fixtures: fix quadratic behavior in the number of autouse fixtures

[bluetech]

Fixes #4824. This contains 3 commits which optimize the slow parts of xunit/autouse fixtes, the last commit fixes the remaining quadratic behavior (continuation of #7929). Please see the commit messages for details.

On the bench/xunit.py benchmark, --collect-only, before:

         51895636 function calls (51265006 primitive calls) in 25.618 seconds

   Ordered by: cumulative time

   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
        1    0.000    0.000   25.101   25.101 main.py:320(pytest_collection)
        1    0.000    0.000   25.101   25.101 main.py:567(perform_collect)
80560/556    0.020    0.000   24.472    0.044 {method 'extend' of 'list' objects}
85001/15001    0.148    0.000   24.468    0.002 main.py:785(genitems)
    10002    0.044    0.000   23.705    0.002 runner.py:455(collect_one_node)
    10002    0.042    0.000   23.281    0.002 runner.py:340(pytest_make_collect_report)
    10002    0.068    0.000   23.201    0.002 runner.py:298(from_call)
    10002    0.017    0.000   23.087    0.002 runner.py:341(<lambda>)
     5001    0.164    0.000   21.569    0.004 python.py:412(collect)
     5000    0.019    0.000   20.634    0.004 python.py:862(collect)
    30003    0.098    0.000   18.282    0.001 python.py:218(pytest_pycollect_makeitem)
    30000    0.157    0.000   17.843    0.001 python.py:450(_genfunctions)
    30000    0.342    0.000   16.682    0.001 python.py:1615(from_parent)
    40001    0.089    0.000   16.454    0.000 nodes.py:183(from_parent)
    40002    0.100    0.000   16.365    0.000 nodes.py:102(_create)
    30000    0.351    0.000   16.186    0.001 python.py:1553(__init__)
    15000    0.116    0.000   14.607    0.001 fixtures.py:1439(getfixtureinfo)
    15000    0.136    0.000   13.693    0.001 fixtures.py:1492(getfixtureclosure)
    15000    7.966    0.001   13.284    0.001 fixtures.py:1479(_getautousenames)
 37643622    5.336    0.000    5.336    0.000 {method 'startswith' of 'str' objects}
    20018    0.032    0.000    2.534    0.000 {method 'sort' of 'list' objects}
    20000    0.025    0.000    2.493    0.000 python.py:443(sort_key)
    20000    0.060    0.000    2.467    0.000 python.py:328(reportinfo)
        1    0.000    0.000    2.069    2.069 python.py:502(collect)
    20000    0.071    0.000    2.058    0.000 code.py:1160(getfslineno)
     5000    0.008    0.000    1.173    0.000 source.py:115(findsource)
     5000    0.049    0.000    1.166    0.000 inspect.py:772(findsource)

After:

         14681410 function calls (14075780 primitive calls) in 12.041 seconds

   Ordered by: cumulative time

   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
        1    0.000    0.000   11.525   11.525 main.py:320(pytest_collection)
        1    0.000    0.000   11.525   11.525 main.py:567(perform_collect)
55560/556    0.015    0.000   10.845    0.020 {method 'extend' of 'list' objects}
85001/15001    0.140    0.000   10.841    0.001 main.py:785(genitems)
    10002    0.042    0.000   10.108    0.001 runner.py:455(collect_one_node)
    10002    0.039    0.000    9.386    0.001 runner.py:340(pytest_make_collect_report)
    10002    0.061    0.000    9.312    0.001 runner.py:298(from_call)
    10002    0.015    0.000    9.209    0.001 runner.py:341(<lambda>)
     5001    0.156    0.000    7.741    0.002 python.py:412(collect)
     5000    0.018    0.000    6.777    0.001 python.py:862(collect)
    30003    0.091    0.000    4.552    0.000 python.py:218(pytest_pycollect_makeitem)
    30000    0.147    0.000    4.137    0.000 python.py:450(_genfunctions)
    40001    0.076    0.000    3.164    0.000 nodes.py:175(from_parent)
    30000    0.076    0.000    3.124    0.000 python.py:1615(from_parent)
    40002    0.081    0.000    3.088    0.000 nodes.py:94(_create)
    30000    0.253    0.000    2.926    0.000 python.py:1553(__init__)
    20018    0.030    0.000    2.459    0.000 {method 'sort' of 'list' objects}
    20000    0.024    0.000    2.423    0.000 python.py:443(sort_key)
    20000    0.058    0.000    2.397    0.000 python.py:328(reportinfo)
        1    0.000    0.000    2.074    2.074 python.py:502(collect)
    20000    0.067    0.000    2.002    0.000 code.py:1160(getfslineno)
    15000    0.107    0.000    1.669    0.000 fixtures.py:1440(getfixtureinfo)
     5000    0.008    0.000    1.177    0.000 source.py:115(findsource)
     5000    0.049    0.000    1.169    0.000 inspect.py:772(findsource)
    20026    0.098    0.000    1.078    0.000 compat.py:112(getfuncargnames)

which is the usual slowness :)

[nicoddemus]

Awesome work @bluetech!

Left two minor comments, feel free to ignore them. 👍

[nicoddemus]

Nice function and docs!

Did you try to measure with @lru_cache being applied to it?

[bluetech]

No, but I think it shouldn't be a hot spot anymore, and shouldn't be called with the same nodeid a million times like before. But if it does show up in a profile again it might make sense.