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Reduce pytest runtime #10203

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merged 23 commits into from
Feb 15, 2022
Merged

Reduce pytest runtime #10203

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4d7ae60
address first few slowest tests
brandon-b-miller Feb 3, 2022
1f9e36d
continue reducing runtime
brandon-b-miller Feb 7, 2022
70932d5
updates
brandon-b-miller Feb 7, 2022
b94cce4
??? IDE added this somehow
brandon-b-miller Feb 7, 2022
67e3994
style
brandon-b-miller Feb 7, 2022
e05d8bc
style
brandon-b-miller Feb 7, 2022
f367e01
remove unused parameters
brandon-b-miller Feb 7, 2022
9e37504
Merge branch 'branch-22.04' into fix-reduce-pytest-time
brandon-b-miller Feb 7, 2022
d298d4a
Update python/cudf/cudf/tests/test_binops.py
brandon-b-miller Feb 8, 2022
6e9a0ef
address reviews
brandon-b-miller Feb 8, 2022
e4a98d0
less from_pandas()
brandon-b-miller Feb 8, 2022
289a13b
combine repr tests
brandon-b-miller Feb 8, 2022
2e25ed2
Update python/cudf/cudf/tests/test_indexing.py
brandon-b-miller Feb 8, 2022
9393bd0
update copyrights
brandon-b-miller Feb 8, 2022
a20102e
Apply suggestions from code review
brandon-b-miller Feb 9, 2022
9c800cd
address reviews
brandon-b-miller Feb 9, 2022
025c69d
temporarily revert changes
brandon-b-miller Feb 9, 2022
60a0a92
copyright
brandon-b-miller Feb 9, 2022
6128b2a
Merge branch 'branch-22.04' into fix-reduce-pytest-time
brandon-b-miller Feb 14, 2022
227be3c
redo test_cudf_isclose parameterization
brandon-b-miller Feb 14, 2022
ecdb986
revert changes to test_cudf_isclose
brandon-b-miller Feb 15, 2022
e3b6500
Merge branch 'branch-22.04' into fix-reduce-pytest-time
brandon-b-miller Feb 15, 2022
62d56be
copyright
brandon-b-miller Feb 15, 2022
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9 changes: 8 additions & 1 deletion python/cudf/cudf/testing/_utils.py
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Original file line number Diff line number Diff line change
@@ -1,5 +1,6 @@
# Copyright (c) 2020-2021, NVIDIA CORPORATION.
# Copyright (c) 2020-2022, NVIDIA CORPORATION.

import itertools
import re
import warnings
from collections.abc import Mapping, Sequence
Expand Down Expand Up @@ -330,3 +331,9 @@ def does_not_raise():

def xfail_param(param, **kwargs):
return pytest.param(param, marks=pytest.mark.xfail(**kwargs))


parametrize_numeric_dtypes_pairwise = pytest.mark.parametrize(
"left_dtype,right_dtype",
list(itertools.combinations_with_replacement(NUMERIC_TYPES, 2)),
)
4 changes: 2 additions & 2 deletions python/cudf/cudf/tests/test_avro_reader_fastavro_integration.py
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@@ -1,4 +1,4 @@
# Copyright (c) 2021, NVIDIA CORPORATION.
# Copyright (c) 2021-2022, NVIDIA CORPORATION.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
Expand Down Expand Up @@ -210,7 +210,7 @@ def test_can_parse_no_schema():
assert_eq(expected, actual)
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@pytest.mark.parametrize("rows", [0, 1, 10, 100000])
@pytest.mark.parametrize("rows", [0, 1, 10, 1000])
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@pytest.mark.parametrize("codec", ["null", "deflate", "snappy"])
def test_avro_compression(rows, codec):
schema = {
Expand Down
15 changes: 7 additions & 8 deletions python/cudf/cudf/tests/test_binops.py
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Expand Up @@ -4,7 +4,7 @@
import decimal
import operator
import random
from itertools import product
from itertools import combinations_with_replacement, product

