[issue10227] Improve performance of MemoryView slicing
Kristján Valur Jónsson krist...@ccpgames.com added the comment: Sure. Flagging this as fixed. Can´t close it until 10181 is closed due to some dependency thing. (perhaps someone else knows what to do?) -- resolution: - fixed ___ Python tracker rep...@bugs.python.org http://bugs.python.org/issue10227 ___ ___ Python-bugs-list mailing list Unsubscribe: http://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
[issue10227] Improve performance of MemoryView slicing
Stefan Krah stefan-use...@bytereef.org added the comment: Great. I removed the dependency since it's fixed in both cpython and pep-3118. -- dependencies: -Problems with Py_buffer management in memoryobject.c (and elsewhere?) stage: - committed/rejected status: open - closed ___ Python tracker rep...@bugs.python.org http://bugs.python.org/issue10227 ___ ___ Python-bugs-list mailing list Unsubscribe: http://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
[issue10227] Improve performance of MemoryView slicing
Stefan Krah stefan-use...@bytereef.org added the comment: Kristján, I ran the benchmarks from http://bugs.python.org/issue10227#msg143731 in the current cpython and pep-3118 repos. In both cases the differences between Linux and Windows are far less pronounced than they used to be. All benchmarks were run with the x64 builds. I also ran the profile guided optimization build for Visual Studio. The results are equal to (or better than) the non-pgo gcc results. In my experience Visual Studio relies heavily on PGO for x64 builds. The default optimizer is just not as good as gcc's. If you can reproduce similar results, I think we can close this issue. ./python -m timeit -n 1000 -s x = ((b'x'*1)) x[:100] linux-cpython (4244e4348362): 0.102 usec linux-pep-3118 (memoryview:534f6bbe5422): 0.098 usec windows-cpython: 0.109 usec windows-pep-3118: 0.112 usec usec windows-pep-3118-pgo: 0.103 usec ./python -m timeit -n 1000 -s x = (bytearray(b'x'*1)) x[:100] linux-cpython (4244e4348362): 0.107 usec linux-pep-3118 (memoryview:534f6bbe5422): 0.109 usec windows-cpython: 0.127 usec windows-pep-3118: 0.128 usec windows-pep-3118-pgo: 0.106 usec ./python -m timeit -n 1000 -s x = memoryview(bytearray(b'x'*1)) x[:100] linux-cpython (4244e4348362): 0.127 usec linux-pep-3118 (memoryview:534f6bbe5422): 0.12 usec windows-cpython: 0.145 usec windows-pep-3118: 0.14 usec windows-pep-3118-pgo: 0.0984 usec -- ___ Python tracker rep...@bugs.python.org http://bugs.python.org/issue10227 ___ ___ Python-bugs-list mailing list Unsubscribe: http://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
[issue10227] Improve performance of MemoryView slicing
Stefan Behnel sco...@users.sourceforge.net added the comment: Updated single slice caching patch for latest Py3.3 hg tip. -- Added file: http://bugs.python.org/file23727/slice-object-cache.patch ___ Python tracker rep...@bugs.python.org http://bugs.python.org/issue10227 ___ ___ Python-bugs-list mailing list Unsubscribe: http://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
[issue10227] Improve performance of MemoryView slicing
Roundup Robot devn...@psf.upfronthosting.co.za added the comment: New changeset fa2f8dd077e0 by Antoine Pitrou in branch 'default': Issue #10227: Add an allocation cache for a single slice object. http://hg.python.org/cpython/rev/fa2f8dd077e0 -- nosy: +python-dev ___ Python tracker rep...@bugs.python.org http://bugs.python.org/issue10227 ___ ___ Python-bugs-list mailing list Unsubscribe: http://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
[issue10227] Improve performance of MemoryView slicing
Antoine Pitrou pit...@free.fr added the comment: Thanks Stefan. I'm leaving the issue open since the original topic is a bit different. -- ___ Python tracker rep...@bugs.python.org http://bugs.python.org/issue10227 ___ ___ Python-bugs-list mailing list Unsubscribe: http://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
