feat(python): 30x speedup initialising Series from python range o…

…bject (#5397)

py-polars/polars/internals/lazy_functions.py

@@ -1387,11 +1387,13 @@ def arange(
     """
     low = pli.expr_to_lit_or_expr(low, str_to_lit=False)
     high = pli.expr_to_lit_or_expr(high, str_to_lit=False)
-
     if eager:
-        df = pli.DataFrame({"a": [1]})
-        return df.select(arange(low, high, step).alias("arange"))["arange"]
-
+        return (
+            pli.DataFrame()
+            .select(arange(low, high, step))
+            .to_series()
+            .rename("arange", in_place=True)
+        )
     return pli.wrap_expr(pyarange(low._pyexpr, high._pyexpr, step))
 
 

py-polars/polars/internals/series/series.py

@@ -206,8 +206,10 @@ def __init__(
             )
         elif isinstance(values, Series):
             self._s = series_to_pyseries(name, values)
+
         elif _PYARROW_TYPE(values) and isinstance(values, (pa.Array, pa.ChunkedArray)):
             self._s = arrow_to_pyseries(name, values)
+
         elif _NUMPY_TYPE(values) and isinstance(values, np.ndarray):
             self._s = numpy_to_pyseries(name, values, strict, nan_to_null)
             if values.dtype.type == np.datetime64:
@@ -223,6 +225,13 @@ def __init__(
 
             if dtype is not None:
                 self._s = self.cast(dtype, strict=True)._s
+
+        elif isinstance(values, range):
+            self._s = (
+                pli.arange(values.start, values.stop, values.step, eager=True)
+                .rename(name, in_place=True)
+                ._s
+            )
         elif isinstance(values, Sequence):
             self._s = sequence_to_pyseries(
                 name, values, dtype=dtype, strict=strict, dtype_if_empty=dtype_if_empty