mirror of
https://github.com/OpenBB-finance/OpenBB.git
synced 2026-10-27 12:40:35 +00:00
Add ratings, and improve CLI interface
This commit is contained in:
didier
@@ -24,8 +24,7 @@ register_matplotlib_converters()
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from stock_market_helper_funcs import *
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import stock_market_menu as smm
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import stock_market_technical_analysis as smta
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import stock_market_fundamental_analysis as smfa
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# -----------------------------------------------------------------------------------------------------------------------
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def print_help(s_ticker, s_start, b_is_market_open):
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@@ -36,37 +35,38 @@ def print_help(s_ticker, s_start, b_is_market_open):
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print("\nMenu:")
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print(" gainers show latest top gainers")
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print(" view view and load a specific stock ticker for technical analysis")
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print(" clear clear a specific stock ticker from technical analysis")
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print(" load load a specific stock ticker for technical analysis")
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print(" clear clear a specific stock ticker from analysis")
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print(" load load a specific stock ticker for analysis")
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print(" help help to see this menu again")
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print(" quit to abandon the program")
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if s_ticker and s_start:
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print(f"\n-----> {s_ticker} starting at {s_start.strftime('%Y-%m-%d')} <-----")
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print(f"\nStock: {s_ticker} (from {s_start.strftime('%Y-%m-%d')})")
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elif s_ticker:
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print(f"\n-----> {s_ticker} <-----")
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print(f"\nStock: {s_ticker}")
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else:
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print("\n-----> ? <-----")
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print("\nStock: ?")
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print("\nFundamental Analysis:")
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print(" example not yet covered")
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if s_ticker:
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print("\nFundamental Analysis:")
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print(" ratings company ratings from strong sell to strong buy")
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print("\nTechnical Analysis:")
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print(" sma simple moving average")
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print(" ema exponential moving average")
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print("\nTechnical Analysis:")
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print(" sma simple moving average")
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print(" ema exponential moving average")
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print("\nPrediction:")
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print(" ma")
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print(" ema")
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print(" lr")
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print(" knn")
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print(" arima")
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print(" rnn")
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print(" lstm")
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print(" prophet")
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print("\nPrediction:")
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print(" ma")
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print(" ema")
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print(" lr")
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print(" knn")
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print(" arima")
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print(" rnn")
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print(" lstm")
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print(" prophet")
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print(f"\nMarket {('Closed', 'Open')[b_is_market_open]}. Play stocks:")
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print("Stock name, and how much money to bet?")
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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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@@ -86,7 +86,7 @@ def main():
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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' ,'view', 'load', 'clear', 'sma', 'ema'])
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main_parser.add_argument('cmd', choices=['quit', 'help', 'gainers' ,'view', 'load', 'clear', 'sma', 'ema', 'ratings'])
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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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@@ -143,26 +143,29 @@ def main():
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# ------------------------------------------- FUNDAMENTAL ANALYSIS ---------------------------------------------
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# --------------------------------------------------------------------------------------------------------------
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# --------------------------------------------------- RATINGS --------------------------------------------------
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elif ns_known_args.cmd == 'ratings':
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smfa.ratings(l_args, s_ticker)
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continue
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# --------------------------------------------------------------------------------------------------------------
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# -------------------------------------------- TECHNICAL ANALYSIS ----------------------------------------------
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# --------------------------------------------------------------------------------------------------------------
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# --------------------------------------------------------------------------------------------------------------
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# ------------------------------------------------ PREDICTION --------------------------------------------------
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# --------------------------------------------------------------------------------------------------------------
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# ---------------------------------------------------- SMA ----------------------------------------------------
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elif ns_known_args.cmd == 'sma':
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[s_ticker, s_start] = smta.sma(l_args, s_ticker, s_start)
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smta.sma(l_args, s_ticker, df_stock)
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continue
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# ---------------------------------------------------- EMA ----------------------------------------------------
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elif ns_known_args.cmd == 'ema':
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[s_ticker, s_start] = smta.ema(l_args, s_ticker, s_start)
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smta.ema(l_args, s_ticker, df_stock)
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continue
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# --------------------------------------------------------------------------------------------------------------
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# ------------------------------------------------ PREDICTION --------------------------------------------------
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# --------------------------------------------------------------------------------------------------------------
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else:
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print('Shouldnt see this command!')
