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CoinWizard

alt text A foreign currencies/forex trading management program.

Installation

pip install pytz numpy pandas finplot bs4 prompt_toolkit dateutil pushbullet.py

Start CoinWizard

go to "src" folder and

python3 start.py

TradingAgent BrokerAPI Documentation

Index:

  1. TradingAgent and BrokerAPI
  2. BrokerAPI
  3. Account
  4. Order
  5. Trade
  6. Instrument
  7. NotificationServiceProvider
  8. TechnicalIndicators
  9. coin_wizard.historical_pair_data

0. TradingAgent and BrokerAPI

You shall aquire your BrokerAPI from your TradingAgent start(), test(), train() functions as an entry point. Depended on your choice of launching TradingAgent.

class TradingAgent(object):
    def __init__(self, agent_files_directory):
        pass

    def run(self, BrokerAPI):
        # Can be here.
        pass

    def stop_running(self, BrokerAPI):
        pass

    def train(self, BrokerAPI):
        # Can be here.
        pass

    def stop_training(self, BrokerAPI):
        pass

    def test(self, BrokerAPI):
        # Or can be here.
        pass

    def stop_testing(self, BrokerAPI):
        pass

1. BrokerAPI

BrokerAPI.getAccount

Get the account object.

account = BrokerAPI.getAccount()

BrokerAPI.getInstrument

Get the instrument object.

# Get the EUR_USD instrument.
instrument = BrokerAPI.getInstrument('EUR_USD')

BrokerAPI.order

Order for an instrument with order and trade settings.

# Order 2 units EUR_USD instrument in the market immediately.
order = BrokerAPI.order('EUR_USD', {"type": "market"}, {"units": 2})
# Order stop order of EUR_USD instrument. With load of settings.
order = BrokerAPI.order('EUR_USD', {"type": "stop", "price": 2, "bound": 2.1}, {"units": 1, "take_profit": 2, "stop_lost": 0.5, "trailing_stop_distance": 0.001})

BrokerAPI.getNotificationServiceProvider

Get the notification_service_provider object.

nsp = BrokerAPI.getNotificationServiceProvider()

BrokerAPI.onLoop

Register listener/callback for every loop of event-loop.

# Note that every times that the callback emitted BrokerAPI is passed as parameters.
def loop(BrokerAPI):
  # do something here
  pass

# With every loop of event-loop call loop() function.
BrokerAPI.onLoop(loop)

BrokerAPI.onEvery15Second

Register listener/callback for every 15 seconds.

# Note that every times that the callback emitted BrokerAPI is passed as parameters.
def loop15s(BrokerAPI):
  # do something here
  pass

# With every 15 seconds of event-loop call loop15s() function.
BrokerAPI.onEvery15Second(loop15s)

2. Account

First, get the account object from BrokerAPI.

account = BrokerAPI.getAccount()

Account.getBalance

Get your account balance in float type.

balance = account.getBalance()
# For example 10000.0

Account.getCurrency

Get your account balance in string type.

currency = account.getCurrency()
# For example "USD"

Account.getMarginRate

Get your account margin rate in float type.

margin_rate = account.getMarginRate()
# For example 0.02

Account.getMarginAvailable

Get your account margin available in float type.

margin_available = account.getMarginAvailable()
# For example 99980.0

Account.getMarginUsed

Get your account margin used in float type.

margin_used = account.getMarginUsed()
# For example 20.0

Account.getUnrealizedPL

Get your account unrealized profit&loss in float type.

unrealized_pl = account.getUnrealizedPL()
# For example -20.0

Account.getOrders

Get your account orders in list.

orders = account.getOrders()
# For example [order_object_1, order_object_2]

Account.getTrades

Get your account trades in list.

trades = account.getTrades()
# For example [trade_object_1]

3. Order

First, you should get your order either from BrokerAPI.order(...params) or Account.getOrders()

# Order 2 units EUR_USD instrument in the market immediately.
order = BrokerAPI.order('EUR_USD', {"type": "market"}, {"units": 2})
orders = account.getOrders()
# For example [order_object_1, order_object_2]

Order.onFilled

Register listener/callback for order filled event.

