(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.
invalid file paths for the built-in import machinery which leads to
fewer open calls on startup.
Also fix issue with PEP 302 style import hooks which lead to more open()
calls than necessary.
failures on Windows buildbots, but it's hard to know how since the regrtest
failure output is useless here, and it never fails when a buildbot slave runs
test_tarfile the second time in verbose mode.
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.
Andrew Dalke
Steve Holden
Tim Peters
Bob Ippolito
Georg Brandl
Andrew M. Kuchling
Fredrik Lundh
Thomas Heller
Brett Cannon