def cm_bal(task):
amounts, balances = app.account_total()
previous_amounts = db.config(Const.BALANCE, {})
previous_bal_hash = db.config(Const.BALANCE_HASH, "")
total = app.floor(sum(x[1] for x in amounts), 2)
if task.params and len(task.params) > 0 and task.params[0] == 'short':
return f"Balance: {total}"
account_bal_hash = util_balance_hash(balances)
is_hash_matching = account_bal_hash == previous_bal_hash
msg_lines = []
for x in amounts:
prc_diff = app.floor((x[1] - previous_amounts[x[0]]) * 100 / previous_amounts[x[0]]) \
if x[0] in previous_amounts else 'NA'
bal_str = f'{x[0]} -> {x[1]} ({prc_diff})' if is_hash_matching else f'{x[0]} -> {x[1]}'
if x[1] > 10:
msg_lines.append(bal_str)
msg_lines.append("." * 15)
msg_lines.append(f'Total: {total}')
msg = "\n".join(msg_lines)
if not is_hash_matching:
db.set_config(Const.BALANCE, {x[0]: x[1] for x in amounts})
db.set_config(Const.BALANCE_HASH, account_bal_hash)
log.info("saved new balances!")
return msg
def rsi(df):
methods = ChartHelper()
rsi = TA.RSI(df)
lastRSI = app.floor(sum(rsi.tail(3).values) / 3, 1)
def plottable(ax):
if ax:
stock_rsi = TA.STOCHRSI(df).multiply(100)
rsiPoints = rsi.tail(rsi.shape[0] - 10).apply(
methods.polarity_shift_rsi)
rsiPointsGreen = rsiPoints.where(lambda x: x == 1).shift(
0).dropna().tail(2)
rsiPointsRed = rsiPoints.where(lambda x: x == -1).shift(
0).dropna().tail(2)
pd.concat([rsi, stock_rsi],
axis=1).tail(chart_tail_count).plot(figsize=figure_size,
ax=ax)
try:
if rsiPointsRed.shape[0] > 0:
ax.scatter(rsiPointsRed.index,
rsi[rsiPointsRed.index].values,
s=100,
c='red')
if rsiPointsGreen.shape[0] > 0:
ax.scatter(rsiPointsGreen.index,
rsi[rsiPointsGreen.index].values,
s=100,
c='green')
except Exception as e1:
log.exception(e1)
signal = 'Buy' if lastRSI < 35 else 'WAIT'
return {'signal': signal, 'info': f'RSI: {lastRSI}', 'plot': plottable}
def ta(asset, timeframe, count, fig, ax):
methods = ChartHelper()
matplotlib.use('agg')
matplotlib.pyplot.switch_backend('Agg')
plt.style.use(theme)
signal = f"{asset} {timeframe} ->"
# https://github.com/matplotlib/matplotlib/issues/14304
klines = app.klines(asset, timeframe, count)
df = app.dataframe(klines)
if ax[0]:
close = df['close']
ema50 = TA.EMA(df, period=50)
vwma = TA.EVWMA(df)
pd.concat([close, ema50, vwma],
axis=1).tail(chart_tail_count).plot(ax=ax[0],
figsize=figure_size)
macd_resp = macd_x_over(df)
buysell, lastTime = macd_resp['signal'], macd_resp['time']
hoursAgo = int((time.time() - lastTime.timestamp()) / 60 / 60)
signal = signal + f"\n {buysell}: at {lastTime}, {hoursAgo} hours ago"
if ax[1]:
macd_resp['plot'](ax[1])
rsi_resp = rsi(df)
signal = signal + f"\n {rsi_resp['signal']}: {rsi_resp['info']}"
if ax[2]:
rsi_resp['plot'](ax[2])
# Prepare TA Hints
# - SMA50
sma = TA.SMA(df, period=20 if timeframe == '1d' else 50)
current_ma_20 = app.floor(sum(sma.tail(1).values), 9)
current_price = float(klines[-1][4])
prc_from_ema20 = app.floor_new(
(current_price - current_ma_20) * 100 / current_ma_20, 2)
signal = signal + f"\n Price ovr SMA: {prc_from_ema20} "
