mirror of
https://github.com/wassname/ray.git
synced 2026-08-02 13:01:01 +08:00
Capability to serialize most primitive Python types
This commit is contained in:
Philipp Moritz
@@ -0,0 +1,88 @@
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#include "numpy.h"
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#include <numbuf/tensor.h>
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using namespace arrow;
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namespace numbuf {
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#define ARROW_TYPE_TO_NUMPY_CASE(TYPE) \
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case Type::TYPE: \
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return NPY_##TYPE;
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#define DESERIALIZE_ARRAY_CASE(TYPE, ArrayType, type) \
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case Type::TYPE: { \
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auto values = std::dynamic_pointer_cast<ArrayType>(content->values()); \
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DCHECK(values); \
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type* data = const_cast<type*>(values->raw_data()) \
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+ content->offset(offset); \
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*out = PyArray_SimpleNewFromData(num_dims, dim.data(), NPY_##TYPE, \
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reinterpret_cast<void*>(data)); \
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} \
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return Status::OK();
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Status DeserializeArray(std::shared_ptr<Array> array, int32_t offset, PyObject** out) {
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DCHECK(array);
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auto tensor = std::dynamic_pointer_cast<StructArray>(array);
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DCHECK(tensor);
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auto dims = std::dynamic_pointer_cast<ListArray>(tensor->field(0));
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auto content = std::dynamic_pointer_cast<ListArray>(tensor->field(1));
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npy_intp num_dims = dims->value_length(offset);
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std::vector<npy_intp> dim(num_dims);
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for (int i = dims->offset(offset); i < dims->offset(offset+1); ++i) {
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dim[i - dims->offset(offset)] =
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std::dynamic_pointer_cast<Int64Array>(dims->values())->Value(i);
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}
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switch (content->value_type()->type) {
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DESERIALIZE_ARRAY_CASE(INT8, Int8Array, int8_t)
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DESERIALIZE_ARRAY_CASE(INT16, Int16Array, int16_t)
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DESERIALIZE_ARRAY_CASE(INT32, Int32Array, int32_t)
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DESERIALIZE_ARRAY_CASE(INT64, Int64Array, int64_t)
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DESERIALIZE_ARRAY_CASE(UINT8, UInt8Array, uint8_t)
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DESERIALIZE_ARRAY_CASE(UINT16, UInt16Array, uint16_t)
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DESERIALIZE_ARRAY_CASE(UINT32, UInt32Array, uint32_t)
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DESERIALIZE_ARRAY_CASE(UINT64, UInt64Array, uint64_t)
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DESERIALIZE_ARRAY_CASE(FLOAT, FloatArray, float)
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DESERIALIZE_ARRAY_CASE(DOUBLE, DoubleArray, double)
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default:
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DCHECK(false) << "arrow type not recognized: " << content->value_type()->type;
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}
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return Status::OK();
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}
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Status SerializeArray(PyArrayObject* array, SequenceBuilder& builder) {
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size_t ndim = PyArray_NDIM(array);
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int dtype = PyArray_TYPE(array);
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std::vector<int64_t> dims(ndim);
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for (int i = 0; i < ndim; ++i) {
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dims[i] = PyArray_DIM(array, i);
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}
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auto data = PyArray_DATA(array);
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switch (dtype) {
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case NPY_UINT8:
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return builder.Append(dims, reinterpret_cast<uint8_t*>(data));
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case NPY_INT8:
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return builder.Append(dims, reinterpret_cast<int8_t*>(data));
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case NPY_UINT16:
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return builder.Append(dims, reinterpret_cast<uint16_t*>(data));
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case NPY_INT16:
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return builder.Append(dims, reinterpret_cast<int16_t*>(data));
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case NPY_UINT32:
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return builder.Append(dims, reinterpret_cast<uint32_t*>(data));
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case NPY_INT32:
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return builder.Append(dims, reinterpret_cast<int32_t*>(data));
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case NPY_UINT64:
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return builder.Append(dims, reinterpret_cast<uint64_t*>(data));
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case NPY_INT64:
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return builder.Append(dims, reinterpret_cast<int64_t*>(data));
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case NPY_FLOAT:
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return builder.Append(dims, reinterpret_cast<float*>(data));
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case NPY_DOUBLE:
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return builder.Append(dims, reinterpret_cast<double*>(data));
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default:
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DCHECK(false) << "numpy data type not recognized: " << dtype;
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}
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return Status::OK();
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}
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}
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@@ -0,0 +1,22 @@
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#ifndef PYNUMBUF_NUMPY_H
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#define PYNUMBUF_NUMPY_H
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#include <arrow/api.h>
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#include <Python.h>