# Note that every times that the callback emitted order and trade is passed as parameters.
def filled_listener(order, trade):
  # do something here
  pass

# When the order filled, call "filled_listener".
order.onFilled(filled_listener)

Order.onCanceled

Register listener/callback for order filled event.

# Note that every times that the callback emitted order and reason(string type) is passed as parameters.
def canceled_listener(order, reason):
  # do something here
  pass

# When the order canceled, call "canceled_listener".
order.onCanceled(canceled_listener)

Order.cancel

Cancel the order itself.

order.cancel()

Do not forget to register order canceled listener.

order.onCanceled(canceled_listener)

Order.getInstrumentName

Get your order instrument name.

instrument_name = order.getInstrumentName()
# For example "EUR_USD"

Order.getOrderSettings

Get your order's order settings.

order_settings = order.getOrderSettings()
# For example
# {
#  "type": "market"
# }

Order.getTradeSettings

Get your order's trade setting.

trade_settings = order.getTradeSettings()
# For example
# {
#  "units": -7997.0,
#  "current_units": -7996.0,
#  "take_profit": 0.543,
#  "stop_loss": 2.0,
#  "trailing_stop_distance": 0.1
# }

4. Trade

First, you should get your order either from order.onFilled or Account.getTrades()

def filled_listener(order, trade):
  # You get your trade of that order here.
  pass

# When the order filled, call "filled_listener".
order.onFilled(filled_listener)
trades = account.getTrades()
# For example [trade_object_1, trade_object_2]

Trade.onClosed

Register listener/callback for trade closed event.

# Note that every times that the callback emitted.
# trade, realized_pl, close_price, spread, timestamp is passed as parameters.
def closed_listener(self, trade, realized_pl, close_price, spread, timestamp):
  # do something here
  pass

# When the trade closed, call "closed_listener".
trade.onClosed(closed_listener)

Trade.onReduced

Register listener/callback for trade closed event.

# Note that every times that the callback emitted.
# trade, units, realized_pl, close_price, spread, timestamp is passed as parameters.
# Different from Trade.onClosed, Trade.onReduced pass units parameters. For example: units = -1.0, units = 2.0.
def reduced_listener(trade, units, realized_pl, close_price, spread, timestamp):
  # do something here
  pass

# When the trade reduced, call "reduced_listener".
trade.onReduced(reduced_listener)

Trade.close

Close the trade itself.

trade.close()

Do not forget to register trade closed listener.

trade.onClosed(closed_listener)

Trade.reduce

Reduce 10 units of long position trade. Both accepted.

trade.reduce(-10)
trade.reduce(10)

Reduce 10 units of short position.

trade.reduce(10)

Do not forget to register trade closed listener.

trade.onClosed(closed_listener)

Trade.getInstrumentName

Get your trade instrument name.

instrument_name = trade.getInstrumentName()
# For example "EUR_USD"

Trade.getOpenPrice

Get your trade open price.

price = trade.getOpenPrice()
# For example 1.4325

Trade.getTradeSettings

Get your trade's trade setting.

trade_settings = trade.getTradeSettings()
# For example
# {
#  "units": -7997.0,
#  "current_units": -7996.0,
#  "take_profit": 0.543,
#  "stop_loss": 2.0,
#  "trailing_stop_distance": 0.1
# }

Trade.getUnrealizedPL

Get your trade unrealized profit&loss.

unrealized_pl = trade.getUnrealizedPL()
# For example -21.011

5. Instrument

First, get the account object from BrokerAPI.

