Windowell Expressions |verified| < macOS FRESH >

def range_between(self, start: int, end: int): self.frame = WindowFrame( start=(start, FrameBound.PRECEDING), end=(end, FrameBound.FOLLOWING), frame_type="range" ) return self

def partition(self, *columns): self.partition_by.extend(columns) return self windowell expressions

@dataclass class WindowFrame: start: tuple[int, FrameBound] # (offset, bound_type) end: tuple[int, FrameBound] frame_type: str = "rows" # rows, range, groups def range_between(self, start: int, end: int): self

def test_dynamic_boundary(self): self.df['threshold'] = [1, 2, 1, 3, 2] dynamic = DynamicBoundary(lambda df: df['threshold'].median()) self.assertEqual(dynamic.evaluate(self.df), 2) if == ' main ': unittest.main() 5. Performance Optimizations class OptimizedWindowellEngine(WindowellEngine): """Performance-optimized version""" def apply_window_optimized(self, df, window, agg_func, alias): """Use vectorized operations where possible""" window_expr = self.resolve_window(window) if not window_expr.order_by and not window_expr.frame: # Simple partition aggregate (fast path) return df.assign(** alias: df.groupby(window_expr.partition_by)[agg_func.__name__].transform(agg_func) ) # Use numba for JIT-compiled rolling windows if window_expr.frame and window_expr.frame.frame_type == 'rows': return self._numba_rolling_apply(df, window_expr, agg_func, alias) return super().apply_window(df, window, agg_func, alias) end: int): self.frame = WindowFrame( start=(start

def setUp(self): self.engine = WindowellEngine() self.df = pd.DataFrame( 'product': ['A', 'A', 'A', 'B', 'B'], 'date': pd.date_range('2024-01-01', periods=5), 'sales': [100, 150, 200, 50, 75] )

@staticmethod def overlay(window1: WindowellExpression, window2: WindowellExpression): """Overlay windows: combine frame definitions""" return WindowellExpression( partition_by=window1.partition_by or window2.partition_by, order_by=window1.order_by or window2.order_by, frame=window2.frame if window2.frame else window1.frame ) class DynamicBoundary: """Compute frame boundaries dynamically from data""" def __init__(self, expression: Callable[[pd.DataFrame], int]): self.expression = expression