
||||
print("\n")
|
||||
print("")
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
|
||||
@@ -38,6 +38,126 @@ def info(l_args, s_ticker):
|
||||
print("ERROR!\n")
|
||||
|
||||
|
||||
# ---------------------------------------------------- OVERVIEW ----------------------------------------------------
|
||||
def overview(l_args, s_ticker):
|
||||
parser = argparse.ArgumentParser(prog='overview',
|
||||
description="""Gives an overview about the company. The following fields are expected:
|
||||
Symbol, Asset type, Name, Description, Exchange, Currency, Country, Sector, Industry,
|
||||
Address, Full time employees, Fiscal year end, Latest quarter, Market capitalization,
|
||||
EBITDA, PE ratio, PEG ratio, Book value, Dividend per share, Dividend yield, EPS,
|
||||
Revenue per share TTM, Profit margin, Operating margin TTM, Return on assets TTM,
|
||||
Return on equity TTM, Revenue TTM, Gross profit TTM, Diluted EPS TTM, Quarterly earnings growth YOY,
|
||||
Quarterly revenue growth YOY, Analyst target price, Trailing PE, Forward PE,
|
||||
Price to sales ratio TTM, Price to book ratio, EV to revenue, EV to EBITDA, Beta, 52 week high,
|
||||
52 week low, 50 day moving average, 200 day moving average, Shares outstanding, Shares float,
|
||||
Shares short, Shares short prior month, Short ratio, Short percent outstanding, Short percent float,
|
||||
Percent insiders, Percent institutions, Forward annual dividend rate, Forward annual dividend yield,
|
||||
Payout ratio, Dividend date, Ex dividend date, Last split factor, and Last split date.
|
||||
[Source: Alpha Vantage API]""")
|
||||
|
||||
try:
|
||||
(ns_parser, l_unknown_args) = parser.parse_known_args(l_args)
|
||||
except SystemExit:
|
||||
print("")
|
||||
return
|
||||
|
||||
if l_unknown_args:
|
||||
print(f"The following args couldn't be interpreted: {l_unknown_args}")
|
||||
|
||||
try:
|
||||
# Request OVERVIEW data from Alpha Vantage API
|
||||
s_req = f"https://www.alphavantage.co/query?function=OVERVIEW&symbol={s_ticker}&apikey={cfg.API_KEY_FINANCIALMODELINGPREP}"
|
||||
result = requests.get(s_req, stream=True)
|
||||
|
||||
# If the returned data was successful
|
||||
if result.status_code == 200:
|
||||
# Parse json data to dataframe
|
||||
df_fa = json_normalize(result.json())
|
||||
# Keep json data sorting in dataframe
|
||||
df_fa = df_fa[list(result.json().keys())].T
|
||||
df_fa = df_fa.applymap(lambda x: long_number_format(x))
|
||||
df_fa.index = [''.join(' ' + char if char.isupper() else char.strip() for char in idx).strip() for idx in df_fa.index.tolist()]
|
||||
df_fa.index = [s_val.capitalize() for s_val in df_fa.index]
|
||||
df_fa = df_fa.rename(index={"E b i t d a":"EBITDA",
|
||||
"P e ratio":"PE ratio",
|
||||
"P e g ratio":"PEG ratio",
|
||||
"E p s":"EPS",
|
||||
"Revenue per share t t m":"Revenue per share TTM",
|
||||
"Operating margin t t m":"Operating margin TTM",
|
||||
"Return on assets t t m":"Return on assets TTM",
|
||||
"Return on equity t t m":"Return on equity TTM",
|
||||
"Revenue t t m":"Revenue TTM",
|
||||
"Gross profit t t m":"Gross profit TTM",
|
||||
"Diluted e p s t t m":"Diluted EPS TTM",
|
||||
"Quarterly earnings growth y o y":"Quarterly earnings growth YOY",
|
||||
"Quarterly revenue growth y o y":"Quarterly revenue growth YOY",
|
||||
"Trailing p e":"Trailing PE",
|
||||
"Forward p e":"Forward PE",
|
||||
"Price to sales ratio t t m":"Price to sales ratio TTM",
|
||||
"E v to revenue":"EV to revenue",
|
||||
"E v to e b i t d a":"EV to EBITDA"})
|
||||
|
||||
pd.set_option('display.max_colwidth', -1)
|
||||
|
||||
print(df_fa.drop(index=['Description']).to_string(header=False))
|
||||
print(f"Description: {df_fa.loc['Description'][0]}")
|
||||
print("")
|
||||
else:
|
||||
print(f"Error: {result.status_code}")
|
||||
|
||||
except:
|
||||
print("ERROR!\n")
|
||||
|
||||
|
||||
# ------------------------------------------------------ KEY ------------------------------------------------------
|
||||
def key(l_args, s_ticker):
|
||||
parser = argparse.ArgumentParser(prog='key',
|
||||
description="""Gives main key metrics about the company (it's a subset of the
|
||||
Overview data from Alpha Vantage API). The following fields are expected:
|
||||
Market capitalization, EBITDA, EPS, PE ratio, PEG ratio, Price to book ratio,
|
||||
Return on equity TTM, Payout ratio, Price to sales ratio TTM, Dividend yield,
|
||||
50 day moving average, Analyst target price, Beta [Source: Alpha Vantage API]""")
|
||||
|
||||
try:
|
||||
(ns_parser, l_unknown_args) = parser.parse_known_args(l_args)
|
||||
except SystemExit:
|
||||
print("")
|
||||
return
|
||||
|
||||
if l_unknown_args:
|
||||
print(f"The following args couldn't be interpreted: {l_unknown_args}")
|
||||
|
||||
try:
|
||||
# Request OVERVIEW data
|
||||
s_req = f"https://www.alphavantage.co/query?function=OVERVIEW&symbol={s_ticker}&apikey={cfg.API_KEY_ALPHAVANTAGE}"
|
||||
result = requests.get(s_req, stream=True)
|
||||
|
||||
# If the returned data was successful
|
||||
if result.status_code == 200:
|
||||
df_fa = json_normalize(result.json())
|
||||
df_fa = df_fa[list(result.json().keys())].T
|
||||
|
||||
df_fa = df_fa.applymap(lambda x: long_number_format(x))
|
||||
df_fa.index = [''.join(' ' + char if char.isupper() else char.strip() for char in idx).strip() for idx in df_fa.index.tolist()]
|
||||
df_fa.index = [s_val.capitalize() for s_val in df_fa.index]
|
||||
df_fa = df_fa.rename(index={"E b i t d a":"EBITDA",
|
||||
"P e ratio":"PE ratio",
|
||||
"P e g ratio":"PEG ratio",
|
||||
"E p s":"EPS",
|
||||
"Return on equity t t m":"Return on equity TTM",
|
||||
"Price to sales ratio t t m":"Price to sales ratio TTM"})
|
||||
as_key_metrics = ["Market capitalization", "EBITDA", "EPS", "PE ratio", "PEG ratio", "Price to book ratio",
|
||||
"Return on equity TTM", "Payout ratio", "Price to sales ratio TTM", "Dividend yield",
|
||||
"50 day moving average", "Analyst target price", "Beta"]
|
||||
print(df_fa.loc[as_key_metrics].to_string(header=False))
|
||||
print("")
|
||||
else:
|
||||
print(f"Error: {result.status_code}")
|
||||
|
||||
except:
|
||||
print("ERROR!\n")
|
||||
|
||||
|
||||
# ---------------------------------------------------- PROFILE ----------------------------------------------------
|
||||
def profile(l_args, s_ticker):
|
||||
parser = argparse.ArgumentParser(prog='profile',
|
||||
@@ -208,77 +328,6 @@ def discounted_cash_flow(l_args, s_ticker):
|
||||
print("ERROR!\n")
|
||||
|
||||
|
||||
# ---------------------------------------------------- OVERVIEW ----------------------------------------------------
|
||||
def overview(l_args, s_ticker):
|
||||
parser = argparse.ArgumentParser(prog='overview',
|
||||
description="""Gives an overview about the company. The following fields are expected:
|
||||
Symbol, Asset type, Name, Description, Exchange, Currency, Country, Sector, Industry,
|
||||
Address, Full time employees, Fiscal year end, Latest quarter, Market capitalization,
|
||||
EBITDA, PE ratio, PEG ratio, Book value, Dividend per share, Dividend yield, EPS,
|
||||
Revenue per share TTM, Profit margin, Operating margin TTM, Return on assets TTM,
|
||||
Return on equity TTM, Revenue TTM, Gross profit TTM, Diluted EPS TTM, Quarterly earnings growth YOY,
|
||||
Quarterly revenue growth YOY, Analyst target price, Trailing PE, Forward PE,
|
||||
Price to sales ratio TTM, Price to book ratio, EV to revenue, EV to EBITDA, Beta, 52 week high,
|
||||
52 week low, 50 day moving average, 200 day moving average, Shares outstanding, Shares float,
|
||||
Shares short, Shares short prior month, Short ratio, Short percent outstanding, Short percent float,
|
||||
Percent insiders, Percent institutions, Forward annual dividend rate, Forward annual dividend yield,
|
||||
Payout ratio, Dividend date, Ex dividend date, Last split factor, and Last split date.
