If it comes from pandas (and is eligible for zero-copy) then the
buffer implementation will be `NumPyBuffer`. Printing one in GDB
yields...
```
$12 = {_vptr.Buffer = 0x7f0b66e147f8 <vtable for
arrow::py::NumPyBuffer+16>, is_mutable_ = true, is_cpu_ = true, data_
= 0x55b71f901a70 "\001", mutable_data_ = 0x0, size_ = 16, capacity_ =
16,
parent_ = {<std::__shared_ptr<arrow::Buffer,
(__gnu_cxx::_Lock_policy)2>> =
{<std::__shared_ptr_access<arrow::Buffer, (__gnu_cxx::_Lock_policy)2,
false, false>> = {<No data fields>}, _M_ptr = 0x0,
_M_refcount = {_M_pi = 0x0}}, <No data fields>},
memory_manager_ = {<std::__shared_ptr<arrow::MemoryManager,
(__gnu_cxx::_Lock_policy)2>> =
{<std::__shared_ptr_access<arrow::MemoryManager,
(__gnu_cxx::_Lock_policy)2, false, false>> = {<No data fields>},
_M_ptr = 0x55b71fdca4e0, _M_refcount = {_M_pi =
0x55b71fb90640}}, <No data fields>}}
```
Notice that `is_cpu_` and `is_mutable_` are both `true`. It's maybe a
bug that `is_mutable_` is true. Although maybe not as it appears to
be telling whether the underlying numpy buffer itself is mutable or
not...
```
if (PyArray_FLAGS(ndarray) & NPY_ARRAY_WRITEABLE) {
is_mutable_ = true;
}
```
On Tue, Apr 20, 2021 at 2:15 PM Niranda Perera <[email protected]> wrote:
>
> Hi all,
>
> We have been using Arrow v2.0.0 and we encountered the following issue.
>
> I was reading a table with numeric data using pandas.read_csv and then
> converting it into pyarrow table. In our application (Cylon
> <https://github.com/cylondata/cylon>), we are accessing this pyarrow table
> from c++. We want to access the mutable data of the arrays in the pyarrow
> table.
>
> But the following returns a nullptr.
> T *mutable_data = array->data()->GetMutableValues<T>(1); // returns nullptr
>
> Interestingly,
> array->data()->buffers[1]->IsMutable(); // returns true
> array->data()->buffers[1]->IsCpu(); // returns true
>
> This only happens when I use pandas df to create a pyarrow table. It
> wouldn't happen when I use pyarrow.read_csv. So, I am guessing there's some
> issue in the buffer creation from pandas df.
>
> Is this an expected behavior? or has this been resolved in v2.0< releases?
>
> Best
> --
> Niranda Perera
> https://niranda.dev/
> @n1r44 <https://twitter.com/N1R44>
