Resolve PyObject* conversion warnings

The `Read as arrow` commit introduced a `UTF_DYNAMIC32` type whose value
types can't safely be converted to pointers.

Author: IvoDD

cpp/arcticdb/column_store/statistics.hpp

@@ -187,7 +187,7 @@ FieldStatsImpl generate_column_statistics(ColumnData column_data) {
         const size_t count = block->row_count();
         if constexpr (is_numeric_type(TagType::DataTypeTag::data_type)) {
             return generate_numeric_statistics<RawType>(std::span{ptr, count});
-        } else if constexpr (is_dynamic_string_type(TagType::DataTypeTag::data_type) && !is_output_only_type(TagType::DataTypeTag::data_type)) {
+        } else if constexpr (is_dynamic_string_type(TagType::DataTypeTag::data_type) && !is_arrow_output_only_type(TagType::DataTypeTag::data_type)) {
             return generate_string_statistics(std::span{ptr, count});
         } else {
             util::raise_rte("Cannot generate statistics for data type");
@@ -200,7 +200,7 @@ FieldStatsImpl generate_column_statistics(ColumnData column_data) {
             if constexpr (is_numeric_type(TagType::DataTypeTag::data_type)) {
                 auto local_stats = generate_numeric_statistics<RawType>(std::span{ptr, count});
                 stats.compose<RawType>(local_stats);
-           } else if constexpr (is_dynamic_string_type(TagType::DataTypeTag::data_type) && !is_output_only_type(TagType::DataTypeTag::data_type)) {
+           } else if constexpr (is_dynamic_string_type(TagType::DataTypeTag::data_type) && !is_arrow_output_only_type(TagType::DataTypeTag::data_type)) {
                 auto local_stats = generate_string_statistics(std::span{ptr, count});
                 stats.compose<RawType>(local_stats);
             } else {

cpp/arcticdb/entity/types.hpp

@@ -297,7 +297,7 @@ constexpr bool is_dynamic_string_type(DataType v) {
     return is_dynamic_string_type(slice_value_type(v));
 }
 
-constexpr bool is_output_only_type(DataType d) {
+constexpr bool is_arrow_output_only_type(DataType d) {
     return d == DataType::UTF_DYNAMIC32;
 }
 
@@ -500,6 +500,10 @@ constexpr bool is_object_type(TypeDescriptor td) {
     || is_array_type(td);
 }
 
+constexpr bool is_arrow_output_only_type(TypeDescriptor td) {
+    return is_arrow_output_only_type(td.data_type());
+}
+
 inline void set_data_type(DataType data_type, TypeDescriptor &type_desc) {
     type_desc.data_type_ = data_type;
 }

cpp/arcticdb/pipeline/pandas_output_frame.cpp

@@ -33,32 +33,38 @@ PandasOutputFrame::~PandasOutputFrame() {
     if(frame_.is_null())
         return;
 
-    for (auto &column : frame_.columns()) {
-        auto dt = column->type().data_type();
-        if (is_dynamic_string_type(dt) && column->is_inflated()) {
-            auto column_data = column->data();
-            column_data.type().visit_tag([&](auto type_desc_tag) {
-                using TDT = decltype(type_desc_tag);
-                constexpr auto td = TypeDescriptor(type_desc_tag);
-                if constexpr (is_object_type(TypeDescriptor(type_desc_tag))) {
-                    if constexpr(is_array_type(td)) {
-                        auto it = column_data.buffer().iterator(sizeof(PyObject*));
-                        while(!it.finished()) {
-                            util::check(reinterpret_cast<PyObject*>(it.value()) != nullptr, "Can't delete null item");
-                            Py_DECREF(reinterpret_cast<PyObject*>(it.value()));
-                            it.next();
-                        }
-                    } else {
-                        while (auto block = column_data.next<TDT>()) {
-                            for (auto item : *block) {
-                                util::check(reinterpret_cast<PyObject *>(item) != nullptr, "Can't delete null item");
-                                Py_DECREF(reinterpret_cast<PyObject *>(item));
+    try {
+        for (auto &column : frame_.columns()) {
+            auto dt = column->type().data_type();
+            if (is_dynamic_string_type(dt) && column->is_inflated()) {
+                auto column_data = column->data();
+                column_data.type().visit_tag([&](auto type_desc_tag) {
+                    using TDT = decltype(type_desc_tag);
+                    constexpr auto td = TypeDescriptor(type_desc_tag);
+                    if constexpr (is_object_type(td)) {
+                        if constexpr(is_array_type(td)) {
+                            auto it = column_data.buffer().iterator(sizeof(PyObject*));
+                            while(!it.finished()) {
+                                util::check(reinterpret_cast<PyObject*>(it.value()) != nullptr, "Can't delete null item");
+                                Py_DECREF(reinterpret_cast<PyObject*>(it.value()));
+                                it.next();
+                            }
+                        } else if constexpr (!is_arrow_output_only_type(td)) {
+                            while (auto block = column_data.next<TDT>()) {
+                                for (auto item : *block) {
+                                    util::check(reinterpret_cast<PyObject *>(item) != nullptr, "Can't delete null item");
+                                    Py_DECREF(reinterpret_cast<PyObject *>(item));
+                                }
                             }
+                        } else {
+                            internal::raise<ErrorCode::E_ASSERTION_FAILURE>("Unexpected arrow output format seen in PandasOutputFrame");
                         }
                     }
-                }
-            });
+                });
+            }
         }
+    } catch (const std::exception &e) {
+        log::version().warn("Exception in PandasOutputFrame destructor: {}", e.what());
     }
 }