<｜begin▁of▁sentence｜>### Instruction:
As a Public Relations Specialist, I'm tasked with developing and implementing public relations (PR) strategies for a technology company that specializes in network infrastructure. One of our key initiatives involves showcasing our expertise in network analysis and optimization, and we're planning a series of events to demonstrate our capabilities.

To ensure the success of these events, I need to calculate the maximum flow between different points within a network, representing the efficient transfer of information or resources. Specifically, I have a directed graph with the following edges and weights: [(0, 1), (1, 2), (2, 3), (0, 3)] with respective weights [4, 2, 1, 5]. 

Using the igraph library, I'm seeking to leverage network analysis to determine the maximum flow between vertex 0 and vertex 3, a critical aspect of our PR campaign to highlight our technological prowess.
### Response:
import igraph as ig

# Create a graph with weighted edges
edges = [(0, 1), (1, 2), (2, 3), (0, 3)]
weights = [4, 2, 1, 5]
g = ig.Graph(edges=edges)
g.es['weight'] = weights

# Compute the maximum flow between vertex 0 and vertex 3
max_flow = g.maxflow(0, 3, weights)

# Print the max flow using the Flow object's __repr__
print(max_flow)
<|EOT|>
