chore: bump pyarrow-stubs==19.1

narwhals/_arrow/series.py

@@ -191,11 +191,11 @@ def __narwhals_namespace__(self: Self) -> ArrowNamespace:
 
     def __eq__(self: Self, other: object) -> Self:  # type: ignore[override]
         ser, other = extract_native(self, other)
-        return self._with_native(pc.equal(ser, other))  # type: ignore[arg-type]
+        return self._with_native(pc.equal(ser, other))  # type: ignore[call-overload]
 
     def __ne__(self: Self, other: object) -> Self:  # type: ignore[override]
         ser, other = extract_native(self, other)
-        return self._with_native(pc.not_equal(ser, other))  # type: ignore[arg-type]
+        return self._with_native(pc.not_equal(ser, other))  # type: ignore[call-overload]
 
     def __ge__(self: Self, other: Any) -> Self:
         ser, other = extract_native(self, other)
@@ -271,14 +271,14 @@ def __truediv__(self: Self, other: Any) -> Self:
         if not isinstance(other, (pa.Array, pa.ChunkedArray)):
             # scalar
             other = lit(other)
-        return self._with_native(pc.divide(*cast_for_truediv(ser, other)))
+        return self._with_native(pc.divide(*cast_for_truediv(ser, other)))  # type: ignore[arg-type, type-var]
 
     def __rtruediv__(self: Self, other: Any) -> Self:
         ser, other = extract_native(self, other)
         if not isinstance(other, (pa.Array, pa.ChunkedArray)):
             # scalar
             other = lit(other) if not isinstance(other, pa.Scalar) else other
-        return self._with_native(pc.divide(*cast_for_truediv(other, ser)))  # pyright: ignore[reportArgumentType]
+        return self._with_native(pc.divide(*cast_for_truediv(other, ser)))  # type: ignore[arg-type, type-var]
 
     def __mod__(self: Self, other: Any) -> Self:
         floor_div = (self // other).native
@@ -596,11 +596,11 @@ def value_counts(
         counts = cast("ArrowChunkedArray", val_counts.field("counts"))
 
         if normalize:
-            arrays = [values, pc.divide(*cast_for_truediv(counts, pc.sum(counts)))]
+            arrays = [values, pc.divide(*cast_for_truediv(counts, pc.sum(counts)))]  # type: ignore[type-var]
         else:
             arrays = [values, counts]
 
-        val_count = pa.Table.from_arrays(arrays, names=[index_name_, value_name_])
+        val_count = pa.Table.from_arrays(arrays, names=[index_name_, value_name_])  # type: ignore[arg-type]
 
         if sort:
             val_count = val_count.sort_by([(value_name_, "descending")])
@@ -662,7 +662,7 @@ def fill_aux(
                 )[::-1]
                 distance = valid_index - indices
             return pc.if_else(
-                pc.and_(pc.is_null(arr), pc.less_equal(distance, lit(limit))),
+                pc.and_(pc.is_null(arr), pc.less_equal(distance, lit(limit))),  # pyright: ignore[reportArgumentType, reportCallIssue]
                 arr.take(valid_index),
                 arr,
             )
@@ -1041,8 +1041,6 @@ def rank(
             )
             raise ValueError(msg)
 
-        # ignore-banned-import
-
         sort_keys: Order = "descending" if descending else "ascending"
         tiebreaker: TieBreaker = "first" if method == "ordinal" else method
 
@@ -1078,7 +1076,7 @@ def _hist_from_bin_count(bin_count: int):  # type: ignore[no-untyped-def] # noqa
             lower, upper = d["min"], d["max"]
             pa_float = pa.type_for_alias("float")
             if lower == upper:
-                range_ = lit(1.0)
+                range_: pa.Scalar[Any] = lit(1.0)
                 mid = lit(0.5)
                 width = pc.divide(range_, lit(bin_count))
                 lower = pc.subtract(lower, mid)
@@ -1094,9 +1092,9 @@ def _hist_from_bin_count(bin_count: int):  # type: ignore[no-untyped-def] # noqa
             bin_indices = pc.if_else(
                 pc.and_(
                     pc.equal(bin_indices, bin_proportions),
-                    pc.greater(bin_indices, 0),
+                    pc.greater(bin_indices, lit(0)),
                 ),
-                pc.subtract(bin_indices, 1),
+                pc.subtract(bin_indices, lit(1)),
                 bin_indices,
             )
             possible = pa.Table.from_arrays(

narwhals/_arrow/series_dt.py

@@ -16,7 +16,6 @@
     from typing_extensions import Self
 
     from narwhals._arrow.series import ArrowSeries
-    from narwhals._arrow.typing import ArrowChunkedArray
     from narwhals.dtypes import Datetime
     from narwhals.typing import TimeUnit
 
