CI/TST: slow tests

[jreback]

xref #30641

from the new arm64 job, but indicative of general slowness: https://travis-ci.org/github/pandas-dev/pandas/jobs/685955999

• let's make these much faster
• we can still mark some as slow if needed
• let's change the https://github.com/pandas-dev/pandas/blob/master/ci/run_tests.sh#L23, durations to 20 or 30

This issue can be closed by multiple PRs

========================== slowest 10 test durations ===========================
88.88s call     pandas/tests/resample/test_datetime_index.py::test_nearest_upsample_with_limit[tzlocal()-30S-Y]
65.15s call     pandas/tests/resample/test_datetime_index.py::test_nearest_upsample_with_limit[tzlocal()-30S-10M]
22.33s call     pandas/tests/io/parser/test_multi_thread.py::test_multi_thread_path_multipart_read_csv[python]
21.54s call     pandas/tests/io/parser/test_multi_thread.py::test_multi_thread_path_multipart_read_csv[c_high]
21.03s call     pandas/tests/io/parser/test_multi_thread.py::test_multi_thread_path_multipart_read_csv[c_low]
19.46s call     pandas/tests/resample/test_datetime_index.py::test_nearest_upsample_with_limit['dateutil/US/Pacific'-30S-Y]
15.75s call     pandas/tests/resample/test_datetime_index.py::test_nearest_upsample_with_limit['dateutil/Asia/Singapore'-30S-10M]
15.71s call     pandas/tests/resample/test_datetime_index.py::test_nearest_upsample_with_limit['dateutil/Asia/Singapore'-30S-Y]
15.61s call     pandas/tests/resample/test_datetime_index.py::test_nearest_upsample_with_limit['Asia/Tokyo'-30S-Y]
15.59s call     pandas/tests/resample/test_datetime_index.py::test_nearest_upsample_with_limit['US/Eastern'-30S-Y]
14.27s call     pandas/tests/resample/test_datetime_index.py::test_nearest_upsample_with_limit['Asia/Tokyo'-30S-10M]
13.18s call     pandas/tests/groupby/transform/test_transform.py::test_cython_transform_frame[shift-args3-<lambda>]
13.11s call     pandas/tests/test_sorting.py::TestSorting::test_int64_overflow_moar
12.98s call     pandas/tests/resample/test_datetime_index.py::test_nearest_upsample_with_limit['US/Eastern'-30S-10M]
12.92s call     pandas/tests/resample/test_datetime_index.py::test_nearest_upsample_with_limit['dateutil/US/Pacific'-30S-10M]
12.78s call     pandas/tests/io/sas/test_sas7bdat.py::TestSAS7BDAT::test_iterator_loop
12.76s call     pandas/tests/io/sas/test_xport.py::TestXport::test1_basic
12.18s call     pandas/tests/groupby/transform/test_transform.py::test_cython_transform_frame[shift-args2-<lambda>]
11.97s call     pandas/tests/indexing/multiindex/test_chaining_and_caching.py::test_indexer_caching
11.95s call     pandas/tests/resample/test_datetime_index.py::test_nearest_upsample_with_limit[pytz.FixedOffset(300)-30S-Y]
11.28s call     pandas/tests/io/parser/test_multi_thread.py::test_multi_thread_string_io_read_csv[python]
11.19s call     pandas/tests/resample/test_datetime_index.py::test_nearest_upsample_with_limit[datetime.timezone(datetime.timedelta(0, 3600))-30S-Y]
10.60s call     pandas/tests/resample/test_datetime_index.py::test_nearest_upsample_with_limit[tzutc()-30S-Y]
10.45s call     pandas/tests/resample/test_datetime_index.py::test_nearest_upsample_with_limit[<UTC>-30S-Y]
10.35s call     pandas/tests/resample/test_datetime_index.py::test_nearest_upsample_with_limit[datetime.timezone.utc-30S-Y]
10.19s call     pandas/tests/resample/test_datetime_index.py::test_nearest_upsample_with_limit[datetime.timezone(datetime.timedelta(-1, 82800), 'foo')-30S-Y]
10.12s call     pandas/tests/resample/test_datetime_index.py::test_nearest_upsample_with_limit[tzutc()-30S-10M]
10.05s call     pandas/tests/resample/test_datetime_index.py::test_nearest_upsample_with_limit['UTC'-30S-Y]
9.99s call     pandas/tests/resample/test_datetime_index.py::test_nearest_upsample_with_limit[pytz.FixedOffset(-300)-30S-Y]
9.58s call     pandas/tests/resample/test_datetime_index.py::test_nearest_upsample_with_limit[<UTC>-30S-10M]```

[jreback]

updated the above list for top 30: https://travis-ci.org/github/pandas-dev/pandas/jobs/686095405 is the build (one of the standard ones)

[dsaxton]

For test_nearest_upsample_with_limits from pandas/tests/resample/test_datetime_index.py is it necessary to parametrize over so many timezones? Removing that fixture causes a speedup for me from around 5 minutes to less than a second. Looks there was a timezone specific issue, but I suppose a smaller set could be tested? #33895

[jreback]

The issue is here: https://github.com/pandas-dev/pandas/pull/33939/files#diff-dd427a6bbdfef7e333ac320adb15614dR539

its not the tz's at all, rather upsampling creates an enormous array

e.g.

In [10]: ts = pd.Series(1, index=pd.date_range("1/1/2000", periods=3, freq='Y'))                                                                              

In [11]: ts.resample('1min').nearest(limit=2)                                                                                                                 
Out[11]: 
2000-12-31 00:00:00    1.0
2000-12-31 00:01:00    1.0
2000-12-31 00:02:00    1.0
2000-12-31 00:03:00    NaN
2000-12-31 00:04:00    NaN
2000-12-31 00:05:00    NaN
                      ... 
2002-12-30 23:55:00    NaN
2002-12-30 23:56:00    NaN
2002-12-30 23:57:00    NaN
2002-12-30 23:58:00    1.0
2002-12-30 23:59:00    1.0
2002-12-31 00:00:00    1.0
Freq: T, Length: 1051201, dtype: float64

In [12]: ts.resample('10s').nearest(limit=2)                                                                                                                  
Out[12]: 
2000-12-31 00:00:00    1.0
2000-12-31 00:00:10    1.0
2000-12-31 00:00:20    1.0
2000-12-31 00:00:30    NaN
2000-12-31 00:00:40    NaN
2000-12-31 00:00:50    NaN
                      ... 
2002-12-30 23:59:10    NaN
2002-12-30 23:59:20    NaN
2002-12-30 23:59:30    NaN
2002-12-30 23:59:40    1.0
2002-12-30 23:59:50    1.0
2002-12-31 00:00:00    1.0
Freq: 10S, Length: 6307201, dtype: float64

so should split this test up into 2, e.g. no real need to upsample Y to 10s

[avirlrma]

take