code: def _copytobuffer(
      xxx: Any, inplace: bool = False
  ) -> tuple[Any, DataType]:
      """
      Prepares data for PROJ C-API:
      - Makes a copy because PROJ modifies buffer in place
      - Make sure dtype is double as that is what PROJ expects
      - Makes sure object supports Python Buffer API
  
      If the data is a numpy array, it ensures the data is in C order.
  
      Parameters
      ----------
      xxx: Any
          A scalar, list, tuple, numpy.array,
          pandas.Series, xaray.DataArray, or dask.array.Array.
      inplace: bool, default=False
          If True, will return the array without a copy if it
          meets the requirements of the Python Buffer API & PROJ C-API.
  
      Returns
      -------
      tuple[Any, DataType]
          The copy of the data prepared for the PROJ API & Python Buffer API.
      """
      # check for pandas.Series, xarray.DataArray or dask.array.Array
      # also handle numpy masked Arrays; note that pandas.Series also has a
      # "mask" attribute, hence checking for simply the "mask" attr in that
      # case isn't sufficient
      if (
          not hasattr(xxx, "hardmask")
          and hasattr(xxx, "__array__")
          and callable(xxx.__array__)
      ):
          xxx = xxx.__array__()
  
      # handle numpy data
      if hasattr(xxx, "shape"):
          if xxx.shape == ():
              # convert numpy array scalar to float
              # (array scalars don't support buffer API)
              return _copytobuffer_return_scalar(xxx)
          # Use C order when copying to handle arrays in fortran order
          return (
              xxx.astype("d", order="C", copy=not inplace),
              DataType.ARRAY,
          )
      data_type = DataType.ARRAY
      if isinstance(xxx, array):
          if not inplace or xxx.typecode != "d":
              xxx = array("d", xxx)
      elif isinstance(xxx, list):
          xxx = array("d", xxx)
          data_type = DataType.LIST
      elif isinstance(xxx, tuple):
          xxx = array("d", xxx)
          data_type = DataType.TUPLE
      else:
          return _copytobuffer_return_scalar(xxx)
      return xxx, data_type
  
file_path: pyproj/pyproj/utils.py
imports: import json
  from array import array
  from enum import Enum, auto
  from typing import Any
label_desc: Use image node_id 4 for calling a global function with example usage: _copytobuffer(xxx, inplace) and returns: xxx,  data_type, xxx,  DataType, _copytobuffer_return_scalar, _copytobuffer_return_scalar