PERF: Profiling test collection?

[jbrockmendel]

The pandas tests suite clocks in at 90292 tests, which for me takes 67 seconds to run pytest pandas/tests --collect-only. This becomes troublesome when I want to re-run just a few failed tests with --lf, and doesn't appear amenable to parallelization.

When profiling with cProfile, it looks like just over half the time is spent in cacheprovider.pytest_collection_modifyitems

Are there suggested patterns for profiling and/or optimizing the test collection?

[bluetech]

Hi @jbrockmendel, this in particular is probably a performance bug that was fixed here: 4a42afdc2f3bb21f1685ac5c49b806ae34c36355

If you're able to confirm this fixes the problem by trying with pytest master, that'd be great. We can also consider backporting it to 5.4.x as it might be a little more time until 6.0.0 is released with that fix.

[jbrockmendel]

Thanks for the tip. Running on master:

• the time for pytest pandas/tests --collect-only is roughly cut in half (35 seconds)
• pytest pandas/tests --lf still collects everything even if just running 2 tests
• pytest_collection_modifyitems, (now located in pytest.fixtures) totals .003 seconds internally, 2.293 cumulative.
• Sorting by "tottime", nothing stands out:
  • _pytest.mark.structures.__getitem__ at 2.064 seconds for >4M calls
  • posix.stat 1.029 seconds for 626k calls
  • _pytest.python.__init__ at 1.02 seconds for 144k calls.

Is there anything we can do on our end to keep this from growing with the test suite? What I have in mind here is antipatterns, likely fixture-related, that we should watch out for.

[bluetech]

the time for pytest pandas/tests --collect-only is roughly cut in half (35 seconds)

OK, most of it is likely from the fix, but some other optimizations might have contributed as well.

pytest pandas/tests --lf still collects everything even if just running 2 tests

Yep, it works that way.

Sorting by "tottime", nothing stands out:

We have been working on reducing the overhead, but all the easy optimizations have been made, so now it's progressively harder. I'd be interested to see the full cProfile (sorted by cumtime), on a non-synthetic large test suite like pandas.

Is there anything we can do on our end to keep this from growing with the test suite?

I don't have a good answer for that, maybe others can chime in here.

You can try to disable plugins you don't use, although the costly ones are usually the most useful ones.

[jbrockmendel]

