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--- contrib/libs/apache/arrow/cpp/src/arrow/python/arrow_to_pandas.cc (index)
+++ contrib/libs/apache/arrow/cpp/src/arrow/python/arrow_to_pandas.cc (working tree)
@@ -234,7 +234,8 @@ Status SetBufferBase(PyArrayObject* arr, const std::shared_ptr<Buffer>& buffer)
}
inline void set_numpy_metadata(int type, const DataType* datatype, PyArray_Descr* out) {
- auto metadata = reinterpret_cast<PyArray_DatetimeDTypeMetaData*>(out->c_metadata);
+ auto metadata =
+ reinterpret_cast<PyArray_DatetimeDTypeMetaData*>(PyDataType_C_METADATA(out));
if (type == NPY_DATETIME) {
if (datatype->id() == Type::TIMESTAMP) {
const auto& timestamp_type = checked_cast<const TimestampType&>(*datatype);
@@ -255,7 +256,7 @@ Status PyArray_NewFromPool(int nd, npy_intp* dims, PyArray_Descr* descr, MemoryP
//
// * Track allocations
// * Get better performance through custom allocators
- int64_t total_size = descr->elsize;
+ int64_t total_size = PyDataType_ELSIZE(descr);
for (int i = 0; i < nd; ++i) {
total_size *= dims[i];
}
@@ -511,8 +512,9 @@ class PandasWriter {
void SetDatetimeUnit(NPY_DATETIMEUNIT unit) {
PyAcquireGIL lock;
- auto date_dtype = reinterpret_cast<PyArray_DatetimeDTypeMetaData*>(
- PyArray_DESCR(reinterpret_cast<PyArrayObject*>(block_arr_.obj()))->c_metadata);
+ auto date_dtype =
+ reinterpret_cast<PyArray_DatetimeDTypeMetaData*>(PyDataType_C_METADATA(
+ PyArray_DESCR(reinterpret_cast<PyArrayObject*>(block_arr_.obj()))));
date_dtype->meta.base = unit;
}
--- contrib/libs/apache/arrow/cpp/src/arrow/python/numpy_convert.cc (index)
+++ contrib/libs/apache/arrow/cpp/src/arrow/python/numpy_convert.cc (working tree)
@@ -46,7 +46,7 @@ NumPyBuffer::NumPyBuffer(PyObject* ao) : Buffer(nullptr, 0) {
PyArrayObject* ndarray = reinterpret_cast<PyArrayObject*>(ao);
auto ptr = reinterpret_cast<uint8_t*>(PyArray_DATA(ndarray));
data_ = const_cast<const uint8_t*>(ptr);
- size_ = PyArray_SIZE(ndarray) * PyArray_DESCR(ndarray)->elsize;
+ size_ = PyArray_NBYTES(ndarray);
capacity_ = size_;
is_mutable_ = !!(PyArray_FLAGS(ndarray) & NPY_ARRAY_WRITEABLE);
}
@@ -148,7 +148,7 @@ Status NumPyDtypeToArrow(PyArray_Descr* descr, std::shared_ptr<DataType>* out) {
TO_ARROW_TYPE_CASE(UNICODE, utf8);
case NPY_DATETIME: {
auto date_dtype =
- reinterpret_cast<PyArray_DatetimeDTypeMetaData*>(descr->c_metadata);
+ reinterpret_cast<PyArray_DatetimeDTypeMetaData*>(PyDataType_C_METADATA(descr));
switch (date_dtype->meta.base) {
case NPY_FR_s:
*out = timestamp(TimeUnit::SECOND);
@@ -173,7 +173,7 @@ Status NumPyDtypeToArrow(PyArray_Descr* descr, std::shared_ptr<DataType>* out) {
} break;
case NPY_TIMEDELTA: {
auto timedelta_dtype =
- reinterpret_cast<PyArray_DatetimeDTypeMetaData*>(descr->c_metadata);
+ reinterpret_cast<PyArray_DatetimeDTypeMetaData*>(PyDataType_C_METADATA(descr));
switch (timedelta_dtype->meta.base) {
case NPY_FR_s:
*out = duration(TimeUnit::SECOND);
--- contrib/libs/apache/arrow/cpp/src/arrow/python/numpy_interop.h (index)
+++ contrib/libs/apache/arrow/cpp/src/arrow/python/numpy_interop.h (working tree)
@@ -67,6 +67,13 @@
#define NPY_INT32_IS_INT 0
#endif
+// Backported NumPy 2 API (can be removed if numpy 2 is required)
+#if NPY_ABI_VERSION < 0x02000000
+#define PyDataType_ELSIZE(descr) ((descr)->elsize)
+#define PyDataType_C_METADATA(descr) ((descr)->c_metadata)
+#define PyDataType_FIELDS(descr) ((descr)->fields)
+#endif
+
namespace arrow {
namespace py {
--- contrib/libs/apache/arrow/cpp/src/arrow/python/numpy_to_arrow.cc (index)
+++ contrib/libs/apache/arrow/cpp/src/arrow/python/numpy_to_arrow.cc (working tree)
@@ -193,7 +193,7 @@ class NumPyConverter {
mask_ = reinterpret_cast<PyArrayObject*>(mo);
}
length_ = static_cast<int64_t>(PyArray_SIZE(arr_));
- itemsize_ = static_cast<int>(PyArray_DESCR(arr_)->elsize);
+ itemsize_ = static_cast<int64_t>(PyArray_ITEMSIZE(arr_));
stride_ = static_cast<int64_t>(PyArray_STRIDES(arr_)[0]);
}
@@ -470,7 +470,8 @@ inline Status NumPyConverter::ConvertData<Date32Type>(std::shared_ptr<Buffer>* d
RETURN_NOT_OK(PrepareInputData<Date32Type>(data));
- auto date_dtype = reinterpret_cast<PyArray_DatetimeDTypeMetaData*>(dtype_->c_metadata);
+ auto date_dtype =
+ reinterpret_cast<PyArray_DatetimeDTypeMetaData*>(PyDataType_C_METADATA(dtype_));
if (dtype_->type_num == NPY_DATETIME) {
// If we have inbound datetime64[D] data, this needs to be downcasted
// separately here from int64_t to int32_t, because this data is not
@@ -506,7 +507,8 @@ inline Status NumPyConverter::ConvertData<Date64Type>(std::shared_ptr<Buffer>* d
RETURN_NOT_OK(PrepareInputData<Date64Type>(data));
- auto date_dtype = reinterpret_cast<PyArray_DatetimeDTypeMetaData*>(dtype_->c_metadata);
+ auto date_dtype =
+ reinterpret_cast<PyArray_DatetimeDTypeMetaData*>(PyDataType_C_METADATA(dtype_));
if (dtype_->type_num == NPY_DATETIME) {
// If we have inbound datetime64[D] data, this needs to be downcasted
// separately here from int64_t to int32_t, because this data is not
@@ -736,12 +738,13 @@ Status NumPyConverter::Visit(const StructType& type) {
PyAcquireGIL gil_lock;
// Create converters for each struct type field
- if (dtype_->fields == NULL || !PyDict_Check(dtype_->fields)) {
+ if (PyDataType_FIELDS(dtype_) == NULL || !PyDict_Check(PyDataType_FIELDS(dtype_))) {
return Status::TypeError("Expected struct array");
}
for (auto field : type.fields()) {
- PyObject* tup = PyDict_GetItemString(dtype_->fields, field->name().c_str());
+ PyObject* tup =
+ PyDict_GetItemString(PyDataType_FIELDS(dtype_), field->name().c_str());
if (tup == NULL) {
return Status::Invalid("Missing field '", field->name(), "' in struct array");
}
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