Here's an implementation of the Floyd-Warshall algorithm in Python, which uses dynamic programming to find the shortest path between all pairs of nodes in a graph:

```
def floydWarshall(graph):
    n = len(graph)
    dist = [[float('inf')] * n for _ in range(n)]
    
    for i in range(n):
        for j in range(n):
            if i == j:
                dist[i][j] = 0
            elif graph[i][j] != None:
                dist[i][j] = graph[i][j]

    for k in range(n):
        for i in range(n):
            for j in range(n):
                dist[i][j] = min(dist[i][j], dist[i][k] + dist[k][j])

    return dist
```

Here, `graph` is a 2D matrix representing the weighted adjacency matrix of the graph, where `graph[i][j]` is the weight of the edge from node `i` to node `j`, or `None` if there is no such edge. The `dist` matrix is used to store the shortest path distances between pairs of nodes.

The algorithm initializes `dist[i][j]` to the weight of edge `(i,j)` if it exists, or infinity otherwise, and `dist[i][i]` to 0 for all `i`. Then, it iterates over all pairs of nodes using a triple nested loop, and updates `dist[i][j]` to the minimum of its current value and the sum of `dist[i][k]` and `dist[k][j]`, where `k` is an intermediate node in the path from `i` to `j`.

Once the algorithm is complete, the `dist` matrix will contain the shortest path distances between all pairs of nodes in the graph.
Scrivi una funzione che utilizzi la programmazione dinamica per trovare il percorso più breve tra tutte le coppie di nodi in un grafo.