[issue10227] Improve performance of MemoryView slicing
Stefan Krah stefan-use...@bytereef.org added the comment: Kristján, could you check out the new implementation over at #10181? I have trouble reproducing a big speed difference between bytearray and memoryview (Linux, 64-bit). Here are the timings I get for the current and the new version: Slicing --- 1) ./python -m timeit -n 1000 -s x = bytearray(b'x'*1) x[:100] 2) ./python -m timeit -n 1000 -s x = memoryview(bytearray(b'x'*1)) x[:100] 1) cpython: 0.137 usec pep-3118: 0.138 usec 2) cpython: 0.132 usec pep-3118: 0.132 usec Slicing with overhead for multidimensional capabilities: 1) ./python -m timeit -n 1000 -s import _testbuffer; x = _testbuffer.ndarray([ord('x') for _ in range(1)], shape=[1]) x[:100] 2) ./python -m timeit -n 1000 -s import numpy; x = numpy.ndarray(buffer=bytearray(b'x'*1), shape=[1], dtype='B') x[:100] 1) _testbuffer.c: 0.198 usec 2) numpy: 0.415 usec Slice assignment 1) ./python -m timeit -n 1000 -s x = bytearray(b'x'*1) x[5:10] = x[7:12] 2) ./python -m timeit -n 1000 -s x = memoryview(bytearray(b'x'*1)) x[5:10] = x[7:12] 1) cpython: 0.242 usec pep-3118: 0.240 usec 2) cpython: 0.282 usec pep-3118: 0.287 usec Slice assignment, overhead for multidimensional capabilities 1) ./python -m timeit -n 1000 -s import _testbuffer; x = _testbuffer.ndarray([ord('x') for _ in range(1)], shape=[1], flags=_testbuffer.ND_WRITABLE) x[5:10] = x[7:12] 2) ./python -m timeit -n 1000 -s import numpy; x = numpy.ndarray(buffer=bytearray(b'x'*1), shape=[1], dtype='B') x[5:10] = x[7:12] _testbuffer.c: 0.469 usec numpy: 1.37 usec tolist -- 1) ./python -m timeit -n 1 -s import array; x = array.array('B', b'x'*1) x.tolist() 2) ./python -m timeit -n 1 -s x = memoryview(bytearray(b'x'*1)) x.tolist() 1) cpython, array: 104.0 usec 2) pep-3118, memoryview: 90.5 usec tolist, struct module overhead -- 1) ./python -m timeit -n 1 -s import _testbuffer; x = _testbuffer.ndarray([ord('x') for _ in range(1)], shape=[1]) x.tolist() 2) ./python -m timeit -n 1 -s import numpy; x = numpy.ndarray(buffer=bytearray(b'x'*1), shape=[1], dtype='B') x.tolist() _testbuffer.c: 1.38 msec (yes, that's microseconds!) numpy: 104 usec -- nosy: +skrah ___ Python tracker rep...@bugs.python.org http://bugs.python.org/issue10227 ___ ___ Python-bugs-list mailing list Unsubscribe: http://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
[issue10227] Improve performance of MemoryView slicing
Changes by Stefan Krah stefan-use...@bytereef.org: -- dependencies: +Problems with Py_buffer management in memoryobject.c (and elsewhere?) ___ Python tracker rep...@bugs.python.org http://bugs.python.org/issue10227 ___ ___ Python-bugs-list mailing list Unsubscribe: http://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
[issue10227] Improve performance of MemoryView slicing
Kristján Valur Jónsson krist...@ccpgames.com added the comment: I'm afraid I had put this matter _far_ out of my head :) Seeing the amount of discussion on that other defect (stuff I had already come across and scrathced my head over) I think there is a lot of catching up that I'd need to do and I am unable to give this any priority at the moment. My original patch sought to even out the slicing performance difference between bytes and bytearray. bytes objects were very streamlined while other were not. python.exe -m timeit -n 1000 -s x = ((b'x'*1)) x[:100] 1000 loops, best of 3: 0.125 usec per loop python.exe -m timeit -n 1000 -s x = (bytearray(b'x'*1)) x[:100] 1000 loops, best of 3: 0.202 usec per loop Did you take a look at this at all? -- ___ Python tracker rep...@bugs.python.org http://bugs.python.org/issue10227 ___ ___ Python-bugs-list mailing list Unsubscribe: http://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
[issue10227] Improve performance of MemoryView slicing
