code: def cityblock(u, v, w=None):
      """
      Compute the City Block (Manhattan) distance.
  
      Computes the Manhattan distance between two 1-D arrays `u` and `v`,
      which is defined as
  
      .. math::
  
         \\sum_i {\\left| u_i - v_i \\right|}.
  
      Parameters
      ----------
      u : (N,) array_like
          Input array.
      v : (N,) array_like
          Input array.
      w : (N,) array_like, optional
          The weights for each value in `u` and `v`. Default is None,
          which gives each value a weight of 1.0
  
      Returns
      -------
      cityblock : double
          The City Block (Manhattan) distance between vectors `u` and `v`.
  
      Examples
      --------
      >>> from scipy.spatial import distance
      >>> distance.cityblock([1, 0, 0], [0, 1, 0])
      2
      >>> distance.cityblock([1, 0, 0], [0, 2, 0])
      3
      >>> distance.cityblock([1, 0, 0], [1, 1, 0])
      1
  
      """
      u = _validate_vector(u)
      v = _validate_vector(v)
      l1_diff = abs(u - v)
      if w is not None:
          w = _validate_weights(w)
          l1_diff = w * l1_diff
      return l1_diff.sum()
  
imports: import math
  import warnings
  import numpy
  import dataclasses
  from typing import Optional, Callable
  from functools import partial
  from scipy._lib._util import _asarray_validated
  from .None import _distance_wrap
  from .None import _hausdorff
  from ..linalg import norm
  from ..special import rel_entr
  from .None import _distance_pybind
label_desc: Use image node_id 26 for calling a global function with example usage: cityblock(u, v, w) and returns: l1_diff