feat: retrive the change rate

auto_trading/interfaces.py

@@ -50,6 +50,10 @@ class DataBroker(ABC):
     def properties(self) -> CandlesProperties:
         """Return the properties of the candles for this broker."""
 
+    @abstractproperty
+    def current_change(self) -> DataFrame:
+        """Return the current change for each money."""
+
     def __iter__(self) -> "DataBroker":
         """Initialise the iterator."""
         return self

auto_trading/ptf/in_memory.py

@@ -4,6 +4,7 @@ from pandas import DataFrame  # type: ignore
 
 from ..interfaces import PTF, PTFState
 from ..orders import Long, Short
+from ..bot import Bot
 
 
 class InMemoryPortfolio(PTF):
@@ -12,12 +13,17 @@ class InMemoryPortfolio(PTF):
     _blanance: float
     _stocks: Dict[str, float]
 
+    def __init__(self, bot_class: Bot):
+        """Init the class with a pointer to the bot to retrieve the change rate."""
+        self.bot = bot_class
+
     @property
     def state(self):
-        return PTFState(
-            0,
-            self._stocks.copy(),
-        )
+        return PTFState(0, self._stocks.copy())
+
+    @property
+    def change_rate(self):
+        return self.bot.broker.change_rate
 
     def execute_short(self, order: Short) -> None:
         """Sell actions."""

main.py

@@ -5,9 +5,10 @@ from auto_trading.predictor.mean_agg import MeanAggregator
 from auto_trading.predictor.normalized import NormalizedPredictor
 from auto_trading.predictor.selector import SelectorPredictor
 from auto_trading.predictor.random_predictor import RandomPredictor
-from auto_trading.main import Bot
+from auto_trading.bot import Bot
 from tqdm import tqdm  # type: ignore
 import pandas as pd  # type: ignore
+
 pd.options.plotting.backend = "plotly"
 
 
@@ -15,11 +16,13 @@ if __name__ == "__main__":
     csv = "data/gold.csv"
 
     bt = Backtest(csv, start=10, index_col=0)
-    
+
     start = {name: 0 for name in bt.data.columns}
     start["USD"] = 10_000
 
-    pred = MeanAggregator([RandomPredictor(), SelectorPredictor({"USD": -0.1}), RandomPredictor()])
+    pred = MeanAggregator(
+        [RandomPredictor(), SelectorPredictor({"USD": -0.1}), RandomPredictor()]
+    )
 
     bot = Bot(
         ptf=InMemoryPortfolio(start.copy()), strategy=AllIn(), broker=bt, predictor=pred
@@ -30,7 +33,10 @@ if __name__ == "__main__":
     for date in tqdm(data.index):
         bot.run_once()
         current_investments = bot.ptf.content()
-        converted_investments = {name: amount * bot.current_conversion_rate[name] for name, amount in current_investments.items()}
+        converted_investments = {
+            name: amount * bot.current_conversion_rate[name]
+            for name, amount in current_investments.items()
+        }
         data.loc[date] = converted_investments
     bot.print_results()