class_docstr: DataSource describes properties in a benchmark data.
  
  DataSource contains the metadata of a benchmark data including the total
  number of records, the number of partitioned files and a scenario. A scenario
  defines the features used in benchmark with the feature name, tensor spec,
  and Generator used to generate the value. DataSource can be consumed by
  FileWriter to generate the benchmark data descrbied by itself.
docstr: Return the number of partitioned files in this data as int.
docstr_tok: ["Return","the","number","of","partitioned","files","in","this","data","as","int","."]
code: def partitions(self):
      """Return the number of partitioned files in this data as int."""
      return self._partitions
  
file_path: io/tests/test_atds_avro/utils/data_source.py
imports: import hashlib
  from tests.test_atds_avro.utils.hash_util import int_to_bytes
label_desc: Use image node_id 4 for calling the DataSource obj's underlying member method code with example usage: obj.partitions() and returns: self