TST: Broken asv performance test sparse.py #17658
Description
Code Sample, a copy-pastable example if possible
- asv version
[asv_bench] asv --version asv 0.3.dev1126+2320b0f - Input
# Your code here asv continuous -f 1.1 origin/master HEAD -b sparse- Output
· Creating environments · Discovering benchmarks ·· Uninstalling from conda-py3.6-Cython-matplotlib-numexpr-numpy-openpyxl-pytables-pytest-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt.. ·· Installing into conda-py3.6-Cython-matplotlib-numexpr-numpy-openpyxl-pytables-pytest-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt.. · Running 42 total benchmarks (2 commits * 1 environments * 21 benchmarks) [ 0.00%] · For pandas commit hash 8276a420: [ 0.00%] ·· Building for conda-py3.6-Cython-matplotlib-numexpr-numpy-openpyxl-pytables-pytest-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt.... [ 0.00%] ·· Benchmarking conda-py3.6-Cython-matplotlib-numexpr-numpy-openpyxl-pytables-pytest-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt [ 2.38%] ··· Running reshape.unstack_sparse_keyspace.time_unstack_sparse_keyspace 1.88±0.06ms [ 4.76%] ··· Running sparse.sparse_arithmetic_block.time_sparse_addition failed ... Problem description
Whole pandas/asv_bench/benchmarks/sparse.py tests fail.
It seems that from itertools import repeat conflicts with the repeat parameter for asv.
[asv_bench] head benchmarks/sparse.py from itertools import repeat from .pandas_vb_common import * import scipy.sparse from pandas import SparseSeries, SparseDataFrame class sparse_series_to_frame(object): goal_time = 0.2Expected Output
After removing from itertools import repeat, it works well.
[asv_bench] head benchmarks/sparse.py import itertools from .pandas_vb_common import * import scipy.sparse from pandas import SparseSeries, SparseDataFrame class sparse_series_to_frame(object): goal_time = 0.2[asv_bench] asv continuous -f 1.1 origin/master HEAD -b sparse · Creating environments · Discovering benchmarks ·· Uninstalling from conda-py3.6-Cython-matplotlib-numexpr-numpy-openpyxl-pytables-pytest-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt. ·· Installing into conda-py3.6-Cython-matplotlib-numexpr-numpy-openpyxl-pytables-pytest-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt... · Running 42 total benchmarks (2 commits * 1 environments * 21 benchmarks) [ 0.00%] · For pandas commit hash 965c1c89: [ 0.00%] ·· Building for conda-py3.6-Cython-matplotlib-numexpr-numpy-openpyxl-pytables-pytest-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt............................................................... [ 0.00%] ·· Benchmarking conda-py3.6-Cython-matplotlib-numexpr-numpy-openpyxl-pytables-pytest-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt [ 2.38%] ··· Running reshape.unstack_sparse_keyspace.time_unstack_sparse_keyspace 1.80±0.03ms [ 4.76%] ··· Running sparse.sparse_arithmetic_block.time_sparse_addition 6.54±0.07ms [ 7.14%] ··· Running sparse.sparse_arithmetic_block.time_sparse_addition_zero 6.73±0.3ms ...Output of pd.show_versions()
INSTALLED VERSIONS ------------------ commit: None python: 3.6.2.final.0 python-bits: 64 OS: Darwin OS-release: 15.4.0 machine: x86_64 processor: i386 byteorder: little LC_ALL: None LANG: ja_JP.UTF-8 LOCALE: ja_JP.UTF-8
pandas: 0.20.3
pytest: 3.2.1
pip: 9.0.1
setuptools: 32.2.0
Cython: 0.26
numpy: 1.13.1
scipy: 0.19.1
xarray: None
IPython: 6.1.0
sphinx: None
patsy: None
dateutil: 2.6.1
pytz: 2017.2
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: 2.0.2
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: 0.999999999
sqlalchemy: 1.1.14
pymysql: None
psycopg2: None
jinja2: 2.9.6
s3fs: None
pandas_gbq: None
pandas_datareader: None