feat: main class

auto_trading/orders.py

@@ -17,6 +17,9 @@ class Long(Order):
         """The amount in $"""
         return self.amount * self.price
 
+    def __repr__(self) -> str:
+        return f"{self.__class__.__name__}({self.stock}: {self.amount_usd}$)"
+
 
 @dataclass
 class Short(Order):
@@ -30,3 +33,6 @@ class Short(Order):
     def amount_usd(self) -> float:
         """The amount in $"""
         return self.amount * self.price
+
+    def __repr__(self) -> str:
+        return f"{self.__class__.__name__}({self.stock}: {self.amount_usd}$)"

main.py

@@ -1,44 +1,19 @@
 from auto_trading.broker.backtest import Backtest
-from auto_trading.strat.all_in import AllIn
+from auto_trading.strat.hold import Hold
 from auto_trading.ptf.in_memory import InMemoryPortfolio
-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.bot import Bot
-from tqdm import tqdm  # type: ignore
-import pandas as pd  # type: ignore
-
-pd.options.plotting.backend = "plotly"
 
 
 if __name__ == "__main__":
-    csv = "data/gold.csv"
-
-    bt = Backtest(csv, start=10)
-
-    start = {name: 0 for name in bt.data.columns}
-    start["USD"] = 10_000
-
-    pred = MeanAggregator(
-        [RandomPredictor(), SelectorPredictor({"USD": -0.1}), RandomPredictor()]
-    )
-
-    bot = Bot(
-        ptf=InMemoryPortfolio(start.copy()), strategy=AllIn(), broker=bt, predictor=pred
+    bt = Backtest("./data/NYSE_smallest.csv")
+    ptf = InMemoryPortfolio(
+        base_balance=100, change_rate_getter=lambda: bt.current_change
     )
+    strategy = Hold("GOOGL")
 
-    data = pd.DataFrame(index=bt.data.index, columns=bt.data.columns)
+    bot = Bot(ptf, strategy, bt)
 
-    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()
-        }
-        data.loc[date] = converted_investments
-    bot.print_results()
+    bot.run()
 
-    # data.plot().show()  # faster plot
-    data.plot.area().show()
+    for order in ptf.history:
+        print(order)

tests/orders/test_orders.py

@@ -18,3 +18,19 @@ from auto_trading.orders import Short, Long
 def test_order_usd(order: Union[Long, Short], usd: float):
     """Test the USD value of an order."""
     assert order.amount_usd == usd
+
+
+@pytest.mark.parametrize(
+    "order, string",
+    [
+        (Long("BTC", 1, 1), "Long(BTC: 1$)"),
+        (Short("BTC", 1, 1), "Short(BTC: 1$)"),
+        (Long("BTC", 1, 10), "Long(BTC: 10$)"),
+        (Short("BTC", 1, 10), "Short(BTC: 10$)"),
+        (Long("BTC", 10, 1), "Long(BTC: 10$)"),
+        (Short("BTC", 10, 1), "Short(BTC: 10$)"),
+    ],
+)
+def test_repr(order: Union[Long, Short], string: str):
+    """Test repr of an order."""
+    assert repr(order) == string