pitrou commented on code in PR #40565:
URL: https://github.com/apache/arrow/pull/40565#discussion_r1530352684
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python/pyarrow/src/arrow/python/arrow_to_pandas.cc:
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@@ -620,37 +620,42 @@ inline Status ConvertAsPyObjects(const PandasOptions&
options, const ChunkedArra
using ArrayType = typename TypeTraits<Type>::ArrayType;
using Scalar = typename MemoizationTraits<Type>::Scalar;
- ::arrow::internal::ScalarMemoTable<Scalar> memo_table(options.pool);
- std::vector<PyObject*> unique_values;
- int32_t memo_size = 0;
-
- auto WrapMemoized = [&](const Scalar& value, PyObject** out_values) {
- int32_t memo_index;
- RETURN_NOT_OK(memo_table.GetOrInsert(value, &memo_index));
- if (memo_index == memo_size) {
- // New entry
- RETURN_NOT_OK(wrap_func(value, out_values));
- unique_values.push_back(*out_values);
- ++memo_size;
- } else {
- // Duplicate entry
- Py_INCREF(unique_values[memo_index]);
- *out_values = unique_values[memo_index];
- }
- return Status::OK();
- };
-
- auto WrapUnmemoized = [&](const Scalar& value, PyObject** out_values) {
- return wrap_func(value, out_values);
- };
+ std::shared_ptr<::arrow::internal::ScalarMemoTable<Scalar>> memo_table =
nullptr;
+ std::shared_ptr<std::vector<PyObject*>> unique_values = nullptr;
+ std::shared_ptr<int32_t> memo_size = std::make_shared<int32_t>(0);
+
+ std::function<Status(const typename MemoizationTraits<Type>::Scalar&,
PyObject**)>
Review Comment:
`std::function` will add a layer of indirection. Did you try to measure
performance to see if that matters?
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