old_contents: import numpy as np
  
  # Note: we use dtype objects instead of dtype classes. The spec does not
  # require any behavior on dtypes other than equality.
  int8 = np.dtype('int8')
  int16 = np.dtype('int16')
  int32 = np.dtype('int32')
  int64 = np.dtype('int64')
  uint8 = np.dtype('uint8')
  uint16 = np.dtype('uint16')
  uint32 = np.dtype('uint32')
  uint64 = np.dtype('uint64')
  float32 = np.dtype('float32')
  float64 = np.dtype('float64')
  # Note: This name is changed
  bool = np.dtype('bool')
  
  _all_dtypes = [int8, int16, int32, int64, uint8, uint16, uint32, uint64,
                 float32, float64, bool]
  _boolean_dtypes = [bool]
  _floating_dtypes = [float32, float64]
  _integer_dtypes = [int8, int16, int32, int64, uint8, uint16, uint32, uint64]
  _integer_or_boolean_dtypes = [bool, int8, int16, int32, int64, uint8, uint16, uint32, uint64]
  _numeric_dtypes = [float32, float64, int8, int16, int32, int64, uint8, uint16, uint32, uint64]
  
new_contents: import numpy as np
  
  # Note: we use dtype objects instead of dtype classes. The spec does not
  # require any behavior on dtypes other than equality.
  int8 = np.dtype('int8')
  int16 = np.dtype('int16')
  int32 = np.dtype('int32')
  int64 = np.dtype('int64')
  uint8 = np.dtype('uint8')
  uint16 = np.dtype('uint16')
  uint32 = np.dtype('uint32')
  uint64 = np.dtype('uint64')
  float32 = np.dtype('float32')
  float64 = np.dtype('float64')
  # Note: This name is changed
  bool = np.dtype('bool')
  
  _all_dtypes = (int8, int16, int32, int64, uint8, uint16, uint32, uint64,
                 float32, float64, bool)
  _boolean_dtypes = (bool)
  _floating_dtypes = (float32, float64)
  _integer_dtypes = (int8, int16, int32, int64, uint8, uint16, uint32, uint64)
  _integer_or_boolean_dtypes = (bool, int8, int16, int32, int64, uint8, uint16, uint32, uint64)
  _numeric_dtypes = (float32, float64, int8, int16, int32, int64, uint8, uint16, uint32, uint64)
  
subject: Use tuples for internal type lists in the array API