mirror of
https://github.com/OpenBB-finance/OpenBB.git
synced 2026-11-10 11:21:12 +00:00
87 lines
3.3 KiB
Python
87 lines
3.3 KiB
Python
import config_bot as cfg
|
|
import argparse
|
|
import datetime
|
|
from datetime import datetime
|
|
from stock_market_helper_funcs import *
|
|
import config_bot as cfg
|
|
import pandas as pd
|
|
import matplotlib.pyplot as plt
|
|
from pandas.plotting import register_matplotlib_converters
|
|
register_matplotlib_converters()
|
|
|
|
from prediction_techniques import sma
|
|
from prediction_techniques import knn
|
|
from prediction_techniques import lr
|
|
|
|
# -----------------------------------------------------------------------------------------------------------------------
|
|
def print_prediction(s_ticker, s_start, s_interval):
|
|
""" Print help """
|
|
|
|
s_intraday = (f'Intraday {s_interval}', 'Daily')[s_interval == "1440min"]
|
|
|
|
if s_start:
|
|
print(f"\n{s_intraday} Stock: {s_ticker} (from {s_start.strftime('%Y-%m-%d')})")
|
|
else:
|
|
print(f"\n{s_intraday} Stock: {s_ticker}")
|
|
|
|
print("\nPrediction Techniques:")
|
|
print(" help show this prediction techniques menu again")
|
|
print(" q quit this menu, and shows back to main menu")
|
|
print(" quit quit to abandon program")
|
|
print("")
|
|
print(" sma simple moving average")
|
|
print(" knn k-Nearest Neighbors")
|
|
print(" lr linear regression")
|
|
print("")
|
|
|
|
|
|
# ---------------------------------------------------- MENU ----------------------------------------------------
|
|
def pred_menu(df_stock, s_ticker, s_start, s_interval):
|
|
|
|
# Add list of arguments that the prediction techniques parser accepts
|
|
pred_parser = argparse.ArgumentParser(prog='technical_analysis', add_help=False)
|
|
pred_parser.add_argument('cmd', choices=['help', 'q', 'quit',
|
|
'sma', 'knn', 'lr'])
|
|
|
|
print_prediction(s_ticker, s_start, s_interval)
|
|
|
|
# Loop forever and ever
|
|
while True:
|
|
# Get input command from user
|
|
as_input = input('> ')
|
|
|
|
# Parse prediction techniques command of the list of possible commands
|
|
try:
|
|
(ns_known_args, l_args) = pred_parser.parse_known_args(as_input.split())
|
|
|
|
except SystemExit:
|
|
print("The command selected doesn't exist\n")
|
|
continue
|
|
|
|
if ns_known_args.cmd == 'help':
|
|
print_prediction(s_ticker, s_start, s_interval)
|
|
|
|
elif ns_known_args.cmd == 'q':
|
|
# Just leave the FA menu
|
|
return False
|
|
|
|
elif ns_known_args.cmd == 'quit':
|
|
# Abandon the program
|
|
return True
|
|
|
|
# ------------------------------------------ SIMPLE MOVING AVERAGE ------------------------------------------
|
|
elif ns_known_args.cmd == 'sma':
|
|
sma.simple_moving_average(l_args, s_ticker, s_interval, df_stock)
|
|
|
|
# ------------------------------------------ k NEAREST NEIGHBORS ------------------------------------------
|
|
elif ns_known_args.cmd == 'knn':
|
|
knn.k_nearest_neighbors(l_args, s_ticker, s_interval, df_stock)
|
|
|
|
# --------------------------------------------- LINEAR REGRESSION ---------------------------------------------
|
|
elif ns_known_args.cmd == 'lr':
|
|
lr.linear_regression(l_args, s_ticker, s_interval, df_stock)
|
|
|
|
# ------------------------------------------------------------------------------------------------------------
|
|
else:
|
|
print("Command not recognized!")
|