Mailman 3 December 2013 - pypy-issue

[issue1662] 'is' should be '==' in datetime.py
by Kevin Duffy 18 Dec '13

18 Dec '13

New submission from Kevin Duffy <kmdext(a)apple.com>: There are a few places in datetime.py where the 'is' operator is used but it should really be '=='. This can cause comparisons to fail even when two tzinfo's are equivalent. Simple patch attached. ---------- files: pypy-datetime.patch messages: 6424 nosy: kmdext, pypy-issue priority: bug release: 2.2 status: unread title: 'is' should be '==' in datetime.py ________________________________________ PyPy bug tracker <tracker(a)bugs.pypy.org> <https://bugs.pypy.org/issue1662> ________________________________________

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[issue1661] numpy: rec.fromarrays fails with TypeError: data type not understood
by Anders Kaseorg 15 Dec '13

15 Dec '13

New submission from Anders Kaseorg <andersk(a)mit.edu>: Python 2.7.3 (55f7a6da11c7, Dec 14 2013, 23:00:23) [PyPy 2.3.0-alpha0 with GCC 4.6.3] on linux2 Type "help", "copyright", "credits" or "license" for more information. And now for something completely different: ``fijal: can I initiate you on the (easy but) non-trivial topic of writing C function types? :-)'' >>>> import numpy as np >>>> np.rec.fromarrays((np.array([10, 20, 30]), np.array([40, 50, 60])), dtype=[('a', int), ('b', int)]) Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/home/anders/pypy-nightly-env/site-packages/numpy/core/records.py", line 564, in fromarrays _array = recarray(shape, descr) File "/home/anders/pypy-nightly-env/site-packages/numpy/core/records.py", line 402, in __new__ self = ndarray.__new__(subtype, shape, (record, descr), order=order) TypeError: data type not understood (value of type type not expected here) ---------- messages: 6423 nosy: andersk, pypy-issue priority: bug status: unread title: numpy: rec.fromarrays fails with TypeError: data type not understood ________________________________________ PyPy bug tracker <tracker(a)bugs.pypy.org> <https://bugs.pypy.org/issue1661> ________________________________________

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[issue1660] numpy: triu_indices, tril_indices fails with AttributeError: 'ufunc' object has no attribute 'outer'
by Anders Kaseorg 15 Dec '13

15 Dec '13

New submission from Anders Kaseorg <andersk(a)mit.edu>: Although http://buildbot.pypy.org/numpy-status/latest.html claims that triu_indices and tril_indices should work, they don’t: Python 2.7.3 (55f7a6da11c7, Dec 14 2013, 23:00:23) [PyPy 2.3.0-alpha0 with GCC 4.6.3] on linux2 Type "help", "copyright", "credits" or "license" for more information. And now for something completely different: ``it is the expected behavior, except when you don't expect it'' >>>> import numpy as np >>>> np.triu_indices(4) Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/home/anders/pypy-nightly-env/site-packages/numpy/lib/twodim_base.py", line 900, in triu_indices return mask_indices(n, triu, k) File "/home/anders/pypy-nightly-env/site-packages/numpy/lib/twodim_base.py", line 723, in mask_indices a = mask_func(m, k) File "/home/anders/pypy-nightly-env/site-packages/numpy/lib/twodim_base.py", line 450, in triu out = multiply((1 - tri(m.shape[0], m.shape[1], k - 1, dtype=m.dtype)), m) File "/home/anders/pypy-nightly-env/site-packages/numpy/lib/twodim_base.py", line 388, in tri m = greater_equal(subtract.outer(arange(N), arange(M)), -k) AttributeError: 'ufunc' object has no attribute 'outer' ---------- messages: 6422 nosy: andersk, pypy-issue priority: bug status: unread title: numpy: triu_indices, tril_indices fails with AttributeError: 'ufunc' object has no attribute 'outer' ________________________________________ PyPy bug tracker <tracker(a)bugs.pypy.org> <https://bugs.pypy.org/issue1660> ________________________________________

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[issue1659] numpy: 0-d arrays should be indexable with np.newaxis
by Anders Kaseorg 14 Dec '13

