<｜begin▁of▁sentence｜>### Instruction:
Imagine you're crafting a new model of a precision firearm, one that requires an internal mechanism akin to a complex network with multiple pathways for the firing pin to strike the primer. In this network, akin to a series of interconnected chambers, there are two primary routes where the firing pin might travel: one follows a path looping through chambers 0, 1, 2, and 3, and the other leads through chambers 0, 3, 4, and 5.

In fine-tuning the efficiency of this weapon's internal design, you're looking to identify the most streamlined set of pathways that still allows for the full range of motion—like finding the minimum number of paths that can still represent all possible routes the firing pin can take without any redundant detours. How would you, using the tools of NetworkX if it were a digital network, calculate the simplest basis set of these cyclical pathways in the chamber mechanism? Keep in mind that just like in your craft, the goal is to shave off any unnecessary complexity to ensure a swift and reliable action upon the trigger pull.
### Response:
import networkx as nx

# Create a graph
G = nx.Graph()

# Add cycles to the graph
nx.add_cycle(G, [0, 1, 2, 3])
nx.add_cycle(G, [0, 3, 4, 5])

# Get the minimum cycle basis of the graph
minimum_cycles = nx.minimum_cycle_basis(G)

print(minimum_cycles)
<|EOT|>
