Function NdarrayToTensor

python/pyarrow/src/arrow/python/numpy_convert.cc:199–230

#undef TO_ARROW_TYPE_CASE

Status NdarrayToTensor(MemoryPool* pool, PyObject* ao,
                       const std::vector<std::string>& dim_names,
                       std::shared_ptr<Tensor>* out) {
  if (!PyArray_Check(ao)) {
    return Status::TypeError("Did not pass ndarray object");
  }

  PyArrayObject* ndarray = reinterpret_cast<PyArrayObject*>(ao);

  // TODO(wesm): What do we want to do with non-contiguous memory and negative strides?

  int ndim = PyArray_NDIM(ndarray);

  std::shared_ptr<Buffer> data = std::make_shared<NumPyBuffer>(ao);
  std::vector<int64_t> shape(ndim);
  std::vector<int64_t> strides(ndim);

  npy_intp* array_strides = PyArray_STRIDES(ndarray);
  npy_intp* array_shape = PyArray_SHAPE(ndarray);
  for (int i = 0; i < ndim; ++i) {
    if (array_strides[i] < 0) {
      return Status::Invalid("Negative ndarray strides not supported");
    }
    shape[i] = array_shape[i];
    strides[i] = array_strides[i];
  }

  ARROW_ASSIGN_OR_RAISE(
      auto type, GetTensorType(reinterpret_cast<PyObject*>(PyArray_DESCR(ndarray))));
  *out = std::make_shared<Tensor>(type, data, shape, strides, dim_names);
  return Status::OK();
}

Status TensorToNdarray(const std::shared_ptr<Tensor>& tensor, PyObject* base,
                       PyObject** out) {