def main():
parser = argparse.ArgumentParser()
parser.add_argument("action", choices=["backtest", "trade"])
args = parser.parse_args()
if args.action == "backtest":
backtest.backtest()
if args.action == "trade":
trade.trade()
def run():
stk_pairs = strategy.filter_pairs(dataFrame, sequence=FILTER_SEQ, number=n)
global resDataFrame
resDataFrame = trade.trade(tb, m, open_lim, loss_lim, g, U, dataFrame,
values, stk_pairs, M)
utils.xprint(os.linesep + 'Trade processed successfully!')
def process_cycle(monograph, graph):
cycle = collect_negative_cycle(graph)
if cycle != None:
logs = trade(graph, monograph, cycle)
logger.write(logs)
#json_io.save(graph)
#csv_io.save(graph)
time.sleep(1)
time.sleep(2)
def __init__(self):
self.data_handler = datahandler_factory.data_handler_factory(
).get_data_handler()
self.reporter = reporter_factory.reporter_factory().get_reporter()
self.utility = utility.utility()
self.trades = {}
pair_list = config.PAIR_LIST.split()
for pair in pair_list:
self.trades[pair] = trade.trade(pair)
def initial(self):
'''每天初始化设置
'''
logger.info("[INITIAL]:start initial !!!!!")
logger.info("[INITIAL]:try to create connect... ")
self.connect()
self.trader = trade(UserID=self.userid,api=self.api,mock=False,server=self.server)
logger.info("[INITIAL]:connect successful!")
self.trading = self.judgetradeday()
logger.info("[INITIAL]:initial finished !!!!!")
def market(numberOfAgents, numberOfGoods, utilityExponents, endownments, adj,
quantum):
m = numberOfAgents
n = numberOfGoods
agents = []
for i in range(0, m):
u = walrasian.cobbDouglas(np.array([utilityExponents[i, :]]))
g = goods.Goods(np.array([endownments[i, :]]), np.zeros((1, n)))
a = agent.Agent(i, g, u)
a.setAdj(adj)
agents.append(a)
net = network.Network(agents, adj)
netAfterTrade = trade.trade(net, quantum, 100)
return netAfterTrade
def initial(self):
'''每天初始化设置
'''
logger.info("[INITIAL]:start initial !!!!")
if not self.istradeday:
self.trading = False
return
self.trading = True
logger.info("[INITIAL]:try to create connect... ")
self.connect()
self.trader = trade(UserID=self.userid,
api=self.api,
mock=self.mock,
server=self.server)
logger.info("[INITIAL]:connect successful!")
self.set_number() #设置手数
logger.info("[INITIAL]:initial finished !!!!!")
def initial(self):
'''每天初始化设置
'''
logger.info("[INITIAL]:start initial !!!!!!")
if not self.istradeday:
self.trading = False
return
self.trading = True
logger.info("[INITIAL]:try to create connect... ")
self.connect()
self.trader = trade(UserID=self.userid,api=self.api,mock=self.mock,server=self.server)
logger.info("[INITIAL]:connect successful!")
logger.info("[INITIAL]:initial account info...")
self.updatetotal() #更新账户总资金
self.set_permoney() #设置单个品种资金上限
logger.info("[INITIAL]:set per product money limit:{}".format(self.permoney))
self.set_instrument() #设置交易股票和手数
logger.info("[INITIAL]:set stock list succcessful !!!")
logger.info("[INITIAL]:initial finished!!!!!!")
