# pypy / pypy / doc / release-1.9.0.rst

 Maciej Fijalkows… 0624114 2012-06-06 Armin Rigo a76be72 2012-06-06 Maciej Fijalkows… 0624114 2012-06-06 Armin Rigo a76be72 2012-06-06 Maciej Fijalkows… 0624114 2012-06-06 Armin Rigo a76be72 2012-06-06 Maciej Fijalkows… 7aaa37a 2012-06-07 Armin Rigo a76be72 2012-06-06 Maciej Fijalkows… 7aaa37a 2012-06-07 Armin Rigo a76be72 2012-06-06 Maciej Fijalkows… 7aaa37a 2012-06-07 Armin Rigo a76be72 2012-06-06 Maciej Fijalkows… 52591d7 2012-06-07 Armin Rigo a76be72 2012-06-06 Maciej Fijalkows… c18c988 2012-06-07 Armin Rigo a76be72 2012-06-06 Maciej Fijalkows… c18c988 2012-06-07 Armin Rigo a76be72 2012-06-06 Maciej Fijalkows… c18c988 2012-06-07 Armin Rigo a76be72 2012-06-06 Maciej Fijalkows… 0e45473 2012-06-07 Armin Rigo a76be72 2012-06-06 Antonio Cuni d4cd53e 2012-06-07 Antonio Cuni 503851d 2012-06-07 Antonio Cuni d4cd53e 2012-06-07 Armin Rigo a76be72 2012-06-06 Maciej Fijalkows… 0e45473 2012-06-07 Armin Rigo a76be72 2012-06-06 Maciej Fijalkows… c18c988 2012-06-07 Maciej Fijalkows… 0e45473 2012-06-07 Maciej Fijalkows… d3e13f5 2012-06-08   1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 ==================== PyPy 1.9 - Yard Wolf ==================== We're pleased to announce the 1.9 release of PyPy. This release brings mostly bugfixes, performance improvements, other small improvements and overall progress on the numpypy_ effort. It also brings an improved situation on windows and OS X. You can download the PyPy 1.9 release here: http://pypy.org/download.html .. _numpypy: http://pypy.org/numpydonate.html What is PyPy? ============= PyPy is a very compliant Python interpreter, almost a drop-in replacement for CPython 2.7. It's fast (pypy 1.9 and cpython 2.7.2_ performance comparison) due to its integrated tracing JIT compiler. This release supports x86 machines running Linux 32/64, Mac OS X 64 or Windows 32. Windows 64 work is still stalling, we would welcome a volunteer to handle that. .. _pypy 1.9 and cpython 2.7.2: http://speed.pypy.org Thanks to our donators ====================== But first of all, we would like to say thank you to all people who donated some money to one of our four calls: * NumPy in PyPy_ (got so far $44502 out of$60000, 74%) * Py3k (Python 3)_ (got so far $43563 out of$105000, 41%) * Software Transactional Memory_ (got so far $21791 of$50400, 43%) * as well as our general PyPy pot. Thank you all for proving that it is indeed possible for a small team of programmers to get funded like that, at least for some time. We want to include this thank you in the present release announcement even though most of the work is not finished yet. More precisely, neither Py3k nor STM are ready to make it an official release yet: people interested in them need to grab and (attempt to) translate PyPy from the corresponding branches (respectively py3k and stm-thread). .. _NumPy in PyPy: http://pypy.org/numpydonate.html .. _Py3k (Python 3): http://pypy.org/py3donate.html .. _Software Transactional Memory: http://pypy.org/tmdonate.html Highlights ========== * This release still implements Python 2.7, the standard library has been upgraded to CPython 2.7.2. * Many bugs were corrected for Windows 32 bit. This includes new functionality to test the validity of file descriptors; and correct handling of the calling convensions for ctypes. (Still not much progress on Win64.) A lot of work on this has been done by Matti Picus and Amaury Forgeot D'Arc. * Improvements in cpyext, our emulator for CPython C extension modules. For example PyOpenSSL should now work. * Sets now have strategies just like dictionaries. This means for example that a set containing only ints will be more compact (and faster). * A lot of progress on various aspects of numpypy. See numpy-status_ page for the automatic report. * It is now possible to create and manipulate C-like structures using the PyPy-only _ffi module. The advantage over using e.g. ctypes is that _ffi is very JIT-friendly, and getting/setting of fields is translated to few assembler instructions by the JIT. However, this is mostly intended as a low-level backend to be used by more user-friendly FFI packages, and the API might change in the future. Use it at your own risk. * The non-x86 backends for the JIT are progressing but are still not merged (ARMv7 and PPC64). * JIT hooks for inspecting the created assembler code has been improved. See JIT hooks documentation_ for details. * select.kqueue has been added. * Handling of keyword arguments has been drastically improved in the best-case scenario. * List comprehension has been improved. JitViewer ========= There is a corresponding 1.9 release of JitViewer which is guaranteed to work with PyPy 1.9. See JitViewer docs_ for details. .. _numpy status: http://buildbot.pypy.org/numpy-status/latest.html .. _JitViewer docs: http://bitbucket.org/pypy/jitviewer .. _JIT hooks documentation: http://doc.pypy.org/en/latest/jit-hooks.html Cheers, The PyPy Team 
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