"Shed Skin is able to speed up the examples by an average factor of about 29 times (not percent, times :)), while PyPy is able to speed up the examples by an average factor of about 16 times. Given that PyPy has its hands tied behind its back trying to support unrestricted Python code, and was not optimized specifically for these examples (that I am aware of), that is actually still quite an impressive result."
"As for the few cases where PyPy performs better than Shed Skin, this appears to be mainly because of PyPy being able to optimize away heap allocations for short-lived objects (in many cases, custom Vector(x,y,z) instances). In a few cases also, the STL unordered_map that Shed Skin uses to implement dictionaries appears to perform poorly compared to more modern implementations. Of course it is possible for Shed Skin to improve in these areas with future releases."
Benchmarks compare CPython 3.10, CPython 3.14, Nuitka, PyPy, and Shed Skin across many Shed Skin example programs, excluding randomized or interactive cases. Shed Skin delivers an average speedup of roughly 29× versus CPython 3.10, while PyPy averages about 16×. PyPy sometimes outperforms Shed Skin by eliminating heap allocations for short-lived objects and via other runtime optimizations. The STL unordered_map used by Shed Skin can be slower in certain dictionary-heavy workloads. Shed Skin runtime can improve with options that disable wrap-around and bounds checking. CPython 3.14 shows about a 60% average improvement over CPython 3.10 for these examples.
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