database-automation/ohlc/update_ohlc_data.py

import pandas as pd
import schedule
import time

from database.ohlc import insert
from datetime import datetime, date, timedelta
from iqfeed import get_daily_data, get_historical_data, minutes

# Symbols and timeframes to process.
# TODO: Store in database to make re-deployment unnecessary.
symbols_and_timeframes = [
    ('SPX.XO', '5m'),
    ('SPX.XO', '1d'),
    ('SPY', '5m'),
    ('SPY', '1d'),
    ('VIX.XO', '5m'),
    ('VIX.XO', '1d'),
    ('VVIX.XO', '5m'),
    ('VVIX.XO', '1d'),
    ('VIX1D.XO', '1d'),
    ('VIX9D.XO', '1d'),
    ('VIX3M.XO', '1d'),
    ('VIX6M.XO', '1d'),
    ('VIX1Y.XO', '1d')
]

def update_ohlc_data():
    for symbol, timeframe in symbols_and_timeframes:
        yesterday = date.today() - timedelta(days=1)
        if timeframe == '1d':
            data = get_daily_data(symbol, 
                start_date = datetime.combine(yesterday, datetime.min.time()), 
                end_date = datetime.combine(yesterday, datetime.max.time()))
        else: # Assuming minutes for now.
            data = get_historical_data(symbol, minutes(int(timeframe[:-1])), 
                start_date = datetime.combine(yesterday, datetime.min.time()), 
                end_date = datetime.combine(yesterday, datetime.max.time()))

        data['Symbol'] = symbol
        data['Timeframe'] = timeframe
        data['Timestamp'] = pd.to_datetime(data['Date'])
        data['Date'] = data['Timestamp'].dt.date
        data = data.rename(columns={
            'Period Volume': 'Volume'
        })
        data = data[['Symbol', 'Date', 'Timeframe', 'Timestamp', 'Open', 'High', 'Low', 'Close', 'Volume']]

        insert(data)

if __name__ == '__main__':
    schedule.every().day.at('01:00', 'America/Los_Angeles').do(update_ohlc_data)
    while True:
        schedule.run_pending()
        time.sleep(1)