code: def read_json(
      path_or_buf,
      engine="auto",
      orient=None,
      dtype=None,
      lines=False,
      compression="infer",
      byte_range=None,
      keep_quotes=False,
      storage_options=None,
      *args,
      **kwargs,
  ):
      """{docstring}"""
  
      if dtype is not None and not isinstance(
          dtype, (abc.Mapping, bool)
      ):
          raise TypeError(
              "'dtype' parameter only supports "
              "a dict of column names and types as key-value pairs, "
              f"or a bool, or None. Got {type(dtype)}"
          )
  
      if engine == "cudf_experimental":
          raise ValueError(
              "engine='cudf_experimental' support has been removed, "
              "use `engine='cudf'`"
          )
  
      if engine == "cudf_legacy":
          # TODO: Deprecated in 23.02, please
          # give some time until(more than couple of
          # releases from now) `cudf_legacy`
          # support can be removed completely.
          warnings.warn(
              "engine='cudf_legacy' is a deprecated engine."
              "This will be removed in a future release."
              "Please switch to using engine='cudf'.",
              FutureWarning,
          )
      if engine == "cudf_legacy" and not lines:
          raise ValueError(
              f"{engine} engine only supports JSON Lines format"
          )
      if engine == "auto":
          engine = "cudf" if lines else "pandas"
      if engine != "cudf" and keep_quotes:
          raise ValueError(
              "keep_quotes='True' is supported only with engine='cudf'"
          )
  
      if engine == "cudf_legacy" or engine == "cudf":
          if dtype is None:
              dtype = True
  
          if kwargs:
              raise ValueError(
                  "cudf engine doesn't support the "
                  f"following keyword arguments: {list(kwargs.keys())}"
              )
          if args:
              raise ValueError(
                  "cudf engine doesn't support the "
                  f"following positional arguments: {list(args)}"
              )
  
          # Multiple sources are passed as a list. If a single source is passed,
          # wrap it in a list for unified processing downstream.
          if not is_list_like(path_or_buf):
              path_or_buf = [path_or_buf]
  
          filepaths_or_buffers = []
          for source in path_or_buf:
              if ioutils.is_directory(
                  path_or_data=source, storage_options=storage_options
              ):
                  fs = ioutils._ensure_filesystem(
                      passed_filesystem=None,
                      path=source,
                      storage_options=storage_options,
                  )
                  source = ioutils.stringify_pathlike(source)
                  source = fs.sep.join([source, "*.json"])
  
              (
                  tmp_source,
                  compression,
              ) = ioutils.get_reader_filepath_or_buffer(
                  path_or_data=source,
                  compression=compression,
                  iotypes=(BytesIO, StringIO),
                  allow_raw_text_input=True,
                  storage_options=storage_options,
              )
              if isinstance(tmp_source, list):
                  filepaths_or_buffers.extend(tmp_source)
              else:
                  filepaths_or_buffers.append(tmp_source)
  
          df = libjson.read_json(
              filepaths_or_buffers,
              dtype,
              lines,
              compression,
              byte_range,
              engine == "cudf_legacy",
              keep_quotes,
          )
      else:
          warnings.warn(
              "Using CPU via Pandas to read JSON dataset, this may "
              "be GPU accelerated in the future"
          )
  
          if not ioutils.ensure_single_filepath_or_buffer(
              path_or_data=path_or_buf,
              storage_options=storage_options,
          ):
              raise NotImplementedError(
                  "`read_json` does not yet support reading "
                  "multiple files via pandas"
              )
  
          (
              path_or_buf,
              compression,
          ) = ioutils.get_reader_filepath_or_buffer(
              path_or_data=path_or_buf,
              compression=compression,
              iotypes=(BytesIO, StringIO),
              allow_raw_text_input=True,
              storage_options=storage_options,
          )
  
          pd_value = pd.read_json(
              path_or_buf,
              lines=lines,
              dtype=dtype,
              compression=compression,
              storage_options=storage_options,
              orient=orient,
              *args,
              **kwargs,
          )
          df = cudf.from_pandas(pd_value)
  
      if dtype is None:
          dtype = True
  
      if dtype is True or isinstance(dtype, abc.Mapping):
          # There exists some dtypes in the result columns that is inferred.
          # Find them and map them to the default dtypes.
          specified_dtypes = {} if dtype is True else dtype
          df_dtypes = df._dtypes
          unspecified_dtypes = {
              name: df_dtypes[name]
              for name in df._column_names
              if name not in specified_dtypes
          }
          default_dtypes = {}
  
          for name, dt in unspecified_dtypes.items():
              if dt == np.dtype("i1"):
                  # csv reader reads all null column as int8.
                  # The dtype should remain int8.
                  default_dtypes[name] = dt
              else:
                  default_dtypes[name] = _maybe_convert_to_default_type(
                      dt
                  )
          df = df.astype(default_dtypes)
  
      return df
  
file_path: cudf/python/cudf/cudf/io/json.py
imports: import warnings
  from collections import abc
  from io import BytesIO, StringIO
  import numpy
  import pandas
  import cudf
  from cudf._lib import json
  from cudf.api.types import is_list_like
  from cudf.utils import ioutils
  from cudf.utils.dtypes import _maybe_convert_to_default_type
label_desc: Use image node_id 1 for calling a global function with example usage: read_json(path_or_buf, engine, orient, dtype, lines, compression, byte_range, keep_quotes, storage_options) and returns: df