Numerous FutureWarning with asv_bench

[gliptak]

[  1.85%] ····· /tmp/pandas/asv_bench/benchmarks/algorithms.py:64: FutureWarning: pd.match() is deprecated and will be removed in a future version
                pd.match(self.all, self.uniques)

[  8.79%] ····· /tmp/pandas/asv_bench/benchmarks/frame_ctor.py:67: FutureWarning: consolidate is deprecated and will be removed in a future release.
                self.df = self.df.consolidate()

[ 16.99%] ····· /tmp/pandas/asv_bench/benchmarks/frame_methods.py:528: FutureWarning: by argument to sort_index is deprecated, please use .sort_values(by=...)
                self.df.sort_index(by=['key1', 'key2'])

[ 20.69%] ····· /tmp/pandas/asv_bench/benchmarks/gil.py:337: FutureWarning: pd.rolling_kurt is deprecated for ndarrays and will be removed in a future version
                rolling_kurt(arr, win)

[ 20.81%] ····· /tmp/pandas/asv_bench/benchmarks/gil.py:319: FutureWarning: pd.rolling_max is deprecated for ndarrays and will be removed in a future version
                rolling_max(arr, win)

[ 20.92%] ····· /tmp/pandas/asv_bench/benchmarks/gil.py:307: FutureWarning: pd.rolling_mean is deprecated for ndarrays and will be removed in a future version
                rolling_mean(arr, win)

[ 21.04%] ····· /tmp/pandas/asv_bench/benchmarks/gil.py:313: FutureWarning: pd.rolling_min is deprecated for ndarrays and will be removed in a future version
                rolling_min(arr, win)

[ 21.16%] ····· /tmp/pandas/asv_bench/benchmarks/gil.py:331: FutureWarning: pd.rolling_skew is deprecated for ndarrays and will be removed in a future version
                rolling_skew(arr, win)

[ 21.27%] ····· /tmp/pandas/asv_bench/benchmarks/gil.py:343: FutureWarning: pd.rolling_std is deprecated for ndarrays and will be removed in a future version
                rolling_std(arr, win)

[ 21.39%] ····· /tmp/pandas/asv_bench/benchmarks/gil.py:325: FutureWarning: pd.rolling_var is deprecated for ndarrays and will be removed in a future version
                rolling_var(arr, win)

[ 21.50%] ····· /tmp/pandas/asv_bench/benchmarks/gil.py:290: FutureWarning: pd.rolling_median is deprecated for ndarrays and will be removed in a future version
                rolling_median(arr, win)

[ 31.10%] ····· /tmp/pandas/asv_bench/benchmarks/groupby.py:383: FutureWarning: pd.TimeGrouper is deprecated and will be removed; Please use pd.Grouper(freq=...)
                self.df.groupby(TimeGrouper(key='dates', freq='M')).size()

[ 42.89%] ····· /tmp/pandas/asv_bench/benchmarks/indexing.py:190: FutureWarning: sortlevel is deprecated, use sort_index(level= ...)
                self.mdt2 = self.mdt.set_index(['A', 'B', 'C', 'D']).sortlevel()

[ 43.01%] ····· /tmp/pandas/asv_bench/benchmarks/indexing.py:190: FutureWarning: sortlevel is deprecated, use sort_index(level= ...)
                self.mdt2 = self.mdt.set_index(['A', 'B', 'C', 'D']).sortlevel()

[ 43.12%] ····· /tmp/pandas/asv_bench/benchmarks/indexing.py:190: FutureWarning: sortlevel is deprecated, use sort_index(level= ...)
                self.mdt2 = self.mdt.set_index(['A', 'B', 'C', 'D']).sortlevel()

[ 43.24%] ····· /tmp/pandas/asv_bench/benchmarks/indexing.py:190: FutureWarning: sortlevel is deprecated, use sort_index(level= ...)
                self.mdt2 = self.mdt.set_index(['A', 'B', 'C', 'D']).sortlevel()

[ 43.35%] ····· /tmp/pandas/asv_bench/benchmarks/indexing.py:190: FutureWarning: sortlevel is deprecated, use sort_index(level= ...)
                self.mdt2 = self.mdt.set_index(['A', 'B', 'C', 'D']).sortlevel()

[ 43.47%] ····· /tmp/pandas/asv_bench/benchmarks/indexing.py:190: FutureWarning: sortlevel is deprecated, use sort_index(level= ...)
                self.mdt2 = self.mdt.set_index(['A', 'B', 'C', 'D']).sortlevel()

[ 43.58%] ····· /tmp/pandas/asv_bench/benchmarks/indexing.py:190: FutureWarning: sortlevel is deprecated, use sort_index(level= ...)
                self.mdt2 = self.mdt.set_index(['A', 'B', 'C', 'D']).sortlevel()

