Pypy is a Python interpreter that uses just-in-time (JIT) compilation instead of ahead-of-time (AOT) compilation peculiar to this language. As a result, PyPy allows our developers to speed up code execution by compiling and optimizing the code on the fly during runtime.
But how does it compare to CPython in terms of compatibility and performance? Let’s get right into it with the details!
Compatibility: Pypy is fully compatible with Python 2 and 3, which means that you can use all your favorite libraries without any issues. However, there are some limitations when using certain modules or packages due to their implementation. For example, PyPy does not support C extensions by default because they require a different compilation process. Don’t Worry! There is a way around this limitation: you can install the RPython package and use it to compile your own C extensions for Pypy.
Speed Comparison: Now performance. In general, PyPy is slower than CPython due to its JIT compilation process. However, there are some cases where PyPy can outperform CPython in terms of speed. For example, when running numeric calculations or heavily object-oriented programs, PyPy’s JIT can optimize the code and improve performance significantly.
But what about long-running scripts? Unfortunately, PyPy is not as efficient for short-running scripts because it takes longer to warm up its JIT. This means that if you run a script that only runs for a few seconds, PyPy will be slower than CPython due to the overhead of compiling and optimizing the code on the fly.
In terms of runtime functions provided by Pypy’s runtime, they are generally not as optimized as CPython’s. This means that if you use a lot of these functions in your code, PyPy may be slower than CPython due to their implementation.
A quick overview of Pypy compatibility and speed comparison. If you want to learn more about how to optimize your Python code for performance using PyPy, check out our blog post on the topic. And if you’re interested in trying out PyPy for yourself, head over to their website and download a copy today!
But before we go, let’s leave you with this thought: “Pypy is not just another Python interpreter; it’s your ticket to faster code execution!”
However, there are some things that Pypy is slower at than CPython. For example, PyPy’s runtime functions are generally not as optimized as CPython’s and can take twice as long to execute in certain cases. Additionally, using itertools for the wrong purposes or relying too heavily on ctypes can also result in slower performance with Pypy compared to CPython.
If you find any issues that are not documented here, please report them to PyPy’s bug tracker for investigation.