def addHashRate():
a = getSlushPool()
hr = float(a["hashrate"])
hr /= 1000000
hr = round(hr, 2)
r = float(a["confirmed_reward"])
r = float(Bitfinex().get_current_price()) * r
r = round(r, 2)
d = Label(text=("Hashrate: " + str(hr) + " Th/s"),
bd=2,
fg="white",
bg="black",
anchor="nw",
width=50,
font=("Helvetica Neue light", 15))
d.place(x=LEFT_SIDE, y=31)
m = Label(text=("Reward: $" + str(r)),
bd=2,
fg="white",
bg="black",
anchor="nw",
width=50,
font=("Helvetica Neue light", 15))
m.place(x=LEFT_SIDE, y=61)
list_of_Labels.append(d)
list_of_Labels.append(m)
def print_price(now):
global last_price
"""main price function"""
try:
price = Bitfinex().get_current_price()
except Exception as e:
return
price = int(round(price))
tick_color = 4 if price >= last_price else 2
usd_color = 5 if price >= last_price else 3
last_price = price
time_line = str(price)
time_array = ["" for i in range(0, 7)]
for char in time_line:
char_array = glyph[char]
for row in range(0, len(char_array)):
time_array[row] += char_array[row]
total_x = 65
offset_x = int(round((total_x - len(time_array[0])) / 2))
for y in range(0, len(time_array)):
for x in range(0, len(time_array[y])):
char = time_array[y][x]
color = 1 if char == " " else tick_color
addstr(y, x + offset_x, " ", curses.color_pair(color))
addstr(6, offset_x + len(time_array[0]), 'USD',
curses.color_pair(usd_color))
def create_exchange(exchange):
if exchange == "liqui":
from exchanges.liqui import Liqui
return Liqui()
if exchange == "hitbtc":
from exchanges.hitbtc import Hitbtc
return Hitbtc()
if exchange == "bittrex":
from exchanges.bittrex import Bittrex
return Bittrex()
if exchange == "binance":
from exchanges.binance import Binance
return Binance()
if exchange == "bithumb":
from exchanges.bithumb import Bithumb
return Bithumb()
if exchange == "bitfinex":
from exchanges.bitfinex import Bitfinex
return Bitfinex()
if exchange == "poloniex":
from exchanges.poloniex import Poloniex
return Poloniex()
if exchange == "bitstamp":
from exchanges.bitstamp import Bitstamp
return Bitstamp()
if exchange == "huobi":
from exchanges.huobi import Huobi
return Huobi()
if exchange == "wex":
from exchanges.wex import Wex
return Wex()
if exchange == "yobit":
from exchanges.yobit import Yobit
return Yobit()
def bitfinex():
try:
bitfinex = Bitfinex().get_current_price()
print(rdata.hset("prices", "bitfinex:btc-usd", bitfinex))
print(rdata.hset("prices", "bitfinex:lastupdate", int(time.time())))
except:
print("Failed to load from Bitfinex")
async def buy(ctx, *, amount):
price = Bitfinex().get_current_price()
if amount.isdigit():
amount = int(amount)
payable = price * amount
await ctx.send(
f'Please send {payable} UnBelievaBoat currency to me and type b!check'
)
else:
await ctx.send('no')
def getFlights(request):
flights = Flights('Zt0AY8d5B9UA7ERLccCjiGF6l6gpcUoS')
if request.method == 'POST':
form = FlightForm(request.POST)
if form.is_valid():
data = form.cleaned_data
resp = flights.extensive_search(
origin=data['origin'],
destination=data['destination'],
#departure_date = '2018-05-15--2018-05-30'
departure_date=data['startdate'])
#print(resp)
#return HttpResponse(resp['results'][0]['price'])
resp['bitcoin'] = str(Bitfinex().get_current_price())
return HttpResponse(json.dumps(resp))
def populate(self):
self.exchanges = [
Bancor(self.base, self.term),
Tidex(self.base, self.term, self.depth),
Huobi(self.base, self.term, self.depth),