Stefan Krah stefan-use...@bytereef.org added the comment: I see. I thought this was mainly about memoryview performance, so I did not specifically look at bytearray. The poor performance seems to be Windows specific: C:\Users\stefan\hg\pep-3118\PCbuildamd64\python.exe -m timeit -n 1000 -s x = ((b'x'*1)) x[:100] 1000 loops, best of 3: 0.118 usec per loop C:\Users\stefan\hg\pep-3118\PCbuildamd64\python.exe -m timeit -n 1000 -s x = (bytearray(b'x'*1)) x[:100] 1000 loops, best of 3: 0.191 usec per loop C:\Users\stefan\hg\pep-3118\PCbuildamd64\python.exe -m timeit -n 1000 -s x = memoryview(bytearray(b'x'*1)) x[:100] 1000 loops, best of 3: 0.146 usec per loop Linux: bytes: 10.9 usec bytearray: 0.14 usec memoryview: 0.14 usec -- ___ Python tracker rep...@bugs.python.org http://bugs.python.org/issue10227 ___ ___ Python-bugs-list mailing list Unsubscribe: http://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
[issue10227] Improve performance of MemoryView slicing
Stefan Krah stefan-use...@bytereef.org added the comment: With Stefan Behnel's slice-object-cache.patch, I get this (PEP-3118 branch): Linux: bytes: 0.097 usec bytearray: 0.127 usec memoryview: 0.12 usec Windows: bytes: 0.11 usec bytearray: 0,184 usec memoryview: 0.139 usec On Linux, that's quite a nice speedup. -- ___ Python tracker rep...@bugs.python.org http://bugs.python.org/issue10227 ___ ___ Python-bugs-list mailing list Unsubscribe: http://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
[issue10227] Improve performance of MemoryView slicing
Changes by Mark Dickinson dicki...@gmail.com: -- assignee: mark.dickinson - ___ Python tracker rep...@bugs.python.org http://bugs.python.org/issue10227 ___ ___ Python-bugs-list mailing list Unsubscribe: http://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
[issue10227] Improve performance of MemoryView slicing
Stefan Behnel sco...@users.sourceforge.net added the comment: Here are some real micro benchmarks (note that the pybench benchmarks actually do lots of other stuff besides slicing): base line: $ ./python -m timeit -s 'l = list(range(100)); s=slice(None)' 'l[s]' 100 loops, best of 3: 0.464 usec per loop $ ./python -m timeit -s 'l = list(range(10)); s=slice(None)' 'l[s]' 1000 loops, best of 3: 0.149 usec per loop $ ./python -m timeit -s 'l = list(range(10)); s=slice(None,1)' 'l[s]' 1000 loops, best of 3: 0.135 usec per loop patched: $ ./python -m timeit -s 'l = list(range(100))' 'l[:1]' 1000 loops, best of 3: 0.158 usec per loop $ ./python -m timeit -s 'l = list(range(100))' 'l[:]' 100 loops, best of 3: 0.49 usec per loop $ ./python -m timeit -s 'l = list(range(100))' 'l[1:]' 100 loops, best of 3: 0.487 usec per loop $ ./python -m timeit -s 'l = list(range(100))' 'l[1:3]' 1000 loops, best of 3: 0.184 usec per loop $ ./python -m timeit -s 'l = list(range(10))' 'l[:]' 1000 loops, best of 3: 0.185 usec per loop $ ./python -m timeit -s 'l = list(range(10))' 'l[1:]' 1000 loops, best of 3: 0.181 usec per loop original: $ ./python -m timeit -s 'l = list(range(100))' 'l[:1]' 1000 loops, best of 3: 0.171 usec per loop $ ./python -m timeit -s 'l = list(range(100))' 'l[:]' 100 loops, best of 3: 0.499 usec per loop $ ./python -m timeit -s 'l = list(range(100))' 'l[1:]' 100 loops, best of 3: 0.509 usec per loop $ ./python -m timeit -s 'l = list(range(100))' 'l[1:3]' 1000 loops, best of 3: 0.198 usec per loop $ ./python -m timeit -s 'l = list(range(10))' 'l[:]' 1000 loops, best of 3: 0.188 usec per loop $ ./python -m timeit -s 'l = list(range(10))' 'l[1:]' 100 loops, best of 3: 0.196 usec per loop So the maximum impact seems to be 8% for very short slices (10) and it quickly goes down for longer slices where the copy impact clearly dominates. There's still some 2% for 100 items, though. I find it interesting that the base line is way below the other timings. That makes me think it's actually worth caching constant slice instances, as CPython already does for tuples. Cython also caches both now. I would expect that constant slices like [:], [1:] or [:-1] are extremely common. As you can see above, caching them could speed up slicing by up to 30% for short lists, and still some 7% for a list of length 100. Stefan -- ___ Python tracker rep...@bugs.python.org http://bugs.python.org/issue10227 ___ ___ Python-bugs-list mailing list Unsubscribe: http://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
