code: def _execute_partitioned(cls, ctx, op: "DataFrameReadParquet"):
      out = op.outputs[0]
      engine = get_engine(op.engine)
      with open_file(op.path, storage_options=op.storage_options) as f:
          ctx[out.key] = engine.read_partitioned_to_pandas(
              f,
              op.partitions,
              op.partition_keys,
              columns=op.columns,
              nrows=op.nrows,
              use_arrow_dtype=op.use_arrow_dtype,
              **op.read_kwargs or dict(),
          )
  
imports: import os
  from typing import Dict
  from urllib.parse import urlparse
  import numpy
  import pandas
  from ...None import opcodes
  from ...config import options
  from ...lib.filesystem import file_size, get_fs, glob, open_file, FileSystem
  from ...serialization.serializables import AnyField, BoolField, DictField, ListField, StringField, Int32Field, Int64Field
  from ...utils import is_object_dtype, lazy_import
  from ..arrays import ArrowStringDtype
  from ..operands import OutputType
  from ..utils import parse_index, to_arrow_dtypes, contain_arrow_dtype
  from .core import IncrementalIndexDatasource, ColumnPruneSupportedDataSourceMixin, IncrementalIndexDataSourceMixin, merge_small_files
label_desc: Use image node_id 7 for calling the DataFrameReadParquet obj's underlying member method code with example usage: obj._execute_partitioned(cls, ctx, op) without return types