remove all ctypes.pointer[]

python-package/xgboost/core.py

@@ -33,29 +33,31 @@
 # ArrayLike = Union[np.ndarray, Sequence]
 ArrayLike = Any
 T = TypeVar("T")
-ctype_t = Union[ctypes.c_void_p, ctypes.c_char_p, ctypes.c_int, ctypes.c_float, ctypes.c_uint, ctypes.c_size_t]
 
-ctype_numeric_t = Union[
+ctype_t = Union[ctypes.c_void_p, ctypes.c_char_p, ctypes.c_int, ctypes.c_float, ctypes.c_uint, ctypes.c_size_t]
+c_numeric_t = Union[
     ctypes.c_float,
     ctypes.c_double,
     ctypes.c_uint,
     ctypes.c_uint64,
     ctypes.c_int32,
     ctypes.c_int64
 ]
-
-# cptr_numeric_t = Union[
+# c_numeric_t = Union[
 #     ctypes.pointer[ctypes.c_float],
 #     ctypes.pointer[ctypes.c_double],
 #     ctypes.pointer[ctypes.c_uint],
 #     ctypes.pointer[ctypes.c_uint64],
 #     ctypes.pointer[ctypes.c_int32],
 #     ctypes.pointer[ctypes.c_int64],
 # ]
-cptr_numeric_t = ctypes.pointer
-
-# cstr_ptr_t = ctypes.pointer[ctypes.c_char_p]
-cstr_ptr_t = Any
+c_numeric_ptr_t = ctypes.pointer
+# c_str_ptr_t = ctypes.pointer[ctypes.c_char_p]
+c_str_pptr_t = Any
+# c_str_ptr_t = ctypes.pointer[ctypes.c_char]
+c_str_ptr_t = Any
+# c_float_ptr_t = ctypes.pointer[ctypes.c_float]
+c_float_ptr_t = Any
 
 DataType = Any
 cupy_t = ArrayLike
@@ -66,7 +68,7 @@ class XGBoostError(ValueError):
     """Error thrown by xgboost trainer."""
 
 
-def from_pystr_to_cstr(data: Union[str, List[str]]) -> Union[bytes, cstr_ptr_t]:
+def from_pystr_to_cstr(data: Union[str, List[str]]) -> Union[bytes, c_str_pptr_t]:
     """Convert a Python str or list of Python str to C pointer
 
     Parameters
@@ -85,7 +87,7 @@ def from_pystr_to_cstr(data: Union[str, List[str]]) -> Union[bytes, cstr_ptr_t]:
     raise TypeError()
 
 
-def from_cstr_to_pystr(data: cstr_ptr_t, length: c_bst_ulong) -> List[str]:
+def from_cstr_to_pystr(data: c_str_pptr_t, length: c_bst_ulong) -> List[str]:
     """Revert C pointer to Python str
 
     Parameters
@@ -242,8 +244,8 @@ def build_info() -> dict:
     return res
 
 
-def _numpy2ctypes_type(dtype: Type[np.number]) -> Type[ctype_numeric_t]:
-    _NUMPY_TO_CTYPES_MAPPING: Dict[Type[np.number], Type[ctype_numeric_t]] = {
+def _numpy2ctypes_type(dtype: Type[np.number]) -> Type[c_numeric_t]:
+    _NUMPY_TO_CTYPES_MAPPING: Dict[Type[np.number], Type[c_numeric_t]] = {
         np.float32: ctypes.c_float,
         np.float64: ctypes.c_double,
         np.uint32: ctypes.c_uint,
@@ -271,9 +273,9 @@ def _cuda_array_interface(data: DataType) -> bytes:
     return interface_str
 
 
-def ctypes2numpy(cptr: cptr_numeric_t, length: int, dtype: Type[np.number]) -> np.ndarray:
+def ctypes2numpy(cptr: c_numeric_ptr_t, length: int, dtype: Type[np.number]) -> np.ndarray:
     """Convert a ctypes pointer array to a numpy array."""
-    ctype: Type[ctype_numeric_t] = _numpy2ctypes_type(dtype)
+    ctype: Type[c_numeric_t] = _numpy2ctypes_type(dtype)
     if not isinstance(cptr, ctypes.POINTER(ctype)):
         raise RuntimeError(f"expected {ctype} pointer")
     res = np.zeros(length, dtype=dtype)
@@ -282,7 +284,7 @@ def ctypes2numpy(cptr: cptr_numeric_t, length: int, dtype: Type[np.number]) -> n
     return res
 
 
-def ctypes2cupy(cptr: cptr_numeric_t, length: int, dtype: Type[np.number]) -> cupy_t:
+def ctypes2cupy(cptr: c_numeric_ptr_t, length: int, dtype: Type[np.number]) -> cupy_t:
     """Convert a ctypes pointer array to a cupy array."""
     # pylint: disable=import-error
     import cupy
@@ -308,7 +310,7 @@ def ctypes2cupy(cptr: cptr_numeric_t, length: int, dtype: Type[np.number]) -> cu
     return arr
 
 
-def ctypes2buffer(cptr: ctypes.pointer[ctypes.c_char], length: int) -> bytearray:
+def ctypes2buffer(cptr: c_str_ptr_t, length: int) -> bytearray:
     """Convert ctypes pointer to buffer type."""
     if not isinstance(cptr, ctypes.POINTER(ctypes.c_char)):
         raise RuntimeError('expected char pointer')
@@ -332,9 +334,9 @@ def c_array(ctype: Type[ctype_t], values: ArrayLike) -> ctypes.Array:
 
 
 def _prediction_output(
-    shape: cptr_numeric_t,
+    shape: c_numeric_ptr_t,
     dims: c_bst_ulong,
-    predts: ctypes.pointer[ctypes.c_float],
+    predts: c_float_ptr_t,
     is_cuda: bool
 ) -> numpy_or_cupy_t:
     arr_shape = ctypes2numpy(shape, dims.value, np.uint64)