Reproducing assignment with min cost flow in networkx

[mntfr]

Hi so I have seen the ortools webpage ortools where it states that you can solve the assignment problem with the min cost flow algorithm, however when I try to reproduce this process with networkx I get an error. Can somebody point me to what am I doing wrong?

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workersList = ['s1', 's2', 's3', 's4'] tasksList = ['c1', 'c2', 'c3', 'c4'] costs = [[90, 76, 75, 70], [35, 85, 55, 65], [125, 95, 90, 105], [45, 110, 95, 115]]   import networkx as nx G = nx.DiGraph() G.add_node('Start', demand = len(workersList)) G.add_node('End', demand = -len(workersList)) G.add_nodes_from(workersList) G.add_nodes_from(tasksList)   for worker in workersList:     G.add_edge('Start', work, weight=0, capacity=1)   for task in tasksList:     G.add_edge(task, 'End', weigth=0, capacity=1)   for i, worker in enumerate(workersList):     for j, task in enumerate(tasksList):         if costs[i][j] != 'NA':             G.add_edge(worker, task, weight=costs[i][j], capacity=1)   flowDict = nx.min_cost_flow(G) print(flowDict)