14 Dec '13

New submission from Anders Kaseorg <andersk(a)mit.edu>: In CPython, np.array(1)[np.newaxis] returns array([1]). In PyPy, it raises “IndexError: 0-d arrays can't be indexed”. This also shows up in code like this: a = np.zeros(10) b = np.array([3,4,5]) a[b] = 1 # CPython: a == array([0, 0, 0, 1, 1, 1, 0, 0, 0, 0]) # PyPy: IndexError: 0-d arrays can't be indexed (Is it useful to report bugs in PyPy’s numpy implementation at this stage?) Version info: Python 2.7.3 (0edc9b68247e, Dec 13 2013, 23:00:16) [PyPy 2.3.0-alpha0 with GCC 4.6.3] on linux2 ---------- messages: 6420 nosy: andersk, pypy-issue priority: bug status: unread title: numpy: 0-d arrays should be indexable with np.newaxis ________________________________________ PyPy bug tracker <tracker(a)bugs.pypy.org> <https://bugs.pypy.org/issue1659> ________________________________________

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[issue1658] Add an accompanying env variable for --jit
by Philip Jenvey 13 Dec '13

13 Dec '13

New submission from Philip Jenvey <pjenvey(a)underboss.org>: The pypy-c --jit cmd line option could probably use an accompanying env variable, e.g. PYPY_JIT=off ---------- messages: 6419 nosy: pypy-issue priority: feature status: unread title: Add an accompanying env variable for --jit ________________________________________ PyPy bug tracker <tracker(a)bugs.pypy.org> <https://bugs.pypy.org/issue1658> ________________________________________

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[issue1657] numpy failing with AttributeError: 'ndarray' object has no attribute 'flags'
by lesshaste 13 Dec '13

13 Dec '13

New submission from lesshaste <drraph(a)gmail.com>: Some simple code fails with the error Traceback (most recent call last): File "app_main.py", line 72, in run_toplevel File "counterfeit.py", line 9, in <module> F = np.matrix(list(itertools.product([0,1],repeat = n))).transpose() File "/usr/local/lib/pypy2.7/dist-packages/numpy/matrixlib/defmatrix.py", line 279, in __new__ if (ndim == 2) and arr.flags.fortran: AttributeError: 'ndarray' object has no attribute 'flags' ---------- files: counterfeit.py messages: 6414 nosy: lesshaste, pypy-issue priority: bug status: unread title: numpy failing with AttributeError: 'ndarray' object has no attribute 'flags' ________________________________________ PyPy bug tracker <tracker(a)bugs.pypy.org> <https://bugs.pypy.org/issue1657> ________________________________________

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[issue1655] ctypes errcheck protocol different from cpython implementation
by Roman Valov 08 Dec '13

08 Dec '13

New submission from Roman Valov <roman.valov(a)gmail.com>: Hi, folks. Currently I'm working on bindings for C-based library using ctypes and once bindings were complete I've tried to test them using PyPy. The library I'm working on have a lots of function definitions that return pointer to the list with number of items in the list returned via passed-by-ref argument. Here is example of C source: #include <stdio.h> int data[] = { -1, -2, -3, -4 }; int *get_data(char const *tag, int *len) { printf("tag: %s\n", tag); *len = sizeof(data) / sizeof(data[0]); return data; } Once saved as sample.c, it should be compiled to shared library: gcc sample.c -o libsample.so -fPIC -shared Next, I'd wrapped such functions using both paramflags and errcheck functionality of ctypes function prototypes. Here is it: #!/usr/bin/python from ctypes import cdll, CFUNCTYPE, POINTER, c_int, c_char_p lib = cdll.LoadLibrary('./libsample.so') def ret_list_p(icount): def sz_array_p(obj, func, args): print (repr(obj)) print (repr(args)) return [ obj[i] for i in range(args[icount].value) ] return sz_array_p get_data_prototype = CFUNCTYPE(POINTER(c_int), c_char_p, POINTER(c_int)) get_data_paramflag = ((1,), (2,)) get_data_signature = ('get_data', lib) get_data = get_data_prototype( get_data_signature, get_data_paramflag ) print get_data('noerrcheck') get_data.errcheck = ret_list_p(1) print get_data('doerrcheck') Once this code is invoked with CPython implementation I've got following result: tag: noerrcheck 4 tag: doerrcheck <__main__.LP_c_int object at 0x7ffb124775f0> ('doerrcheck', c_int(4)) [-1, -2, -3, -4] but with PyPy I'm faced with errors due to errcheck got python wrapper args, but not args binded function was called with: tag: noerrcheck 4 tag: doerrcheck <_ctypes.pointer.LP_c_int object at 0x00007f27b7d62250> ('doerrcheck',) Traceback (most recent call last): File "app_main.py", line 72, in run_toplevel File "./sample.py", line 24, in <module> print get_data('doerrcheck') File "/usr/lib/pypy/lib_pypy/_ctypes/function.py", line 343, in __call__ result = self._do_errcheck(result, args) File "/usr/lib/pypy/lib_pypy/_ctypes/function.py", line 387, in _do_errcheck v = self._errcheck_(result, self, args) File "./sample.py", line 11, in sz_array_p return [ obj[i] for i in range(args[icount].value) ] IndexError: tuple index out of range ---------- files: sample.py messages: 6407 nosy: pypy-issue, reddot priority: bug status: unread title: ctypes errcheck protocol different from cpython implementation ________________________________________ PyPy bug tracker <tracker(a)bugs.pypy.org> <https://bugs.pypy.org/issue1655> ________________________________________

