PyPy 1.8 - business as usual

We’re pleased to announce the 1.8 release of PyPy. As became a habit, this release brings a lot of bugfixes, performance and memory improvements over the 1.7 release. The main highlight of the release is the introduction of list strategies which makes homogenous lists more efficient both in terms of performance and memory. Otherwise it’s “business as usual” in the sense that performance improved roughly 10% on average since the previous release. You can download the PyPy 1.8 release here:

What is PyPy?

PyPy is a very compliant Python interpreter, almost a drop-in replacement for CPython 2.7. It’s fast (pypy 1.8 and cpython 2.7.1 performance comparison) due to its integrated tracing JIT compiler.

This release supports x86 machines running Linux 32/64, Mac OS X 32/64 or Windows 32. Windows 64 work is ongoing, but not yet natively supported.

Highlights

  • List strategies. Now lists that contain only ints or only floats should be as efficient as storing them in a binary-packed array. It also improves the JIT performance in places that use such lists. There are also special strategies for unicode and string lists.
  • As usual, numerous performance improvements. There are many examples of python constructs that now should behave faster; too many to list them.
  • Bugfixes and compatibility fixes with CPython.
  • Windows fixes.
  • NumPy effort progress; for the exact list of things that have been done, consult the numpy status page. A tentative list of things that has been done:
    • multi dimensional arrays
    • various sizes of dtypes
    • a lot of ufuncs
    • a lot of other minor changes
  • Since the last release there was a significant breakthrough in PyPy’s fundraising. We now have enough funds to work on first stages of numpypy and py3k

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