[ 43.70%] ····· /tmp/pandas/asv_bench/benchmarks/indexing.py:190: FutureWarning: sortlevel is deprecated, use sort_index(level= ...)
                self.mdt2 = self.mdt.set_index(['A', 'B', 'C', 'D']).sortlevel()

[ 43.82%] ····· /tmp/pandas/asv_bench/benchmarks/indexing.py:190: FutureWarning: sortlevel is deprecated, use sort_index(level= ...)
                self.mdt2 = self.mdt.set_index(['A', 'B', 'C', 'D']).sortlevel()

[ 43.93%] ····· /tmp/pandas/asv_bench/benchmarks/indexing.py:190: FutureWarning: sortlevel is deprecated, use sort_index(level= ...)
                self.mdt2 = self.mdt.set_index(['A', 'B', 'C', 'D']).sortlevel()

[ 44.05%] ····· /tmp/pandas/asv_bench/benchmarks/indexing.py:190: FutureWarning: sortlevel is deprecated, use sort_index(level= ...)
                self.mdt2 = self.mdt.set_index(['A', 'B', 'C', 'D']).sortlevel()

[ 44.16%] ····· /tmp/pandas/asv_bench/benchmarks/indexing.py:190: FutureWarning: sortlevel is deprecated, use sort_index(level= ...)
                self.mdt2 = self.mdt.set_index(['A', 'B', 'C', 'D']).sortlevel()

[ 50.52%] ····· /tmp/pandas/asv_bench/benchmarks/join_merge.py:25: FutureWarning: consolidate is deprecated and will be removed in a future release.
                self.mdf1.consolidate(inplace=True)

[ 50.64%] ····· /tmp/pandas/asv_bench/benchmarks/join_merge.py:25: FutureWarning: consolidate is deprecated and will be removed in a future release.
                self.mdf1.consolidate(inplace=True)

[ 81.97%] ····· /tmp/pandas/asv_bench/benchmarks/stat_ops.py:205: FutureWarning: pd.rolling_kurt is deprecated for ndarrays and will be removed in a future version
                rolling_kurt(self.arr, self.win)

[ 82.08%] ····· /tmp/pandas/asv_bench/benchmarks/stat_ops.py:190: FutureWarning: pd.rolling_max is deprecated for ndarrays and will be removed in a future version
                rolling_max(self.arr, self.win)

[ 82.20%] ····· /tmp/pandas/asv_bench/benchmarks/stat_ops.py:181: FutureWarning: pd.rolling_mean is deprecated for ndarrays and will be removed in a future version
                rolling_mean(self.arr, self.win)

[ 82.31%] ····· /tmp/pandas/asv_bench/benchmarks/stat_ops.py:184: FutureWarning: pd.rolling_median is deprecated for ndarrays and will be removed in a future version
                rolling_median(self.arr, self.win)

[ 82.43%] ····· /tmp/pandas/asv_bench/benchmarks/stat_ops.py:187: FutureWarning: pd.rolling_min is deprecated for ndarrays and will be removed in a future version
                rolling_min(self.arr, self.win)

[ 82.54%] ····· /tmp/pandas/asv_bench/benchmarks/stat_ops.py:202: FutureWarning: pd.rolling_skew is deprecated for ndarrays and will be removed in a future version
                rolling_skew(self.arr, self.win)

[ 82.66%] ····· /tmp/pandas/asv_bench/benchmarks/stat_ops.py:196: FutureWarning: pd.rolling_std is deprecated for ndarrays and will be removed in a future version
                rolling_std(self.arr, self.win)

[ 82.77%] ····· /tmp/pandas/asv_bench/benchmarks/stat_ops.py:193: FutureWarning: pd.rolling_sum is deprecated for ndarrays and will be removed in a future version
                rolling_sum(self.arr, self.win)

[ 82.89%] ····· /tmp/pandas/asv_bench/benchmarks/stat_ops.py:199: FutureWarning: pd.rolling_var is deprecated for ndarrays and will be removed in a future version
                rolling_var(self.arr, self.win)

[ 84.05%] ····· /tmp/pandas/asv_bench/benchmarks/strings.py:43: FutureWarning: currently extract(expand=None) means expand=False (return Index/Series/DataFrame) but in a future version of pandas this will be changed to expand=True (return DataFrame)
                self.many.str.extract('(\\w*)matchthis(\\w*)')

[ 88.90%] ····· /tmp/pandas/asv_bench/benchmarks/timeseries.py:96: FutureWarning: the infer_dst=True keyword is deprecated, use ambiguous='infer' instead
                self.index.tz_localize('US/Eastern', infer_dst=True)

