Here is a statistic for most called PyObject_INIT or PyObject_INIT_VAR
for types (collected during running Python tests on 32-bit Linux).
type count % acc.%
builtin_function_or_method 116012007 36.29% 36.29%
method 52465386 16.41% 52.70%
int 42828741 13.40% 66.09%
str 37017098 11.58% 77.67%
generator 14026583 4.39% 82.06%
list_iterator 8731329 2.73% 84.79%
bytes 7217934 2.26% 87.04%
tuple_iterator 5042563 1.58% 88.62%
float 4672980 1.46% 90.08%
set 3319699 1.04% 91.12%
_io.StringIO 3000369 0.94% 92.06%
str_iterator 2126838 0.67% 92.73%
list 2031059 0.64% 93.36%
dict 1691993 0.53% 93.89%
method-wrapper 1573139 0.49% 94.38%
function 1472062 0.46% 94.84%
traceback 1388278 0.43% 95.28%
tuple 1132071 0.35% 95.63%
memoryview 1092173 0.34% 95.97%
cell 1049496 0.33% 96.30%
managedbuffer 1036889 0.32% 96.63%
bytearray 711969 0.22% 96.85%
range_iterator 496924 0.16% 97.00%
range 483971 0.15% 97.15%
super 472447 0.15% 97.30%
map 449567 0.14% 97.44%
frame 427320 0.13% 97.58%
set_iterator 423392 0.13% 97.71%
Leaf 398705 0.12% 97.83%
symtable 374412 0.12% 97.95%
Types for which free lists already are used: builtin_function_or_method,
method, float, tuple, list, dict, frame. Some free list implementations
(e.g. for tuple) don't call PyObject_INIT/PyObject_INIT_VAR. That is why
numbers are such low for tuples.
Perhaps it is worth to add free lists for other types: int, str, bytes,
generator, list and tuple iterators?
Shortened tables for variable-sized objects (that calls PyObject_INIT_VAR):
int 42828741 13.40%
0 425353 0.99% 0.99%
1 21399290 49.96% 50.96%
2 10496856 24.51% 75.47%
3 4873346 11.38% 86.85%
4 1021563 2.39% 89.23%
5 1246444 2.91% 92.14%
6 733676 1.71% 93.85%
7 123074 0.29% 94.14%
8 139203 0.33% 94.47%
...
bytes 7217934 2.26%
0 842 0.01% 0.01%
1 179469 2.49% 2.50%
2 473306 6.56% 9.06%
3 254968 3.53% 12.59%
4 1169164 16.20% 28.79%
5 72806 1.01% 29.79%
6 128668 1.78% 31.58%
7 169694 2.35% 33.93%
8 155154 2.15% 36.08%
9 67320 0.93% 37.01%
10 51703 0.72% 37.73%
11 42574 0.59% 38.32%
12 108947 1.51% 39.83%
13 40812 0.57% 40.39%
14 126783 1.76% 42.15%
15 37873 0.52% 42.67%
16 447482 6.20% 48.87%
17 194320 2.69% 51.56%
18 251685 3.49% 55.05%
19 159435 2.21% 57.26%
20 212521 2.94% 60.20%
...
31 18751 0.26% 67.32%
32 159781 2.21% 69.54%
33 8332 0.12% 69.65%
...
63 19841 0.27% 79.21%
64 144982 2.01% 81.22%
65 5216 0.07% 81.29%
...
127 1354 0.02% 85.44%
128 376539 5.22% 90.66%
129 17468 0.24% 90.90%
...
255 178 0.00% 92.39%
256 11993 0.17% 92.55%
257 124 0.00% 92.56%
...
_______________________________________________
Python-Dev mailing list
Python-Dev@python.org
https://mail.python.org/mailman/listinfo/python-dev
Unsubscribe:
https://mail.python.org/mailman/options/python-dev/archive%40mail-archive.com