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27
stock_market_fundamental_analysis.py
Normal file
27
stock_market_fundamental_analysis.py
Normal file
@@ -0,0 +1,27 @@
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import FundamentalAnalysis as fa
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import config_bot as cfg
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import argparse
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from stock_market_helper_funcs import *
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# ---------------------------------------------------- RATINGS ----------------------------------------------------
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def ratings(l_args, s_ticker):
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parser = argparse.ArgumentParser(prog='ratings',
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description=""" Gives information about the rating of a company which includes
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i.a. the company rating and recommendation as well as ratings based
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on a variety of ratios.""")
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try:
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(ns_parser, l_unknown_args) = parser.parse_known_args(l_args)
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except SystemExit:
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print("")
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return
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if l_unknown_args:
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print(f"The following args couldn't be interpreted: {l_unknown_args}")
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try:
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df_ratings = fa.rating(s_ticker, cfg.API_KEY_FINANCIALMODELINGPREP)
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print(df_ratings)
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print("")
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except:
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print("")
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@@ -41,7 +41,7 @@ def plot_view_stock(df, symbol):
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# -----------------------------------------------------------------------------------------------------------------------
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def plot_stock_ta(df_stock, s_stock, df_ta, s_ta):
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plt.plot(df_stock.index, df_stock['4. close'].values)
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plt.plot(df_stock.index, df_stock.values)
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plt.plot(df_ta.index, df_ta.values)
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plt.title(f"{s_ta} on {s_stock}")
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plt.xlim(df_stock.index[0], df_stock.index[-1])
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@@ -52,6 +52,7 @@ def plot_stock_ta(df_stock, s_stock, df_ta, s_ta):
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plt.minorticks_on()
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plt.grid(b=True, which='minor', color='#999999', linestyle='-', alpha=0.2)
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plt.show()
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print("")
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# -----------------------------------------------------------------------------------------------------------------------
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@@ -5,7 +5,7 @@ import config_bot as cfg
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from stock_market_helper_funcs import *
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# ----------------------------------------------------- SMA -----------------------------------------------------
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def sma(l_args, s_ticker, s_start):
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def sma(l_args, s_ticker, df_stock):
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parser = argparse.ArgumentParser(prog='sma',
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description=""" Moving Averages are used to smooth the data in an array to
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help eliminate noise and identify trends. The Simple Moving Average is literally
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@@ -16,52 +16,26 @@ def sma(l_args, s_ticker, s_start):
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filtering out those changes. """)
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parser.add_argument('-p', "--period", action="store", dest="n_time_period", type=check_positive, default=20,
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help='Number of data points used to calculate each moving average value.')
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parser.add_argument("-s", "--start", type=valid_date, dest="s_start_date",
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help="The starting date (format YYYY-MM-DD) of the stock")
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if s_ticker:
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parser.add_argument('-t', "--ticker", action="store", dest="s_ticker", default=s_ticker, help='Stock ticker')
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else:
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parser.add_argument('-t', "--ticker", action="store", dest="s_ticker", required=True, help='Stock ticker')
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try:
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(ns_parser, l_unknown_args) = parser.parse_known_args(l_args)
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except SystemExit:
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print("")
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return [s_ticker, s_start]
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return
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if l_unknown_args:
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print(f"The following args couldn't be interpreted: {l_unknown_args}")
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try: # Get stock data
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ts = TimeSeries(key=cfg.API_KEY_ALPHAVANTAGE, output_format='pandas')
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df_stock, d_stock_metadata = ts.get_daily(symbol=ns_parser.s_ticker, outputsize='full')
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try:
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df_ta = ta.sma(df_stock, timeperiod=ns_parser.n_time_period).dropna()
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plot_stock_ta(df_stock, s_ticker, df_ta, f"{ns_parser.n_time_period} SMA")
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except:
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print("ERROR! Try again!")