|
||||
[Source: Alpha Vantage API]""")
|
||||
|
||||
try:
|
||||
(ns_parser, l_unknown_args) = parser.parse_known_args(l_args)
|
||||
except SystemExit:
|
||||
print("")
|
||||
return
|
||||
|
||||
if l_unknown_args:
|
||||
print(f"The following args couldn't be interpreted: {l_unknown_args}")
|
||||
|
||||
try:
|
||||
# Request OVERVIEW data from Alpha Vantage API
|
||||
s_req = f"https://www.alphavantage.co/query?function=OVERVIEW&symbol={s_ticker}&apikey={cfg.API_KEY_FINANCIALMODELINGPREP}"
|
||||
result = requests.get(s_req, stream=True)
|
||||
|
||||
# If the returned data was successful
|
||||
if result.status_code == 200:
|
||||
# Parse json data to dataframe
|
||||
df_fa = json_normalize(result.json())
|
||||
# Keep json data sorting in dataframe
|
||||
df_fa = df_fa[list(result.json().keys())].T
|
||||
df_fa = df_fa.applymap(lambda x: long_number_format(x))
|
||||
df_fa.index = [''.join(' ' + char if char.isupper() else char.strip() for char in idx).strip() for idx in df_fa.index.tolist()]
|
||||
df_fa.index = [s_val.capitalize() for s_val in df_fa.index]
|
||||
df_fa = df_fa.rename(index={"E b i t d a":"EBITDA",
|
||||
"P e ratio":"PE ratio",
|
||||
"P e g ratio":"PEG ratio",
|
||||
"E p s":"EPS",
|
||||
"Revenue per share t t m":"Revenue per share TTM",
|
||||
"Operating margin t t m":"Operating margin TTM",
|
||||
"Return on assets t t m":"Return on assets TTM",
|
||||
"Return on equity t t m":"Return on equity TTM",
|
||||
"Revenue t t m":"Revenue TTM",
|
||||
"Gross profit t t m":"Gross profit TTM",
|
||||
"Diluted e p s t t m":"Diluted EPS TTM",
|
||||
"Quarterly earnings growth y o y":"Quarterly earnings growth YOY",
|
||||
"Quarterly revenue growth y o y":"Quarterly revenue growth YOY",
|
||||
"Trailing p e":"Trailing PE",
|
||||
"Forward p e":"Forward PE",
|
||||
"Price to sales ratio t t m":"Price to sales ratio TTM",
|
||||
"E v to revenue":"EV to revenue",
|
||||
"E v to e b i t d a":"EV to EBITDA"})
|
||||
|
||||
pd.set_option('display.max_colwidth', -1)
|
||||
|
||||
print(df_fa.drop(index=['Description']).to_string(header=False))
|
||||
print(f"Description: {df_fa.loc['Description'][0]}")
|
||||
print("")
|
||||
else:
|
||||
print(f"Error: {result.status_code}")
|
||||
|
||||
except:
|
||||
print("ERROR!\n")
|
||||
|
||||
|
||||
# ---------------------------------------------------- EARNINGS ----------------------------------------------------
|
||||
def earnings(l_args, s_ticker):
|
||||
parser = argparse.ArgumentParser(prog='earnings',
|
||||
|
||||
@@ -21,7 +21,7 @@ def sectors(l_args):
|
||||
|
||||
sp = SectorPerformances(key=cfg.API_KEY_ALPHAVANTAGE, output_format='pandas')
|
||||
df_sectors, d_meta_data = sp.get_sector()
|
||||
df_sectorsf['Rank A: Real-Time Performance'].plot(kind='bar')
|
||||
df_sectors['Rank A: Real-Time Performance'].plot(kind='bar')
|
||||
plt.title('Real Time Performance (%) per Sector')
|
||||
plt.tight_layout()
|
||||
plt.grid()
|
||||
|
||||
Reference in New Issue
Block a user