mirror of
https://github.com/OpenBB-finance/OpenBB.git
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212 lines
8.9 KiB
Python
212 lines
8.9 KiB
Python
import argparse
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from alpha_vantage.sectorperformance import SectorPerformances
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from alpha_vantage.timeseries import TimeSeries
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import config_bot as cfg
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import pandas as pd
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from stock_market_helper_funcs import *
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# ----------------------------------------------- PRINT_HELP ----------------------------------------------------------
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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(" 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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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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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("\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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'''
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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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'''
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# ---------------------------------------------------- SECTORS ----------------------------------------------------
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def sectors(l_args):
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parser = argparse.ArgumentParser(prog='sectors', description='Plot sectors performance')
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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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sp = SectorPerformances(key=cfg.API_KEY_ALPHAVANTAGE, output_format='pandas')
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df_sectors, d_meta_data = sp.get_sector()
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df_sectors['Rank A: Real-Time Performance'].plot(kind='bar')
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plt.title('Real Time Performance (%) per Sector')
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plt.tight_layout()
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plt.grid()
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plt.show()
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print("")
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# ---------------------------------------------------- GAINERS ----------------------------------------------------
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def gainers(l_args):
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parser = argparse.ArgumentParser(prog='gainers',
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description='Show top ticker gainers from Yahoo Finance')
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parser.add_argument('-n', "--num", action="store", dest="n_gainers", type=int, default=5, choices=range(1, 25),
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help='Number of the top gainers stocks to retrieve (default 5)')
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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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df_gainers = pd.read_html('https://finance.yahoo.com/screener/predefined/day_gainers')[0]
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print(df_gainers.head(ns_parser.n_gainers).to_string(index=False))
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print("")
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# ----------------------------------------------------- LOAD -----------------------------------------------------
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def load(l_args, s_ticker, s_start, s_interval, df_stock):
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parser = argparse.ArgumentParser(prog='load', description=""" Load a stock in order to perform analysis""")
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parser.add_argument('-t', "--ticker", action="store", dest="s_ticker", required=True, help="Stock ticker")
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parser.add_argument('-s', "--start", type=valid_date, dest="s_start_date", help="The starting date (format YYYY-MM-DD) of the stock")
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parser.add_argument('-i', "--interval", action="store", dest="n_interval", type=int, default=1440, choices=[1,5,15,30,60], help="Intraday stock minutes")
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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, s_interval, df_stock]
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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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# Update values:
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s_ticker = ns_parser.s_ticker
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s_start = ns_parser.s_start_date
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s_interval = str(ns_parser.n_interval)+'min'
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try:
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ts = TimeSeries(key=cfg.API_KEY_ALPHAVANTAGE, output_format='pandas')
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# Daily
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if s_interval == "1440min":
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df_stock, d_stock_metadata = ts.get_daily_adjusted(symbol=ns_parser.s_ticker, outputsize='full')
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# Intraday
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else:
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df_stock, d_stock_metadata = ts.get_intraday(symbol=ns_parser.s_ticker, outputsize='full', interval=s_interval)
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except:
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print("Either the ticker or the API_KEY are invalids. Try again!")
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return [s_ticker, s_start, s_interval, df_stock]
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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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# Slice dataframe from the starting date YYYY-MM-DD selected
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df_stock = df_stock[ns_parser.s_start_date:]
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print(f"Loading {s_intraday} {s_ticker} stock with starting period {s_start.strftime('%Y-%m-%d')} for analysis.\n")
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else:
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print(f"Loading {s_intraday} {s_ticker} stock for analysis.\n")
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return [s_ticker, s_start, s_interval, df_stock]
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# ----------------------------------------------------- VIEW -----------------------------------------------------
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def view(l_args, s_ticker, s_start, s_interval, df_stock):
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parser = argparse.ArgumentParser(prog='view', description='Visualise historical data of a stock. An alpha_vantage key is necessary.')
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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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parser.add_argument('-s', "--start", type=valid_date, dest="s_start_date", help="The starting date (format YYYY-MM-DD) of the stock")
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parser.add_argument('-i', "--interval", action="store", dest="n_interval", type=int, default=0, choices=[1,5,15,30,60], help="Intraday stock minutes")
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parser.add_argument("--type", action="store", dest="n_type", type=check_positive, default=5, # in case it's daily
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help='1234 corresponds to types: 1. open; 2. high; 3.low; 4. close; while 14 corresponds to types: 1.open; 4. close')
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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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# Update values:
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s_ticker = ns_parser.s_ticker
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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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# A new interval intraday period was given
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if ns_parser.n_interval != 0:
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s_interval = str(ns_parser.n_interval)+'min'
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try:
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ts = TimeSeries(key=cfg.API_KEY_ALPHAVANTAGE, output_format='pandas')
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# Daily
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if s_interval == "1440min":
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df_stock, d_stock_metadata = ts.get_daily_adjusted(symbol=s_ticker, outputsize='full')
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# Intraday
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else:
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df_stock, d_stock_metadata = ts.get_intraday(symbol=s_ticker, outputsize='full', interval=s_interval)
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except:
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print("Either the ticker or the API_KEY are invalids. Try again!")
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return
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# Slice dataframe from the starting date YYYY-MM-DD selected
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df_stock = df_stock[s_start:]
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# Daily
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if s_interval == "1440min":
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# The default doesn't exist for intradaily data
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ln_col_idx = [int(x)-1 for x in list(str(ns_parser.n_type))]
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if 4 not in ln_col_idx:
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ln_col_idx.append(4)
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# Check that the types given are not bigger than 4, as there are only 5 types (0-4)
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if len([i for i in ln_col_idx if i > 4]) > 0:
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print("An index bigger than 4 was given, which is wrong. Try again")
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return
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# Append last column of df to be filtered which corresponds to: 6. Volume
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ln_col_idx.append(5)
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# Intraday
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else:
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# The default doesn't exist for intradaily data
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if ns_parser.n_type == 5:
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ln_col_idx = [3]
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else:
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ln_col_idx = [int(x)-1 for x in list(str(ns_parser.n_type))]
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# Check that the types given are not bigger than 3, as there are only 4 types (0-3)
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if len([i for i in ln_col_idx if i > 3]) > 0:
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print("An index bigger than 3 was given, which is wrong. Try again")
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return
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# Append last column of df to be filtered which corresponds to: 5. Volume
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ln_col_idx.append(4)
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# Plot view of the stock
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plot_view_stock(df_stock.iloc[:, ln_col_idx], ns_parser.s_ticker)
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