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print("Check that: 1. The ticker symbol exists and is valid")
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print(" 2. Less than 5 AlphaVantage requests have been made in 1 minute")
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print(" 3. The API_KEY is (still) valid")
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return [s_ticker, s_start]
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# Update TA ticker
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s_ticker = ns_parser.s_ticker
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# Update TA starting point if needed
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if ns_parser.s_start_date:
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s_start = ns_parser.s_start_date
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# Slice dataframe from the starting date YYYY-MM-DD selected
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if s_start:
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df_stock = df_stock[ns_parser.s_start_date:]
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df_ta = ta.sma(df_stock['4. close'], timeperiod=ns_parser.n_time_period).dropna()
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plot_stock_ta(df_stock, d_stock_metadata['2. Symbol'], df_ta, f"{ns_parser.n_time_period} SMA")
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return [s_ticker, s_start]
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print("")
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return
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# ----------------------------------------------------- EMA -----------------------------------------------------
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def ema(l_args, s_ticker, s_start):
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def ema(l_args, s_ticker, df_stock):
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parser = argparse.ArgumentParser(prog='ema',
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description=""" The Exponential Moving Average is a staple of technical
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analysis and is used in countless technical indicators. In a Simple Moving
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@@ -73,45 +47,19 @@ def ema(l_args, s_ticker, s_start):
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in the data. """)
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parser.add_argument('-p', "--period", action="store", dest="n_time_period", type=check_positive, default=20,
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help='Number of data points used to calculate each moving average value.')
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parser.add_argument("-s", "--start", type=valid_date, dest="s_start_date",
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help="The starting date (format YYYY-MM-DD) of the stock")
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if s_ticker:
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parser.add_argument('-t', "--ticker", action="store", dest="s_ticker", default=s_ticker, help='Stock ticker')
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else:
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parser.add_argument('-t', "--ticker", action="store", dest="s_ticker", required=True, help='Stock ticker')
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try:
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(ns_parser, l_unknown_args) = parser.parse_known_args(l_args)
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except SystemExit:
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print("")
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return [s_ticker, s_start]
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return
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if l_unknown_args:
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print(f"The following args couldn't be interpreted: {l_unknown_args}")
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try: # Get stock data
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ts = TimeSeries(key=cfg.API_KEY_ALPHAVANTAGE, output_format='pandas')
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df_stock, d_stock_metadata = ts.get_daily(symbol=ns_parser.s_ticker, outputsize='full')
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try:
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df_ta = ta.ema(df_stock, timeperiod=ns_parser.n_time_period).dropna()
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plot_stock_ta(df_stock, s_ticker, df_ta, f"{ns_parser.n_time_period} EMA")
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except:
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print("ERROR! Try again!")
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print("Check that: 1. The ticker symbol exists and is valid")
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print(" 2. Less than 5 AlphaVantage requests have been made in 1 minute")
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print(" 3. The API_KEY is (still) valid")
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return [s_ticker, s_start]
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# Update TA ticker
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s_ticker = ns_parser.s_ticker
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# Update TA starting point if needed
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if ns_parser.s_start_date:
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s_start = ns_parser.s_start_date
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# Slice dataframe from the starting date YYYY-MM-DD selected
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if s_start:
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df_stock = df_stock[ns_parser.s_start_date:]
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df_ta = ta.ema(df_stock['4. close'], timeperiod=ns_parser.n_time_period).dropna()
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plot_stock_ta(df_stock, d_stock_metadata['2. Symbol'], df_ta, f"{ns_parser.n_time_period} EMA")
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return [s_ticker, s_start]
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print("")
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return
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