<｜begin▁of▁sentence｜>### Instruction:
As a product manager overseeing the development of our latest navigation software, we're exploring ways to enhance the routing algorithm's efficiency. Our team has provided a preliminary dataset representing the transit times (in minutes) between various checkpoints within our network. The dataset includes the following transit times: checkpoint A to B at 3 minutes, B to C at 7 minutes, A to C at 1 minute, and C to D at 2 minutes.

We need to optimize our application to ensure the fastest journey for our users. Could you integrate the provided transit times into a simulation using NetworkX, to ascertain the minimum transit time required for a user to navigate from checkpoint A to checkpoint D? This will serve as a critical step in refining our routing algorithm, guaranteeing quicker and more effective travel recommendations within our product.
### Response:
import networkx as nx

# Create a weighted graph
G = nx.Graph()
G.add_weighted_edges_from([('A', 'B', 3), ('B', 'C', 7), ('A', 'C', 1), ('C', 'D', 2)])

# Compute the shortest path length from A to D
length = nx.dijkstra_path_length(G, 'A', 'D', weight='weight')
print('Shortest path length from A to D:', length)
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