<｜begin▁of▁sentence｜>### Instruction:
As an architect meticulously designing a linear arrangement of community spaces, envision a schematic where these spaces are represented as 10 interconnected points in a sequence, akin to a path graph that we architects model for various functional pathways. Now, to optimize the use of these spaces, we seek to identify the largest set of these points such that none are directly connected — a concept we might liken to allocating distinct, non-overlapping activities in the communal design. Additionally, we aim to determine all substantial groupings of points where each is directly linked to every other, much like identifying potential clusters of community areas that can serve as social nodes. 

Could we model this scenario by utilizing NetworkX's algorithm that systematically removes cliques and, in turn, reveals both the largest non-overlapping set of these communal spaces and the comprehensive list of social node clusters within our designed community schematic?
### Response:
import networkx as nx

# Create an undirected graph
G = nx.path_graph(10)

# Use the clique_removal function which returns the largest independent set
# and the list of maximal cliques found
max_ind_set, maximal_cliques = nx.approximation.clique_removal(G)

print('The largest independent set:', max_ind_set)
print('The list of maximal cliques:', maximal_cliques)
<|EOT|>
