tweak (#36)

src/alpaca_daily_losers/liquidate.py

@@ -5,9 +5,10 @@
 
 from alpaca_daily_losers.global_functions import send_message, send_position_messages
 
+LIQUIDATE_PERCENTAGE = 1.0
+
 
 class Liquidate:
-    FIXED_FEE = 5.00
 
     def __init__(self, trading_client: Trading, py_logger: logging.Logger):
         self.trade = trading_client
@@ -25,7 +26,7 @@ def calculate_cash_needed(total_holdings: float, cash_row: pd.DataFrame) -> floa
         Returns:
             float: The amount of cash needed for liquidation, including a fixed fee of $5.00.
         """
-        return (total_holdings * 0.1 - cash_row["market_value"].iloc[0]) + Liquidate.FIXED_FEE
+        return total_holdings * 0.1 - cash_row["market_value"].iloc[0]
 
     @staticmethod
     def get_top_performers(current_positions: pd.DataFrame) -> pd.DataFrame:
@@ -39,13 +40,11 @@ def get_top_performers(current_positions: pd.DataFrame) -> pd.DataFrame:
             pd.DataFrame: DataFrame containing the top performers.
         """
         non_cash_positions = current_positions[current_positions["symbol"] != "Cash"]
-        non_cash_positions = non_cash_positions[non_cash_positions["profit_pct"] > 0.5].sort_values(
-            by="profit_pct", ascending=False
-        )
+        non_cash_positions = non_cash_positions[
+            non_cash_positions["profit_pct"] > LIQUIDATE_PERCENTAGE
+        ].sort_values(by="profit_pct", ascending=False)
 
-        return non_cash_positions.iloc[
-            : len(non_cash_positions) // 2 if len(non_cash_positions) > 1 else 1
-        ]
+        return non_cash_positions.iloc[: len(non_cash_positions)]
 
     def liquidate_positions(self) -> None:
         """

tests/test_liquidate.py

@@ -7,12 +7,12 @@ def test_calculate_cash_needed():
     cash_row = pd.DataFrame({"market_value": [200.0]})
 
     # Test with a total_holdings value that would result in a positive cash direction after fee
-    assert Liquidate.calculate_cash_needed(3000.0, cash_row) == 105.0
+    assert Liquidate.calculate_cash_needed(3000.0, cash_row) == 100.0
 
     # Test with a negative cash direction in cash_row and total_holdings being 2000.0
     negative_cash_row = pd.DataFrame({"market_value": [-200.0]})
-    assert Liquidate.calculate_cash_needed(2000.0, negative_cash_row) == 405.00
-    assert Liquidate.calculate_cash_needed(0.0, cash_row) == -195.0
+    assert Liquidate.calculate_cash_needed(2000.0, negative_cash_row) == 400.00
+    assert Liquidate.calculate_cash_needed(0.0, cash_row) == -200.00
 
 
 def test_liquidates_positions_when_cash_less_than_10_percent_with_sold_positions_with_empty(
@@ -31,7 +31,7 @@ def test_liquidates_positions_when_cash_less_than_10_percent_with_sold_positions
         {
             "symbol": ["AAPL", "GOOGL", "Cash"],
             "market_value": [5000, 3000, 500],
-            "profit_pct": [2.0, 1.1, 0],
+            "profit_pct": [2.0, 0.4, 0],
         }
     )
     mock_trade.positions.get_all.return_value = current_positions

tests/test_liquidate4.py

@@ -61,7 +61,7 @@ def test_calculate_cash_needed(self):
         total_holdings = 13245.0
         cash_row = pd.DataFrame([{"symbol": "Cash", "market_value": 0}])
         cash_needed = self.liquidator.calculate_cash_needed(total_holdings, cash_row)
-        assert cash_needed == 1324.5 + 5.00
+        assert cash_needed == 1324.5
 
     def test_get_top_performers(self):
         current_positions = pd.DataFrame(

tests/test_liquidate5.py

@@ -29,19 +29,19 @@ def test_calculate_cash_needed():
     total_holdings = 10000.0
     cash_row = pd.DataFrame({"market_value": [500.0]})
     result = Liquidate.calculate_cash_needed(total_holdings, cash_row)
-    assert result == 505.0
+    assert result == 500.0
 
 
 def test_get_top_performers():
     current_positions = pd.DataFrame(
-        {"symbol": ["AAPL", "MSFT", "GOOGL", "Cash"], "profit_pct": [5, 20, 30, 0]}
+        {"symbol": ["AAPL", "MSFT", "GOOGL", "Cash"], "profit_pct": [0.2, 20, 30, 0]}
     )
     result = Liquidate.get_top_performers(current_positions)
     expected = pd.DataFrame({"symbol": ["GOOGL", "MSFT"], "profit_pct": [30, 20]})
     assert (
         result["symbol"].tolist()
         == expected["symbol"]
-        .iloc[: len(current_positions[current_positions["symbol"] != "Cash"]) // 2]
+        .iloc[: len(current_positions[current_positions["symbol"] != "Cash"])]
         .tolist()
     )