googleapis · sycai · Feb 14, 2025 · Feb 11, 2025 · Feb 12, 2025 · Feb 12, 2025
@@ -747,6 +747,11 @@ def timestamp_add_op_impl(x: ibis_types.TimestampValue, y: ibis_types.IntegerVal
     return x + y.to_interval("us")
 
 
+@scalar_op_compiler.register_binary_op(ops.timestamp_sub_op)
+def timestamp_sub_op_impl(x: ibis_types.TimestampValue, y: ibis_types.IntegerValue):
+    return x - y.to_interval("us")
+
+
 @scalar_op_compiler.register_unary_op(ops.FloorDtOp, pass_op=True)
 def floor_dt_op_impl(x: ibis_types.Value, op: ops.FloorDtOp):
     supported_freqs = ["Y", "Q", "M", "W", "D", "h", "min", "s", "ms", "us", "ns"]

@@ -110,6 +110,9 @@ def _rewrite_sub_op(left: _TypedExpr, right: _TypedExpr) -> _TypedExpr:
     if dtypes.is_datetime_like(left.dtype) and dtypes.is_datetime_like(right.dtype):
         return _TypedExpr.create_op_expr(ops.timestamp_diff_op, left, right)
 
+    if dtypes.is_datetime_like(left.dtype) and right.dtype is dtypes.TIMEDELTA_DTYPE:
+        return _TypedExpr.create_op_expr(ops.timestamp_sub_op, left, right)
+
     return _TypedExpr.create_op_expr(ops.sub_op, left, right)
 
 

@@ -178,7 +178,11 @@
 )
 from bigframes.operations.struct_ops import StructFieldOp, StructOp
 from bigframes.operations.time_ops import hour_op, minute_op, normalize_op, second_op
-from bigframes.operations.timedelta_ops import timestamp_add_op, ToTimedeltaOp
+from bigframes.operations.timedelta_ops import (
+    timestamp_add_op,
+    timestamp_sub_op,
+    ToTimedeltaOp,
+)
 
 __all__ = [
     # Base ops
@@ -251,6 +255,7 @@
     "normalize_op",
     # Timedelta ops
     "timestamp_add_op",
+    "timestamp_sub_op",
     "ToTimedeltaOp",
     # Datetime ops
     "date_op",

@@ -151,6 +151,9 @@ def output_type(self, *input_types):
         if dtypes.is_datetime_like(left_type) and dtypes.is_datetime_like(right_type):
             return dtypes.TIMEDELTA_DTYPE
 
+        if dtypes.is_datetime_like(left_type) and right_type is dtypes.TIMEDELTA_DTYPE:
+            return left_type
+
         raise TypeError(f"Cannot subtract dtypes {left_type} and {right_type}")
 
 

@@ -54,3 +54,23 @@ def output_type(self, *input_types: dtypes.ExpressionType) -> dtypes.ExpressionT
 
 
 timestamp_add_op = TimestampAdd()
+
+
+@dataclasses.dataclass(frozen=True)
+class TimestampSub(base_ops.BinaryOp):
+    name: typing.ClassVar[str] = "timestamp_sub"
+
+    def output_type(self, *input_types: dtypes.ExpressionType) -> dtypes.ExpressionType:
+        # timestamp - timedelta => timestamp
+        if (
+            dtypes.is_datetime_like(input_types[0])
+            and input_types[1] is dtypes.TIMEDELTA_DTYPE
+        ):
+            return input_types[0]
+
+        raise TypeError(
+            f"unsupported types for timestamp_sub. left: {input_types[0]} right: {input_types[1]}"
+        )
+
+
+timestamp_sub_op = TimestampSub()
@@ -178,6 +178,96 @@ def test_timestamp_add_dataframes(temporal_dfs):
     )
 
 
+@pytest.mark.parametrize(
+    ("column", "pd_dtype"),
+    [
+        ("datetime_col", "<M8[ns]"),
+        ("timestamp_col", "datetime64[ns, UTC]"),
+    ],
+)
+def test_timestamp_sub__ts_series_minus_td_series(temporal_dfs, column, pd_dtype):
+    bf_df, pd_df = temporal_dfs
+
+    actual_result = (
+        (bf_df[column] - bf_df["timedelta_col_1"]).to_pandas().astype(pd_dtype)
+    )
+
+    expected_result = pd_df[column] - pd_df["timedelta_col_1"]
+    pandas.testing.assert_series_equal(
+        actual_result, expected_result, check_index_type=False
+    )
+
+
+@pytest.mark.parametrize(
+    ("column", "pd_dtype"),
+    [
+        ("datetime_col", "<M8[ns]"),
+        ("timestamp_col", "datetime64[ns, UTC]"),
+    ],
+)
+def test_timestamp_sub__ts_series_minus_td_literal(temporal_dfs, column, pd_dtype):
+    bf_df, pd_df = temporal_dfs
+    literal = pd.Timedelta(1, "h")
+
+    actual_result = (bf_df[column] - literal).to_pandas().astype(pd_dtype)
+
+    expected_result = pd_df[column] - literal
+    pandas.testing.assert_series_equal(
+        actual_result, expected_result, check_index_type=False
+    )
+
+
+def test_timestamp_sub__ts_literal_minus_td_series(temporal_dfs):
+    bf_df, pd_df = temporal_dfs
+    literal = pd.Timestamp("2025-01-01 01:00:00")
+
+    actual_result = (literal - bf_df["timedelta_col_1"]).to_pandas().astype("<M8[ns]")
+
+    expected_result = literal - pd_df["timedelta_col_1"]
+    pandas.testing.assert_series_equal(
+        actual_result, expected_result, check_index_type=False
+    )
+
+
+@pytest.mark.parametrize(
+    ("column", "pd_dtype"),
+    [
+        ("datetime_col", "<M8[ns]"),
+        ("timestamp_col", "datetime64[ns, UTC]"),
+    ],
+)
+def test_timestamp_sub_with_numpy_op(temporal_dfs, column, pd_dtype):
+    bf_df, pd_df = temporal_dfs
+
+    actual_result = (
+        np.subtract(bf_df[column], bf_df["timedelta_col_1"])
+        .to_pandas()
+        .astype(pd_dtype)
+    )
+
+    expected_result = np.subtract(pd_df[column], pd_df["timedelta_col_1"])
+    pandas.testing.assert_series_equal(
+        actual_result, expected_result, check_index_type=False
+    )
+
+
+def test_timestamp_sub_dataframes(temporal_dfs):
+    columns = ["datetime_col", "timestamp_col"]
+    timedelta = pd.Timedelta(1, unit="s")
+    bf_df, pd_df = temporal_dfs
+
+    actual_result = (bf_df[columns] - timedelta).to_pandas()
+    actual_result["datetime_col"] = actual_result["datetime_col"].astype("<M8[ns]")
+    actual_result["timestamp_col"] = actual_result["timestamp_col"].astype(
+        "datetime64[ns, UTC]"
+    )
+
+    expected_result = pd_df[columns] - timedelta
+    pandas.testing.assert_frame_equal(
+        actual_result, expected_result, check_index_type=False
+    )
+
+
 @pytest.mark.parametrize(
     "compare_func",
     [