# Get the EUR_USD instrument.
instrument = BrokerAPI.getInstrument('EUR_USD')

Instrument.getCurrentCloseoutBidAsk

Get instrument current closeout bid, ask and timestamp.

bid, ask, timestamp = instrument.getCurrentCloseoutBidAsk()
# For example: 1.19289, 1.19303, datetime.datetime(2021, 3, 15, 12, 15, 29, 271891, tzinfo=tzutc())

Instrument.getActive1MCandle

Get instrument active 1m candle dataframe(pandas).

the_candle_df = instrument.getActive1MCandle()
# Return pandas dataframe with below fields:
# timestamp, open, high, low, close
# Note that timestamp is in utc iso format

Instrument.getRecent1MCandles

Get instrument active recent 1m candle dataframe(pandas).

# Get 1000 candles.
candles_df = instrument.getRecent1MCandles(1000)
# Return pandas 1000 rows dataframe with below fields:
# timestamp, open, high, low, close
# Note that timestamp is in utc iso format

Instrument.isTradable

Check if such instrument is tradable.

tradable = instrument.isTradable()
# For example: False

6. NotificationServiceProvider

First, get the notification_service_provider object from BrokerAPI.

nsp = BrokerAPI.getNotificationServiceProvider()

NotificationServiceProvider.pushImmediately()

Push a notification immediately.

# Push notification with title and context.
nsp.pushImmediately('Title1', 'Hello')

NotificationServiceProvider.addLine()

Add a notification line for later push. (Not yet sent/push)

# Add a line.
nsp.addLine('Hello')

NotificationServiceProvider.push()

Push accumulated notification lines with title.

# Add a line.
nsp.addLine('Hello')
# Push.
nsp.push('Title1')

7. TechnicalIndicators

In your trading agent

ti = BrokerAPI.TechnicalIndicators

TechnicalIndicators.ma(series, period=10)

Moving average

TechnicalIndicators.ema(series, period=10)

Exponential moving average

TechnicalIndicators.macd(series, short=12, long=26)

Moving average convergence divergence

TechnicalIndicators.roc(series, period=2)

Rate of change

TechnicalIndicators.momentum(series, period=4)

Momentum

TechnicalIndicators.rsi_ma(series, period=10)

Relative strength index ma

TechnicalIndicators.rsi_ema(series, period=10)

Relative strength index ema

TechnicalIndicators.bb(series, period=20, std_num=2)

Bollinger bands

TechnicalIndicators.cci(high_series, low_series, close_series, period=20)

Commodity channel index

8. coin_wizard.historical_pair_data

In your trading agent

import coin_wizard.historical_pair_data as historical_pair_data

historical_pair_data.get_historical_pair_data

Get your historical data in numpy format with utc timestamp from 1970, 1, 1.

# Get historical data in with eastern time setup.
historical_pair_data.get_historical_pair_data('eurusd', datetime(2021, 1, 8, 0, 0), datetime(2021, 1, 11, 23, 59))
# Get historical data in with eastern time setup.
import pytz
eastern = pytz.timezone('US/Eastern')
historical_pair_data.get_historical_pair_data('eurusd', eastern.localize(datetime(2021, 1, 8, 0, 0)), eastern.localize(datetime(2021, 1, 11, 23, 59)))

historical_pair_data.get_historical_pair_data_pandas

Get your historical data in pandas format. With default UTC timezone.

# Get historical data in with eastern time setup.
historical_pair_data.get_historical_pair_data_pandas('eurusd', datetime(2021, 1, 8, 0, 0), datetime(2021, 1, 11, 23, 59))
# Get historical data in with eastern time setup. And too output with timezone 'US/Eastern' as the latest parameter.
import pytz
eastern = pytz.timezone('US/Eastern')
historical_pair_data.get_historical_pair_data_pandas('eurusd', eastern.localize(datetime(2021, 1, 8, 0, 0)), eastern.localize(datetime(2021, 1, 11, 23, 59)), 'US/Eastern')

historical_pair_data.plot_historical_pair_data

Plot your historical data.

# Plot historical data in with eastern time setup.
import pytz
eastern = pytz.timezone('US/Eastern')
historical_pair_data.plot_historical_pair_data('eurusd', eastern.localize(datetime(2021, 1, 8, 0, 0)), eastern.localize(datetime(2021, 1, 11, 23, 59)), 'US/Eastern')