def test_RealTimeBTC():
from pricing_engine.engine import realtime_price
ticker = 'BTC'
results = realtime_price(ticker)
run_time = datetime.now()
if results is None:
health = False
price = None
error_message = 'Realtime Price returned None'
try:
price = results['price']
health = True
error_message = None
except Exception as e:
health = False
price = None
error_message = f"Realtime Price returned an error: {e}"
data = {
'health': health,
'price': price,
'error_message': error_message,
'run_time': run_time
}
filename = 'status_realtime_btc.pkl'
pickle_it(action='save', filename=filename, data=data)
return (data)
def realtime_btc():
try:
fx_details = fx_rate()
fx_r = {
'cross': fx_details['symbol'],
'fx_rate': fx_details['fx_rate']
}
fx_r['btc_usd'] = realtime_price("BTC", fx='USD')['price']
fx_r['btc_fx'] = fx_r['btc_usd'] * fx_r['fx_rate']
except Exception as e:
logging.warn(
f"There was an error while getting realtime prices. Error: {e}")
fx_r = 0
return json.dumps(fx_r)
def positions_json():
# Get all transactions and cost details
# This serves the main page
try:
dfdyn, piedata = positions_dynamic()
btc_price = realtime_price("BTC")['price'] * fx_rate()['fx_rate']
dfdyn = dfdyn.to_dict(orient='index')
except Exception:
dfdyn = piedata = None
btc_price = 0
try:
btc = realtime_price("BTC")['price']
except TypeError:
btc = 0
if not btc:
btc = 0
json_dict = {
'positions': dfdyn,
'piechart': piedata,
'user': current_app.fx,
'btc': btc_price
}
return simplejson.dumps(json_dict, ignore_nan=True)
def price_and_position():
# Gets price and position data for a specific ticker
ticker = request.args.get("ticker")
fx = request.args.get("fx")
if fx is None:
fx = fx_rate()['base']
# Gets Price and market data first
realtime_data = realtime_price(ticker=ticker, fx=fx)
historical_data = historical_prices(ticker=ticker, fx=fx)
historical_data.index = historical_data.index.astype('datetime64[ns]')
filemeta = (ticker + "_" + fx + ".meta")
historical_meta = pickle_it(action='load', filename=filemeta)
price_chart = historical_data[["close_converted", "close"]].copy()
# dates need to be in Epoch time for Highcharts
price_chart.index = price_chart.index.astype('datetime64[ns]')
price_chart.index = (price_chart.index -
datetime(1970, 1, 1)).total_seconds()
price_chart.index = price_chart.index * 1000
price_chart.index = price_chart.index.astype(np.int64)
price_chart = price_chart.to_dict()
price_chart_usd = price_chart["close"]
price_chart = price_chart["close_converted"]
# Now gets position data
df = positions()
if isinstance(df, pd.DataFrame):
if not df.empty:
df = df[df['trade_asset_ticker'] == ticker]
df_trades = transactions_fx()
position_chart = None
if isinstance(df_trades, pd.DataFrame):
df_trades = df_trades[df_trades['trade_asset_ticker'] == ticker]
if not df_trades.empty:
df_trades = df_trades.sort_index(ascending=True)
df_trades['trade_quantity_cum'] = df_trades[
'trade_quantity'].cumsum()
position_chart = df_trades[["trade_quantity_cum"]].copy()
# dates need to be in Epoch time for Highcharts
position_chart.index = position_chart.index.astype(
'datetime64[ns]')
position_chart.index = (position_chart.index -
datetime(1970, 1, 1)).total_seconds()
position_chart.index = position_chart.index * 1000
position_chart.index = position_chart.index.astype(np.int64)
position_chart = position_chart.to_dict()
position_chart = position_chart["trade_quantity_cum"]
if ticker == 'GBTC':
from pricing_engine.engine import GBTC_premium
from parseNumbers import parseNumber
GBTC_price = parseNumber(realtime_data['price'])
GBTC_fairvalue, GBTC_premium = GBTC_premium(GBTC_price)
else:
GBTC_premium = GBTC_fairvalue = None
return render_template("warden/price_and_position.html",
title="Ticker Price and Positions",
current_app=current_app,
current_user=fx_rate(),
realtime_data=realtime_data,
historical_data=historical_data,
historical_meta=historical_meta,
positions=df,
ticker=ticker,
fx=fx,
price_chart=price_chart,
price_chart_usd=price_chart_usd,
position_chart=position_chart,
GBTC_premium=GBTC_premium,
GBTC_fairvalue=GBTC_fairvalue)
def find_data(ticker):
notes = None
last_up_source = None
source = None
try:
# Parse the cryptocompare data
price = multi_price["RAW"][ticker][fx]["PRICE"]
# GBTC should not be requested from multi_price as there is a
# coin with same ticker
if ticker in ['GBTC', 'MSTR', 'TSLA', 'SQ']:
raise KeyError
price = float(price)
high = float(multi_price["RAW"][ticker][fx]["HIGHDAY"])
low = float(multi_price["RAW"][ticker][fx]["LOWDAY"])
chg = multi_price["RAW"][ticker][fx]["CHANGEPCT24HOUR"]
mktcap = multi_price["DISPLAY"][ticker][fx]["MKTCAP"]
volume = multi_price["DISPLAY"][ticker][fx]["VOLUME24HOURTO"]
last_up_source = multi_price["RAW"][ticker][fx]["LASTUPDATE"]
source = multi_price["DISPLAY"][ticker][fx]["LASTMARKET"]
last_update = datetime.now()
except (KeyError, TypeError):
# Couldn't find price with CryptoCompare. Let's try a different source
# and populate data in the same format [aa = alphavantage]
try:
single_price = realtime_price(ticker)
if single_price is None:
raise KeyError
price = clean_float(single_price['price'])
last_up_source = last_update = single_price['time']
try:
chg = parseNumber(single_price['chg'])
except Exception:
chg = 0
try:
source = last_up_source = single_price['source']
except Exception:
source = last_up_source = '-'
try:
high = single_price['high']
low = single_price['low']
mktcap = volume = '-'
except Exception:
mktcap = high = low = volume = '-'
except Exception:
try:
# Finally, if realtime price is unavailable, find the latest
# saved value in historical prices
# Create a price class
price_class = historical_prices(ticker, fx)
if price_class is None:
raise KeyError
price = clean_float(
price_class.df['close_converted'].iloc[0])
high = '-'
low = '-'
volume = '-'
mktcap = chg = 0
source = last_up_source = 'Historical Data'
last_update = price_class.df.index[0]
except Exception as e:
price = high = low = chg = mktcap = last_up_source = last_update = volume = 0
source = '-'
logging.error(
f"There was an error getting the price for {ticker}." +
f"Error: {e}")
if ticker.upper() == 'BTC':
nonlocal btc_price
btc_price = price
# check if 24hr change is indeed 24h or data is old, if so 24hr change = 0
try:
checker = last_update
if not isinstance(checker, datetime):
checker = parser.parse(last_update)
if checker < (datetime.now() - timedelta(days=1)):
chg = 0
except Exception:
pass
return price, last_update, high, low, chg, mktcap, last_up_source, volume, source, notes
def single_price(ticker):
return (realtime_price(ticker)['price'], datetime.now())
def test_realtime_parsed(self):
ticker_list = ['BTC', 'GBTC', 'ETH', 'IBM', 'MSTR', 'TSLA']
for ticker in ticker_list:
results = realtime_price(ticker)['price']
self.assertIsNotNone(results,
f'Could not get realtime price for {ticker}')