[issue10227] Improve performance of MemoryView slicing
Stefan Behnel sco...@users.sourceforge.net added the comment: Here's another base line test: slicing an empty list patched: $ ./python -m timeit -s 'l = []' 'l[:]' 1000 loops, best of 3: 0.0847 usec per loop original: $ ./python -m timeit -s 'l = []' 'l[:]' 1000 loops, best of 3: 0.0977 usec per loop That's about 13% less overhead. -- ___ Python tracker rep...@bugs.python.org http://bugs.python.org/issue10227 ___ ___ Python-bugs-list mailing list Unsubscribe: http://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
[issue10227] Improve performance of MemoryView slicing
Antoine Pitrou pit...@free.fr added the comment: I find it interesting that the base line is way below the other timings. That makes me think it's actually worth caching constant slice instances, as CPython already does for tuples. Indeed. I have never touched it, but I suppose it needs an upgrade of the marshal format to support slices. (of course, this will not help for other common cases such as l[x:x+2]). -- ___ Python tracker rep...@bugs.python.org http://bugs.python.org/issue10227 ___ ___ Python-bugs-list mailing list Unsubscribe: http://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
[issue10227] Improve performance of MemoryView slicing
Stefan Behnel sco...@users.sourceforge.net added the comment: of course, this will not help for other common cases such as l[x:x+2] ... which is exactly what this slice caching patch is there for. ;-) -- ___ Python tracker rep...@bugs.python.org http://bugs.python.org/issue10227 ___ ___ Python-bugs-list mailing list Unsubscribe: http://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
[issue10227] Improve performance of MemoryView slicing
Stefan Behnel sco...@users.sourceforge.net added the comment: A quick test against the py3k stdlib: find -name *.py | while read file; do egrep '\[[-0-9]*:[-0-9]*\]' $file; done | wc -l This finds 2096 lines in 393 files. -- ___ Python tracker rep...@bugs.python.org http://bugs.python.org/issue10227 ___ ___ Python-bugs-list mailing list Unsubscribe: http://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
[issue10227] Improve performance of MemoryView slicing
Stefan Behnel sco...@users.sourceforge.net added the comment: Created follow-up issue 11107 for caching constant slice objects. -- ___ Python tracker rep...@bugs.python.org http://bugs.python.org/issue10227 ___ ___ Python-bugs-list mailing list Unsubscribe: http://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
[issue10227] Improve performance of MemoryView slicing
Antoine Pitrou pit...@free.fr added the comment: Any benchmark numbers for the slice cache? Also, is the call to PyObject_INIT necessary? -- ___ Python tracker rep...@bugs.python.org http://bugs.python.org/issue10227 ___ ___ Python-bugs-list mailing list Unsubscribe: http://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
[issue10227] Improve performance of MemoryView slicing