I'd be interested to see the full cProfile (sorted by cumtime), on a non-synthetic large test suite like pandas.

``` >>> p.print_stats(.1) Mon Jun 8 13:49:30 2020 stats.dat 53447019 function calls (51055552 primitive calls) in 35.915 seconds Ordered by: cumulative time List reduced from 16772 to 1677 due to restriction <0.1> ncalls tottime percall cumtime percall filename:lineno(function) 3573/1 0.039 0.000 36.133 36.133 {built-in method builtins.exec} 1 0.000 0.000 36.133 36.133 runpy.py:195(run_module) 1 0.000 0.000 36.024 36.024 runpy.py:62(_run_code) 1 0.000 0.000 36.024 36.024 pytest-5.4.1.dev462+g322190fd8-py3.7.egg/pytest/__main__.py:3() 1 0.000 0.000 36.024 36.024 pytest-5.4.1.dev462+g322190fd8-py3.7.egg/_pytest/config/__init__.py:145(console_main) 1 0.000 0.000 36.024 36.024 pytest-5.4.1.dev462+g322190fd8-py3.7.egg/_pytest/config/__init__.py:100(main) 226744/56 0.096 0.000 35.995 0.643 pluggy/manager.py:90(_hookexec) 226744/56 0.216 0.000 35.995 0.643 pluggy/manager.py:84() 226744/56 0.601 0.000 35.995 0.643 pluggy/callers.py:157(_multicall) 226548/2 0.580 0.000 35.994 17.997 pluggy/hooks.py:272(__call__) 1 0.000 0.000 34.136 34.136 pytest-5.4.1.dev462+g322190fd8-py3.7.egg/_pytest/main.py:249(pytest_cmdline_main) 1 0.000 0.000 34.136 34.136 pytest-5.4.1.dev462+g322190fd8-py3.7.egg/_pytest/main.py:188(wrap_session) 1 0.000 0.000 34.059 34.059 pytest-5.4.1.dev462+g322190fd8-py3.7.egg/_pytest/main.py:253(_main) 1 0.000 0.000 34.058 34.058 pytest-5.4.1.dev462+g322190fd8-py3.7.egg/_pytest/main.py:266(pytest_collection) 1 0.000 0.000 34.058 34.058 pytest-5.4.1.dev462+g322190fd8-py3.7.egg/_pytest/main.py:474(perform_collect) 1 0.000 0.000 30.333 30.333 pytest-5.4.1.dev462+g322190fd8-py3.7.egg/_pytest/main.py:501(_perform_collect) 439390/1839 0.064 0.000 29.557 0.016 {method 'extend' of 'list' objects} 447529/90381 0.380 0.000 29.506 0.000 pytest-5.4.1.dev462+g322190fd8-py3.7.egg/_pytest/main.py:722(genitems) 2636 0.015 0.000 27.638 0.010 pytest-5.4.1.dev462+g322190fd8-py3.7.egg/_pytest/runner.py:431(collect_one_node) 2636 0.011 0.000 26.790 0.010 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pytest-5.4.1.dev462+g322190fd8-py3.7.egg/_pytest/config/__init__.py:607(consider_module) 1 0.000 0.000 0.004 0.004 jinja2/lexer.py:6() 4762 0.002 0.000 0.004 0.000 pkg_resources/_vendor/packaging/version.py:114(_parse_version_parts) 55533 0.004 0.000 0.004 0.000 {built-in method builtins.chr} 1 0.000 0.000 0.004 0.004 doctest.py:46() 109 0.001 0.000 0.004 0.000 pandas/core/indexes/multi.py:709(_set_levels) 1 0.000 0.000 0.004 0.004 pandas/tests/arithmetic/test_datetime64.py:42(TestDatetime64ArrayLikeComparisons) 9/6 0.000 0.000 0.004 0.001 jinja2/compiler.py:1077(visit_For) 9722 0.003 0.000 0.004 0.000 :855(__enter__) 23 0.000 0.000 0.004 0.000 pandas/core/reshape/util.py:6(cartesian_product) 1 0.000 0.000 0.004 0.004 scipy/ndimage/filters.py:31() 10 0.000 0.000 0.004 0.000 astropy/utils/decorators.py:655(__get__) 204 0.000 0.000 0.004 0.000 configparser.py:830(items) 1 0.000 0.000 0.004 0.004 numba/core/codegen.py:141(_optimize_final_module) 1 0.000 0.000 0.004 0.004 pandas/tests/reshape/test_cut.py:1() 1 0.000 0.000 0.004 0.004 astropy/extern/configobj/configobj.py:1069(ConfigObj) 91/84 0.000 0.000 0.004 0.000 py/_vendored_packages/apipkg.py:133(__makeattr) 4714 0.003 0.000 0.004 0.000 