[ 92.49%] ····· /tmp/pandas/asv_bench/benchmarks/timeseries.py:162: FutureWarning: how in .resample() is deprecated
                the new syntax is .resample(...)..apply(<func>)
                  self.df.resample('1s', how=np.max)

[ 92.60%] ····· /tmp/pandas/asv_bench/benchmarks/timeseries.py:165: FutureWarning: how in .resample() is deprecated
                the new syntax is .resample(...).max()
                  self.df.resample('1s', how='max')

[ 92.72%] ····· /tmp/pandas/asv_bench/benchmarks/timeseries.py:168: FutureWarning: how in .resample() is deprecated
                the new syntax is .resample(...)..apply(<func>)
                  self.df.resample('1s', how=np.mean)

[ 92.83%] ····· /tmp/pandas/asv_bench/benchmarks/timeseries.py:171: FutureWarning: how in .resample() is deprecated
                the new syntax is .resample(...).mean()
                  self.df.resample('1s', how='mean')

[ 92.95%] ····· /tmp/pandas/asv_bench/benchmarks/timeseries.py:174: FutureWarning: how in .resample() is deprecated
                the new syntax is .resample(...)..apply(<func>)
                  self.df.resample('1s', how=np.min)

[ 93.06%] ····· /tmp/pandas/asv_bench/benchmarks/timeseries.py:177: FutureWarning: how in .resample() is deprecated
                the new syntax is .resample(...).min()
                  self.df.resample('1s', how='min')

[ 93.18%] ····· /tmp/pandas/asv_bench/benchmarks/timeseries.py:205: FutureWarning: how in .resample() is deprecated
                the new syntax is .resample(...).mean()
                  self.ts2[:10000].resample('5min', how='mean')

[ 93.29%] ····· /tmp/pandas/asv_bench/benchmarks/timeseries.py:208: FutureWarning: how in .resample() is deprecated
                the new syntax is .resample(...).ohlc()
                  self.ts2[:10000].resample('5min', how='ohlc')

[ 93.41%] ····· /tmp/pandas/asv_bench/benchmarks/timeseries.py:195: FutureWarning: how in .resample() is deprecated
                the new syntax is .resample(...).mean()
                  self.ts1.resample('D', how='mean')

[ 93.53%] ····· /tmp/pandas/asv_bench/benchmarks/timeseries.py:202: FutureWarning: how in .resample() is deprecated
                the new syntax is .resample(...).last()
                  self.dt_ts.resample('1S', how='last')

[ 93.64%] ····· /tmp/pandas/asv_bench/benchmarks/timeseries.py:198: FutureWarning: how in .resample() is deprecated
                the new syntax is .resample(...).mean()
                  self.ts2.resample('D', how='mean')

[ 99.54%] ····· /tmp/pandas/asv_bench/benchmarks/timestamp.py:17: FutureWarning: .offset is deprecated. Use .freq instead
                self.ts.offset

Output of pd.show_versions()

INSTALLED VERSIONS ------------------ commit: baadad7 python: 2.7.14.final.0 python-bits: 64 OS: Linux OS-release: 4.13.0-12-generic machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_US.UTF-8 LOCALE: None.None

pandas: 0.21.0.dev+550.gbaadad758.dirty
pytest: 3.1.2
pip: 9.0.1
setuptools: 36.0.1
Cython: 0.27
numpy: 1.13.1
scipy: 0.19.0
pyarrow: None
xarray: None
IPython: 5.4.1
sphinx: None
patsy: 0.4.1
dateutil: 2.6.1
pytz: 2017.2
blosc: None
bottleneck: None
tables: 3.4.2
numexpr: 2.6.4
feather: None
matplotlib: 2.0.2
openpyxl: 2.4.8
xlrd: 1.0.0
xlwt: 1.3.0
xlsxwriter: 1.0.0
lxml: 3.8.0
bs4: 4.6.0
html5lib: 0.999999999
sqlalchemy: 1.1.14
pymysql: None
psycopg2: None
jinja2: 2.9.6
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: 0.5.0

[jorisvandenbossche]

Yes, that's a known issues (I thought we had it mentioned somewhere in an issue, but can't find it).
We mainly need to figure out a way to keep it running for older versions as well without having those warnings / code breaks.

Eg for resample that could be a small wrapper like

def resample(df, freq, how):
    if (check version):
        return getattr(df.resample(freq), how)()
    else:
        return df.resample(freq, how)

For others it might not always be worth to make this effort

[gliptak]

@jorisvandenbossche How many major previous releases do you see supporting? (one could checkout and run the corresponding version of the performance bench ...)

[mroeschke]

All warning on the asv benches should have been caught since #19236 was merged recently

[jorisvandenbossche]

OK, closing this then. When we actually remove deprecated functionality, and asv would break, it will be catched by travis now.