code: def can_cast(from_, to, casting=None):
      """
      can_cast(from_, to, casting='safe')
  
      Returns True if cast between data types can occur according to the
      casting rule.  If from is a scalar or array scalar, also returns
      True if the scalar value can be cast without overflow or truncation
      to an integer.
  
      Parameters
      ----------
      from_ : dtype, dtype specifier, scalar, or array
          Data type, scalar, or array to cast from.
      to : dtype or dtype specifier
          Data type to cast to.
      casting : {'no', 'equiv', 'safe', 'same_kind', 'unsafe'}, optional
          Controls what kind of data casting may occur.
  
            * 'no' means the data types should not be cast at all.
            * 'equiv' means only byte-order changes are allowed.
            * 'safe' means only casts which can preserve values are allowed.
            * 'same_kind' means only safe casts or casts within a kind,
              like float64 to float32, are allowed.
            * 'unsafe' means any data conversions may be done.
  
      Returns
      -------
      out : bool
          True if cast can occur according to the casting rule.
  
      Notes
      -----
      .. versionchanged:: 1.17.0
         Casting between a simple data type and a structured one is possible only
         for "unsafe" casting.  Casting to multiple fields is allowed, but
         casting from multiple fields is not.
  
      .. versionchanged:: 1.9.0
         Casting from numeric to string types in 'safe' casting mode requires
         that the string dtype length is long enough to store the maximum
         integer/float value converted.
  
      See also
      --------
      dtype, result_type
  
      Examples
      --------
      Basic examples
  
      >>> np.can_cast(np.int32, np.int64)
      True
      >>> np.can_cast(np.float64, complex)
      True
      >>> np.can_cast(complex, float)
      False
  
      >>> np.can_cast('i8', 'f8')
      True
      >>> np.can_cast('i8', 'f4')
      False
      >>> np.can_cast('i4', 'S4')
      False
  
      Casting scalars
  
      >>> np.can_cast(100, 'i1')
      True
      >>> np.can_cast(150, 'i1')
      False
      >>> np.can_cast(150, 'u1')
      True
  
      >>> np.can_cast(3.5e100, np.float32)
      False
      >>> np.can_cast(1000.0, np.float32)
      True
  
      Array scalar checks the value, array does not
  
      >>> np.can_cast(np.array(1000.0), np.float32)
      True
      >>> np.can_cast(np.array([1000.0]), np.float32)
      False
  
      Using the casting rules
  
      >>> np.can_cast('i8', 'i8', 'no')
      True
      >>> np.can_cast('<i8', '>i8', 'no')
      False
  
      >>> np.can_cast('<i8', '>i8', 'equiv')
      True
      >>> np.can_cast('<i4', '>i8', 'equiv')
      False
  
      >>> np.can_cast('<i4', '>i8', 'safe')
      True
      >>> np.can_cast('<i8', '>i4', 'safe')
      False
  
      >>> np.can_cast('<i8', '>i4', 'same_kind')
      True
      >>> np.can_cast('<i8', '>u4', 'same_kind')
      False
  
      >>> np.can_cast('<i8', '>u4', 'unsafe')
      True
  
      """
      return (from_,)
  
imports: import functools
  import sys
  import warnings
  from .None import overrides
  from .None import _multiarray_umath
  import numpy
  from numpy.core._multiarray_umath import *
  from numpy.core._multiarray_umath import _fastCopyAndTranspose, _flagdict, _insert, _reconstruct, _vec_string, _ARRAY_API, _monotonicity, _get_ndarray_c_version
label_desc: Use image node_id 6 for calling a global function with example usage: can_cast(from_, to, casting) and returns: from_