code: def guess_plotly_rangebreaks(dt_index: pd.DatetimeIndex):
      """
      This function `guesses` the rangebreaks required to remove gaps in datetime index.
      It basically calculates the difference between a `continuous` datetime index and index given.
  
      For more details on `rangebreaks` params in plotly, see
      https://plotly.com/python/reference/layout/xaxis/#layout-xaxis-rangebreaks
  
      Parameters
      ----------
      dt_index: pd.DatetimeIndex
      The datetimes of the data.
  
      Returns
      -------
      the `rangebreaks` to be passed into plotly axis.
  
      """
      dt_idx = dt_index.sort_values()
      gaps = dt_idx[1:] - dt_idx[:-1]
      min_gap = gaps.min()
      gaps_to_break = {}
      for gap, d in zip(gaps, dt_idx[:-1]):
          if gap > min_gap:
              gaps_to_break.setdefault(gap - min_gap, []).append(
                  d + min_gap
              )
      return [
          dict(values=v, dvalue=int(k.total_seconds() * 1000))
          for k, v in gaps_to_break.items()
      ]
  
label_desc: Use image node_id 2 for calling a global function with example usage: guess_plotly_rangebreaks(dt_index) and returns: unknown