52 lines
1.7 KiB
Python
52 lines
1.7 KiB
Python
import pandas as pd
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import schedule
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import time
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from database.ohlc import insert
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from datetime import datetime, date, timedelta
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from iqfeed import get_daily_data, get_historical_data, minutes
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# Symbols and timeframes to process.
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# TODO: Store in database to make re-deployment unnecessary.
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symbols_and_timeframes = [
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('SPX.XO', '5m'),
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('SPX.XO', '1d'),
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('SPY', '5m'),
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('SPY', '1d'),
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('VIX.XO', '5m'),
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('VIX.XO', '1d'),
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('VIX1D.XO', '1d'),
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('VIX9D.XO', '1d'),
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('VIX3M.XO', '1d'),
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('VIX6M.XO', '1d'),
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('VIX1Y.XO', '1d')
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]
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def update_ohlc_data():
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for symbol, timeframe in symbols_and_timeframes:
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yesterday = date.today() - timedelta(days=1)
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if timeframe == '1d':
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data = get_daily_data(symbol,
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start_date = datetime.combine(yesterday, datetime.min.time()),
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end_date = datetime.combine(yesterday, datetime.max.time()))
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else: # Assuming minutes for now.
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data = get_historical_data(symbol, minutes(int(timeframe[:-1])),
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start_date = datetime.combine(yesterday, datetime.min.time()),
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end_date = datetime.combine(yesterday, datetime.max.time()))
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data['Symbol'] = symbol
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data['Timeframe'] = timeframe
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data['Timestamp'] = pd.to_datetime(data['Date'])
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data['Date'] = data['Timestamp'].dt.date
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data = data.rename(columns={
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'Period Volume': 'Volume'
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})
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data = data[['Symbol', 'Date', 'Timeframe', 'Timestamp', 'Open', 'High', 'Low', 'Close', 'Volume']]
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insert(data)
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if __name__ == '__main__':
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schedule.every().day.at('01:00', 'America/Los_Angeles').do(update_ohlc_data)
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while True:
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schedule.run_pending()
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time.sleep(1) |