class Trader:
new_table = False
SMA_PERIOD = 20
EMA_PERIOD = 10
def __init__(self,
api_key=None,
api_secret=None,
api_passphrase=None,
ticker_span=100):
self.api_key = api_key
self.api_secret = api_secret
self.api_passphrase = api_passphrase
self.client = Client(api_key,
api_secret,
api_passphrase,
sandbox=False)
self.ticker_span = ticker_span #Number of candlestick data points to acquire
self.kline_data = []
self.historical_data = []
now = int(time.time())
self.kline_data = np.array(
self.client.get_kline_data('BTC-USDT', '1min',
(now - self.ticker_span * 60), now))
self.historical_data = pd.DataFrame(self.kline_data,
columns=[
'TimeStamp', 'Open', 'Close',
'High', 'Low', 'Tx Amount',
'Tx Volume'
])
self.candle_stick = self.kline_data[0] #Most recenr candle stick info
self.update_indicators()
def update_indicators(
self): #Call this to update the CP, SMA, and EMA arrays
self.get_cp()
self.get_sma()
self.get_ema()
return self.cp, self.sma, self.ema
def get_ema(self, period=EMA_PERIOD):
closing_price = []
for items in reversed(list(self.historical_data.loc[:, 'Close'])):
closing_price.append(float(items)) #Gives a list
var = np.array(closing_price)
self.ema = np.flip(talib.EMA(var, timeperiod=period)).tolist()
def get_sma(self, period=SMA_PERIOD):
closing_price = []
for items in reversed(list(self.historical_data.loc[:, 'Close'])):
closing_price.append(float(items)) #Gives a list
var = np.array(closing_price)
self.sma = np.flip(talib.SMA(var, timeperiod=period)).tolist()
def get_cp(self):
closing_price = []
for items in reversed(list(self.historical_data.loc[:, 'Close'])):
closing_price.append(float(items)) #Gives a list
self.cp = np.flip(closing_price).tolist()
def get_historical_klines_tv(symbol, interval, start_str, end_str=None):
"""Get Historical Klines from Kucoin (Trading View)
See dateparse docs for valid start and end string formats http://dateparser.readthedocs.io/en/latest/
If using offset strings for dates add "UTC" to date string e.g. "now UTC", "11 hours ago UTC"
:param symbol: Name of symbol pair e.g BNBBTC
:type symbol: str
:param interval: Trading View Kline interval
:type interval: str
:param start_str: Start date string in UTC format
:type start_str: str
:param end_str: optional - end date string in UTC format
:type end_str: str
:return: list of OHLCV values
"""
# init our array for klines
klines = []
client = Client("", "", "")
# convert our date strings to seconds
start_ts = date_to_seconds(start_str)
# if an end time was not passed we need to use now
if end_str is None:
end_str = 'now UTC'
end_ts = date_to_seconds(end_str)
kline_res = client.get_kline_data(symbol, interval, start_ts, end_ts)
# print(kline_res)
# check if we got a result
if 't' in kline_res and len(kline_res['t']):
# now convert this array to OHLCV format and add to the array
for i in range(1, len(kline_res['t'])):
klines.append(
(kline_res['t'][i], kline_res['o'][i], kline_res['h'][i],
kline_res['l'][i], kline_res['c'][i], kline_res['v'][i]))
# finally return our converted klines
return klines
#sets beginning and ending timestamp
now = datetime.datetime.now()
nowtime = now.timestamp()
start = now - datetime.timedelta(days=2)
starttime = start.timestamp()
start72 = now - datetime.timedelta(days=3)
starttime72 = start72.timestamp()
endTime = math.floor(nowtime)
beginTime = math.floor(starttime)
beginTime72 = math.floor(starttime72)
#first list that runs through selection of swing trading coins
c = ['ARPA-USDT', 'BEPRO-USDT', 'ONE-USDT', 'DAPPT-USDT']
#brings in OHLC Data for percent change metrics
for i in c:
kline48 = client.get_kline_data(i, '1day', beginTime72, endTime)
kline1h = client.get_kline_data(i, '1hour', beginTime, endTime)
data1h = pd.DataFrame(kline1h)
data1h = data1h[[0, 2]]
data1h[0] = pd.to_datetime(data1h[0], unit='s', origin='unix')
data1h[2] = data1h[2].astype(float)
data1h = data1h.reindex(index=data1h.index[::-1])
closeprice = data1h[2]
data48 = pd.DataFrame(kline48)
data48 = data48[[0, 2]]
data48[0] = pd.to_datetime(data48[0], unit='s', origin='unix')
data48[2] = data48[2].astype(float)
data48 = data48.reindex(index=data48.index[::-1])
price48 = data48[2]
thirdDay = price48.iloc[0]
secondDay = price48.iloc[1]
