def f(): l = [0] for i in range(100000000): l += [2] return l x = f() print(x[0])
3.9: 8.6s 3.14: 8.7s 3.14 (free-threading): 11.6s
3.9: 2.78
3.14: 3.86
3.14t: 3.91
This is a silly benchmark though. Look at pyperformance if you want something that might represent real script/application performance. Generally 3.14t is about 0.9x the performance of the default build. That depends on a lot of things though.
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This benchmark demonstrates that global variables are not needed to find severe regressions.
If you don't want to use global variables just add the result of f to x and stop using the global variable, i.e.
x += f()
