Why shouldn't I use PyPy over CPython if PyPy is 6.3 times faster?
Whenever we talk about dynamic languages like Python, speed is one of the top issues. To solve this, they say PyPy is 6.3 times faster.
If PyPy can solve these great challenges, what are its weaknesses that are preventing wider adoption? That is to say, what's preventing someone like me, a typical Python developer, from switching to PyPy right now?
- PyPy, as others have been quick to mention, has tenuous support for C extensions. It has support, but typically at slower-than-Python speeds and it's iffy at best. Hence a lot of modules simply require CPython. Cython and Numpy are awesome for numerics, and most people who actually need speed in Python are using those (+ Pandas, SciPy, etc.) heavily. Since they're either non-existent or tenuously supported and slow the people who need a fast Python often are better off with CPython both for speed and ease-of-use.
- Python 3 support
is experimental at the moment.has just reached stable! As of 20th June 2014,PyPy3 2.3.1 - Fulcrum is out!
- PyPy sometimes isn't actually faster for "scripts", which a lot of people use Python for. These are the short-running programs that do something simple and small. Because PyPy is a JIT compiler its main advantages come from long run times and simple types (such as numbers). Frankly, PyPy's pre-JIT speeds are pretty bad compared to CPython.
- Inertia. Moving to PyPy often requires retooling, which for some people and organizations is simply too much work.
Those are the main reasons that affect me, I'd say.
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