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}')