def main():
cnx = mysql.connector.connect(user='******',
password='******',
host='192.168.0.16',
database='gekkoTests')
startingDate = datetime(2018, 7, 24)
# startingDate.date.replace()
dateDelta = 30
currencyToTrade = 'ETH'
assetToTrade = 'V'
candle_Size_Minutes = 15
warmup_Size_Minutes = 55
tradeExchange = 'binance'
Initial_Assets = 100
Initial_Currency = 100
strat = 'McKee_EMA_RSI_Strat_Stoploss'
trader = trade(startingDate, dateDelta, currencyToTrade, assetToTrade,
candle_Size_Minutes, warmup_Size_Minutes, tradeExchange,
Initial_Assets, Initial_Currency, strat, cnx)
#trader.run(True)
#trader.Initial_Assets = 100
#trader.Initial_Currency = 0
#trader.run(False)
while True:
trader.start_date = trader.start_date - timedelta(dateDelta)
trader.asset = 'EOS'
trader.run(False)
trader.asset = 'ZRX'
trader.run(False)
trader.asset = 'TRX'
trader.run(True)
TD = 4 # today
H = 5
L = 6
NUM = 7
plt.rcParams['animation.ffmpeg_path'] = u'.\\ffmpeg.exe'
# filen = '601318.XSHG.txt'
filen = 'lL0.txt'
fig = plt.figure()
ax = fig.add_subplot(111)
dohlc = data_ohlc(filen, True)
trd = trade()
plts = list(range(PLTS.NUM))
maxs = []
mins = []
csv = log_csv(filen, ['D', 'P'], False)
opened = [False, False]
seq = []
class V:
summit_range = 15
open_percentage = 0.5
waiting_for_input = False
user.keepalive()
account_flag = flag.flag()
limit = zxb_limit.zxb_limit(-2.31)
#添加trade
if ed.is_tradetime_now():
file_name = '/home/way/signal/chicang'
file_name1 = '/home/way/signal/zhenfu'
# with open(file_name) as f:
# yiyue = str(f.readlines()[0])
m = multiprocessing.Process(target=account_info,args=(account_flag,))
m.start()
if account_flag.read_flag() == 2:
chiyou_feed = feed.feed('chicang')
chicang_trade = trade.trade(chiyou_feed.load(), user)
print('chiyou')
p=multiprocessing.Process(target=chiyou, args=(chicang_trade, limit))
p.start()
elif account_flag.read_flag() in (4,8):
# with open(file_name1) as f:
# yiyue = str(f.readlines()[0])
# s = stockpool.Stockpool()
#
# eryuedata = s.load(table=yiyue, day=120)
#
# base_info, data = tradable()
#
# zhenfu = cser.zhenfu(base_info, eryuedata)
def play1():
object = trade.trade()
print object.eyes
print object.trade()
# coding=utf-8
from appium import webdriver
from time import sleep
from homepage import home
from market import market
from trade import trade
from news import news
desired_caps = {
'platformName': 'iOS',
'noReset': True,
'platformVersion': '10.3',
"deviceName": "iPhone 6s Plus",
"bundleId": "com.lanyilive.YXFuture",
"udid": "6eaec690714d9d23c386339e0c07268109d9fabc",
"automationName": "XCUITest"
}
driver = webdriver.Remote('http://localhost:4723/wd/hub', desired_caps)
sleep(2)
x = driver.get_window_size()['width']
y = driver.get_window_size()['height']
home(driver, x, y)
market(driver)
trade(driver)
news(driver, x, y)
from Param import Param
from model import model
from predict import predict
import dataHelper as dh
from trade import trade
# BEGIN
for i in range(len(Param.filenames)):
if Param.remodel:
model(file_number=i)
else:
# Fetch data to ensure proper scalers are available
train_X = dh.get_training_input(Param.filenames[i])
train_Y = dh.get_training_output(Param.filenames[i])
# END if
predictions = predict(file_number=i)
predictions = dh.get_column(Param.col_to_trade_on, predictions)
profit = trade(predictions, file_number=i)
print("Profit for model " + str(i) + ": " + str(profit))
# END for
else:
btypes.append(0)
scress.append(isscre)
counts.append(count)
amounts.append(cent.balance)
stores.append(cent.store)
sumAmount = float(
cent.balance) + float(cent.store) * float(close_prices[i])
sumAmounts.append(sumAmount)
return btypes, scress, counts, amounts, stores, sumAmounts
amount = 10000
start = ''
end = ''
tcode = sys.argv[1]
if len(sys.argv) > 2:
amount = sys.argv[2]
if len(sys.argv) > 3:
start = sys.argv[3]
if len(sys.argv) > 4:
end = sys.argv[4]
cent = trade(tcode, begin=start, end=end, balance=amount)
df = cent.data
df['buy'], df['scress'], df['counts'], df['amounts'], df['store'], df[
'sumAmount'] = fitter(df)
df['date'] = numpy.array(df.index)
print(df.to_json(orient='records'))
try:
if api.connect(ip, 7709):
return
except:
pass
connect(api)
if __name__ == '__main__':
userid = os.environ.get('userid', "test1")
buylist = eval(os.environ.get('buylist', "[]"))
selllist = eval(os.environ.get('selllist', "[]"))
query = os.environ.get("query", False)
trader = trade(UserID=userid, api=api, mock=True)
accountinfo, holdlists = trader.position()
if query:
logger.info(accountinfo.to_dict('records'))
logger.info(holdlists.to_dict('records'))
else:
if holdlists.shape[0] > 0:
holdlists.set_index("证券代码", inplace=True)
for stock, number in buylist:
logger.info("buy: {} number:{}".format(stock, number))
trader.buy(stock, int(number))
for stock, number in selllist:
try:
h_number = holdlists.ix[stock]["参考持股"]
import numpy as np
import csv
from trade import trade
from dqn_agent import DQNAgent
from datetime import datetime as dt
if __name__ == "__main__":
# parameters
n_epochs = 10000
# environment, agent
env = trade()
agent = DQNAgent(env.enable_actions)
#histrical data
f = open('./data/USDJPY1_201810.csv', 'r')
reader = csv.reader(f)
header = next(reader)
HisData = []
for row in reader:
HisData.append(row)
#log file
fout = open('./logs/train_log.txt', 'w')
# variables
prft = 0
for e in range(n_epochs):
cnt = 0
loss = 0
ship = UNI.ships[current_player.ship_current]
print(f"Cargo: {ship['cargo']}\n Wallet: {current_player.wallet}")
elif command == 'S':
utils.scanner(current_player.current_node, UNI)
elif command == 'P':
node_data = UNI.graph.node[current_player.current_node]
station = node_data.get('station', None)
if station is not None:
selection = ''
print("\n<T> Trade at this Port\n<Q> Quit, nevermind")
while selection.upper() not in ['T', 'Q']:
selection = input('Enter your choice? ')
if selection.upper() == 'T':
trade(UNI, current_player, station)
elif command == '?':
print("\n This is the help menu. P to trade at a Port, Q to quit, V to view jump history. C to show your wallet and cargo. S to use the scanner on planets and stars.")
else:
print("Invalid command!")
pickle.dump(UNI, open(UNI_PATH, 'wb'))
r.publish('GAMEWORLD', '{} leaves the game...'.format(current_player.name))
p.unsubscribe()
print(UNI.players)
#t = bitcoin_ticker(content.decode("utf-8"))
#t.update();
# TO DEBUG
#pdb.set_trace()
link_thicker = "https://www.mercadobitcoin.com.br/api/trades/"
c = pycurl.Curl()
c.setopt(c.URL,link_thicker)
storage = io.BytesIO()
c.setopt(c.WRITEFUNCTION,storage.write)
c.perform()
c.close()
content = storage.getvalue().decode("utf-8")
tr = trade(content)
link_thicker = "https://www.mercadobitcoin.com.br/api/orderbook/"
c = pycurl.Curl()
c.setopt(c.URL,link_thicker)
storage = io.BytesIO()
c.setopt(c.WRITEFUNCTION,storage.write)
c.perform()
c.close()
content = storage.getvalue().decode("utf-8")
order = orderbook(content)
link_thicker = "https://www.mercadobitcoin.com.br/api/trades_litecoin/"
c = pycurl.Curl()
c.setopt(c.URL,link_thicker)
storage = io.BytesIO()
def main():
try:
print("\n>> CoinAnalyze v0.7 by cloud <<\n\n")
sendMessageTelegram("Coin Analyzer Bot v0.7 Started")
##### TRADE MODULE#######
trading = 0
tr = trade()
if trading == 1:
print("Trading module : On")
sendMessageTelegram("Trading module : On")
end = 0
else:
print("Trading module : Off")
sendMessageTelegram("Trading module : Off")
#########################
#We initialize the different timer
timer1hnext = (datetime.now() + timedelta(seconds=3600)).hour
