code: def min_cost_flow_cost(
      G, demand="demand", capacity="capacity", weight="weight"
  ):
      r"""Find the cost of a minimum cost flow satisfying all demands in digraph G.
  
      G is a digraph with edge costs and capacities and in which nodes
      have demand, i.e., they want to send or receive some amount of
      flow. A negative demand means that the node wants to send flow, a
      positive demand means that the node want to receive flow. A flow on
      the digraph G satisfies all demand if the net flow into each node
      is equal to the demand of that node.
  
      Parameters
      ----------
      G : NetworkX graph
          DiGraph on which a minimum cost flow satisfying all demands is
          to be found.
  
      demand : string
          Nodes of the graph G are expected to have an attribute demand
          that indicates how much flow a node wants to send (negative
          demand) or receive (positive demand). Note that the sum of the
          demands should be 0 otherwise the problem in not feasible. If
          this attribute is not present, a node is considered to have 0
          demand. Default value: 'demand'.
  
      capacity : string
          Edges of the graph G are expected to have an attribute capacity
          that indicates how much flow the edge can support. If this
          attribute is not present, the edge is considered to have
          infinite capacity. Default value: 'capacity'.
  
      weight : string
          Edges of the graph G are expected to have an attribute weight
          that indicates the cost incurred by sending one unit of flow on
          that edge. If not present, the weight is considered to be 0.
          Default value: 'weight'.
  
      Returns
      -------
      flowCost : integer, float
          Cost of a minimum cost flow satisfying all demands.
  
      Raises
      ------
      NetworkXError
          This exception is raised if the input graph is not directed or
          not connected.
  
      NetworkXUnfeasible
          This exception is raised in the following situations:
  
              * The sum of the demands is not zero. Then, there is no
                flow satisfying all demands.
              * There is no flow satisfying all demand.
  
      NetworkXUnbounded
          This exception is raised if the digraph G has a cycle of
          negative cost and infinite capacity. Then, the cost of a flow
          satisfying all demands is unbounded below.
  
      See also
      --------
      cost_of_flow, max_flow_min_cost, min_cost_flow, network_simplex
  
      Notes
      -----
      This algorithm is not guaranteed to work if edge weights or demands
      are floating point numbers (overflows and roundoff errors can
      cause problems). As a workaround you can use integer numbers by
      multiplying the relevant edge attributes by a convenient
      constant factor (eg 100).
  
      Examples
      --------
      A simple example of a min cost flow problem.
  
      >>> G = nx.DiGraph()
      >>> G.add_node("a", demand=-5)
      >>> G.add_node("d", demand=5)
      >>> G.add_edge("a", "b", weight=3, capacity=4)
      >>> G.add_edge("a", "c", weight=6, capacity=10)
      >>> G.add_edge("b", "d", weight=1, capacity=9)
      >>> G.add_edge("c", "d", weight=2, capacity=5)
      >>> flowCost = nx.min_cost_flow_cost(G)
      >>> flowCost
      24
      """
      return nx.network_simplex(
          G, demand=demand, capacity=capacity, weight=weight
      )[0]
  
imports: import networkx
label_desc: Use image node_id 1 for calling a global function with example usage: min_cost_flow_cost(G, demand, capacity, weight) and returns: nx