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https://issues.apache.org/jira/browse/ARROW-2091?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16352633#comment-16352633
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Uwe L. Korn commented on ARROW-2091:
------------------------------------
Yes, this is possible using the code supplied in {{arrow/python/pyarrow.h}}:
{code:java}
#include <arrow/python/pyarrow.h>
PyObject* process_table(PyObject* table)
{
arrow::py::import_pyarrow();
std::shared_ptr<arrow::Table> tablePtr;
if (not arrow::py::unwrap_table(table, &tablePtr).ok()) {
// Handle error
}
// work on the tablePtr
}{code}
> Interacting with arrow/pyarrow in C++
> -------------------------------------
>
> Key: ARROW-2091
> URL: https://issues.apache.org/jira/browse/ARROW-2091
> Project: Apache Arrow
> Issue Type: Improvement
> Reporter: Jun
> Priority: Minor
>
> I've been searching online for a while but cannot figure out how to do this.
> Please help if this is already a resolved issue.
> I have a c++/python application that interacts with arrow/pyarrow. I want to
> write a C++ api that takes python objects directly and operate on them in c++.
> {code:java}
> PyObject* process_table(PyObject* table)
> {
> // process the arrow table
> std::shared_ptr<arrow::Table> tablePtr = table; // How?
> }{code}
> The problem here is: how do I extract the internal std::shared_ptr<Table>
> from the PyObject?
> Unfortunately we are not using cython in our stack, we operate on PyObject *
> directly in c++.
> I can easily do this on numpy arrays:
> {code:java}
> PyObject * process_array(PyObject* arr)
> {
> PyArray_Check(arr);
> // process the PyArrayObject directly
> ...
> }{code}
> I wonder is there any way to achieve this level of c++ integration without
> using cython? Thanks!
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