Stefan Behnel sco...@users.sourceforge.net added the comment: Any benchmark numbers for the slice cache? I ran the list tests in pybench and got this: Test minimum run-timeaverage run-time thisother diffthisother diff ListSlicing:66ms67ms -2.2%67ms68ms -2.7% SmallLists:61ms64ms -4.5%61ms65ms -5.6% Totals: 127ms 131ms -3.3% 128ms 133ms -4.1% Repeating this gave me anything between 1.5% and 3.5% in total, with 2% for the small lists benchmark (which is the expected best case as slicing large lists obviously dominates the slice object creation). IMHO, even 2% would be pretty good for such a small change. Also, is the call to PyObject_INIT necessary? In any case, the ref-count needs to be re-initialised to 1. A call to _Py_NewReference() would be enough, though, following the example in listobject.c. So you can replace PyObject_INIT(obj, PySlice_Type); by _Py_NewReference((PyObject *)obj); in the patch. New patch attached. -- Added file: http://bugs.python.org/file20650/slice-object-cache.patch ___ Python tracker rep...@bugs.python.org http://bugs.python.org/issue10227 ___ ___ Python-bugs-list mailing list Unsubscribe: http://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
[issue10227] Improve performance of MemoryView slicing
Antoine Pitrou pit...@free.fr added the comment: I ran the list tests in pybench and got this: Test minimum run-timeaverage run-time thisother diffthisother diff ListSlicing:66ms67ms -2.2%67ms68ms -2.7% SmallLists:61ms64ms -4.5%61ms65ms -5.6% Totals: 127ms 131ms -3.3% 128ms 133ms -4.1% Repeating this gave me anything between 1.5% and 3.5% in total, with 2% for the small lists benchmark (which is the expected best case as slicing large lists obviously dominates the slice object creation). IMHO, even 2% would be pretty good for such a small change. Well, 3% on such micro-benchmarks (and, I assume, 0% on the rest) is generally considered very small. On the other hand, I agree the patch itself is quite simple. by _Py_NewReference((PyObject *)obj); in the patch. New patch attached. Don't you also need a _Py_ForgetReference() at the other end? Or have I missed it? -- ___ Python tracker rep...@bugs.python.org http://bugs.python.org/issue10227 ___ ___ Python-bugs-list mailing list Unsubscribe: http://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
[issue10227] Improve performance of MemoryView slicing
Stefan Behnel sco...@users.sourceforge.net added the comment: There's a PyObject_Del(obj) in all code paths. -- ___ Python tracker rep...@bugs.python.org http://bugs.python.org/issue10227 ___ ___ Python-bugs-list mailing list Unsubscribe: http://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
[issue10227] Improve performance of MemoryView slicing
Stefan Behnel sco...@users.sourceforge.net added the comment: I've extracted and fixed the part of this patch that implements the slice object cache. In particular, PySlice_Fini() was incorrectly implemented. This patch applies cleanly for me against the latest py3k branch. -- Added file: http://bugs.python.org/file20639/slice-object-cache.patch ___ Python tracker rep...@bugs.python.org http://bugs.python.org/issue10227 ___ ___ Python-bugs-list mailing list Unsubscribe: http://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
[issue10227] Improve performance of MemoryView slicing
Changes by Antoine Pitrou pit...@free.fr: -- assignee: - mark.dickinson nosy: +mark.dickinson versions: +Python 3.3 -Python 3.2 ___ Python tracker rep...@bugs.python.org http://bugs.python.org/issue10227 ___ ___ Python-bugs-list mailing list Unsubscribe: http://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
[issue10227] Improve performance of MemoryView slicing
Stefan Behnel sco...@users.sourceforge.net added the comment: I find it a lot easier to appreciate patches that implement a single change than those that mix different changes. There are three different things in your patch, which I would like to see in at least three different commits. I'd be happy if you could separate the changes into more readable feature patches. That makes it easier to accept them. I'm generally happy about the slice changes, but you will have to benchmark the equivalent changes in Py3.2 to prove that they are similarly worth applying there. -- nosy: +scoder ___ Python tracker rep...@bugs.python.org http://bugs.python.org/issue10227 ___ ___ Python-bugs-list mailing list Unsubscribe: http://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
[issue10227] Improve performance of MemoryView slicing
