code: def multi_source_dijkstra(
      G, sources, target=None, cutoff=None, weight="weight"
  ):
      """Find shortest weighted paths and lengths from a given set of
      source nodes.
  
      Uses Dijkstra's algorithm to compute the shortest paths and lengths
      between one of the source nodes and the given `target`, or all other
      reachable nodes if not specified, for a weighted graph.
  
      Parameters
      ----------
      G : NetworkX graph
  
      sources : non-empty set of nodes
          Starting nodes for paths. If this is just a set containing a
          single node, then all paths computed by this function will start
          from that node. If there are two or more nodes in the set, the
          computed paths may begin from any one of the start nodes.
  
      target : node label, optional
          Ending node for path
  
      cutoff : integer or float, optional
          Length (sum of edge weights) at which the search is stopped.
          If cutoff is provided, only return paths with summed weight <= cutoff.
  
      weight : string or function
          If this is a string, then edge weights will be accessed via the
          edge attribute with this key (that is, the weight of the edge
          joining `u` to `v` will be ``G.edges[u, v][weight]``). If no
          such edge attribute exists, the weight of the edge is assumed to
          be one.
  
          If this is a function, the weight of an edge is the value
          returned by the function. The function must accept exactly three
          positional arguments: the two endpoints of an edge and the
          dictionary of edge attributes for that edge. The function must
          return a number or None to indicate a hidden edge.
  
      Returns
      -------
      distance, path : pair of dictionaries, or numeric and list
          If target is None, returns a tuple of two dictionaries keyed by node.
          The first dictionary stores distance from one of the source nodes.
          The second stores the path from one of the sources to that node.
          If target is not None, returns a tuple of (distance, path) where
          distance is the distance from source to target and path is a list
          representing the path from source to target.
  
      Examples
      --------
      >>> G = nx.path_graph(5)
      >>> length, path = nx.multi_source_dijkstra(G, {0, 4})
      >>> for node in [0, 1, 2, 3, 4]:
      ...     print(f"{node}: {length[node]}")
      0: 0
      1: 1
      2: 2
      3: 1
      4: 0
      >>> path[1]
      [0, 1]
      >>> path[3]
      [4, 3]
  
      >>> length, path = nx.multi_source_dijkstra(G, {0, 4}, 1)
      >>> length
      1
      >>> path
      [0, 1]
  
      Notes
      -----
      Edge weight attributes must be numerical.
      Distances are calculated as sums of weighted edges traversed.
  
      The weight function can be used to hide edges by returning None.
      So ``weight = lambda u, v, d: 1 if d['color']=="red" else None``
      will find the shortest red path.
  
      Based on the Python cookbook recipe (119466) at
      https://code.activestate.com/recipes/119466/
  
      This algorithm is not guaranteed to work if edge weights
      are negative or are floating point numbers
      (overflows and roundoff errors can cause problems).
  
      Raises
      ------
      ValueError
          If `sources` is empty.
      NodeNotFound
          If any of `sources` is not in `G`.
  
      See Also
      --------
      multi_source_dijkstra_path
      multi_source_dijkstra_path_length
  
      """
      if not sources:
          raise ValueError("sources must not be empty")
      for s in sources:
          if s not in G:
              raise nx.NodeNotFound(f"Node {s} not found in graph")
      if target in sources:
          return (0, [target])
      weight = _weight_function(G, weight)
      paths = {
          source: [source] for source in sources
      }  # dictionary of paths
      dist = _dijkstra_multisource(
          G, sources, weight, paths=paths, cutoff=cutoff, target=target
      )
      if target is None:
          return (dist, paths)
      try:
          return (dist[target], paths[target])
      except KeyError as err:
          raise nx.NetworkXNoPath(f"No path to {target}.") from err
  
imports: from collections import deque
  from heapq import heappop, heappush
  from itertools import count
  import networkx
  from networkx.algorithms.shortest_paths.generic import _build_paths_from_predecessors
label_desc: Use image node_id 9 for calling a global function with example usage: multi_source_dijkstra(G, sources, target, cutoff, weight) and returns: int,  list, dist,  paths, dist,  paths