Why shouldn't I use PyPy over CPython if PyPy is 6.3 times faster?

 

I've been hearing a lot about the PyPy project. They claim it is 6.3 times faster than the CPython interpreter on their site.

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.

The second issue is parallelism, the infamous Global Interpreter Lock (GIL). For this, PyPy says it can give GIL-less Python.

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.

    NOTE: This question is ancient! Avoid drawing conclusions from out-of-date information.

    That site does not claim PyPy is 6.3 times faster than CPython. To quote:

    The geometric average of all benchmarks is 0.16 or 6.3 times faster than CPython

    This is a very different statement to the blanket statement you made, and when you understand the difference, you'll understand at least one set of reasons why you can't just say "use PyPy". It might sound like I'm nit-picking, but understanding why these two statements are totally different is vital.

    To break that down:

  • The statement they make only applies to the benchmarks they've used. It says absolutely nothing about your program (unless your program is exactly the same as one of their benchmarks).

  • The statement is about an average of a group of benchmarks. There is no claim that running PyPy will give a 6.3 times improvement even for the programs they have tested.

  • There is no claim that PyPy will even run all the programs that CPython runs at all , let alone faster.

    • Because pypy is not 100% compatible, takes 8 gigs of ram to compile, is a moving target, and highly experimental, where cpython is stable, the default target for module builders for 2 decades (including c extensions that don't work on pypy), and already widely deployed.

    Pypy will likely never be the reference implementation, but it is a good tool to have.

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