@@ -56,47 +55,48 @@ def timestamp(self: Self, time_unit: TimeUnit) -> ArrowSeries:
             s_cast = self.native.cast(pa.int64())
             if unit == "ns":
                 if time_unit == "ns":
-                    result = s_cast
+                    result_64 = s_cast
                 elif time_unit == "us":
-                    result = floordiv_compat(s_cast, 1_000)
+                    result_64 = floordiv_compat(s_cast, 1_000)
                 else:
-                    result = floordiv_compat(s_cast, 1_000_000)
+                    result_64 = floordiv_compat(s_cast, 1_000_000)
             elif unit == "us":
                 if time_unit == "ns":
-                    result = cast("ArrowChunkedArray", pc.multiply(s_cast, 1_000))
+                    result_64 = pc.multiply(s_cast, lit(1_000))
                 elif time_unit == "us":
-                    result = s_cast
+                    result_64 = s_cast
                 else:
-                    result = floordiv_compat(s_cast, 1_000)
+                    result_64 = floordiv_compat(s_cast, 1_000)
             elif unit == "ms":
                 if time_unit == "ns":
-                    result = cast("ArrowChunkedArray", pc.multiply(s_cast, 1_000_000))
+                    result_64 = pc.multiply(s_cast, lit(1_000_000))
                 elif time_unit == "us":
-                    result = cast("ArrowChunkedArray", pc.multiply(s_cast, 1_000))
+                    result_64 = pc.multiply(s_cast, lit(1_000))
                 else:
-                    result = s_cast
+                    result_64 = s_cast
             elif unit == "s":
                 if time_unit == "ns":
-                    result = cast("ArrowChunkedArray", pc.multiply(s_cast, 1_000_000_000))
+                    result_64 = pc.multiply(s_cast, lit(1_000_000_000))
                 elif time_unit == "us":
-                    result = cast("ArrowChunkedArray", pc.multiply(s_cast, 1_000_000))
+                    result_64 = pc.multiply(s_cast, lit(1_000_000))
                 else:
-                    result = cast("ArrowChunkedArray", pc.multiply(s_cast, 1_000))
+                    result_64 = pc.multiply(s_cast, lit(1_000))
             else:  # pragma: no cover
                 msg = f"unexpected time unit {unit}, please report an issue at https://github.com/narwhals-dev/narwhals"
                 raise AssertionError(msg)
+            return self.with_native(result_64)
         elif isinstance(ser.dtype, dtypes.Date):
-            time_s = pc.multiply(self.native.cast(pa.int32()), 86400)
+            time_s = pc.multiply(self.native.cast(pa.int32()), lit(86_400))
             if time_unit == "ns":
-                result = cast("ArrowChunkedArray", pc.multiply(time_s, 1_000_000_000))
+                result_32 = pc.multiply(time_s, lit(1_000_000_000))
             elif time_unit == "us":
-                result = cast("ArrowChunkedArray", pc.multiply(time_s, 1_000_000))
+                result_32 = pc.multiply(time_s, lit(1_000_000))
             else:
-                result = cast("ArrowChunkedArray", pc.multiply(time_s, 1_000))
+                result_32 = pc.multiply(time_s, lit(1_000))
+            return self.with_native(result_32)
         else:
             msg = "Input should be either of Date or Datetime type"
             raise TypeError(msg)
-        return self.with_native(result)
 
     def date(self: Self) -> ArrowSeries:
         return self.with_native(self.native.cast(pa.date32()))

narwhals/_pandas_like/series_dt.py

@@ -58,10 +58,12 @@ def microsecond(self) -> PandasLikeSeries:
             # crazy workaround for https://github.com/pandas-dev/pandas/issues/59154
             import pyarrow.compute as pc  # ignore-banned-import()
 
+            from narwhals._arrow.utils import lit
+
             arr_ns = self.native.array
             arr = arr_ns.__arrow_array__()
             result_arr = pc.add(
-                pc.multiply(pc.millisecond(arr), 1000), pc.microsecond(arr)
+                pc.multiply(pc.millisecond(arr), lit(1_000)), pc.microsecond(arr)
             )
             result = type(self.native)(type(arr_ns)(result_arr), name=self.native.name)
             return self.with_native(result)

pyproject.toml

@@ -67,7 +67,7 @@ typing = [
   "typing_extensions",
   "mypy~=1.15.0",
   "pyright",
-  "pyarrow-stubs==17.18",
+  "pyarrow-stubs==19.1",
   "sqlframe",
   "polars==1.25.2",
   "uv",