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#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION
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#define NO_IMPORT_ARRAY
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#define PY_ARRAY_UNIQUE_SYMBOL NUMBUF_ARRAY_API
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#include <numpy/arrayobject.h>
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#include <numbuf/tensor.h>
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#include <numbuf/sequence.h>
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namespace numbuf {
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arrow::Status SerializeArray(PyArrayObject* array, SequenceBuilder& builder);
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arrow::Status DeserializeArray(std::shared_ptr<arrow::Array> array, int32_t offset, PyObject** out);
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}
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#endif
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@@ -0,0 +1,193 @@
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#include "python.h"
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#include <sstream>
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#include "scalars.h"
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using namespace arrow;
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namespace numbuf {
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PyObject* get_value(ArrayPtr arr, int32_t index, int32_t type) {
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PyObject* result;
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switch (arr->type()->type) {
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case Type::BOOL:
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return PyBool_FromLong(std::static_pointer_cast<BooleanArray>(arr)->Value(index));
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case Type::INT64:
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return PyInt_FromLong(std::static_pointer_cast<Int64Array>(arr)->Value(index));
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case Type::STRING: {
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int32_t nchars;
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const uint8_t* str = std::static_pointer_cast<StringArray>(arr)->GetValue(index, &nchars);
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return PyString_FromStringAndSize(reinterpret_cast<const char*>(str), nchars);
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}
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case Type::FLOAT:
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return PyFloat_FromDouble(std::static_pointer_cast<FloatArray>(arr)->Value(index));
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case Type::DOUBLE:
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return PyFloat_FromDouble(std::static_pointer_cast<DoubleArray>(arr)->Value(index));
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case Type::STRUCT: {
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auto s = std::static_pointer_cast<StructArray>(arr);
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auto l = std::static_pointer_cast<ListArray>(s->field(0));
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if (s->type()->child(0)->name == "list") {
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ARROW_CHECK_OK(DeserializeList(l->values(), l->value_offset(index), l->value_offset(index+1), &result));
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} else if (s->type()->child(0)->name == "tuple") {
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ARROW_CHECK_OK(DeserializeTuple(l->values(), l->value_offset(index), l->value_offset(index+1), &result));
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} else if (s->type()->child(0)->name == "dict") {
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ARROW_CHECK_OK(DeserializeDict(l->values(), l->value_offset(index), l->value_offset(index+1), &result));
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} else {
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ARROW_CHECK_OK(DeserializeArray(arr, index, &result));
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}
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return result;
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}
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default:
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DCHECK(false) << "union tag not recognized " << type;
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}
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return NULL;
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}
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Status append(PyObject* elem, SequenceBuilder& builder,
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std::vector<PyObject*>& sublists,
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std::vector<PyObject*>& subtuples,
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std::vector<PyObject*>& subdicts) {
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// The bool case must precede the int case (PyInt_Check passes for bools)
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if (PyBool_Check(elem)) {
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RETURN_NOT_OK(builder.Append(elem == Py_True));
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} else if (PyFloat_Check(elem)) {
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RETURN_NOT_OK(builder.Append(PyFloat_AS_DOUBLE(elem)));
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} else if (PyLong_Check(elem)) {
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int overflow = 0;
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int64_t data = PyLong_AsLongLongAndOverflow(elem, &overflow);
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RETURN_NOT_OK(builder.Append(data));
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if(overflow) {
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return Status::NotImplemented("long overflow");
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}
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} else if (PyInt_Check(elem)) {
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RETURN_NOT_OK(builder.Append(PyInt_AS_LONG(elem)));
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} else if (PyString_Check(elem)) {
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RETURN_NOT_OK(builder.Append(PyString_AS_STRING(elem), PyString_GET_SIZE(elem)));
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} else if (PyList_Check(elem)) {
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builder.AppendList(PyList_Size(elem));
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sublists.push_back(elem);
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} else if (PyDict_Check(elem)) {
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builder.AppendDict(PyDict_Size(elem));
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subdicts.push_back(elem);
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} else if (PyTuple_Check(elem)) {
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builder.AppendTuple(PyTuple_Size(elem));
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subtuples.push_back(elem);
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} else if (PyArray_IsScalar(elem, Generic)) {
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RETURN_NOT_OK(AppendScalar(elem, builder));
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} else if (PyArray_Check(elem)) {
