The Futures Exchange Interface object is similar to the Exchange object, except it is designed to work with exchanges or brokerages that trade perpetual futures.

Creation

Interfaces are pre-generated when an exchange object is created. They can then be accessed by using .get_interface() on an exchange:

import blankly
from blankly import futures

exchange = futures.BinanceFutures()

interface = exchange.get_interface()  # Use the getter

print(interface.get_account())

Functions

get_exchange_type()

Determine which exchange an interface is running on.

Response

get_products()

Get all trading pairs currently on the exchange.

Response

[
    {
        "symbol": "BTC-USD",
        "base_asset": "BTC",
        "quote_asset": "USD",
        "price_precision": 2,
        "size_precision": 4,
    },
    ...
]

get_account(symbol=None)

Gets the current account holdings if symbol is None, otherwise will return the symbol holdings. Important: If you're using futures you may want .get_positions(). The positions you take when you buy or sell contracts will show up there, .get_account() is not very useful in FuturesExchangeInterface.

Arguments

Response

If symbol='USD':

{
    "available": 1000.23,
    "hold": 0.0
}

If symbol=None:

{
  "USD": {
      "available": 1000.23,
      "hold": 0.0
  }
}

market_order(symbol, side, size) -> MarketOrder

Create a new live market order.

Arguments

Response

A FuturesOrder object. Documentation can be found here

limit_order(symbol, side, price, size) -> LimitOrder

Create a new live limit order on your exchange.

Arguments

Response

A FuturesOrder object. Documentation can be found here

take_profit_order(symbol, price, size) -> TakeProfitOrder

Create a new live take-profit order on your exchange. This is a market sell order that will execute when the price reaches a certain high.

Arguments

Response

A FuturesOrder object. Documentation can be found here

stop_loss_order(symbol, price, size) -> StopLossOrder

Create a new live stop-loss order on your exchange. This is a market sell order that will execute when the price reaches a certain low.

Arguments

Response

A FuturesOrder object. Documentation can be found here

cancel_order(symbol, order_id) -> dict

Cancel a particular order.

Arguments

Response

A FuturesOrder object. Documentation can be found here

get_open_orders(symbol=None)

Get a full list of open orders.

Arguments

Response

A list of FuturesOrder objects, each representing one open order. Documentation can be found here

get_order(symbol, order_id) -> dict

Get info about a particular order.

Arguments

Response

A FuturesOrder object. Documentation can be found here

get_fees() -> dict

Get the maker and taker fee rates of a particular exchange.

Response

{
    "maker": 0.0050,
    "taker": 0.0050
}

get_leverage(symbol=None) -> leverage, set_leverage(leverage, symbol=None)

Used for getting and setting leverage. If symbol is None, this will set account-wide leverage. Note that not all exchanges support this.

Arguuments

Response

get_leverage(symbol=None) will return the leverage for symbol, or account wide leverage if symbol is None.

history(symbol, to = 200, resolution = '1d', start_date = None, end_date = None, return_as = 'df') -> pandas.DataFrame

Download historical data with rows of at least time (epoch seconds), low', high, open, close, volume as columns. This is a wrapper for get_product_history(), and exists to allow users to more easily download OHCLV data

Arguments

Response

Pandas dataframe with at least these columns.

Or if return_as is set to list:

{
    'time': [1591110000, 1591113600],
    'low': [9270.0, 9417.38],
    'open': [9583.36, 9464.44],
    'close': [9464.46, 9478.95],
    'volume': [5979.77327365, 1185.12835638]
}

Example Use Case

a = Alpaca()
interface = a.Interface
interface.history('MSFT', to=300, resolution='15m',
                  end_date='2020-05-03')  # get 300 points from May 3rd, 2020 as a dataframe
interface.history('MSFT', to=300, resolution='15m', end_date='2020-05-03', return_as='list')[
    'close']  # get 300 points from May 3rd, 2020 as a dictionary of np.arrays

get_product_history(symbol, epoch_start, epoch_stop, resolution) -> pandas.DataFrame

Download historical data with rows of at least time (epoch seconds), low', high, open, close, volume as columns.

Arguments

Response

Pandas dataframe with at least these columns.

get_price(symbol) -> float

Get the quoted price of the trading pair.

Arguments

Response

Returns a float which is the price of the trading pair, such as 53000 or 35000.

get_funding_rate(symbol) -> float

Get the current funding rate of the symbol.

Arguments

Response

Returns a float which is the current funding rate of the trading pair, such as 0.0001 or -0.0001.

.cash -> float

Get the amount of cash (generally the quote currency) inside the portfolio. This default quote can be set in the settings.json file for each exchange independently. This is used as a shortcut for easily determining buying power when making a transaction. This property is configurable because users may be using a variety of cash quotes such as USD, USDT, USDC or EUR. See here.

Response

A single float which represents the size value of the account defined in settings.json.

5931.533