Struct scalar from host dictionary (#8629)

Allows the creation of a `struct_scalar` from python dictionary. Partly addresses #8558.

Authors:
  - https://github.com/shaneding

Approvers:
  - https://github.com/brandon-b-miller
  - Ram (Ramakrishna Prabhu) (https://github.com/rgsl888prabhu)

URL: #8629

python/cudf/cudf/_lib/cpp/scalar/scalar.pxd

@@ -70,4 +70,5 @@ cdef extern from "cudf/scalar/scalar.hpp" namespace "cudf" nogil:
         column_view view() except +
 
     cdef cppclass struct_scalar(scalar):
+        struct_scalar(table_view cols, bool valid) except +
         table_view view() except +

python/cudf/cudf/_lib/scalar.pyx

@@ -30,7 +30,7 @@ from cudf._lib.column cimport Column
 from cudf._lib.cpp.column.column_view cimport column_view
 from cudf._lib.cpp.table.table_view cimport table_view
 from cudf._lib.table cimport Table
-from cudf._lib.interop import to_arrow
+from cudf._lib.interop import to_arrow, from_arrow
 
 from cudf._lib.cpp.wrappers.timestamps cimport (
     timestamp_s,
@@ -87,6 +87,8 @@ cdef class DeviceScalar:
         elif isinstance(dtype, cudf.ListDtype):
             _set_list_from_pylist(
                 self.c_value, value, dtype, valid)
+        elif isinstance(dtype, cudf.StructDtype):
+            _set_struct_from_pydict(self.c_value, value, dtype, valid)
         elif pd.api.types.is_string_dtype(dtype):
             _set_string_from_np_string(self.c_value, value, valid)
         elif pd.api.types.is_numeric_dtype(dtype):
@@ -172,7 +174,6 @@ cdef class DeviceScalar:
 
         s.c_value = move(ptr)
         cdtype = s.get_raw_ptr()[0].type()
-
         if cdtype.id() == libcudf_types.DECIMAL64 and dtype is None:
             raise TypeError(
                 "Must pass a dtype when constructing from a fixed-point scalar"
@@ -308,6 +309,36 @@ cdef _set_decimal64_from_scalar(unique_ptr[scalar]& s,
         )
     )
 
+cdef _set_struct_from_pydict(unique_ptr[scalar]& s,
+                             object value,
+                             object dtype,
+                             bool valid=True):
+    arrow_schema = dtype.to_arrow()
+    columns = [str(i) for i in range(len(arrow_schema))]
+    if valid:
+        pyarrow_table = pa.Table.from_arrays(
+            [
+                pa.array([value[f.name]], from_pandas=True, type=f.type)
+                for f in arrow_schema
+            ],
+            names=columns
+        )
+    else:
+        pyarrow_table = pa.Table.from_arrays(
+            [
+                pa.array([], from_pandas=True, type=f.type)
+                for f in arrow_schema
+            ],
+            names=columns
+        )
+
+    cdef Table table = from_arrow(pyarrow_table, column_names=columns)
+    cdef table_view struct_view = table.view()
+
+    s.reset(
+        new struct_scalar(struct_view, valid)
+    )
+
 cdef _get_py_dict_from_struct(unique_ptr[scalar]& s):
     if not s.get()[0].is_valid():
         return cudf.NA

python/cudf/cudf/core/scalar.py

@@ -7,7 +7,7 @@
 
 from cudf._lib.scalar import DeviceScalar, _is_null_host_scalar
 from cudf.core.column.column import ColumnBase
-from cudf.core.dtypes import Decimal64Dtype, ListDtype
+from cudf.core.dtypes import Decimal64Dtype, ListDtype, StructDtype
 from cudf.core.index import BaseIndex
 from cudf.core.series import Series
 from cudf.utils.dtypes import (
@@ -131,6 +131,21 @@ def _preprocess_host_value(self, value, dtype):
                 raise ValueError(f"Can not coerce {value} to ListDtype")
             else:
                 return NA, dtype
+
+        if isinstance(value, dict):
+            if dtype is not None:
+                raise TypeError("dict may not be cast to a different dtype")
+            else:
+                dtype = StructDtype.from_arrow(
+                    pa.infer_type([value], from_pandas=True)
+                )
+                return value, dtype
+        elif isinstance(dtype, StructDtype):
+            if value is not None:
+                raise ValueError(f"Can not coerce {value} to StructDType")
+            else:
+                return NA, dtype
+
         if isinstance(dtype, Decimal64Dtype):
             value = pa.scalar(
                 value, type=pa.decimal128(dtype.precision, dtype.scale)

python/cudf/cudf/tests/test_struct.py

@@ -6,6 +6,7 @@
 import pytest
 
 import cudf
+from cudf.core.dtypes import StructDtype
 from cudf.testing._utils import assert_eq
 
 
@@ -98,3 +99,23 @@ def test_serialize_struct_dtype(fields):
 def test_struct_getitem(series, expected):
     sr = cudf.Series(series)
     assert sr[0] == expected
+
+
+@pytest.mark.parametrize(
+    "data",
+    [
+        {"a": 1, "b": "rapids", "c": [1, 2, 3, 4]},
+        {"a": 1, "b": "rapids", "c": [1, 2, 3, 4], "d": cudf.NA},
+        {"a": "Hello"},
+        {"b": [], "c": [1, 2, 3]},
+    ],
+)
+def test_struct_scalar_host_construction(data):
+    slr = cudf.Scalar(data)
+    assert slr.value == data
+    assert list(slr.device_value.value.values()) == list(data.values())
+
+
+def test_struct_scalar_null():
+    slr = cudf.Scalar(cudf.NA, dtype=StructDtype)
+    assert slr.device_value.value is cudf.NA