import cupy as cp
import numpy as np
Expand Down Expand Up @@ -216,13 +216,12 @@ def test_series_compare(cmpop, obj_class, dtype):


def _series_compare_nulls_typegen():
tests = []
tests += list(product(DATETIME_TYPES, DATETIME_TYPES))
tests += list(product(TIMEDELTA_TYPES, TIMEDELTA_TYPES))
tests += list(product(NUMERIC_TYPES, NUMERIC_TYPES))
tests += list(product(STRING_TYPES, STRING_TYPES))

return tests
return [
*combinations_with_replacement(DATETIME_TYPES, 2),
*combinations_with_replacement(TIMEDELTA_TYPES, 2),
*combinations_with_replacement(NUMERIC_TYPES, 2),
*combinations_with_replacement(STRING_TYPES, 2),
]


@pytest.mark.parametrize("cmpop", _cmpops)
Expand Down
11 changes: 6 additions & 5 deletions python/cudf/cudf/tests/test_csv.py
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@@ -1,4 +1,4 @@
# Copyright (c) 2018-2021, NVIDIA CORPORATION.
# Copyright (c) 2018-2022, NVIDIA CORPORATION.

import gzip
import os
Expand All @@ -8,6 +8,7 @@
from io import BytesIO, StringIO
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from pathlib import Path

import cupy as cp
import numpy as np
import pandas as pd
import pytest
Expand Down Expand Up @@ -1009,17 +1010,17 @@ def test_small_zip(tmpdir):
def test_csv_reader_carriage_return(tmpdir):
rows = 1000
names = ["int_row", "int_double_row"]

buffer = ",".join(names) + "\r\n"
for row in range(rows):
buffer += str(row) + ", " + str(2 * row) + "\r\n"

df = read_csv(StringIO(buffer))
expect = cudf.DataFrame(
{"int_row": cp.arange(rows), "int_double_row": cp.arange(rows) * 2}
)

assert len(df) == rows
for row in range(0, rows):
assert df[names[0]][row] == row
assert df[names[1]][row] == 2 * row
assert_eq(expect, df)


def test_csv_reader_tabs():
Expand Down
12 changes: 9 additions & 3 deletions python/cudf/cudf/tests/test_extension_compilation.py
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@@ -1,13 +1,17 @@
# Copyright (c) 2021-2022, NVIDIA CORPORATION.
import operator
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import cupy as cp
import numpy as np
import pytest
from numba import cuda, types
from numba.cuda import compile_ptx
from numba.np.numpy_support import from_dtype

from cudf import NA
from cudf.core.udf.api import Masked
from cudf.core.udf.typing import MaskedType
from cudf.testing._utils import parametrize_numeric_dtypes_pairwise

arith_ops = (
operator.add,
Expand Down Expand Up @@ -159,19 +163,21 @@ def func(x):


@pytest.mark.parametrize("op", ops)
@pytest.mark.parametrize("ty1", number_types, ids=number_ids)
@pytest.mark.parametrize("ty2", number_types, ids=number_ids)
@parametrize_numeric_dtypes_pairwise
@pytest.mark.parametrize(
"masked",
((False, True), (True, False), (True, True)),
ids=("um", "mu", "mm"),
)
def test_compile_arith_masked_ops(op, ty1, ty2, masked):
def test_compile_arith_masked_ops(op, left_dtype, right_dtype, masked):
def func(x, y):
return op(x, y)

cc = (7, 5)

ty1 = from_dtype(np.dtype(left_dtype))
ty2 = from_dtype(np.dtype(right_dtype))

if masked[0]:
ty1 = MaskedType(ty1)
if masked[1]:
Expand Down
46 changes: 22 additions & 24 deletions python/cudf/cudf/tests/test_indexing.py
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@@ -1,4 +1,4 @@
# Copyright (c) 2021, NVIDIA CORPORATION.
# Copyright (c) 2021-2022, NVIDIA CORPORATION.

