Moving position to an interface

pytrade/broker.py

@@ -3,7 +3,8 @@
 from pytrade.instruments import Granularity, Instrument
 from pytrade.interfaces.broker import IBroker
 from pytrade.interfaces.client import IClient
-from pytrade.models import Order, Position
+from pytrade.interfaces.position import IPosition
+from pytrade.models import Order
 
 
 class Broker(IBroker):
@@ -24,7 +25,7 @@ def margin_available(self) -> float:
     def leverage(self) -> float:
         raise NotImplementedError()
 
-    def get_position(self, instrument: Instrument) -> Position:
+    def get_position(self, instrument: Instrument) -> IPosition:
         raise NotImplementedError()
 
     def close_position(self, instrument: Instrument):

pytrade/interfaces/broker.py

@@ -2,7 +2,8 @@
 
 from pytrade.instruments import Granularity, Instrument
 from pytrade.interfaces.data import IInstrumentData
-from pytrade.models import Order, Position
+from pytrade.interfaces.position import IPosition
+from pytrade.models import Order
 
 
 class IBroker(metaclass=abc.ABCMeta):
@@ -33,7 +34,7 @@ def leverage(self) -> float:
         raise NotImplementedError()
 
     @abc.abstractmethod
-    def get_position(self, instrument: Instrument) -> Position:
+    def get_position(self, instrument: Instrument) -> IPosition:
         raise NotImplementedError()
 
     @abc.abstractmethod

pytrade/interfaces/position.py

@@ -0,0 +1,42 @@
+from abc import abstractmethod
+
+
+class IPosition:
+    """
+    Currently held asset position, available as
+    `backtesting.backtesting.Strategy.position` within
+    `backtesting.backtesting.Strategy.next`.
+    Can be used in boolean contexts, e.g.
+
+        if self.position:
+            ...  # we have a position, either long or short
+    """
+
+    @property
+    @abstractmethod
+    def size(self) -> float:
+        raise NotImplementedError()
+
+    @property
+    @abstractmethod
+    def pl(self) -> float:
+        """Profit (positive) or loss (negative) of the current position in cash units."""
+        raise NotImplementedError()
+
+    @property
+    @abstractmethod
+    def pl_pct(self) -> float:
+        """Profit (positive) or loss (negative) of the current position in percent."""
+        raise NotImplementedError()
+
+    @property
+    @abstractmethod
+    def is_long(self) -> bool:
+        """True if the position is long (position size is positive)."""
+        raise NotImplementedError()
+
+    @property
+    @abstractmethod
+    def is_short(self) -> bool:
+        """True if the position is short (position size is negative)."""
+        raise NotImplementedError()

pytrade/models.py

@@ -2,7 +2,6 @@
 from math import copysign
 from typing import Any, Optional
 
-import numpy as np
 import pandas as pd
 from pandas import Timestamp
 
@@ -266,61 +265,3 @@ def tp(self) -> Optional[Order]:
     @tp.setter
     def tp(self, order: Order):
         self.__tp_order = order
-
-
-class Position:
-    """
-    Currently held asset position, available as
-    `backtesting.backtesting.Strategy.position` within
-    `backtesting.backtesting.Strategy.next`.
-    Can be used in boolean contexts, e.g.
-
-        if self.position:
-            ...  # we have a position, either long or short
-    """
-
-    def __init__(self, instrument: Instrument, trades: list[Trade]):
-        self.__instrument = instrument
-        self.__trades = trades
-
-    def __bool__(self):
-        return self.size != 0
-
-    @property
-    def trades(self):
-        return [
-            trade for trade in self.__trades if trade.instrument == self.__instrument
-        ]
-
-    @property
-    def size(self) -> float:
-        """Position size in units of asset. Negative if position is short."""
-        return sum(trade.size for trade in self.trades)
-
-    @property
-    def pl(self) -> float:
-        """Profit (positive) or loss (negative) of the current position in cash units."""
-        return sum(trade.pl for trade in self.trades)
-
-    @property
-    def pl_pct(self) -> float:
-        """Profit (positive) or loss (negative) of the current position in percent."""
-        weights = np.abs([trade.size for trade in self.trades])
-        weights = weights / weights.sum()
-        pl_pcts = np.array([trade.pl_pct for trade in self.trades])
-        return (pl_pcts * weights).sum()
-
-    @property
-    def is_long(self) -> bool:
-        """True if the position is long (position size is positive)."""
-        return self.size > 0
-
-    @property
-    def is_short(self) -> bool:
-        """True if the position is short (position size is negative)."""
-        return self.size < 0
-
-    def __repr__(self):
-        return (
-            f"<Position[{self.__instrument}]: {self.size} ({len(self.trades)} trades)>"
-        )