timer20mnnext = (datetime.now() + timedelta(seconds=60))
while (int(str(timer20mnnext.minute)) % 20) != 0:
timer20mnnext = timer20mnnext + timedelta(seconds=60)
market = coinmarketcap()
binancecoin = binance()
listcoin = []
ticker = {}
ticker = binancecoin.checkTicker()
symbol = binancecoin.getListSymbol(ticker)
#We create an object by coin
for c in symbol:
coinC = coin(c)
listcoin.append(coinC)
while True:
time.sleep(1)
timer = datetime.now()
####### EVERY 1H ###############
if timer.hour == timer1hnext:
print(timer)
if trading == 1:
msg = tr.summaryTrade()
print(msg)
sendMessageTelegram(msg)
timer1hnext = (datetime.now() + timedelta(seconds=3600)).hour
### We check General coinmarketcap every 60mn
market.checkGlobal()
checkmarket = market.analyze_total_market_cap_eur()
#Analyze Market
msg = ""
msg = msg + printcheckmarket(market, checkmarket)
msg = msg + "\n"
checkmarket = market.analyze_bitcoin_percentage_of_market_cap()
msg = msg + printbtcdominance(market, checkmarket)
print(msg)
sendMessageTelegram(msg)
msg = ""
####### EVERY 20mn ###############
## New Symbol check
timer20mn = datetime.now()
period = ['1h', '4h', '1d']
if ((int(timer20mn.minute) % 20) == 0) and (timer20mnnext.minute
== timer20mn.minute):
#if 1 == 1:
if trading == 1:
period = ['1h', '4h', '1d']
timer20mnnext = (datetime.now() + timedelta(seconds=12000))
####### ACTION ###################
for p in period:
msg = ""
#On récupère les infos de chaque coin sur une période de 252 et on les ajoute à chaque coin pour gérer les alertes
listAllValues = []
listAllValues = binancecoin.checkAllInfoValues(p)
for c in listAllValues:
for x in listcoin:
end, msg = tr.checkEndTrade()
if end == 1:
print(msg)
sendMessageTelegram(msg)
trading = 0
period = ['4h', '1d']
if c['symbol'] == x.getSymbol():
x.setValues(c)
if trading == 1:
stoploss = tr.stopLoss(x)
if stoploss == 1:
msg = "STOP LOSS (5%) for " + x.getSymbol(
)
print(msg)
sendMessageTelegram(msg)
if p != '1h':
#RSI must be the first test to set RSI for the PRS test
#RSI alert check
rsi = x.rsiAlert(p)
if rsi != 0:
msg = printRSIAlert(
x.getSymbol(), rsi, p)
print(msg)
#sendMessageTelegram(msg)
msg = ""
#RSI DIV Alert
rsidiv, price = x.rsiDivAlert(p)
if rsidiv != 0:
msg = msg + printRSIDIVAlert(
x.getSymbol(), rsidiv, p, price)
print(msg)
sendMessageTelegram(msg)
msg = ""
#if trading == 1:
# restrade,msg = tr.buysell(rsidiv, x.getSymbol(), price)
# print msg
# sendMessageTelegram(msg)
#MACD alert check
macd, price = x.macdAlert(p)
if macd != 0:
msg = printMACDAlert(
x.getSymbol(), macd, p, price)
print(msg)
#sendMessageTelegram(msg)
msg = ""
#PRS Alert
prs, price = x.prsAlert(p)
if prs != 0:
msg = printAlert(
"PRS", x.getSymbol(), prs, p,
price)
print(msg)
#sendMessageTelegram(msg)
msg = ""
#if trading == 1:
# restrade,msg = tr.buysell(prs, x.getSymbol(), price)
# print msg
# sendMessageTelegram(msg)
#Nightou Alert
nightou, price = x.nightouAlert(p)
if nightou != 0:
msg = msg + printNightouAlert(
x.getSymbol(), p, price)
print(msg)
sendMessageTelegram(msg)
msg = ""
if trading == 1:
restrade, msg = tr.buysell(
nightou, x.getSymbol(), price)
print(msg)
sendMessageTelegram(msg)
#ADX Alert
adx, price = x.adxAlert(p)
if adx != 0:
msg = msg + printAlert(
"ADX", x.getSymbol(), adx, p,
price)
print(msg)
#sendMessageTelegram(msg)
msg = ""
#if trading == 1:
# restrade,msg = tr.buysell(adx, x.getSymbol(), price)
# print msg
# sendMessageTelegram(msg)
#CCI Alert
cci, price = x.cciAlert(p)
if cci != 0:
msg = msg + printAlert(
"CCI", x.getSymbol(), cci, p,
price)
print(msg)
#sendMessageTelegram(msg)
msg = ""
#if trading == 1:
# restrade,msg = tr.buysell(cci, x.getSymbol(), price)
# print msg
# sendMessageTelegram(msg)
#CLOUD Alert
cloud, price = x.cloudStrategy(p)
if cloud != 0:
msg = msg + printAlert(