py/_path/local.py:368(_fastjoin) 1 0.000 0.000 0.004 0.004 pandas/tests/reshape/test_melt.py:1() 1 0.000 0.000 0.004 0.004 pytest-5.4.1.dev462+g322190fd8-py3.7.egg/_pytest/config/__init__.py:1061(_checkversion) 2 0.000 0.000 0.004 0.002 numba/core/typeconv/typeconv.py:113(unsafe_unsafe) 1 0.000 0.000 0.004 0.004 scipy/constants/codata.py:51() 7122 0.002 0.000 0.004 0.000 typing.py:590(_is_dunder) 1186 0.001 0.000 0.004 0.000 <__array_function__ internals>:2(copyto) 1 0.000 0.000 0.004 0.004 matplotlib/font_manager.py:14() 1 0.000 0.000 0.004 0.004 numpy/linalg/__init__.py:71() 1 0.000 0.000 0.004 0.004 pandas/tests/dtypes/cast/test_infer_dtype.py:1() 1 0.000 0.000 0.004 0.004 pandas/tests/reductions/test_reductions.py:1122(TestSeriesMode) 1 0.000 0.000 0.004 0.004 numba/np/arrayobj.py:4() 357 0.002 0.000 0.004 0.000 pandas/core/indexes/base.py:1627(is_unique) 8/7 0.000 0.000 0.004 0.001 py/_vendored_packages/apipkg.py:68(importobj) 408 0.002 0.000 0.004 0.000 numpy/core/_asarray.py:223(require) 1 0.000 0.000 0.004 0.004 pytest-5.4.1.dev462+g322190fd8-py3.7.egg/_pytest/mark/__init__.py:1() 78 0.001 0.000 0.004 0.000 traceback.py:318(extract) 143 0.000 0.000 0.004 0.000 numba/core/extending.py:121(register_jitable) 4244 0.002 0.000 0.004 0.000 pytest-5.4.1.dev462+g322190fd8-py3.7.egg/_pytest/mark/structures.py:37(istestfunc) 840 0.003 0.000 0.004 0.000 pytest-5.4.1.dev462+g322190fd8-py3.7.egg/_pytest/python.py:1073(_validate_ids) 1 0.000 0.000 0.004 0.004 pandas/tests/reshape/test_melt.py:9(TestMelt) 509 0.000 0.000 0.004 0.000 pathlib.py:911(joinpath) 82 0.004 0.000 0.004 0.000 pandas/core/arrays/datetimes.py:2324(_maybe_localize_point) 1 0.000 0.000 0.004 0.004 multiprocessing/__init__.py:15() 1 0.000 0.000 0.004 0.004 pandas/core/groupby/ops.py:7() 32 0.000 0.000 0.004 0.000 pandas/core/indexing.py:586(_get_setitem_indexer) 1 0.000 0.000 0.004 0.004 astropy/units/format/__init__.py:5() 18 0.000 0.000 0.004 0.000 matplotlib/rcsetup.py:860(validate_cycler) 1 0.000 0.000 0.004 0.004 numpy/core/fromnumeric.py:3() 31 0.001 0.000 0.004 0.000 {pandas._libs.tslibs.period.extract_ordinals} 1 0.000 0.000 0.004 0.004 astropy/units/quantity.py:47(Conf) 149 0.003 0.000 0.004 0.000 {method 'factorize' of 'pandas._libs.hashtable.StringHashTable' objects} 50 0.000 0.000 0.004 0.000 sqlalchemy/util/langhelpers.py:165(public_factory) 15280 0.004 0.000 0.004 0.000 {built-in method from_iterable} 1 0.000 0.000 0.004 0.004 scipy/optimize/minpack.py:1() 5514 0.002 0.000 0.004 0.000 :51(_r_long) 1 0.000 0.000 0.004 0.004 openpyxl/chart/text.py:2() 50 0.000 0.000 0.004 0.000 traceback.py:200(extract_stack) 3551 0.003 0.000 0.004 0.000 pytest-5.4.1.dev462+g322190fd8-py3.7.egg/_pytest/store.py:92(__getitem__) 453 0.000 0.000 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importlib_metadata/__init__.py:416(children) 2743 0.004 0.000 0.004 0.000 numpy/core/_internal.py:830(npy_ctypes_check) 1 0.000 0.000 0.004 0.004 pandas/tests/frame/test_to_csv.py:1() ```

[bluetech]

@jbrockmendel Thanks for the stats. We're working on improving collection performance, I think that in every release you'd see it's a bit faster. In particular I've added pandas now as a benchmark for optimization. At this point isn't one thing that slows things down, just many small things.

I don't think the issue is actionable besides that, so I'll close it now.