Bittrex(self.base, self.term),
Bitfinex(self.base, self.term, self.depth),
]
for e in self.exchanges:
if e.bid != None:
self.bids.append([e.bid, e.depth, e.name, e.stamp])
if e.ask != None:
self.asks.append([e.ask, e.depth, e.name, e.stamp])
self.bids = sorted(self.bids, reverse=True)
self.asks = sorted(self.asks)
def main():
ctx = zmq.Context()
socket = ctx.socket(zmq.REP)
socket.bind("tcp://*:%s" % ZMQ_PORT)
# 거래소 객체 생성
# bitstamp = Bitstamp(pairs='BTC/USD', depth=10)
kraken = Kraken(pairs='BTC/USD', depth=10)
bitfinex = Bitfinex(pairs='BTC/USD')
# upbit = Upbit(pairs='BTC/KRW')
threads(kraken, bitfinex)
# 오더북 담을곳
order1 = {}
order2 = {}
while True:
message = json.loads(socket.recv())
# 거래소 이름 검사
try:
if 'Kraken' == message['name']:
order1 = message
if 'Bitfinex' == message['name']:
order2 = message
# order1과 order2에 값이 있을 때
if (order1 and order2):
pprint(order1)
# case1, case2 = calculate(order1, order2)
# 크라켄 ASK 가격 1,2,3 ... N / 비트파이넥스 BID 가격 1,2,3 ... N
# 비트파이넥스 BID 가격 1.2.3 ... N / 크라켄 ASK 가격 1.2.3 ... N
# 각 주문인덱스 끼리 교차계산, 인덱스 N이 5인경우
# BestOffer부터 5틱 즉, 10가지 계산을 순차가 아닌 동시성으로 처리
# 이는 TCP 통신으로 누락이 있을 수 있어 BestOffer만 계산하면 위험하기때문
# print(f"Case1: {case1[:3]}\nCase2: {case2[:3]}\n")
socket.send_json(message)
except TypeError:
continue
def getBtc():
return ("The Value of Bitcoin is: " + str(round(Bitfinex().get_current_price(),2)) + "USD")
inv_yhat = str(inv_yhat[:, 0])
print(inv_yhat)
# test_y = test_y.reshape((len(test_y), 1))
# inv_y = np.concatenate((test_y, test_X[:, -4:]), axis=1)
# inv_y = scaler.inverse_transform(inv_y)
# inv_y = inv_y[:, 0]
#print(inv_y)
#print(inv_yhat.shape)
#df = pd.DataFrame({'forecast': inv_yhat})
from datetime import date
import datetime
today = date.today()
tomorrow = today + datetime.timedelta(days=1)
from exchanges.bitfinex import Bitfinex
price = Bitfinex().get_current_price()
df=pd.read_csv("input_to_chart.csv")
df = df.drop(df.columns[0], axis=1)
df.iloc[-1, df.columns.get_loc('Actual_Price')] = price
inv_yhat = inv_yhat[1:-1]
new_row = {'Date': tomorrow , 'Predicted_Price' : inv_yhat}
df=df.append(new_row, ignore_index=True)
#print(df)
# df.reset_index(drop=True, inplace=True)
# print(df)
df.to_csv('input_to_chart.csv')
def interact_timer(bot, update, top_p, mx, temperature):
while True:
global BUY
global bitold
global dec
global mode
global money
global b
if BUY == True:
money = dec
decimal = float(Bitfinex().get_current_price())
one = decimal - bitold
two = (one / decimal) # * 100
mon = money * two
money = mon + money
up = str(money)
update.message.reply_text('Current money is: ' + up)
print(money)
print(dec)
print(bitold)
print("BUY SIGNAL CALC")
if BUY == False:
dec = money
up = str(money)
update.message.reply_text('Current money is: ' + up)
print(money)
print(dec)
print(bitold)
print("HOLD SIGNAL CALC")
model_name = '1558M'
nsamples = 1
batch_size = 1
top_k = 0
models_dir = 'models'
tex = scrape()
raw_text = str(tex)
#############################################
if mode == False:
cat = len(raw_text.split(" "))
length = cat
if length > 300:
while length > 300:
raw_text = raw_text.split(':', 1)[-1]
length = len(raw_text.split(" "))
cat = length
tx = float(top_p)
cax = float(cat)
cay = float(mx)
caz = float(cax * cay)
ta = ((1 - tx) / caz)
top_p = ((tx) + (ta))
if top_p > 1:
top_p = 1
if top_p < 0.005:
top_p = 0.005
#############################################
update.message.reply_text('Computing for 6 generations...')
