CLN: ASV binary ops benchmark

[mroeschke]

• Utilized params of timezones in the Timeseries class instead of creating a subclass of TimeseriesTZ

• Division was being tested instead of modulo in time_frame_int_mod and time_frame_float_mod

• Added np.random.seed(1234) in setup classes where random data is created xref BENCH: put in np.random.seed on vbenches #8144

• Renamed time_timestamp_ops_diff2 to time_timestamp_ops_diff_with_shift

• Replaced the depreciated np.random.random_integers with np.random.randint

• Ran flake8 and replaced star imports

asv run -q -b ^binary_ops
[  0.00%] ·· Benchmarking conda-py3.6-Cython-matplotlib-numexpr-numpy-openpyxl-pytables-pytest-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt
[  7.14%] ··· Running binary_ops.Ops.time_frame_add                                                                                 46.1ms;...
[ 14.29%] ··· Running binary_ops.Ops.time_frame_comparison                                                                          16.5ms;...
[ 21.43%] ··· Running binary_ops.Ops.time_frame_mult                                                                                55.3ms;...
[ 28.57%] ··· Running binary_ops.Ops.time_frame_multi_and                                                                            126ms;...
[ 35.71%] ··· Running binary_ops.Ops2.time_frame_float_div                                                                              73.0ms
[ 42.86%] ··· Running binary_ops.Ops2.time_frame_float_div_by_zero                                                                      80.7ms
[ 50.00%] ··· Running binary_ops.Ops2.time_frame_float_floor_by_zero                                                                    83.9ms
[ 57.14%] ··· Running binary_ops.Ops2.time_frame_float_mod                                                                              25.3ms
[ 64.29%] ··· Running binary_ops.Ops2.time_frame_int_div_by_zero                                                                        97.2ms
[ 71.43%] ··· Running binary_ops.Ops2.time_frame_int_mod                                                                                46.1ms
[ 78.57%] ··· Running binary_ops.Timeseries.time_series_timestamp_compare                                                           5.40ms;...
[ 85.71%] ··· Running binary_ops.Timeseries.time_timestamp_ops_diff                                                                 42.8ms;...
[ 92.86%] ··· Running binary_ops.Timeseries.time_timestamp_ops_diff_with_shift                                                       157ms;...
[100.00%] ··· Running binary_ops.Timeseries.time_timestamp_series_compare                                                           5.55ms;...

[codecov]

Codecov Report

Merging #18444 into master will decrease coverage by 0.01%.
The diff coverage is n/a.

@@            Coverage Diff             @@
##           master   #18444      +/-   ##
==========================================
- Coverage   91.34%   91.32%   -0.02%     
==========================================
  Files         163      163              
  Lines       49717    49717              
==========================================
- Hits        45413    45404       -9     
- Misses       4304     4313       +9

Flag	Coverage Δ
#multiple	89.12% <ø> (ø)	⬆️
#single	40.51% <ø> (-0.07%)	⬇️

Impacted Files	Coverage Δ
pandas/io/gbq.py	25% <0%> (-58.34%)	⬇️
pandas/core/frame.py	97.8% <0%> (-0.1%)	⬇️

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[jreback]

http://asv.readthedocs.io/en/latest/writing_benchmarks.html

we can add params_names (here) and elsewhere (just for readibility)

[jreback]

I am shocked this works, seeing that the param_names should be ['tz']

[mroeschke]

Yeah I have noticed ASV has some interesting quirks. Nonetheless for consistency, I changed timezone to tz

[jreback]

thanks!