Kristján Valur Jónsson krist...@ccpgames.com added the comment: The benchmarks are from 3.2 Also, I'll do a more relevant profiling session for 3.2. This patch is based on profiling results from 2.7 so there might be more relevant optimization cases in 3.2 -- ___ Python tracker rep...@bugs.python.org http://bugs.python.org/issue10227 ___ ___ Python-bugs-list mailing list Unsubscribe: http://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
[issue10227] Improve performance of MemoryView slicing
Kristján Valur Jónsson krist...@ccpgames.com added the comment: In case I'm not clear enough: The patch is for 3.2, the benchmarks are 3.2, but it was created based on 2.7 results, which may not fully apply for 3.2 -- ___ Python tracker rep...@bugs.python.org http://bugs.python.org/issue10227 ___ ___ Python-bugs-list mailing list Unsubscribe: http://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
[issue10227] Improve performance of MemoryView slicing
New submission from Kristján Valur Jónsson krist...@ccpgames.com: In a recent email exchange on python-dev, Antoine Pitrou mentioned that slicing memoryview objects (lazy slices) wasn't necessarily very efficient when dealing with short slices. The data he posted was: $ ./python -m timeit -s x = b'x'*1 x[:100] 1000 loops, best of 3: 0.134 usec per loop $ ./python -m timeit -s x = memoryview(b'x'*1) x[:100] 1000 loops, best of 3: 0.151 usec per loop Actually, this is not a fair comparison. A more realistic alternative to the memoryview is the bytearray, a mutable buffer. My local tests gave these numbers: python.exe -m timeit -n 1000 -s x = ((b'x'*1)) x[:100] 1000 loops, best of 3: 0.14 usec per loop python.exe -m timeit -n 1000 -s x = (bytearray(b'x'*1)) x[:100] 1000 loops, best of 3: 0.215 usec per loop python.exe -m timeit -n 1000 -s x = memoryview(bytearray(b'x'*1)) x[:100] 1000 loops, best of 3: 0.163 usec per loop In this case, lazy slicing is indeed faster than greedy slicing. However, I was intrigued by how much these cases differ. Why was slicing bytes objects so much faster? Each should just result in the generation of a single object. It turns out that the slicing operation for strings (and sequences is very streamlined in the core. To address this to some extent I provide a patch with three main components: 1) There is now a single object cache of slice objects. These are generated by the core when slicing and immediately released. Reusing them if possible is very beneficial. 2) The PySlice_GetIndicesEx couldn't be optimized because of aliasing. Fixing that function sped it up considerably. 3) Creating a new api to create a memory view from a base memory view and a slice is much faster. The old way would do two copies of a Py_buffer with adverse effects on cache performance. Applying this patch provides the following figures: python.exe -m timeit -n 1000 -s x = ((b'x'*1)) x[:100] 1000 loops, best of 3: 0.125 usec per loop python.exe -m timeit -n 1000 -s x = (bytearray(b'x'*1)) x[:100] 1000 loops, best of 3: 0.202 usec per loop python.exe -m timeit -n 1000 -s x = memoryview(bytearray(b'x'*1)) x[:100] 1000 loops, best of 3: 0.138 usec per loop in memoryobject.c there was a comment stating that there should be an API for this. Now there is, only internal. -- components: Interpreter Core keywords: needs review, patch messages: 119872 nosy: krisvale, pitrou priority: normal severity: normal status: open title: Improve performance of MemoryView slicing type: performance versions: Python 3.2 ___ Python tracker rep...@bugs.python.org http://bugs.python.org/issue10227 ___ ___ Python-bugs-list mailing list Unsubscribe: http://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
[issue10227] Improve performance of MemoryView slicing
Antoine Pitrou pit...@free.fr added the comment: You forgot to attach your patch. -- ___ Python tracker rep...@bugs.python.org http://bugs.python.org/issue10227 ___ ___ Python-bugs-list mailing list Unsubscribe: http://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
