human
I am working on the file "1_foundations/4_simulated_annealing/simulated_annealing.ipynb".
The first task is:
III. Representing the Problem
In order to use simulated annealing we need to build a representation of the problem domain.  The choice of representation can have a significant impact on the performance of simulated annealing and other optimization techniques.  Since the TSP deals with a close loop that visits each city in a list once, we will represent each city by a tuple containing the city name and its position specified by an (x,y) location on a grid.  The state will then consist of an ordered sequence (a list) of the cities.
the path is defined as the sequence generated by traveling from each city in the list to the next in order.
Can you write Python code for it?
 ... Write me a the Python code you requested?
assistant
#Here is the Python code you requested.

Node = Tuple[str, Tuple[int, int]]

class TravelingSalesmanProblem:
    """Representation of a traveling salesman optimization problem.  The goal
    is to find the shortest path that visits every city in a closed loop path.
    
    Students should only need to implement or modify the successors() and
    get_values() methods.
    
    Parameters
    ----------
    cities : list
        A list of cities specified by a tuple containing the name and the x, y
        location of the city on a grid. e.g., ("Atlanta", (585.6, 376.8))
    
    Attributes
    ----------
    names
    coords
    path : list
        The current path between cities as specified by the order of the city
        tuples in the list.
    """
    def __init__(self, cities) -> None:
        self.path = copy.deepcopy(cities)
    
    def copy(self) -> Any:
        """Return a copy of the current board state."""
        new_tsp = TravelingSalesmanProblem(self.path)
        return new_tsp
    
    @property
    def names(self) -> Tuple:
        """Strip and return only the city name from each element of the
        path list. For example,
            [("Atlanta", (585.6, 376.8)), ...] -> ["Atlanta", ...]
        """
        names, _ = zip(*self.path)
        return names
    
    @property
    def coords(self) -> Tuple:
        """Strip the city name from each element of the path list and return
        a list of tuples containing only pairs of xy coordinates for the
        cities. For example,
            [("Atlanta", (585.6, 376.8)), ...] -> [(585.6, 376.8), ...]
        """
        _, coords = zip(*self.path)
        return coords
    
    def successors(self) -> List[Any]:
        """Return a list of states in the neighborhood of the current state by
        switching the order in which any adjacent pair of cities is visited.
        
        For example, if the current list of cities (i.e., the path) is [A, B, C, D]
        then the neighbors will include [A, B, D, C], [A, C, B, D], [B, A, C, D],
        and [D, B, C, A]. (The order of...