Revert FixBacktestMixin

Does not fix all Pandas 2.1 errors. Need to come up with more maintainable way of guaranteeing backwards compatibility.
edtechre · Dec 10, 2023 · f58ef39 · f58ef39
1 parent 1c94717
commit f58ef39
Showing 1 changed file with 6 additions and 23 deletions.
diff --git a/src/pybroker/strategy.py b/src/pybroker/strategy.py
@@ -154,11 +154,7 @@ def backtest_executions(
         Returns:
             :class:`.TestResult` of the backtest.
         """
-        # TODO pandas 2.1.0
-        try:
-            test_dates = test_data[DataCol.DATE.value].unique().to_numpy()
-        except AttributeError:
-            test_dates = test_data[DataCol.DATE.value].unique()
+        test_dates = test_data[DataCol.DATE.value].unique()
         test_dates.sort()
         test_syms = test_data[DataCol.SYMBOL.value].unique()
         test_data = (
@@ -194,19 +190,10 @@ def backtest_executions(
                 )
                 if exec.fn is not None:
                     exec_fns[sym] = exec.fn
-        # TODO pandas 2.1.0
-        try:
-            sym_exec_dates = {
-                sym: frozenset(
-                    test_data.loc[pd.IndexSlice[sym, :]].index.to_numpy()
-                )
-                for sym in exec_ctxs.keys()
-            }
-        except AttributeError:
-            sym_exec_dates = {
-                sym: frozenset(test_data.loc[pd.IndexSlice[sym, :]].index)
-                for sym in exec_ctxs.keys()
-            }
+        sym_exec_dates = {
+            sym: frozenset(test_data.loc[pd.IndexSlice[sym, :]].index.values)
+            for sym in exec_ctxs.keys()
+        }
         cover_sched: dict[np.datetime64, list[ExecResult]] = defaultdict(list)
         buy_sched: dict[np.datetime64, list[ExecResult]] = defaultdict(list)
         sell_sched: dict[np.datetime64, list[ExecResult]] = defaultdict(list)
@@ -657,11 +644,7 @@ def walkforward_split(
             raise ValueError("DataFrame is empty.")
         date_col = DataCol.DATE.value
         dates = df[[date_col]]
-        # TODO pandas 2.1.0
-        try:
-            window_dates = df[date_col].unique().to_numpy()
-        except AttributeError:
-            window_dates = df[date_col].unique()
+        window_dates = df[date_col].unique()
         window_dates.sort()
         error_msg = f"""
         Invalid params for {len(window_dates)} dates: