code: def squared_euclidean(x, y):
      """
      Compute the squared Euclidean distance between two dictionaries or
      two lists of equal length. Suppose `x` and `y` each contain
      :math:`d` variables:
  
      .. math:: D(x, y) = \\sum_i^d (x_i - y_i)^2
  
      Parameters
      ----------
      x : dict or list
          First input vector.
  
      y : dict or list
          Second input vector.
  
      Returns
      -------
      out : float
          Squared Euclidean distance between `x` and `y`.
  
      Notes
      -----
      - If the input vectors are in dictionary form, keys missing in one
        of the two dictionaries are assumed to have value 0.
  
      - Squared Euclidean distance does not satisfy the triangle
        inequality, so it is not a metric. This means the ball tree cannot
        be used to compute nearest neighbors based on this distance.
  
      References
      ----------
      - `Wikipedia - Euclidean distance
        <http://en.wikipedia.org/wiki/Euclidean_distance>`_
  
      Examples
      --------
      >>> tc.distances.squared_euclidean([1, 2, 3], [4, 5, 6])
      27.0
      ...
      >>> tc.distances.squared_euclidean({'a': 2, 'c': 4},
      ...                                {'b': 3, 'c': 12})
      77.0
      """
      return _tc.extensions._distances.squared_euclidean(x, y)
  
file_path: turicreate/src/python/turicreate/toolkits/distances/_distances.py
imports: from __future__ import print_function
  from __future__ import division
  from __future__ import absolute_import
  import turicreate
label_desc: Use image node_id 3 for calling a global function with example usage: squared_euclidean(x, y) and returns: _tc