20230209_gcp_2.py

def make_investment_decision():
    import pandas as pd
    import os
    import json
    IDLE_HOURS_BEFORE_NEXT_PURCHASE = float(os.environ.get('BOT_ONE_IDLE_HOURS_BEFORE_NEXT_PURCHASE'))
    BOLLINGER_LOW_INVEST_EUR = float(os.environ.get('BOT_ONE_INVEST_EUR') or 0)
    MY_CRYPTO_CURRENCIES = json.loads(os.environ['BOT_ONE_CRYPTO_CURRENCIES'])
    MY_QUOTE_CURRENCY = os.environ.get('QUOTE_CURRENCY')
    TRADING_VIEW_SYMBOLS = json.loads(os.environ['TRADING_VIEW_SYMBOLS'])
    df_historic_data = cb_get_enhanced_history(MY_QUOTE_CURRENCY, MY_CRYPTO_CURRENCIES)
    df_historic_data = df_historic_data.sort_values(['date'], ascending=True)
    df_trading_view_signals = get_trading_view_signals(TRADING_VIEW_SYMBOLS)
    df_24hstats = cb_get_24h_data(MY_QUOTE_CURRENCY, MY_CRYPTO_CURRENCIES)
    server_time_now = cb_get_server_time()
    order_results = []
    for currency in MY_CRYPTO_CURRENCIES:
        product_id = currency+'-'+MY_QUOTE_CURRENCY
        current_value = df_24hstats.loc[currency]['last']
        trading_view_recommendation = df_trading_view_signals.loc[currency]['1min_recommendation']
        bb_low = df_historic_data.query('granularity == \'DAILY\' and base_currency == @currency').tail(1)['bb_low'].iloc[0]
        last_buy_fill_date = cb_get_last_buy_fill_date(product_id)
        idle_hours_reached = True
        if last_buy_fill_date is not None:
            last_fill_delta = ((server_time_now - last_buy_fill_date).days*86400 + (server_time_now - last_buy_fill_date).seconds)/3600
            if (last_fill_delta < IDLE_HOURS_BEFORE_NEXT_PURCHASE):
                idle_hours_reached = False
        if (current_value < bb_low and idle_hours_reached and (trading_view_recommendation == 'BUY' or trading_view_recommendation == 'STRONG_BUY')):
            order_id = cb_create_market_order(product_id=product_id, quote_size=BOLLINGER_LOW_INVEST_EUR)
            fire_doc_id = fire_create_order_record(doc_id=order_id,doc_data={'buy_order_id': order_id, 'bb_low': bb_low, 'trading_view_recommendation': trading_view_recommendation, 'sell_order_id': ''})
            order_results.append(f'Order now: {product_id}, price: {current_value}{MY_QUOTE_CURRENCY}, amount: {BOLLINGER_LOW_INVEST_EUR}{MY_QUOTE_CURRENCY} and order id {order_id} and Firestore doc id {fire_doc_id}')
        else:
            order_results.append(f'No order placed for {currency}; current value: {current_value}{MY_QUOTE_CURRENCY}; bb low: {bb_low}{MY_QUOTE_CURRENCY}; signal: {trading_view_recommendation}; last trade was on {last_buy_fill_date} ({idle_hours_reached})')
    return pd.DataFrame(order_results)