a large width is passed on 32-bit platforms. Found by Google.
It would be good for people to review this especially carefully and verify
I don't have an off by one error and there is no other way to cause overflow.
of some of the common builtin types.
Use a bit in tp_flags for each common builtin type. Check the bit
to determine if any instance is a subclass of these common types.
The check avoids a function call and O(n) search of the base classes.
The check is done in the various Py*_Check macros rather than calling
PyType_IsSubtype().
All the bits are set in tp_flags when the type is declared
in the Objects/*object.c files because PyType_Ready() is not called
for all the types. Should PyType_Ready() be called for all types?
If so and the change is made, the changes to the Objects/*object.c files
can be reverted (remove setting the tp_flags). Objects/typeobject.c
would also have to be modified to add conditions
for Py*_CheckExact() in addition to each the PyType_IsSubtype check.
* unified the way intobject, longobject and mystrtoul handle
values around -sys.maxint-1.
* in general, trying to entierely avoid overflows in any computation
involving signed ints or longs is extremely involved. Fixed a few
simple cases where a compiler might be too clever (but that's all
guesswork).
* more overflow checks against bad data in marshal.c.
* 2.5 specific: fixed a number of places that were still confusing int
and Py_ssize_t. Some of them could potentially have caused
"real-world" breakage.
* list.pop(x): fixing overflow issues on x was messy. I just reverted
to PyArg_ParseTuple("n"), which does the right thing. (An obscure
test was trying to give a Decimal to list.pop()... doesn't make
sense any more IMHO)
* trying to write a few tests...
I modified this patch some by fixing style, some error checking, and adding
XXX comments. This patch requires review and some changes are to be expected.
I'm checking in now to get the greatest possible review and establish a
baseline for moving forward. I don't want this to hold up release if possible.
(If compiled without FAST search support, changed the pre-memcmp test
to check the last character as well as the first. This gave a 25%
speedup for my test case.)
Rewrote the split algorithms so they stop when maxsplit gets to 0.
Previously they did a string match first then checked if the maxsplit
was reached. The new way prevents a needless string search.
results list.
Originally it allocated 0 items and used the list growth during append. Now
it preallocates 12 items so the first few appends don't need list reallocs.
("Here are some words ."*2).split(None, 1) is 7% faster
("Here are some words ."*2).split() is is 15% faster
(Your milage may vary, see dealership for details.)
File parsing like this
for line in f:
count += len(line.split())
is also about 15% faster. There is a slowdown of about 3% for large
strings because of the additional overhead of checking if the append is
to a preallocated region of the list or not. This will be the rare case.
It could be improved with special case code but we decided it was not
useful enough.
There is a cost of 12*sizeof(PyObject *) bytes per list. For the normal
case of file parsing this is not a problem because of the lists have
a short lifetime. We have not come up with cases where this is a problem
in real life.
I chose 12 because human text averages about 11 words per line in books,
one of my data sets averages 6.2 words with a final peak at 11 words per
line, and I work with a tab delimited data set with 8 tabs per line (or
9 words per line). 12 encompasses all of these.
Also changed the last rstrip code to append then reverse, rather than
doing insert(0). The strip() and rstrip() times are now comparable.
this is on par with a corresponding find, and nearly twice as fast
as split(sep, 1)
full tests, a unicode version, and documentation will follow to-
morrow.
Martin v. Löwis
Georg Brandl
Neal Norwitz
Raymond Hettinger
Armin Rigo
Fredrik Lundh
Andrew Dalke
Bob Ippolito
Jack Diederich
Andrew M. Kuchling