Repeated calculation of angr CFGFasr leads to low running efficiency and high memory consumption when there are too many function

in AngrAnalysis.__init__()
self.cfg = self.target.analyses.CFG(
resolve_indirect_jumps=True,
cross_references=True,
force_complete_scan=False,
normalize=True,
symbols=True,
)

the edges of functions is already in self.cfg
the way to get edges of function are followings

for func in self.cfg.functions.values():
print(func.addr, len(func.transition_graph.edges))

so I think the code of function get_cyclomatic_complexity(),

cfg = self.target.analyses.CFGFast(
force_complete_scan=False, start_at_entry=hex(func.addr)
)

This code uses CFGFast to recalculate edges for each function.
Leading to low running efficiency and high memory consumption when there are too many function.

Can we optimize this ：)

Best regards
XZJ

Start in AngrAnalysis.__init__() and get_cyclomatic_complexity(), focusing on how self.cfg and each function's transition_graph.edges are used. Compare that with the per-function CFGFast call and identify a way to avoid repeated CFG construction while preserving cyclomatic-complexity results. Done means the repeated calculation is removed and behavior remains correct for functions with many edges.

Written by the indexing model from the issue text.