cache = []
for x in range(0, 6):
seed = random.randint(1431655765, 2863311530)
models_dir = os.path.expanduser(os.path.expandvars(models_dir))
if batch_size is None:
batch_size = 1
assert nsamples % batch_size == 0
enc = encoder.get_encoder(model_name, models_dir)
hparams = model.default_hparams()
with open(os.path.join(models_dir, model_name,
'hparams.json')) as f:
hparams.override_from_dict(json.load(f))
if length is None:
length = hparams.n_ctx // 2
elif length > hparams.n_ctx:
raise ValueError(
"Can't get samples longer than window size: %s" %
hparams.n_ctx)
with tf.Session(graph=tf.Graph()) as sess:
context = tf.placeholder(tf.int32, [batch_size, None])
np.random.seed(seed)
tf.set_random_seed(seed)
output = sample.sample_sequence(hparams=hparams,
length=length,
context=context,
batch_size=batch_size,
temperature=temperature,
top_k=top_k,
top_p=top_p)
saver = tf.train.Saver()
ckpt = tf.train.latest_checkpoint(
os.path.join(models_dir, model_name))
saver.restore(sess, ckpt)
context_tokens = enc.encode(raw_text)
generated = 0
for _ in range(nsamples // batch_size):
out = sess.run(
output,
feed_dict={
context:
[context_tokens for _ in range(batch_size)]
})[:, len(context_tokens):]
for i in range(batch_size):
generated += 1
text = enc.decode(out[i])
pika = text
stripes = pika.encode(encoding=sys.stdout.encoding,
errors='ignore')
tigger = stripes.decode("utf-8")
meow = str(tigger)
analyzer = SentimentIntensityAnalyzer()
vs = analyzer.polarity_scores(meow)
data = vs.get('compound')
cache.append(data)
score = str(vs)
print("==========")
print("{:-<65} {}".format(meow, str(vs)))
print("==========")
lent = str(length)
print("Length: " + lent)
print("==========")
print("Output: " + meow)
print("==========")
tps = str(top_p)
print("top_p out: " + tps)
print("==========")
tpa = str(tx)
print("top_p in: " + tpa)
print("==========")
sess.close()
print(cache)
sent = str(cache)
rounded = mean(cache)
rou = str(rounded)
update.message.reply_text('Sentiment of generations are:' + rou)
if BUY == True:
money = dec
decimal = float(Bitfinex().get_current_price())
one = decimal - bitold
two = (one / decimal) # * 100
mon = money * two
money = mon + money
up = str(money)
print(money)
print(dec)
print(bitold)
print("BUY SIGNAL CALC")
if BUY == False:
dec = money
up = str(money)
print(money)
print(dec)
print(bitold)
print("HOLD SIGNAL CALC")
if rounded < 0:
BUY = True
if rounded > 0:
BUY = False
if BUY == True:
if b == False:
bitold = float(Bitfinex().get_current_price())
b = True
update.message.reply_text('Buy Signal...')
print(money)
print(dec)
print(bitold)
print("BUY SIGNAL")
if BUY == False:
b = False
update.message.reply_text('Hold Signal...')
print(money)
print(dec)
print(bitold)
print("HOLD SIGNAL")
# Temperature (refer to gpt-2 documentation)
temperature = 1
# Multuplier/Divider for top_p/length calc.(The more words the more token learning when positive, top_p decreases.)
# Adjust in small increments. The target is between 0.6 and 1 for top_p.
mx = 1
# Virtual USD
USD = 100
# End settings
mode = False
user = ""
running = False
BUY = False
dec = float(USD)
money = float(USD)
bitold = float(Bitfinex().get_current_price())
b = False
def scrape():
arr = []
for tweet in get_tweets('Bitcoin', pages=1):
a = str(tweet['time'])
b = str(tweet['text'])
if "http" not in b:
if ".com" not in b:
arr.append([a, b])
sort = sorted(arr, key=lambda x: time.strptime(x[0], "%Y-%m-%d %H:%M:%S"))
out = str(sort).strip('[]')
out1 = out.replace("',", ":")
out2 = out1.replace("']", "")
# login to the email server
server = smtplib.SMTP(smtp_server, smtp_port)
server.starttls()
server.login(email_user, email_password)
# send email
server.sendmail(email_from, email_to, msg)
server.quit()
# define buy and sell threshholds for Bitcoin
buy_thresh = 4400
sell_thresh = 4400
# get Bitcoin prices
btc_sell_price = Bitfinex().get_current_bid()
btc_buy_price = Bitfinex().get_current_ask()
# Trigger Buy email if buy price is lower then threadhold
if btc_buy_price < buy_thresh:
email_msg = """
Bitcoin Buy Price is %s which is lower then
threshhold price of %s.