# min, max Bollinger lower band distance in last 4 bars
# kama = TA.KAMA(df) # KAMA instead of SMA
# , MA=kama
bb_resp = bb(df)
if ax[3]:
bb_resp['plot'](ax[3])
signal = signal + f"\n {bb_resp['signal']}: {bb_resp['info']}"
# Average Directional Movement, Directional Movement Indicator
adx = TA.ADX(df).tail(ta_hints_bars)
dmi = TA.DMI(df).tail(ta_hints_bars)
direction = "Buy" if (dmi['DI+'][-1] > dmi['DI-'][-1]) else "Sell"
adxStr = getAdxIntensity(adx.values[-1])
signal = signal + f"\n ADX/DMI: {adxStr} {direction}"
return signal
def cm_stop_loss_info(task):
stats = app.stop_loss_orders_percentage()
msg = []
total = 0
for x in stats:
price = app.floor(x[2] * x[4], 2)
msg.append(f'{x[1]} -> {price} , {app.floor(x[5])}%')
total += price
if len(msg) > 0:
msg.append('-' * 15)
msg.append(f'Stoploss Total -> {app.floor(total, 2)}')
return "\n".join(msg)
else:
return "No Stoploss Orders Found!"
def sell_x_prc_internal(symbol, quantity, priceOverMarket, test=True):
log.debug(f'attempting for {quantity}, {priceOverMarket}')
response = app.sell_x_percent(symbol, quantity, priceOverMarket, test)
log.debug(response)
msgs = [
f'{x["symbol"]} -> {app.floor(float(x["quantity"]) * float(x["price"]), 2)}'
for x in response
]
msgs.append('.' * 15)
total = app.floor(
sum([float(x["quantity"]) * float(x["price"]) for x in response]), 2)
msgs.append(f'Sell Total : {total}')
test_str = "Test " if test else ""
msg = '\n'.join([f' {test_str}Sell Orders Placed'] + msgs)
return msg
def balance_pie():
matplotlib.use('agg')
matplotlib.pyplot.switch_backend('Agg')
plt.style.use(theme)
balances = app.account_total()[0]
total = sum([x[1] for x in balances])
filtered_balances = list(filter(lambda x: x[1] > 10, balances))
labels = [x[0] + "\n" + app.floor_new(x[1], 1) for x in filtered_balances]
sizes = [int(x[1] * 100 / total) for x in filtered_balances]
fig, ax1 = plt.subplots(1)
ax1.pie(sizes, labels=labels, startangle=90, autopct='%1.1f%%')
ax1.axis('equal')
plt.draw()
filename = 'charts/balance)' + str(int(round(time.time() * 1000))) + '.png'
pathlib.Path('charts').mkdir(parents=True, exist_ok=True)
plt.tight_layout()
fig.savefig(filename)
return filename, app.floor(total, 1)
def wrapped(task):
start = time.time_ns()
try:
msg = fn(task)
if msg and len(msg) > 0 and task.message.chat.id:
log.info("chat id %s", task.message.chat.id)
if not isinstance(task.message.chat.id, int) \
or ( isinstance(task.message.chat.id, str) and not task.message.chat.id.isnumeric()):
log.warn("Please set the adminChatID")
else:
app.send_msg(msg, task.message.chat.id)
if task.message.source == 'terminal':
log.info("\n%s", msg)
elif task.message.chat.id:
pass
# app.notify_action(task.message.chat.id)
except Exception as e:
log.exception(e)
end = time.time_ns()
log.debug("time taken for %s : %s ms", fn.__name__,
app.floor((end - start) / 1000 / 1000, 2))
def util_balance_hash(balances: Dict[str, float]):
sorted_keys = sorted(balances.keys())
return "".join([
x + str(app.floor(balances[x], 3)) for x in sorted_keys
if balances[x] > 0.005
])