On average, PyPy is about 3 times faster than CPython 3.11. We currently support python 3.11 and 2.7.
PyPy (with JIT) benchmark times normalized to CPython. Smaller is better. Based on the geometric average of all benchmarks
"... we are avid fans of PyPy and commensurately thankful for the great work by the PyPy team over the years. PyPy has enabled us to use Python for a larger part of our toolset than CPython alone would have supported, and its smooth integration with C/C++ through CFFI has helped us attain a better tradeoff between performance and programmer productivity in our projects" -- Vilhjálmur Þorsteinsson, founder and CEO of Miðeind, Feb 2022
Advantages and distinct Features
Speed: thanks to its Just-in-Time compiler, Python programs often run faster on PyPy. (What is a JIT compiler?)
Memory usage: memory-hungry Python programs (several hundreds of MBs or more) might end up taking less space than they do in CPython.
Compatibility: PyPy is highly compatible with existing python code. It supports cffi, cppyy, and can run popular python libraries like twisted, and django. It can also run NumPy, Scikit-learn and more via a c-extension compatibility layer.
Stackless: PyPy comes by default with support for stackless mode, providing micro-threads for massive concurrency.
As well as other features.
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