"CLOUD", x.getSymbol(), cloud, p,
price)
print(msg)
sendMessageTelegram(msg)
msg = ""
if trading == 1:
restrade, msg = tr.buysell(
cloud, x.getSymbol(), price)
print(msg)
sendMessageTelegram(msg)
#EMA Alert
ema, price = x.emaStrategy(p)
if ema != 0:
msg = msg + printAlert(
"EMA", x.getSymbol(), ema, p, price)
print(msg)
sendMessageTelegram(msg)
msg = ""
if trading == 1:
restrade, msg = tr.buysell(
ema, x.getSymbol(), price)
print(msg)
sendMessageTelegram(msg)
####### NEW SYMBOL #########
ticker = binancecoin.checkTicker()
newsymbol = []
newsymbol = binancecoin.getNewSymbol()
for c in newsymbol:
coinC = coin(c)
listcoin.append(coinC)
msg = printNewSymbol(newsymbol)
if msg != "":
sendMessageTelegram(msg)
print(msg)
except (KeyboardInterrupt, SystemExit):
sendMessageTelegram("Maintenance, I'll be back soon")
return 0
timesd3mo, movingsd3mo = f.movingsd(priceratio, longavgtime, timeratio)
timeavg3mo, movingavg3mo = f.movingavg(priceratio, longavgtime,
timeratio)
timeavg5d, movingavg5d = f.movingavg(priceratio, shortavgtime,
timeratio)
low1, high1 = f.sdbounds(movingavg3mo, movingsd3mo, uppersigma)
zscoree = f.zscore(movingavg5d, movingavg3mo, movingsd3mo)
when, whenlist = f.whentotrade(zscoree, timeavg3mo, cor252, uppersigma)
#print("Cointigration Value: "+str(f.cointigration(price1,price2)))
#instantiates trade objects
trades = []
for tradetime in when:
location = np.sign(zscoree[f.indexoftime(timeavg3mo, tradetime)])
trades.append(
trade.trade(price1, price2, time1, tradetime, location))
trades[len(trades) - 1].set_inputamount(1000)
totalreturns = 0
for q in range(len(trades)):
starttime = trades[q].get_starttime()
startindex = f.indexoftime(timeavg3mo, starttime)
timezscore = timeavg3mo[startindex:]
zscoreupdate = zscoree[startindex:]
sigbounds = lowersigma
for qq in range(len(zscoreupdate) - 2):
trades[q].exittrade(timezscore[qq + 2])
if trades[q].get_totalreturns() < -100:
#print("RETURNS BELOW -100")
starttt = trades[q].get_starttime()
#print("index: "+str(q))
# -*- coding: utf-8 -*-
"""
Created on Mon May 9 21:56:05 2016
@author: way
"""
import sys
sys.path.append("/data/pyquant/signal")
import flag
import zxb_limit
import easytrader as et
from easydealutils import time as ed
import trade
import time
import os
from strategy import cser
import feed
import multiprocessing
from tradable import *
user = et.use("ht")
user.prepare("/data/pyquant/ht.json")
account_flag = flag.flag()
chiyou_feed = feed.feed("chicang")
chicang_trade = trade.trade(chiyou_feed.load(), user)
chicang_trade.stop()
account_flag.set_flag(4)
# 根据macd值买入优化v1.0.0 2020.7.14
# 步骤：
# 1.获取 MACD DEA，DIFF
# 2.如果 MACD>0 --其实也就是20日均线开始向上掉头，判断是否可以买入
# 3.以第一次买入价制定买卖价格11个档位 -- 30日均线 向上5个，向下五个 各以5%为阶梯
# 4.循环判断买入条件
# 1 MACD>0
# 2 b 股价在30日均线1%以内
# 3 股价在当前档位没有持仓
# 5. 卖出条件
# 1 股价超过持仓最低档卖出价
buylogs = []
selllogs = []
plandf = pd.DataFrame()
tradecenter = trade()
def makeplan(price):
# 创建购买计划
logging.info("创建购买计划:%s",price)
input = pd.Series(np.logspace(-9, 1, 10, base=1.05)*price)
tem = (pd.Series(np.arange(24, 14, -1))*0.01)
out = (tem +1)*input
global plandf
plandf = pd.DataFrame({ "input": input, "out": out, "store":0, "tem":tem})
logging.info("购买计划创建完毕\n%s",plandf)
def getbuyprice():
# 获取购买价格
return plandf[plandf.store == 0].input.max()
def init(args):
states, last_datapoints = get_initial_states(args.sequence_length,
args.interval_length)
# Restore trained model
session = tf.Session()
ckpt_file = ''
if not args.model_file:
ckpt_file = tf.train.latest_checkpoint(MODEL_DIR)
else:
ckpt_file = args.model_file
meta_graph = tf.train.import_meta_graph(ckpt_file + '.meta')
meta_graph.restore(session, ckpt_file)
graph = tf.get_default_graph()
inputs = graph.get_tensor_by_name(trainer.INPUT_PLACEHOLDER + ':0')
labels = graph.get_tensor_by_name(trainer.LABEL_PLACEHOLDER + ':0')
