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relevant_stocks.py
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relevant_stocks.py
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import investpy
import numpy as np
# import telebot
import socket
import config
from datetime import datetime
from datetime import date
import time
stocks = investpy.stocks.get_stocks(country='russia')['symbol']
def array_to_string(a):
stroka = '['
for i in range(len(a)):
stroka += a[i]
if i != len(a) - 1:
stroka += ' , '
stroka += ']'
return stroka
counter = 0
index = 1
good_stocks = []
current_date = str(date.today().day) + '/' + str(date.today().month) + '/' + str(date.today().year)
a = date.today().month
if a == 1:
from_date = str(date.today().day) + '/' + str(12) + '/' + str(date.today().year - 1)
else:
from_date = str(date.today().day) + '/' + str(date.today().month - 1) + '/' + str(date.today().year)
for stock in stocks:
if counter == 10:
time.sleep(10)
counter = 0
try:
df = investpy.get_stock_historical_data(stock=stock, country='russia', from_date=from_date,
to_date=current_date)
time.sleep(5)
technical_indicators = investpy.technical.technical_indicators(stock, 'russia', 'stock', interval='daily')
country = 'russia'
except:
continue
tech_sell = len(technical_indicators[technical_indicators['signal'] == 'sell'])
tech_buy = len(technical_indicators[technical_indicators['signal'] == 'buy'])
time.sleep(2)
moving_averages = investpy.technical.moving_averages(stock, country, 'stock', interval='daily')
moving_sma_sell = len(moving_averages[moving_averages['sma_signal'] == 'sell'])
moving_sma_buy = len(moving_averages[moving_averages['sma_signal'] == 'buy'])
moving_ema_sell = len(moving_averages[moving_averages['ema_signal'] == 'sell'])
moving_ema_buy = len(moving_averages[moving_averages['ema_signal'] == 'buy'])
if tech_buy < 9 or tech_sell > 2 or moving_sma_buy < 5 or moving_ema_buy < 5:
continue
sma_20 = moving_averages['sma_signal'][2]
sma_100 = moving_averages['sma_signal'][4]
ema_20 = moving_averages['ema_signal'][2]
ema_100 = moving_averages['ema_signal'][4]
print(str(index) + ') ' + 'STOCK =', stock)
print('Tech sell indicators: to buy =', tech_buy, 'of 12; ', 'to sell =', tech_sell, 'of 12')
print('SMA moving averages: to buy =', moving_sma_buy, 'of 6; ', 'to sell =', moving_sma_sell, 'of 6')
print('EMA moving averages: to buy =', moving_ema_buy, 'of 6; ', 'to sell =', moving_ema_sell, 'of 6')
print('SMA_20 =', sma_20, ';', 'SMA_100 =', sma_100, ';', 'EMA_20 =', ema_20, ';', 'EMA_100 =', ema_100)
print('Prices Last Five days of ' + stock + ' =', np.array(df['Close'][-5:][0]), ';', np.array(df['Close'][-5:][1]),
';', np.array(df['Close'][-5:][2]), ';', np.array(df['Close'][-5:][3]), ';', np.array(df['Close'][-5:][4]))
p_1 = abs(1 - df['Close'][-5:][1] / df['Close'][-5:][0])
if df['Close'][-5:][1] >= df['Close'][-5:][0]:
pp_1 = '+' + str(round(p_1 * 100, 2)) + '%'
else:
pp_1 = '-' + str(round(p_1 * 100, 2)) + '%'
p_2 = abs(1 - df['Close'][-5:][2] / df['Close'][-5:][1])
if df['Close'][-5:][2] >= df['Close'][-5:][1]:
pp_2 = '+' + str(round(p_2 * 100, 2)) + '%'
else:
pp_2 = '-' + str(round(p_2 * 100, 2)) + '%'
p_3 = abs(1 - df['Close'][-5:][3] / df['Close'][-5:][2])
if df['Close'][-5:][3] >= df['Close'][-5:][2]:
pp_3 = '+' + str(round(p_3 * 100, 2)) + '%'
else:
pp_3 = '-' + str(round(p_3 * 100, 2)) + '%'
p_4 = abs(1 - df['Close'][-5:][4] / df['Close'][-5:][3])
if df['Close'][-5:][4] >= df['Close'][-5:][3]:
pp_4 = '+' + str(round(p_4 * 100, 2)) + '%'
else:
pp_4 = '-' + str(round(p_4 * 100, 2)) + '%'
print('Percentage +/- of ' + stock + ' =', pp_1, ';', pp_2, ';', pp_3, ';', pp_4, )
print()
index += 1
counter += 1
good_stocks.append(stock)
time.sleep(2)
print('==================================================')
df = investpy.get_currency_cross_historical_data(currency_cross='USD/RUB', from_date=from_date, to_date=current_date)
print('Prices Last Five days of USD/RUB =', np.array(df['Close'][-5:][0]), ';', np.array(df['Close'][-5:][1]),
';', np.array(df['Close'][-5:][2]), ';', np.array(df['Close'][-5:][3]), ';', np.array(df['Close'][-5:][4]))
p_1 = abs(1 - df['Close'][-5:][1] / df['Close'][-5:][0])
if df['Close'][-5:][1] >= df['Close'][-5:][0]:
pp_1 = '+' + str(round(p_1 * 100, 2)) + '%'
else:
pp_1 = '-' + str(round(p_1 * 100, 2)) + '%'
p_2 = abs(1 - df['Close'][-5:][2] / df['Close'][-5:][1])
if df['Close'][-5:][2] >= df['Close'][-5:][1]:
pp_2 = '+' + str(round(p_2 * 100, 2)) + '%'
else:
pp_2 = '-' + str(round(p_2 * 100, 2)) + '%'
p_3 = abs(1 - df['Close'][-5:][3] / df['Close'][-5:][2])
if df['Close'][-5:][3] >= df['Close'][-5:][2]:
pp_3 = '+' + str(round(p_3 * 100, 2)) + '%'
else:
pp_3 = '-' + str(round(p_3 * 100, 2)) + '%'
p_4 = abs(1 - df['Close'][-5:][4] / df['Close'][-5:][3])
if df['Close'][-5:][4] >= df['Close'][-5:][3]:
pp_4 = '+' + str(round(p_4 * 100, 2)) + '%'
else:
pp_4 = '-' + str(round(p_4 * 100, 2)) + '%'
print('Percentage +/- of USD/RUB =', pp_1, ';', pp_2, ';', pp_3, ';', pp_4, )
# telebot_token = # ваш токен
# telegram_id = # ваш id
# bot = telebot.TeleBot(telebot_token)
# otvet = array_to_string(good_stocks)
# bot.send_message(telegram_id, otvet)
# bot.send_message(telegram_id, 'Всего акций: ' + str(len(good_stocks)))