from itertools import combinations

Expand Down Expand Up @@ -1292,45 +1292,43 @@ def test_loc_datetime_index(sli, is_dataframe):


@pytest.mark.parametrize(
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"gdf",
"gdf_kwargs",
[
cudf.DataFrame({"a": range(1000000)}),
cudf.DataFrame({"a": range(1000000), "b": range(1000000)}),
cudf.DataFrame({"a": range(20), "b": range(20)}),
cudf.DataFrame(
{
{"data": {"a": range(100000)}},
{"data": {"a": range(100000), "b": range(100000)}},
{
"data": {
"a": range(20),
"b": range(20),
"c": ["abc", "def", "xyz", "def", "pqr"] * 4,
}
),
cudf.DataFrame(index=[1, 2, 3]),
cudf.DataFrame(index=range(1000000)),
cudf.DataFrame(columns=["a", "b", "c", "d"]),
cudf.DataFrame(columns=["a"], index=range(1000000)),
cudf.DataFrame(
columns=["a", "col2", "...col n"], index=range(1000000)
),
cudf.DataFrame(index=cudf.Series(range(1000000)).astype("str")),
cudf.DataFrame(
columns=["a", "b", "c", "d"],
index=cudf.Series(range(1000000)).astype("str"),
),
},
{"index": [1, 2, 3]},
{"index": range(100000)},
{"columns": ["a", "b", "c", "d"]},
{"columns": ["a"], "index": range(100000)},
{"columns": ["a", "col2", "...col n"], "index": range(100000)},
{"index": cudf.Series(range(100000)).astype("str")},
{
"columns": ["a", "b", "c", "d"],
"index": cudf.Series(range(100000)).astype("str"),
},
],
)
@pytest.mark.parametrize(
"slice",
[
slice(250000, 500000),
slice(250000, 250001),
slice(500000),
slice(25000, 50000),
slice(25000, 25001),
slice(50000),
slice(1, 10),
slice(10, 20),
slice(15, 24000),
slice(6),
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@bdice bdice Feb 11, 2022 •
edited
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If we're testing multiple combinations, we should have coverage of unique code paths: three-argument slices like slice(start, stop, step), negative indices, reversed slices, and empty slices. In the spirit of reducing runtime, some of the other cases can probably be removed if we aim for covering only unique cases. Also, I see no reason why we can't cut this test down to 100 rows instead of 100,000.

Suggested change
slice(6),
slice(6, None), # start but no stop, [6:]
slice(None, None, 3), # only step, [::3]
slice(1, 10, 2), # start, stop, step
slice(3, -5, 2), # negative stop
slice(-2, -4), # slice is empty
slice(-10, -20, -1), # reversed slice
slice(None), # slices everything, same as [:]

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I tried some of these and we actually get multiple failures with these. Raising an issue now

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Glad I could help catch a bug here. Please tag me in that issue, I'm interested in seeing what you found. Slice all the things! 🥷⚔️🥷

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raised #10292

],
)
def test_dataframe_sliced(gdf, slice):
def test_dataframe_sliced(gdf_kwargs, slice):
gdf = cudf.DataFrame(**gdf_kwargs)
pdf = gdf.to_pandas()

actual = gdf[slice]
Expand Down
24 changes: 13 additions & 11 deletions python/cudf/cudf/tests/test_orc.py
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Expand Up @@ -16,6 +16,7 @@

import cudf
from cudf.io.orc import ORCWriter
from cudf.testing import assert_frame_equal
from cudf.testing._utils import (
assert_eq,
gen_rand_series,
Expand Down Expand Up @@ -93,7 +94,7 @@ def test_orc_reader_basic(datadir, inputfile, columns, use_index, engine):
path, engine=engine, columns=columns, use_index=use_index
)

