storage_client = storage.Client()
bucket = storage_client.get_bucket('derek-algo-trading-bucket')
blob = bucket.blob('alpaca-api-key.txt')
api_key = blob.download_as_text()
blob = bucket.blob('alpaca-secret-key.txt')
secret_key = blob.download_as_text()
base_url = 'https://paper-api.alpaca.markets'
api = REST(api_key, secret_key, base_url, 'v2')
# Check if the market is open today
nyc = timezone('America/New_York')
today = datetime.today().astimezone(nyc)
today_str = today.strftime('%Y-%m-%d')
today = datetime.isoformat(pd.Timestamp(datetime.today().astimezone(nyc)))
try:
calendar = api.get_calendar(start=today, end=today)[0]
except Exception as e:
print(e)
print('Market must not be open')
calendar = None
if calendar and calendar.date.strftime('%Y-%m-%d') == today_str:
# Select the swing stocks to buy, sell, and hold
df_buy, df_sell, df_hold = select_swing_stocks()
alert = f'**Daily Swing Trade Alert**\n'
# Sell all stocks in DataFrame
if not df_sell.empty:
df_sell = df_sell.set_index('symbol', drop=True)
print('\nSELLING:')
# Also need to store the results for each day
day_results = {}
# Create a list of dates in between start and end (inclusive)
dates = pd.date_range(start=start_date, end=end_date, freq='B', tz=nyc)
# Trade each day
for date in dates:
print(
f'------------------ {date.strftime("%Y-%m-%d")} ------------------'
)
# Check if market is open on that date
calendar = api.get_calendar(
start=datetime.isoformat(pd.Timestamp(date)),
end=datetime.isoformat(pd.Timestamp(date)))[0]
if calendar.date.strftime("%Y-%m-%d") != date.strftime("%Y-%m-%d"):
print('Market was not open')
print(calendar.date.strftime("%Y-%m-%d"))
print(date.strftime("%Y-%m-%d"))
continue
# Must update position prices before going into the day
# Something that Alpaca handles for you
if len(position_data.keys()) > 0:
for symbol in position_data.keys():
current_open_price = get_open_price(date, symbol)
position_data[symbol]['current_price'] = str(
current_open_price)
position_data[symbol]['market_value'] = str(