code: def _get_cython_type_upcast(dtype):
      """Upcast a dtype to 'int64_t', 'double', or 'object'"""
      if is_integer_dtype(dtype):
          return "int64_t"
      elif is_float_dtype(dtype):
          return "double"
      else:
          return "object"
  
imports: import copy
  import string
  import warnings
  import numpy
  from pandas._libs import hashtable, join, lib
  import pandas.compat
  from pandas.compat import filter, lzip, map, range, zip
  from pandas.errors import MergeError
  from pandas.util._decorators import Appender, Substitution
  from pandas.core.dtypes.common import ensure_float64, ensure_int64, ensure_object, is_array_like, is_bool, is_bool_dtype, is_categorical_dtype, is_datetime64_dtype, is_datetime64tz_dtype, is_datetimelike, is_dtype_equal, is_extension_array_dtype, is_float_dtype, is_int64_dtype, is_integer, is_integer_dtype, is_list_like, is_number, is_numeric_dtype, is_object_dtype, needs_i8_conversion
  from pandas.core.dtypes.missing import isnull, na_value_for_dtype
  from pandas import Categorical, DataFrame, Index, MultiIndex, Series, Timedelta
  import pandas.core.algorithms
  from pandas.core.arrays.categorical import _recode_for_categories
  import pandas.core.common
  from pandas.core.frame import _merge_doc
  from pandas.core.internals import concatenate_block_managers, items_overlap_with_suffix
  import pandas.core.sorting
  from pandas.core.sorting import is_int64_overflow_possible
label_desc: Use image node_id 9 for calling a global function with example usage: _get_cython_type_upcast(dtype) and returns: str, str, str