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RETURN_NOT_OK(SerializeArray((PyArrayObject*) elem, builder));
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} else if (elem == Py_None) {
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RETURN_NOT_OK(builder.Append());
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} else {
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std::stringstream ss;
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ss << "data type of " << PyString_AS_STRING(PyObject_Repr(elem))
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<< " not recognized";
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return Status::NotImplemented(ss.str());
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}
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return Status::OK();
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}
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Status SerializeSequences(std::vector<PyObject*> sequences, std::shared_ptr<Array>* out) {
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DCHECK(out);
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SequenceBuilder builder(nullptr);
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std::vector<PyObject*> sublists, subtuples, subdicts;
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for (const auto& sequence : sequences) {
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PyObject* item;
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PyObject* iterator = PyObject_GetIter(sequence);
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while (item = PyIter_Next(iterator)) {
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RETURN_NOT_OK(append(item, builder, sublists, subtuples, subdicts));
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Py_DECREF(item);
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}
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Py_DECREF(iterator);
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}
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std::shared_ptr<Array> list;
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if (sublists.size() > 0) {
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RETURN_NOT_OK(SerializeSequences(sublists, &list));
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}
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std::shared_ptr<Array> tuple;
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if (subtuples.size() > 0) {
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RETURN_NOT_OK(SerializeSequences(subtuples, &tuple));
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}
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std::shared_ptr<Array> dict;
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if (subdicts.size() > 0) {
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RETURN_NOT_OK(SerializeDict(subdicts, &dict));
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}
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*out = builder.Finish(list, tuple, dict);
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return Status::OK();
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}
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#define DESERIALIZE_SEQUENCE(CREATE, SET_ITEM) \
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auto data = std::dynamic_pointer_cast<DenseUnionArray>(array); \
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int32_t size = array->length(); \
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PyObject* result = CREATE(stop_idx - start_idx); \
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auto types = std::make_shared<Int8Array>(size, data->types()); \
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auto offsets = std::make_shared<Int32Array>(size, data->offset_buf()); \
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for (size_t i = start_idx; i < stop_idx; ++i) { \
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if (data->IsNull(i)) { \
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Py_INCREF(Py_None); \
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SET_ITEM(result, i-start_idx, Py_None); \
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} else { \
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int32_t offset = offsets->Value(i); \
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int8_t type = types->Value(i); \
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ArrayPtr arr = data->child(type); \
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SET_ITEM(result, i-start_idx, get_value(arr, offset, type)); \
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} \
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} \
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*out = result; \
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return Status::OK();
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Status DeserializeList(std::shared_ptr<Array> array, int32_t start_idx, int32_t stop_idx, PyObject** out) {
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DESERIALIZE_SEQUENCE(PyList_New, PyList_SetItem)
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}
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Status DeserializeTuple(std::shared_ptr<Array> array, int32_t start_idx, int32_t stop_idx, PyObject** out) {
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DESERIALIZE_SEQUENCE(PyTuple_New, PyTuple_SetItem)
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}
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Status SerializeDict(std::vector<PyObject*> dicts, std::shared_ptr<Array>* out) {
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DictBuilder result;
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std::vector<PyObject*> sublists, subtuples, subdicts, dummy;
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for (const auto& dict : dicts) {
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PyObject *key, *value;
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Py_ssize_t pos = 0;
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while (PyDict_Next(dict, &pos, &key, &value)) {
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RETURN_NOT_OK(append(key, result.keys(), dummy, dummy, dummy));
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DCHECK(dummy.size() == 0);
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RETURN_NOT_OK(append(value, result.vals(), sublists, subtuples, subdicts));
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}
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}
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std::shared_ptr<Array> val_list;
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if (sublists.size() > 0) {
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RETURN_NOT_OK(SerializeSequences(sublists, &val_list));
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}
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std::shared_ptr<Array> val_tuples;
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if (subtuples.size() > 0) {
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RETURN_NOT_OK(SerializeSequences(subtuples, &val_tuples));
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}
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std::shared_ptr<Array> val_dict;
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if (subdicts.size() > 0) {
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RETURN_NOT_OK(SerializeDict(subdicts, &val_dict));
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}
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*out = result.Finish(val_list, val_tuples, val_dict);
