code: def load_json(data_source, orient="records", chunksize=None):
      """json files data loader.
  
      Parameters
      ----------
      data_source : str
          Path to a .json file.
      orient : str
          Indicates the expected .json file format. The default ``orient="records"`` assumes the knowledge graph is
          stored as a list like `[{subject_1: value, predicate_1: value, object_1: value}, ...,
          {subject_n: value, predicate_n: value, object_n: value}]`. If looking for more options check the
          `Pandas <https://pandas.pydata.org/docs/reference/api/pandas.read_json.html>`_ website.
      chunksize : int
          The size of chunk to be used while reading the data. If used, the returned type is
          an iterator and not a numpy array.
  
  
      Returns
      -------
      data : ndarray or iter
          Either a numpy array with data or a lazy iterator if ``chunk_size`` was provided.
      """
      if chunksize is not None:
          data = pd.read_json(
              data_source,
              orient=orient,
              lines=True,
              chunksize=chunksize,
          )
      else:
          data = pd.read_json(data_source, orient=orient)
      logger.debug("data type: {}".format(type(data)))
      logger.debug("JSON loaded into iterator data.")
  
      return data.values
  
file_path: AmpliGraph/ampligraph/datasets/source_identifier.py
imports: import logging
  from collections.abc import Iterable
  from itertools import chain, islice
  import numpy
  import pandas
label_desc: Use image node_id 2 for calling a global function with example usage: load_json(data_source, orient, chunksize) and returns: data