assert_eq(expect, got, check_categorical=False)
assert_frame_equal(cudf.from_pandas(expect), got, check_categorical=False)


def test_orc_reader_filenotfound(tmpdir):
Expand Down Expand Up @@ -384,11 +385,13 @@ def test_orc_writer(datadir, tmpdir, reference_file, columns, compression):
else:
print(type(excpr).__name__)

expect = orcfile.read(columns=columns).to_pandas()
cudf.from_pandas(expect).to_orc(gdf_fname.strpath, compression=compression)
got = pa.orc.ORCFile(gdf_fname).read(columns=columns).to_pandas()
expect = cudf.from_pandas(orcfile.read(columns=columns).to_pandas())
expect.to_orc(gdf_fname.strpath, compression=compression)
got = cudf.from_pandas(
pa.orc.ORCFile(gdf_fname).read(columns=columns).to_pandas()
)

assert_eq(expect, got)
assert_frame_equal(expect, got)


@pytest.mark.parametrize("stats_freq", ["NONE", "STRIPE", "ROWGROUP"])
Expand All @@ -405,11 +408,11 @@ def test_orc_writer_statistics_frequency(datadir, tmpdir, stats_freq):
else:
print(type(excpr).__name__)

expect = orcfile.read().to_pandas()
cudf.from_pandas(expect).to_orc(gdf_fname.strpath, statistics=stats_freq)
got = pa.orc.ORCFile(gdf_fname).read().to_pandas()
expect = cudf.from_pandas(orcfile.read().to_pandas())
expect.to_orc(gdf_fname.strpath, statistics=stats_freq)
got = cudf.from_pandas(pa.orc.ORCFile(gdf_fname).read().to_pandas())

assert_eq(expect, got)
assert_frame_equal(expect, got)


@pytest.mark.parametrize("stats_freq", ["NONE", "STRIPE", "ROWGROUP"])
Expand Down Expand Up @@ -492,8 +495,7 @@ def test_chunked_orc_writer(
writer.close()

got = pa.orc.ORCFile(gdf_fname).read(columns=columns).to_pandas()

assert_eq(expect, got)
assert_frame_equal(cudf.from_pandas(expect), cudf.from_pandas(got))


@pytest.mark.parametrize(
Expand Down
8 changes: 4 additions & 4 deletions python/cudf/cudf/tests/test_parquet.py
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Expand Up @@ -1105,9 +1105,9 @@ def test_parquet_reader_list_large_multi_rowgroup_nulls(tmpdir):
assert_eq(expect, got)


@pytest.mark.parametrize("skip", range(0, 128))
@pytest.mark.parametrize("skip", [0, 1, 5, 10])
def test_parquet_reader_list_skiprows(skip, tmpdir):
num_rows = 128
num_rows = 10
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Here I reason that that if 0:10 work then 11:128 should too.

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@bdice bdice Feb 9, 2022 •
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Maybe even replace range(0, 10) with [0, 1, 5, 10]. Maybe even search the tests for the regex parametrize.*range. 🙃

src = pd.DataFrame(
{
"a": list_gen(int_gen, 0, num_rows, 80, 50),
Expand All @@ -1124,9 +1124,9 @@ def test_parquet_reader_list_skiprows(skip, tmpdir):
assert_eq(expect, got, check_dtype=False)


@pytest.mark.parametrize("skip", range(0, 120))
@pytest.mark.parametrize("skip", [0, 1, 5, 10])
def test_parquet_reader_list_num_rows(skip, tmpdir):
num_rows = 128
num_rows = 20
src = pd.DataFrame(
{
"a": list_gen(int_gen, 0, num_rows, 80, 50),
Expand Down
45 changes: 19 additions & 26 deletions python/cudf/cudf/tests/test_repr.py
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@@ -1,4 +1,4 @@
# Copyright (c) 2019-2021, NVIDIA CORPORATION.
# Copyright (c) 2019-2022, NVIDIA CORPORATION.

