<｜begin▁of▁sentence｜>### Instruction:
As a rehabilitation counselor, you're working with a client who's eager to explore vocational opportunities but feels overwhelmed by the complexity of certain tasks. In this case, imagine your client is navigating a new job where they're tasked with optimizing resources in a network setting.

Your client shares a scenario where they're overseeing a network of interconnected nodes representing various tasks or resources, each with its own dependencies. They specifically mention a cycle graph where the vertices correspond to different stages of a project, labeled as {0, 1, 2, 3, 4}, and the edges represent the flow or dependencies between these stages.

To help your client better understand the network's dynamics, they're interested in determining the independence number, which essentially signifies the largest possible subset of nodes that are mutually independent or can operate concurrently without conflicting dependencies.

In exploring solutions, your client mentions the possibility of utilizing the independence_number function available in the igraph API, a powerful tool for analyzing network structures. By leveraging this function, they hope to gain insights into how to optimize resource allocation and streamline workflow processes within the network.
### Response:
import igraph as ig

# Generate a graph
g = ig.Graph(edges=[(0, 1), (1, 2), (2, 3), (3, 4), (4, 0)])

# Get the independence number of the graph
indep_number = g.independence_number()

# Print the independence number
print('The independence number of the graph is:', indep_number)
<|EOT|>
