def test_instrument(self):
# list_instruments
instruments = self.account.list_instruments()
self.assertTrue(isinstance(instruments, dict))
print(instruments[self.currency])
# pip unit
pip_unit = pip(self.currency)
self.assertEqual(pip_unit, Decimal('0.0001'))
pips = pip(self.currency, 0.00315)
self.assertEqual(pips, 31.5)
# calculate_price
price = calculate_price(1.11325, OrderSide.BUY, 31.4, self.currency)
self.assertEqual(price, Decimal('1.11639'))
# get_candle
from_time = datetime.utcnow()
to_time = from_time - relativedelta(minutes=101)
count = 20
# get_candle
candles = self.account.get_candle(self.currency, PERIOD_M5, count=count, fromTime=to_time, toTime=to_time)
self.assertTrue(isinstance(candles, DataFrame))
self.assertEqual(len(candles), count)
def _draw(data, symbol, price, filename=None, to_plotly=False):
symbol = get_mt4_symbol(symbol)
pip_unit = pip(symbol)
fig = plt.figure()
ax = plt.axes()
items = data.items()
y = [
float(v) for k, v in items if pip(symbol,
float(k) - price, True) < 100
]
x = [
float(k) for k, v in items if pip(symbol,
float(k) - price, True) < 100
]
ax.plot(x, y)
plt.axvline(x=price, color='r')
plt.xticks(np.arange(min(x), max(x), float(pip_unit * 10)), rotation=90)
fig.show()
if filename:
fig.savefig('/tmp/%s.png' % filename)
if to_plotly:
trace = go.Bar(x=x, y=y)
result = py.iplot([trace], filename=filename)
print(result.embed_code)
def _process_price(self, price):
instrument = price.instrument
time = dateparser.parse(price.time)
bid = Decimal(str(price.bids[0].price))
ask = Decimal(str(price.asks[0].price))
spread = pip(instrument, ask - bid)
self._prices[instrument] = {'time': time, 'bid': bid, 'ask': ask, 'spread': spread}
def get_lots(self,
instrument,
stop_loss_pips=None,
risk_ratio=Decimal('0.05')):
max_trade = 5
if len(self.get_trades()) >= max_trade:
return 0
equity = self.get_balance()
if not stop_loss_pips:
return equity / 1000 * Decimal('0.1')
instrument = get_fxcm_symbol(instrument)
pip_unit = pip(instrument)
risk = equity * risk_ratio
value = risk / stop_loss_pips / pip_unit
if instrument.upper().endswith('USD'):
price = self.get_price(instrument)
value = value * price
elif instrument.upper().startswith('USD'):
lots = equity / 1000 * Decimal('0.1')
return lots.quantize(Decimal("0.01"))
else:
# cross pair
raise NotImplementedError
units = int(value / 100) * 100
return units_to_lots(units).quantize(Decimal("0.01"))
def tick_to_kinesis(tick, dataframe):
instrument = get_mt4_symbol(tick['Symbol'])
bid = str(Decimal(str(tick['Rates'][0])).quantize(pip(instrument)/10))
ask = str(Decimal(str(tick['Rates'][1])).quantize(pip(instrument)/10))
data = {
'timestamp': int(tick['Updated']) / 1000.0,
'bid': bid,
'ask': ask
}
data = json.dumps(data)
records.append({'Data': bytes(data, 'utf-8'), 'PartitionKey': instrument})
if len(records) == 10:
print(records)
kinesis.put_records(StreamName=inputStream, Records=records)
records.clear()
def tick_data(self, data, dataframe):
try:
instrument = get_mt4_symbol(data['Symbol'])
time = datetime.utcfromtimestamp(int(data['Updated']) / 1000.0)
bid = Decimal(str(data['Rates'][0])).quantize(pip(instrument))
ask = Decimal(str(data['Rates'][1])).quantize(pip(instrument))
tick = TickPriceEvent(self.broker, instrument, time, bid, ask)
self.put(tick)
data = json.dumps(
{'ask': float(ask), 'bid': float(bid), 'time': time.strftime('%Y-%m-%d %H:%M:%S:%f')})
set_tick_price(instrument, data)
set_last_tick(time.strftime('%Y-%m-%d %H:%M:%S:%f'))
self.last_tick_time = datetime.utcnow()
except Exception as ex:
logger.error('tick_data error = %s' % ex)
def get_spread(self, instrument):
tick_price = get_tick_price(instrument)
if tick_price:
spread = tick_price['ask'] - tick_price['bid']
spread_pips = pip(instrument, spread, _abs=True)
return spread_pips
return None
def _process_df(df, result, symbol):
pip_unit = pip(symbol)
for index, row in df.iterrows():
high = Decimal(str(row['askhigh'])).quantize(pip_unit,
rounding=ROUND_HALF_EVEN)
low = Decimal(str(row['bidlow'])).quantize(pip_unit,
rounding=ROUND_HALF_EVEN)
volume = Decimal(str(row['tickqty']))
if not volume:
continue
distance = pip(symbol, high - low, True)
avg_vol = (volume / distance).quantize(pip_unit)
for i in range(int(distance) + 1):
target = low + i * pip_unit
if str(target) not in result:
result[str(target)] = 0
result[str(target)] = Decimal(str(result[str(target)])) + avg_vol
def get_price(self, instrument, type='mid'):
instrument = get_mt4_symbol(instrument)
pip_u = pip(instrument)
price = get_tick_price(instrument)
if not price:
raise Exception('get_price, %s price is None' % instrument)
if type == 'ask':
return Decimal(str(price.get('ask'))).quantize(pip_u)
elif type == 'bid':
return Decimal(str(price.get('bid'))).quantize(pip_u)
elif type == 'mid':
price = (price.get('bid') + price.get('ask')) / 2
return Decimal(str(price)).quantize(pip_u)
def trade_units(self, instrument, stop_loss_pips):
"""get max units for this instrument"""
instrument = get_symbol(instrument)
pip_unit = pip(instrument)
risk = self.equity * self.risk_ratio
value = risk / stop_loss_pips / pip_unit
if instrument.upper().startswith('USD'):
price = self.account.get_price(instrument)
value = value * price
elif instrument.upper().endswith('USD'):
pass
else:
# cross pair
raise NotImplementedError
return int(value / 100) * 100
def process_price(self, instrument, price, volume=None):
_pip = pip(instrument)
price = Decimal(str(price)).quantize(_pip)
volume = volume or 0
if price in self.density.index:
count = self.density.loc[1]['count']
old_volume = self.density.loc[1]['volume']
temp_df = pd.DataFrame(
{
'count': [count + 1],
'volume': [old_volume + volume]
},
index=[price])
self.density.update(temp_df)
else:
temp_df = pd.DataFrame([[price, 1, volume]],
columns=['price', 'count', 'volume'])
temp_df = temp_df.set_index('price')
self.density = pd.concat([self.density, temp_df])
def _process_order_paramters(self, **kwargs):
data = {}
instrument = None
pip_unit = None
if kwargs.get('instrument'):
instrument = get_symbol(kwargs['instrument'])
data['instrument'] = instrument
if kwargs.get('trade_id'):
data['tradeID'] = str(kwargs['trade_id'])
trade = self.trades.get(data['tradeID']) or self.get_trade(
data['tradeID'])
instrument = trade.instrument
if instrument:
pip_unit = pip(instrument)
if kwargs.get('lots'):
units = lots_to_units(kwargs['lots'],
kwargs.get('side') or OrderSide.BUY)
data['units'] = str(units)
if kwargs.get('type'):
data['type'] = kwargs['type']
if kwargs.get('timeInForce'):
data['timeInForce'] = kwargs['timeInForce'] or TimeInForce.FOK
if kwargs.get('priceBound'):
data['priceBound'] = str(kwargs['priceBound'])
if kwargs.get('price'):
data['price'] = str(kwargs['price'])
if kwargs.get('positionFill'):
data['positionFill'] = kwargs[
'positionFill'] or OrderPositionFill.DEFAULT
# The Client Extensions to update for the Order. Do not set, modify, or
# delete clientExtensions if your account is associated with MT4.
if kwargs.get('client_id') or kwargs.get('client_tag') or kwargs.get(
'client_comment'):
data['clientExtensions'] = ClientExtensions(
id=kwargs['client_id'],
tag=kwargs['client_tag'],
comment=kwargs['client_comment'])
if kwargs.get('trade_client_id') or kwargs.get(
'trade_client_tag') or kwargs.get('trade_client_comment'):
data['tradeClientExtensions'] = ClientExtensions(
id=kwargs['trade_client_id'],
tag=kwargs['trade_client_tag'],
comment=kwargs['trade_client_comment'])
if kwargs.get('take_profit_price'):
data['takeProfitOnFill'] = TakeProfitDetails(
price=str(kwargs['take_profit_price']),
clientExtensions=data.get('clientExtensions'))
if kwargs.get('stop_loss_pip') and pip_unit:
stop_loss_price = pip_unit * Decimal(str(kwargs['stop_loss_pip']))
data['stopLossOnFill'] = StopLossDetails(
distance=str(stop_loss_price),
clientExtensions=data.get('clientExtensions'))
if kwargs.get('stop_loss_distance'):
data['stopLossOnFill'] = StopLossDetails(
distance=str(kwargs['stop_loss_distance']),
clientExtensions=data.get('clientExtensions'))
if kwargs.get('trailing_pip'):
trailing_distance_price = pip_unit * Decimal(
str(kwargs['trailing_pip']))
data['trailingStopLossOnFill'] = TrailingStopLossDetails(
distance=str(trailing_distance_price),
clientExtensions=data.get('clientExtensions'))
if kwargs.get('trigger_condition'):
data['triggerCondition'] = kwargs[
'trigger_condition'] or OrderTriggerCondition.DEFAULT
if kwargs.get('gtd_time'):
# todo confirm gtdTime format
data['gtdTime'] = str(kwargs['gtd_time'])
if kwargs.get('client_trade_id'):
data['clientTradeID'] = kwargs['client_trade_id']
if kwargs.get('guaranteed'):
data['guaranteed'] = kwargs['guaranteed']
if kwargs.get('distance'):
data['distance'] = kwargs['distance']
return data