Good time to buy!""" % (btc_buy_price, buy_thresh)
trigger_email(email_msg)
# Trigger sell email if sell price is higher then threashold
if btc_sell_price > sell_thresh:
from bitrex_custom.biterx_client import BittrexClient, BittrexConfig
from koinex.koinex_client import KoinexClient, KoinexConfig
from exchanges.bitfinex import Bitfinex
CONFIG = {"BCH": "BTC-BCC", "ETH": "BTC-ETH", "XRP": "BTC-XRP"}
transaction_mode = "XRP"
VALUE = ["BTC"]
if __name__ == '__main__':
koinex_client = KoinexClient(KoinexConfig.VALUE)
koinex_market_values = koinex_client.get_market_value()
for value in VALUE:
koinex_value = koinex_market_values.get(value)
bitfinex_client = Bitfinex()
current_btc_value = bitfinex_client.get_current_price()
inr_btc_value = int(current_btc_value) * 64.52
print(koinex_value, inr_btc_value)
def fetch():
global price, fetched_at
price = round(Bitfinex().get_current_price(), 2)
fetched_at = datetime.now()
print(f' fetched new price: {price} ({fetched_at})')
import itertools
from exchanges.poloniex import Poloniex
from exchanges.bitfinex import Bitfinex
pn = Poloniex()
bf = Bitfinex()
book_pn = pn.query_order_book('BTC', 'ETH')
book_bf = bf.query_order_book('ETH', 'BTC')
rows_pn = zip(book_pn['bids'], book_pn['asks'])[:10]
rows_bf = zip(book_bf['bids'], book_bf['asks'])[:10]
length = min(len(rows_bf), len(rows_pn))
print '{:>18s}{:>18s}{:>18s}{:>18s}{:>18s}{:>18s}{:>18s}{:>18s}'.format(
'PN BID PRICE', 'PN BID AMNT', 'PN ASK PRICE', 'PN ASK AMNT',
'BF BID PRICE', 'BF BID AMNT', 'BF ASK PRICE', 'BF ASK AMNT',
)
for i in range(length):
print '{:18.6f}{:18.6f}{:18.6f}{:18.6f}{:18.6f}{:18.6f}{:18.6f}{:18.6f}'.format(
float(rows_pn[i][0][0]), float(rows_pn[i][0][1]), float(rows_pn[i][1][0]), float(rows_pn[i][1][1]),
float(rows_bf[i][0][0]), float(rows_bf[i][0][1]), float(rows_bf[i][1][0]), float(rows_bf[i][1][1]),
)
if book_pn['asks'][0][0] < book_bf['bids'][0][0]:
print 'Buy in PN and Sell in BF!'
if book_bf['asks'][0][0] < book_pn['bids'][0][0]:
print 'Buy in BF and Sell in PN!'
import time
from exchanges.bitfinex import Bitfinex
import subprocess as s
# url_inr = "https://live.zebapi.com/api/v2/ticker?currencyCode=INR"
# url_usd = "https://live.zebapi.com/api/v2/ticker?currencyCode=USD"
url_ltc = "https://api.cryptowat.ch/markets/bitfinex/ltcusd/price"
# max_num = 820000
# min_num = 800000
# exchange_rate_orig = 74.46
curr_price_orig = int(Bitfinex().get_current_price())
min_ltc = max_ltc = 0
min_btc = max_btc = 0
init_flag = 1
curr_price_ltc = 125
while (1):
sound_flag = 0
# response_inr = urllib.urlopen(url_inr)
# response_usd = urllib.urlopen(url_usd)
response_ltc = urllib.urlopen(url_ltc)
# data_inr = json.loads(response_inr.read())
# data_usd = json.loads(response_usd.read())
from django.contrib.auth.models import User
from django.shortcuts import render, redirect
from django.template import loader
from django.http import HttpResponse
from django.utils.decorators import method_decorator
from django.views import generic
from django.views.decorators.csrf import csrf_exempt
from django.views.generic import TemplateView
from itertools import chain
from exchanges.bitfinex import Bitfinex
from exchanges.coindesk import CoinDesk
from exchange.forms import ProfileForm, UserForm
from exchange.models import Transactions, Wallets, Contacts, Profile
# Fetching current price at server launch to avoid lagging
current_price_usd = Bitfinex().get_current_price()
# common class context
class WebsiteCommonMixin(generic.base.ContextMixin):
def get_context_data(self, **kwargs):
context = super(WebsiteCommonMixin, self).get_context_data(**kwargs)
try:
context.update(
dict(contact_list=Contacts.objects.filter(
friend=User.objects.filter(
id=self.request.user.id)).order_by('-created_at')[:],
transaction_list=Transactions.objects.filter(
walletFrom=Wallets.objects.filter(
owner=self.request.user.id)).order_by(
'-created_at')[:5],
def commands():
print(
"------------------------------------\nCommands: \n'query' to fetch the answer to a question\n'time' to fetch the time \n'bitcoin' to fetch the current bitcoin price in dollars\n'speak' to make the computer say a message\n-------------------------------"
)
#Main game loop
command = 1
commands()
while True:
typed = input()
#Fetches and speaks bitcoin price
if typed == "bitcoin" and command == 1:
variable = Bitfinex().get_current_price()
print(variable)
engine.say(str(variable))
engine.runAndWait()
commands()
#Fetches and speaks time
elif typed == "time" and command == 1:
now = datetime.now()
current_time = now.strftime("%H:%M")
hour = now.strftime("%H")
if int(hour) < 13:
ampm = " AM"
ampmsay = " Ay Em."
else:
async def value(ctx):
price = Bitfinex().get_current_price()
priceembed = discord.Embed(title=f'**Price of 1 BTC:** {price}',
type='rich',
url='https://www.bitfinex.com/')
await ctx.send(embed=priceembed)