def get_data(granularity=3600, max_=200):
eth_data = gdax_data.get_data("ETH-USD", granularity, max_)
btc_data = gdax_data.get_data("BTC-USD", granularity, max_)
ltc_data = gdax_data.get_data("LTC-USD", granularity, max_)
eth_df = pd.DataFrame(list(reversed(eth_data)), columns=['date', 'low', 'high', 'open', 'close', 'volume'])
btc_df = pd.DataFrame(list(reversed(btc_data)), columns=['date', 'low', 'high', 'open', 'close', 'volume'])
ltc_df = pd.DataFrame(list(reversed(ltc_data)), columns=['date', 'low', 'high', 'open', 'close', 'volume'])
return {"eth": eth_df, "btc": btc_df, "ltc": ltc_df}
def run(interval,
product_id="ETH-USD",
window=20,
sd=2,
lower_limit=10,
upper_limit=90):
best_bid_ask = trading.get_best_bid_ask(product_id)
best_bid = float(best_bid_ask['bid'])
data, start, end = gdax_data.get_data(product_id, interval, window)
df = pd.DataFrame(
list(reversed(data)),
columns=['date', 'low', 'high', 'open', 'close', 'volume'])
indicators.add_bol(df, window, sd)
last_data = df.iloc[-1]
upper_bol = round(float(last_data['Bol_upper']), 2)
lower_bol = round(float(last_data['Bol_lower']), 2)
bol_range = upper_bol - lower_bol
range_pc = round(((1 - (upper_bol - best_bid) / bol_range) * 100), 2)
res_string = ""
res_score = 0
if range_pc > upper_limit:
res = "SELL"
res_score = -10
elif range_pc < lower_limit:
res = "BUY"
res_score = 10
else:
res = "-"
return {"score": res_score, "indicator": "Boll"}
def run(interval, product_id="ETH-USD"):
data, start, end = gdax_data.get_data(product_id, interval, 3)
df = pd.DataFrame(
list(reversed(data)),
columns=['date', 'low', 'high', 'open', 'close', 'volume'])
indicators.check_engulfing(df)
indicators.check_hammer(df)
indicators.check_doji(df)
res_string = ""
res_score = 0
last_data_point = df.iloc[-1]
if bool(last_data_point['engulfing']) is True:
res_string = res_string + "BUY (engulfing)"
res_score = res_score + 10
if bool(last_data_point['hammer']) is True:
res_string = res_string + "BUY (hammer)"
res_score = res_score + 10
if bool(last_data_point['doji']) is True:
res_string = res_string + "BUY (doji)"
res_score = res_score + 10
return {"score": res_score, "indicator": res_string}
def run(intervals, product_id="ETH-USD", window=3):
is_reversed = True
for interval in intervals:
data, start, end = gdax_data.get_data(product_id, interval, 200)
if is_reversed:
df = pd.DataFrame(
list(reversed(data)),
columns=['date', 'low', 'high', 'open', 'close', 'volume'])
else:
df = pd.DataFrame(
list(data),
columns=['date', 'low', 'high', 'open', 'close', 'volume'])
if not is_reversed:
df['temp'] = df['open']
df['open'] = df['close']
df['close'] = df['temp']
indicators.check_color(df)
have_position = False
num_green = 0
fiat_start_balance = 1000.0
fiat_balance = fiat_start_balance
eth_balance = 0.0
close_price = 0.0
for index, row in df.iterrows():
close_price = row['close']
if row['color'] == 'green':
num_green = num_green + 1
if have_position and row['color'] == 'green':
print("HOLD SHIZZLE " + str(close_price))
if not have_position and num_green == 3:
eth_balance = fiat_balance / close_price
fiat_balance = 0.0
have_position = True
num_green = 0
print("BUY " + str(close_price))
if have_position and row['color'] == 'red':
fiat_balance = eth_balance * close_price
eth_balance = 0.0
have_position = False
num_green = 0
print("SELL " + str(close_price))
print(str(fiat_balance) + " " + str(close_price * eth_balance))
def plot(product_id, granularity=60, max=200):
crypto_id = product_id.upper()
product_id = crypto_id + '-USD'
gdax_data_, start, end = gdax_data.get_data(product_id, granularity, max)
df = pd.DataFrame(
list(reversed(gdax_data_)),
columns=['date', 'low', 'high', 'open', 'close', 'volume'])
print(trading.get_best_bid_ask(product_id))
indicators.add_macd(df)
indicators.add_bol(df)
fig, axes = plt.subplots(nrows=2, ncols=1)
df.plot(y=['close', 'Bol_upper', 'Bol_lower'], ax=axes[0])
df.plot(y=['MACD'], ax=axes[1])
plt.show(block=not standalone)
return
def run(interval, product_id="ETH-USD", slow_ema=26, fast_ema=12, history=3):
data, start, end = gdax_data.get_data(product_id, interval,
(slow_ema + history))
df = pd.DataFrame(
list(reversed(data)),
columns=['date', 'low', 'high', 'open', 'close', 'volume'])
indicators.add_macd(df, slow_ema, fast_ema)
is_last_above_zero = False
is_last_below_zero = False
rest_above_zero = False
rest_below_zero = False
for i in range(0, history):
data = df.iloc[-1 - i]
if i == 0:
if float(data['MACD']) > 0.0:
is_last_above_zero = True
else:
is_last_below_zero = True
if i != 0:
if float(data['MACD']) > 0.0:
rest_above_zero = True
else:
rest_below_zero = True
break
res_string = ""
res_score = 0
if is_last_above_zero and rest_below_zero:
res = "BUY"
res_score = 10
elif is_last_below_zero and rest_above_zero:
res = "SELL"
res_score = -10
else:
res = "-"
return {"score": res_score, "indicator": "MACD"}
def run(intervals, product_id="ETH-USD", window=19, history=5):
results = []
for interval in intervals:
data, start, end = gdax_data.get_data(product_id, interval,
(window + history))
df = pd.DataFrame(
list(reversed(data)),
columns=['date', 'low', 'high', 'open', 'close', 'volume'])
indicators.add_ema('mean', df, window)
df = df.dropna(how='any').reset_index(drop=True)
x = list(range(1, history + 1))
y = df['mean'].values[-history:]
z = np.polyfit(x=x, y=y, deg=1)
p = np.poly1d(z)
results.append({
"interval": interval,
"score": z[0],
"indicator": "Slope"
})
print(str(interval) + " " + str(z[0]))
return results
import pandas as pd
import indicators
import trading
from data import gdax_data
intervals = [60, 300, 600, 1200, 3600]
best_bid_ask = trading.get_best_bid_ask('ETH-USD')
best_bid = float(best_bid_ask['bid'])
display_str = ""
for int_ in intervals:
data, start, end = gdax_data.get_data("ETH-USD", int_, 200)
df = pd.DataFrame(list(reversed(data)), columns=['date', 'low', 'high', 'open', 'close', 'volume'])
indicators.add_macd(df)
indicators.add_bol(df)
last_data = df.iloc[-1]
macd = round(float(last_data['MACD']), 2)
upper_bol = round(float(last_data['Bol_upper']), 2)
lower_bol = round(float(last_data['Bol_lower']), 2)
bol_range = upper_bol - lower_bol
range_pc = round(((1 - (upper_bol - best_bid) / bol_range) * 100), 2)
print(str(int_) + " " + str(range_pc) + "/" + str(macd) + " ["
+ str(lower_bol) + " <- " + str(best_bid) + " -> " + str(upper_bol) + "]")
time.sleep(1)