import requests, ring, os from decouple import config import numpy as np from api.models import Order market_cache = {} @ring.dict(market_cache, expire=3) # keeps in cache for 3 seconds def get_exchange_rates(currencies): """ Params: list of currency codes. Checks for exchange rates in several public APIs. Returns the median price list. """ APIS = config("MARKET_PRICE_APIS", cast=lambda v: [s.strip() for s in v.split(",")]) api_rates = [] for api_url in APIS: try: # If one API is unavailable pass if "blockchain.info" in api_url: blockchain_prices = requests.get(api_url).json() blockchain_rates = [] for currency in currencies: try: # If a currency is missing place a None blockchain_rates.append( float(blockchain_prices[currency]["last"])) except: blockchain_rates.append(np.nan) api_rates.append(blockchain_rates) elif "yadio.io" in api_url: yadio_prices = requests.get(api_url).json() yadio_rates = [] for currency in currencies: try: yadio_rates.append(float( yadio_prices["BTC"][currency])) except: yadio_rates.append(np.nan) api_rates.append(yadio_rates) except: pass if len(api_rates) == 0: return None # Wops there is not API available! exchange_rates = np.array(api_rates) median_rates = np.nanmedian(exchange_rates, axis=0) return median_rates.tolist() def get_lnd_version(): # If dockerized, return LND_VERSION envvar used for docker image. # Otherwise it would require LND's version.grpc libraries... try: lnd_version = config("LND_VERSION") return lnd_version except: pass # If not dockerized and LND is local, read from CLI try: stream = os.popen("lnd --version") lnd_version = stream.read()[:-1] return lnd_version except: return "" robosats_commit_cache = {} @ring.dict(robosats_commit_cache, expire=3600) def get_commit_robosats(): commit = os.popen('git log -n 1 --pretty=format:"%H"') commit_hash = commit.read() return commit_hash premium_percentile = {} @ring.dict(premium_percentile, expire=300) def compute_premium_percentile(order): queryset = Order.objects.filter( currency=order.currency, status=Order.Status.PUB).exclude(id=order.id) print(len(queryset)) if len(queryset) <= 1: return 0.5 order_rate = float(order.last_satoshis) / float(order.amount) rates = [] for similar_order in queryset: rates.append( float(similar_order.last_satoshis) / float(similar_order.amount)) rates = np.array(rates) return round(np.sum(rates < order_rate) / len(rates), 2)