Yes, there are several libraries in Python that you can use to implement the Hungarian algorithm. One of the most commonly used libraries is scipy.optimize, which provides the function linear_sum_assignment for solving the assignment problem. Here's how you can use it:

```
import numpy as np
from scipy.optimize import linear_sum_assignment

cost_matrix = np.array([[4, 1, 3], [2, 0, 5], [3, 2, 2]])
row_ind, col_ind = linear_sum_assignment(cost_matrix)

print("Minimum cost:", sum(cost_matrix[row_ind, col_ind]))
print("Assignments:", list(zip(row_ind, col_ind)))

```

In the above code, linear_sum_assignment returns the indices of the rows and columns that correspond to the minimum cost assignment. The function takes the cost_matrix as input and returns the row indices and column indices of the optimal assignment, which can be used to compute the minimum cost by summing up the values at the corresponding entries of the cost matrix.
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