<｜begin▁of▁sentence｜>### Instruction:
Imagine you're deep in the forest, where paths diverge and converge, much like the flow of nutrients and resources within this ecosystem. In managing the forest, consider each tree as a node in a complex network, and the directed paths that connect them—much like the flow of water or the spread of seeds—are the edges. In this network, the trees are interconnected in various ways: some may send resources out to multiple others, while others might receive from many, mimicking a directed graph with edges representing these connections.

In this scenario, you've observed the interactions between trees in a specific area, and they follow a particular pattern resembling edges (1, 2), (2, 3), (3, 2), and (2, 1). Each tree (node) can either send out (out-degree) or receive (in-degree) resources. Your task, as a silviculturist aiming to promote the health and sustainability of this forest section, is to analyze these interactions by pairing each tree based on their functional role in the ecosystem—specifically, by creating pairs of trees where one is characterized by its role in distributing resources (out-degree) and the other by its role in receiving (in-degree), as observed in their connections.

Could you develop a method to synthesize this information, focusing on the degree type for the outgoing connections from a tree and the incoming connections to another? This analysis will aid in understanding the forest's complex dynamics, ensuring informed decisions can be made for its management and conservation.
### Response:
import networkx as nx

# Create a directed graph
G = nx.DiGraph()
# Add edges
d = [(1, 2), (2, 3), (3, 2), (2, 1)]
G.add_edges_from(d)
# Generate node degree-degree pairs for edges
for x, y in nx.node_degree_xy(G, x='out', y='in'):
 print((x, y))
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