import textwrap

Expand All @@ -13,7 +13,14 @@
from cudf.testing import _utils as utils
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from cudf.utils.dtypes import np_dtypes_to_pandas_dtypes

repr_categories = utils.NUMERIC_TYPES + ["str", "category", "datetime64[ns]"]
repr_categories = [
"uint16",
"int64",
"float64",
"str",
"category",
"datetime64[ns]",
]


@pytest.mark.parametrize("dtype", repr_categories)
Expand Down Expand Up @@ -84,36 +91,22 @@ def test_full_series(nrows, dtype):
pd.reset_option("display.max_rows")


@pytest.mark.parametrize("nrows", [5, 10, 15])
@pytest.mark.parametrize("ncols", [5, 10, 15])
@pytest.mark.parametrize("size", [20, 21])
@pytest.mark.parametrize("dtype", repr_categories)
@pytest.mark.parametrize("nrows", [0, 1, 2, 9, 20 / 2, 11, 20 - 1, 20, 20 + 1])
@pytest.mark.parametrize("ncols", [0, 1, 2, 9, 20 / 2, 11, 20 - 1, 20, 20 + 1])
def test_full_dataframe_20(dtype, nrows, ncols):
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Can we just merge test_full_dataframe_20 & test_full_dataframe_21 by parametrizing size into one test and also with reduced parametrization of nrows & ncols?

size = 20
pdf = pd.DataFrame(
{idx: np.random.randint(0, 100, size) for idx in range(size)}
).astype(dtype)
gdf = cudf.from_pandas(pdf)

assert pdf.__repr__() == gdf.__repr__()
assert pdf._repr_html_() == gdf._repr_html_()
assert pdf._repr_latex_() == gdf._repr_latex_()


@pytest.mark.parametrize("dtype", repr_categories)
@pytest.mark.parametrize("nrows", [9, 21 / 2, 11, 21 - 1])
@pytest.mark.parametrize("ncols", [9, 21 / 2, 11, 21 - 1])
def test_full_dataframe_21(dtype, nrows, ncols):
size = 21
def test_full_dataframe_20(dtype, size, nrows, ncols):
pdf = pd.DataFrame(
{idx: np.random.randint(0, 100, size) for idx in range(size)}
).astype(dtype)
gdf = cudf.from_pandas(pdf)

pd.options.display.max_rows = int(nrows)
pd.options.display.max_columns = int(ncols)
assert pdf.__repr__() == gdf.__repr__()
pd.reset_option("display.max_rows")
pd.reset_option("display.max_columns")
with pd.option_context(
"display.max_rows", int(nrows), "display.max_columns", int(ncols)
):
assert repr(pdf) == repr(gdf)
assert pdf._repr_html_() == gdf._repr_html_()
assert pdf._repr_latex_() == gdf._repr_latex_()


@given(
Expand Down
8 changes: 4 additions & 4 deletions python/cudf/cudf/tests/test_reshape.py
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@@ -1,4 +1,4 @@
# Copyright (c) 2021, NVIDIA CORPORATION.
# Copyright (c) 2021-2022, NVIDIA CORPORATION.

import re

Expand All @@ -17,9 +17,9 @@
)
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@pytest.mark.parametrize("num_id_vars", [0, 1, 2, 10])
@pytest.mark.parametrize("num_value_vars", [0, 1, 2, 10])
@pytest.mark.parametrize("num_rows", [1, 2, 1000])
@pytest.mark.parametrize("num_id_vars", [0, 1, 2])
@pytest.mark.parametrize("num_value_vars", [0, 1, 2])
@pytest.mark.parametrize("num_rows", [1, 2, 100])
@pytest.mark.parametrize("dtype", NUMERIC_TYPES + DATETIME_TYPES)
@pytest.mark.parametrize("nulls", ["none", "some", "all"])
def test_melt(nulls, num_id_vars, num_value_vars, num_rows, dtype):
Expand Down
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