[issue10227] Improve performance of MemoryView slicing
Kristján Valur Jónsson krist...@ccpgames.com added the comment: Oh dear. Here it is. -- Added file: http://bugs.python.org/file19410/memoryobj.patch ___ Python tracker rep...@bugs.python.org http://bugs.python.org/issue10227 ___ ___ Python-bugs-list mailing list Unsubscribe: http://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
[issue10227] Improve performance of MemoryView slicing
Kristján Valur Jónsson krist...@ccpgames.com added the comment: But then, perhaps implementing the sequence protocol for memoryviews might be more efficient still. -- ___ Python tracker rep...@bugs.python.org http://bugs.python.org/issue10227 ___ ___ Python-bugs-list mailing list Unsubscribe: http://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
[issue10227] Improve performance of MemoryView slicing
Antoine Pitrou pit...@free.fr added the comment: The sequence protocol (if I'm not confused) only work with a PyObject ** array. -- ___ Python tracker rep...@bugs.python.org http://bugs.python.org/issue10227 ___ ___ Python-bugs-list mailing list Unsubscribe: http://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
[issue10227] Improve performance of MemoryView slicing
Kristján Valur Jónsson krist...@ccpgames.com added the comment: As an additional point: the PyMemoryObject has a base member that I think is redundant. the view.obj should be sufficient. -- ___ Python tracker rep...@bugs.python.org http://bugs.python.org/issue10227 ___ ___ Python-bugs-list mailing list Unsubscribe: http://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
[issue10227] Improve performance of MemoryView slicing
Antoine Pitrou pit...@free.fr added the comment: As an additional point: the PyMemoryObject has a base member that I think is redundant. the view.obj should be sufficient. Yes, that's what I think as well. -- ___ Python tracker rep...@bugs.python.org http://bugs.python.org/issue10227 ___ ___ Python-bugs-list mailing list Unsubscribe: http://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
[issue10227] Improve performance of MemoryView slicing
Kristján Valur Jónsson krist...@ccpgames.com added the comment: In 2.x, strings are sliced using PySequence_GetSlice(). ceval.c in 3.0 is different, there is no apply_slice there (despite comments to that effect). I'd have to take another look with the profiler to figure out how bytes slicing in 3.0 works, but I suspect that it is somehow fasttracked passed the creation of slice objects, etc. -- ___ Python tracker rep...@bugs.python.org http://bugs.python.org/issue10227 ___ ___ Python-bugs-list mailing list Unsubscribe: http://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
[issue10227] Improve performance of MemoryView slicing
Antoine Pitrou pit...@free.fr added the comment: I'd have to take another look with the profiler to figure out how bytes slicing in 3.0 works, but I suspect that it is somehow fasttracked passed the creation of slice objects, etc. I don't think it is fasttracked at all. Even plain indexing is not fasttracked either. -- ___ Python tracker rep...@bugs.python.org http://bugs.python.org/issue10227 ___ ___ Python-bugs-list mailing list Unsubscribe: http://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
[issue10227] Improve performance of MemoryView slicing
Kristján Valur Jónsson krist...@ccpgames.com added the comment: Well then, its back to the profiler for 3.2. I did all of the profiling with 2.7 for practical reasons (it was the only version I had available at the time) and then ported the change to 3.2 today. But obviously there are different rules in 3.2 :) -- ___ Python tracker rep...@bugs.python.org http://bugs.python.org/issue10227 ___ ___ Python-bugs-list mailing list Unsubscribe: http://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com