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return Status::OK();
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}
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Status DeserializeDict(std::shared_ptr<Array> array, int32_t start_idx, int32_t stop_idx, PyObject** out) {
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auto data = std::dynamic_pointer_cast<StructArray>(array);
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// TODO(pcm): error handling, get rid of the temporary copy of the list
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PyObject *keys, *vals;
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PyObject* result = PyDict_New();
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ARROW_RETURN_NOT_OK(DeserializeList(data->field(0), start_idx, stop_idx, &keys));
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ARROW_RETURN_NOT_OK(DeserializeList(data->field(1), start_idx, stop_idx, &vals));
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for (size_t i = start_idx; i < stop_idx; ++i) {
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PyDict_SetItem(result, PyList_GetItem(keys, i - start_idx), PyList_GetItem(vals, i - start_idx));
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}
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Py_XDECREF(keys); // PyList_GetItem(keys, ...) incremented the reference count
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Py_XDECREF(vals); // PyList_GetItem(vals, ...) incremented the reference count
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*out = result;
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return Status::OK();
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}
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}
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@@ -0,0 +1,22 @@
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#ifndef PYNUMBUF_PYTHON_H
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#define PYNUMBUF_PYTHON_H
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#include <Python.h>
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#include <arrow/api.h>
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#include <numbuf/dict.h>
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#include <numbuf/sequence.h>
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#include "numpy.h"
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namespace numbuf {
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arrow::Status SerializeSequences(std::vector<PyObject*> sequences, std::shared_ptr<arrow::Array>* out);
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arrow::Status SerializeDict(std::vector<PyObject*> dicts, std::shared_ptr<arrow::Array>* out);
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arrow::Status DeserializeList(std::shared_ptr<arrow::Array> array, int32_t start_idx, int32_t stop_idx, PyObject** out);
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arrow::Status DeserializeTuple(std::shared_ptr<arrow::Array> array, int32_t start_idx, int32_t stop_idx, PyObject** out);
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arrow::Status DeserializeDict(std::shared_ptr<arrow::Array> array, int32_t start_idx, int32_t stop_idx, PyObject** out);
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}
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#endif
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@@ -0,0 +1,54 @@
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#ifndef PYNUMBUF_SCALARS_H
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#define PYNUMBUF_SCALARS_H
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#include <arrow/api.h>
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#include <Python.h>
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#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION
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#define NO_IMPORT_ARRAY
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#define PY_ARRAY_UNIQUE_SYMBOL NUMBUF_ARRAY_API
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#include <numpy/arrayobject.h>
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#include <numpy/arrayscalars.h>
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#include <numbuf/sequence.h>
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namespace numbuf {
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arrow::Status AppendScalar(PyObject* obj, SequenceBuilder& builder) {
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if (PyArray_IsScalar(obj, Bool)) {
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return builder.Append(((PyBoolScalarObject *)obj)->obval != 0);
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} else if (PyArray_IsScalar(obj, Float)) {
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return builder.Append(((PyFloatScalarObject *)obj)->obval);
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} else if (PyArray_IsScalar(obj, Double)) {
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return builder.Append(((PyDoubleScalarObject *)obj)->obval);
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}
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int64_t value = 0;
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if (PyArray_IsScalar(obj, Byte)) {
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value = ((PyByteScalarObject *)obj)->obval;
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} else if (PyArray_IsScalar(obj, UByte)) {
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value = ((PyUByteScalarObject *)obj)->obval;
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} else if (PyArray_IsScalar(obj, Short)) {
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value = ((PyShortScalarObject *)obj)->obval;
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} else if (PyArray_IsScalar(obj, UShort)) {
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value = ((PyUShortScalarObject *)obj)->obval;
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} else if (PyArray_IsScalar(obj, Int)) {
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value = ((PyIntScalarObject *)obj)->obval;
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} else if (PyArray_IsScalar(obj, UInt)) {
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value = ((PyUIntScalarObject *)obj)->obval;
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} else if (PyArray_IsScalar(obj, Long)) {
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value = ((PyLongScalarObject *)obj)->obval;
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} else if (PyArray_IsScalar(obj, ULong)) {
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value = ((PyULongScalarObject *)obj)->obval;
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} else if (PyArray_IsScalar(obj, LongLong)) {
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value = ((PyLongLongScalarObject *)obj)->obval;
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} else if (PyArray_IsScalar(obj, ULongLong)) {
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value = ((PyULongLongScalarObject *)obj)->obval;
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} else {
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DCHECK(false) << "scalar type not recognized";
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}
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return builder.Append(value);
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}
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} // namespace
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#endif // PYNUMBUF_SCALARS_H
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