<｜begin▁of▁sentence｜>### Instruction:
Imagine that we're orchestrating a project where our objective is to analyze a network of activity, mapped out in a digital diagram. This diagram is structured similarly to a flowchart, with various nodes connected by directional pathways, symbolizing different tasks or dependencies. Each node in our project's diagram has been color-coded with attributes indicative of distinct statuses or teams—specifically 'red', 'blue', and 'green'.

In the course of our project coordination, we've accumulated this network data within a GML file, aptly named 'project_network.gml'. Our current task involves examining the connectivity between these tasks or teams. To facilitate this, we require a listing that pairs up the color attributes of each connected node. This way, we'll have a clear indication of how different statuses or teams are interacting within the project flow.

In essence, could you conceive of a process or tool that would allow us to extract, from our 'project_network.gml', a list showcasing the color pairs for each directional connection? This information is instrumental as we move forward with our project analysis and reporting.
### Response:
import networkx as nx

# Create a directed graph
G = nx.DiGraph()

# Add nodes with the color attribute
G.add_node(1, color='red')
G.add_node(2, color='blue')
G.add_node(3, color='green')

# Add edges
G.add_edge(1, 2)
G.add_edge(2, 3)

# Use node_attribute_xy to get color attributes for nodes in edges
attributes = list(nx.node_attribute_xy(G, 'color'))

print(attributes)
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