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[issue1654] math.factorial is slow
by anon 07 Dec '13

07 Dec '13

New submission from anon <b10419697(a)klzlk.com>: math.factorial uses a very simple algorithm multiplying by each value in range(1,x+1) in turn. A better method would be to do binary splitting. I am unfamiliar with PyPy internals, however I believe app_math.py implements factorial in pure Python. Provided below is a patch that uses binary splitting. It seems much faster for large factorials, but maybe uses slightly more memory and seems 10% slower for very small factorials. def factorial(x): """Find x!.""" if isinstance(x, float): fl = int(x) if fl != x: raise ValueError("float arguments must be integral") x = fl if x < 0: raise ValueError("x must be >= 0") #Experimentally this gap seems good gap = max(100, x>>7) def _fac(low, high): if low+gap >= high: t = 1 for i in range(low, high): t *= i return t mid = (low + high) >> 1 return _fac(low, mid) * _fac(mid, high) return _fac(1, x+1) If someone can improve it further, that would be great. My portion of the code is public domain. ________________________________________ PyPy bug tracker <tracker(a)bugs.pypy.org> <https://bugs.pypy.org/issue1654> ________________________________________

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[issue1654] math.factorial is slow
by anon 06 Dec '13

06 Dec '13

New submission from anon <b10419697(a)klzlk.com>: math.factorial uses a very simple algorithm multiplying by each value in range(1,x+1) in turn. A better method would be to do binary splitting. I am unfamiliar with PyPy internals, however I believe app_math.py implements factorial in pure Python. Provided below is a patch that uses binary splitting. It seems much faster for large factorials, but maybe uses slightly more memory and seems 10% slower for very small factorials. def factorial(x): """Find x!.""" if isinstance(x, float): fl = int(x) if fl != x: raise ValueError("float arguments must be integral") x = fl if x < 0: raise ValueError("x must be >= 0") #Experimentally this gap seems good gap = max(100, x>>7) def _fac(low, high): if low+gap >= high: t = 1 for i in range(low, high): t *= i return t mid = (low + high) >> 1 return _fac(low, mid) * _fac(mid, high) return _fac(1, x+1) If someone can improve it further, that would be great. The code is public domain. ________________________________________ PyPy bug tracker <tracker(a)bugs.pypy.org> <https://bugs.pypy.org/issue1654> ________________________________________

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[issue1654] math.factorial is slow
by anon 06 Dec '13

06 Dec '13

New submission from anon <b10419697(a)klzlk.com>: math.factorial uses a very simple algorithm multiplying by each value in range(1,x+1) in turn. A better method would be to do binary splitting. I am unfamiliar with PyPy internals, however I believe app_math.py implements factorial in pure Python. Provided below is a patch that uses binary splitting. It seems much faster for large factorials, but maybe uses slightly more memory and seems 10% slower for very small factorials. def factorial(x): """Find x!.""" if isinstance(x, float): fl = int(x) if fl != x: raise ValueError("float arguments must be integral") x = fl #Experimentally this gap seems good gap = max(100, x>>7) def _fac(low, high): if low+gap >= high: t = 1 for i in range(low, high): t *= i return t mid = (low + high) >> 1 return _fac(low, mid) * _fac(mid, high) return _fac(1, x+1) If someone can improve it further, that would be great. The code is public domain. ---------- messages: 6402 nosy: anon, pypy-issue priority: performance bug status: unread title: math.factorial is slow ________________________________________ PyPy bug tracker <tracker(a)bugs.pypy.org> <https://bugs.pypy.org/issue1654> ________________________________________

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