pred = graph.get_tensor_by_name(trainer.OUTPUT_LAYER + ':0')
db = MySQLdb.connect(db=constants.MYSQL_DB_NAME,
host=constants.MYSQL_HOST,
user=api_access_data.MYSQL_USER,
passwd=api_access_data.MYSQL_PASSWD)
db.autocommit(True)
while (True):
predictions = []
for (product_idx, (state, product)) in enumerate(zip(states,
PRODUCTS)):
crypto_labels = np.zeros((1, args.sequence_length))
crypto_labels.fill(product_idx)
prediction = session.run([pred], {
inputs: state,
labels: crypto_labels
})
prediction = np.squeeze(prediction).item() * 100
predictions.append((prediction, product))
print('Product: %s Trend prediction: %f%%' % (product, prediction))
if args.test:
print('In test mode: not performing trades. Check grafana for '
'performance metrics')
else:
# Process the predictions in order of magnitude of change
predictions.sort(key=lambda x: abs(x[0]))
for (prediction, product) in predictions:
cursor = db.cursor()
trade.trade(prediction, product, cursor)
time.sleep(args.interval_length * 60)
# Get new data
for (idx, product) in enumerate(PRODUCTS):
# Prevent rate limiting
if (idx > 0):
time.sleep(1)
new_datapoint = get_last_x_interval_data(product, 1,
args.interval_length)
new_datapoint = np.squeeze(new_datapoint)
new_datapoint, last_datapoints[idx] = (
(new_datapoint / last_datapoints[idx]) - 1, new_datapoint)
current_trend = new_datapoint[-2]
new_datapoint = new_datapoint.reshape(1, 1, new_datapoint.shape[0])
states[idx] = np.concatenate(
(states[idx][:, 1:, :], new_datapoint), axis=1)
current_trend *= 100
prediction = list(filter(lambda x: x[1] == product,
predictions))[0][0]
write_prediction_to_influxdb(prediction, current_trend, product)
print('Product: %s Acutal trend: %f%%; Last prediction: %f%%' %
(product, current_trend, prediction))
def recordTrade(self, timeStamp, quantity, buySellIndicator, price):
trades = trade(timeStamp, quantity, buySellIndicator, price)
self.record.append(trades)
def main(argv):
horizontal_line = "-------------------------"
print(horizontal_line * 2)
print("DAT602-assignment3 crypto-trading demo.")
print("Please wait while initializing the database...")
gdax = gw.gdax_websocket()
gdax.start()
time.sleep(1)
ledger = Ledger(100000000)
print("$" + str(ledger.get_current_cash()) +
" available to start trading.")
print(horizontal_line * 2)
fini = False
while not fini:
menu()
choice = input(">>>>> Please select the menu: \n>")
if choice == "6": # Quit
fini = True
gdax.stop()
elif choice == "5": # Show P/L Chart
print(horizontal_line * 3)
print("<<P/L Line Chart>>")
print(horizontal_line * 3)
try:
pl_data = ledger.get_pl_cache()
pldisp.pl_display(pl_data)
print("Should the graph fails to load in the browser,")
print(
"Please click: https://plot.ly/~silverrainb/10/vwap-executedprice-total-pl-cash/"
)
print(horizontal_line * 3)
except KeyError:
print(
"No transactions have been performed to display the history"
)
print(horizontal_line * 3)
elif choice == "4": # Show P/L Records
print(horizontal_line * 3)
print("<<P/L Records>>")
print(horizontal_line * 3)
try:
pl_data = ledger.get_pl_cache()
print(pl_data)
except KeyError:
print(
"No transactions have been performed to display the history"
)
elif choice == "3": # Show P/L
print(horizontal_line * 3)
print("<<P/L>>")
print("Please hold while calculating forecast...")
print(horizontal_line * 3)
ledger.update_positions(gdax)
print(horizontal_line * 3)
elif choice == "2": # Show Blotter
print(horizontal_line * 3)
print("<<Blotter>>")
print(horizontal_line * 3)
try:
blotter = ledger.get_blotter()
print(blotter)
except KeyError:
print(
"No transactions have been performed to display the history"
)
print(horizontal_line * 3)
elif choice == "1": # Trade
trade.trade(ledger, gdax)
print(">>>>> Goodbye!")
