Function ConvertPySequence

python/pyarrow/src/arrow/python/python_to_arrow.cc:1267–1333

}  // namespace

Result<std::shared_ptr<ChunkedArray>> ConvertPySequence(PyObject* obj, PyObject* mask,
                                                        PyConversionOptions options,
                                                        MemoryPool* pool) {
  PyAcquireGIL lock;

  PyObject* seq = nullptr;
  OwnedRef tmp_seq_nanny;

  ARROW_ASSIGN_OR_RAISE(auto is_pandas_imported, internal::IsModuleImported("pandas"));
  if (is_pandas_imported) {
    // If pandas has been already imported initialize the static pandas objects to
    // support converting from pd.Timedelta and pd.Timestamp objects
    internal::InitPandasStaticData();
  }

  int64_t size = options.size;
  RETURN_NOT_OK(ConvertToSequenceAndInferSize(obj, &seq, &size));
  tmp_seq_nanny.reset(seq);

  // In some cases, type inference may be "loose", like strings. If the user
  // passed pa.string(), then we will error if we encounter any non-UTF8
  // value. If not, then we will allow the result to be a BinaryArray
  std::shared_ptr<DataType> extension_type;
  if (options.type == nullptr) {
    ARROW_ASSIGN_OR_RAISE(options.type, InferArrowType(seq, mask, options.from_pandas));
    options.strict = false;
    // If type inference returned an extension type, convert using
    // the storage type and then wrap the result as an extension array
    if (options.type->id() == Type::EXTENSION) {
      extension_type = options.type;
      options.type = checked_cast<const ExtensionType&>(*options.type).storage_type();
    }
  } else {
    options.strict = true;
  }
  ARROW_DCHECK_GE(size, 0);

  ARROW_ASSIGN_OR_RAISE(auto converter, (MakeConverter<PyConverter, PyConverterTrait>(
                                            options.type, options, pool)));
  std::shared_ptr<ChunkedArray> result;
  if (converter->may_overflow()) {
    // The converter hierarchy contains binary- or list-like builders which can overflow
    // depending on the input values. Wrap the converter with a chunker which detects
    // the overflow and automatically creates new chunks.
    ARROW_ASSIGN_OR_RAISE(auto chunked_converter, MakeChunker(std::move(converter)));
    if (mask != nullptr && mask != Py_None) {
      RETURN_NOT_OK(chunked_converter->ExtendMasked(seq, mask, size));
    } else {
      RETURN_NOT_OK(chunked_converter->Extend(seq, size));
    }
    ARROW_ASSIGN_OR_RAISE(result, chunked_converter->ToChunkedArray());
  } else {
    // If the converter can't overflow spare the capacity error checking on the hot-path,
    // this improves the performance roughly by ~10% for primitive types.
    if (mask != nullptr && mask != Py_None) {
      RETURN_NOT_OK(converter->ExtendMasked(seq, mask, size));
    } else {
      RETURN_NOT_OK(converter->Extend(seq, size));