pytrade/strategy.py

@@ -9,7 +9,6 @@
     MINUTES_MAP,
     UPDATE_MAP,
     CandleSubscription,
-    FxInstrument,
     Granularity,
     Instrument,
 )

tests/unit/test_models.py

@@ -2,10 +2,9 @@
 from unittest.mock import MagicMock
 
 import pandas as pd
-import pytest
 from pandas import Timestamp
 
-from pytrade.models import Order, Position, TimeInForce, Trade
+from pytrade.models import Order, TimeInForce, Trade
 
 
 def test_order():
@@ -109,100 +108,3 @@ def test_trade_reduce():
     trade.reduce(50)
 
     assert trade.size == 50
-
-
-def test_position():
-    instrument_1 = "ABC"
-    instrument_2 = "GOOG"
-
-    entry_price = 98.90
-    last_price = 105
-    time1 = Timestamp(datetime.now())
-    exit_price = 110.50
-    time2 = time1 + timedelta(days=1, hours=2)
-    goog_data = MagicMock()
-    goog_data.last_price = last_price
-    goog_df = pd.DataFrame(
-        {"Timestamp": [time1, time2], "Close": [entry_price, exit_price]}
-    )
-    goog_df = goog_df.set_index("Timestamp")
-    goog_data.df = goog_df
-
-    abc_data = MagicMock()
-    abc_data.last_price = last_price
-    abc_df = pd.DataFrame(
-        {"Timestamp": [time1, time2], "Close": [entry_price, exit_price]}
-    )
-    abc_df = abc_df.set_index("Timestamp")
-    abc_data.df = abc_df
-
-    abc_trades = [
-        Trade(instrument_1, 100, 90, time1, abc_data),
-        Trade(instrument_1, 150, 85, time2, abc_data),
-    ]
-    goog_trades = [
-        Trade(instrument_2, 100, 90, time1, goog_data),
-        Trade(instrument_2, 200, 100, time2, goog_data),
-    ]
-    trades = abc_trades + goog_trades
-
-    position = Position(instrument_2, trades)
-
-    assert len(position.trades) == 2
-    assert position.size == 300
-    assert position.pl == 2500
-    trade1_pl_pct = (last_price / 90 - 1) * 100
-    trade2_pl_pct = (last_price / 100 - 1) * 100
-    position_pl_pct = (
-        0.3333333333333333 * trade1_pl_pct + 0.6666666666666666 * trade2_pl_pct
-    )
-    assert position.pl_pct == position_pl_pct
-    assert position.is_long is True
-    assert position.is_short is False
-
-
-def test_position_close():
-    instrument_1 = "ABC"
-    instrument_2 = "GOOG"
-
-    entry_price = 98.90
-    last_price = 105
-    time1 = Timestamp(datetime.now())
-    exit_price = 110.50
-    time2 = time1 + timedelta(days=1, hours=2)
-    goog_data = MagicMock()
-    goog_data.last_price = last_price
-    goog_df = pd.DataFrame(
-        {"Timestamp": [time1, time2], "Close": [entry_price, exit_price]}
-    )
-    goog_df = goog_df.set_index("Timestamp")
-    goog_data.df = goog_df
-
-    abc_data = MagicMock()
-    abc_data.last_price = last_price
-    abc_df = pd.DataFrame(
-        {"Timestamp": [time1, time2], "Close": [entry_price, exit_price]}
-    )
-    abc_df = abc_df.set_index("Timestamp")
-    abc_data.df = abc_df
-
-    abc_trades = [
-        Trade(instrument_1, 100, 90, time1, abc_data),
-        Trade(instrument_1, 150, 85, time2, abc_data),
-    ]
-    trade_1 = Trade(instrument_2, 100, 90, time1, goog_data)
-    trade_2 = Trade(instrument_2, 200, 100, time1, goog_data)
-    goog_trades = [
-        trade_1,
-        trade_2,
-    ]
-    trades = abc_trades + goog_trades
-
-    position = Position("GOOG", trades)
-
-    trade_1.close(exit_price, time2)
-    trade_2.close(exit_price, time2)
-
-    assert position.size == 300
-    assert position.pl == 4150
-    assert position.pl_pct == pytest.approx(14.59, 1e-2)