Skip to content

PERF/CI: fix benchmark import error + run asv check on all builds #26575

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 4 commits into from
May 30, 2019
Merged
Show file tree
Hide file tree
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 2 additions & 0 deletions asv_bench/benchmarks/frame_methods.py
Original file line number Diff line number Diff line change
Expand Up @@ -96,6 +96,8 @@ def time_dict_rename_both_axes(self):


class Iteration:
# mem_itertuples_* benchmarks are slow
timeout = 120

def setup(self):
N = 1000
Expand Down
7 changes: 1 addition & 6 deletions asv_bench/benchmarks/groupby.py
Original file line number Diff line number Diff line change
@@ -1,12 +1,11 @@
from functools import partial
from itertools import product
from string import ascii_letters
import warnings

import numpy as np

from pandas import (
Categorical, DataFrame, MultiIndex, Series, TimeGrouper, Timestamp,
Categorical, DataFrame, MultiIndex, Series, Timestamp,
date_range, period_range)
import pandas.util.testing as tm

Expand Down Expand Up @@ -301,10 +300,6 @@ def setup(self):
def time_multi_size(self):
self.df.groupby(['key1', 'key2']).size()

def time_dt_timegrouper_size(self):
with warnings.catch_warnings(record=True):
self.df.groupby(TimeGrouper(key='dates', freq='M')).size()

def time_category_size(self):
self.draws.groupby(self.cats).size()

Expand Down
8 changes: 6 additions & 2 deletions asv_bench/benchmarks/io/parsers.py
Original file line number Diff line number Diff line change
@@ -1,7 +1,11 @@
import numpy as np

from pandas._libs.tslibs.parsing import (
_concat_date_cols, _does_string_look_like_datetime)
try:
from pandas._libs.tslibs.parsing import (
_concat_date_cols, _does_string_look_like_datetime)
except ImportError:
# Avoid whole benchmark suite import failure on asv (currently 0.4)
pass


class DoesStringLookLikeDatetime(object):
Expand Down
3 changes: 2 additions & 1 deletion azure-pipelines.yml
Original file line number Diff line number Diff line change
Expand Up @@ -97,10 +97,11 @@ jobs:
- script: |
export PATH=$HOME/miniconda3/bin:$PATH
source activate pandas-dev
cd asv_bench
asv check -E existing
git remote add upstream https://github.com/pandas-dev/pandas.git
git fetch upstream
if git diff upstream/master --name-only | grep -q "^asv_bench/"; then
cd asv_bench
asv machine --yes
ASV_OUTPUT="$(asv dev)"
if [[ $(echo "$ASV_OUTPUT" | grep "failed") ]]; then
Expand Down