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TST: Use multiple instances of parametrize instead of product in tests #21602

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Jun 23, 2018
Merged

TST: Use multiple instances of parametrize instead of product in tests #21602

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14 changes: 7 additions & 7 deletions pandas/tests/dtypes/test_dtypes.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2,8 +2,6 @@
import re
import pytest

from itertools import product

import numpy as np
import pandas as pd
from pandas import (
Expand Down Expand Up @@ -233,12 +231,14 @@ def test_dst(self):
assert is_datetimetz(s2)
assert s1.dtype == s2.dtype

def test_parser(self):
@pytest.mark.parametrize('tz', ['UTC', 'US/Eastern'])
@pytest.mark.parametrize('constructor', ['M8', 'datetime64'])
def test_parser(self, tz, constructor):
# pr #11245
for tz, constructor in product(('UTC', 'US/Eastern'),
('M8', 'datetime64')):
assert (DatetimeTZDtype('%s[ns, %s]' % (constructor, tz)) ==
DatetimeTZDtype('ns', tz))
dtz_str = '{con}[ns, {tz}]'.format(con=constructor, tz=tz)
result = DatetimeTZDtype(dtz_str)
expected = DatetimeTZDtype('ns', tz)
assert result == expected

def test_empty(self):
dt = DatetimeTZDtype()
Expand Down
124 changes: 63 additions & 61 deletions pandas/tests/frame/test_rank.py
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Original file line number Diff line number Diff line change
Expand Up @@ -10,7 +10,6 @@
from pandas.util.testing import assert_frame_equal
from pandas.tests.frame.common import TestData
from pandas import Series, DataFrame
from pandas.compat import product


class TestRank(TestData):
Expand All @@ -26,6 +25,13 @@ class TestRank(TestData):
'dense': np.array([1, 3, 4, 2, nan, 2, 1, 5, nan, 3]),
}

@pytest.fixture(params=['average', 'min', 'max', 'first', 'dense'])
def method(self, request):
"""
Fixture for trying all rank methods
"""
return request.param

def test_rank(self):
rankdata = pytest.importorskip('scipy.stats.rankdata')

Expand Down Expand Up @@ -217,34 +223,35 @@ def test_rank_methods_frame(self):
expected = expected.astype('float64')
tm.assert_frame_equal(result, expected)

def test_rank_descending(self):
dtypes = ['O', 'f8', 'i8']
@pytest.mark.parametrize('dtype', ['O', 'f8', 'i8'])
def test_rank_descending(self, method, dtype):

for dtype, method in product(dtypes, self.results):
if 'i' in dtype:
df = self.df.dropna()
else:
df = self.df.astype(dtype)
if 'i' in dtype:
df = self.df.dropna()
else:
df = self.df.astype(dtype)

res = df.rank(ascending=False)
expected = (df.max() - df).rank()
assert_frame_equal(res, expected)
res = df.rank(ascending=False)
expected = (df.max() - df).rank()
assert_frame_equal(res, expected)

if method == 'first' and dtype == 'O':
continue
if method == 'first' and dtype == 'O':
return

expected = (df.max() - df).rank(method=method)
expected = (df.max() - df).rank(method=method)

if dtype != 'O':
res2 = df.rank(method=method, ascending=False,
numeric_only=True)
assert_frame_equal(res2, expected)
if dtype != 'O':
res2 = df.rank(method=method, ascending=False,
numeric_only=True)
assert_frame_equal(res2, expected)

res3 = df.rank(method=method, ascending=False,
numeric_only=False)
assert_frame_equal(res3, expected)
res3 = df.rank(method=method, ascending=False,
numeric_only=False)
assert_frame_equal(res3, expected)

def test_rank_2d_tie_methods(self):
@pytest.mark.parametrize('axis', [0, 1])
@pytest.mark.parametrize('dtype', [None, object])
def test_rank_2d_tie_methods(self, method, axis, dtype):
df = self.df

def _check2d(df, expected, method='average', axis=0):
Expand All @@ -257,43 +264,38 @@ def _check2d(df, expected, method='average', axis=0):
result = df.rank(method=method, axis=axis)
assert_frame_equal(result, exp_df)

dtypes = [None, object]
disabled = set([(object, 'first')])
results = self.results

for method, axis, dtype in product(results, [0, 1], dtypes):
if (dtype, method) in disabled:
continue
frame = df if dtype is None else df.astype(dtype)
_check2d(frame, results[method], method=method, axis=axis)


@pytest.mark.parametrize(
"method,exp", [("dense",
[[1., 1., 1.],
[1., 0.5, 2. / 3],
[1., 0.5, 1. / 3]]),
("min",
[[1. / 3, 1., 1.],
[1. / 3, 1. / 3, 2. / 3],
[1. / 3, 1. / 3, 1. / 3]]),
("max",
[[1., 1., 1.],
[1., 2. / 3, 2. / 3],
[1., 2. / 3, 1. / 3]]),
("average",
[[2. / 3, 1., 1.],
[2. / 3, 0.5, 2. / 3],
[2. / 3, 0.5, 1. / 3]]),
("first",
[[1. / 3, 1., 1.],
[2. / 3, 1. / 3, 2. / 3],
[3. / 3, 2. / 3, 1. / 3]])])
def test_rank_pct_true(method, exp):
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This test was the only one in that was outside the class, which seemed a bit strange, so I moved it inside the class.

# see gh-15630.

df = DataFrame([[2012, 66, 3], [2012, 65, 2], [2012, 65, 1]])
result = df.rank(method=method, pct=True)

expected = DataFrame(exp)
tm.assert_frame_equal(result, expected)
if (dtype, method) in disabled:
return
frame = df if dtype is None else df.astype(dtype)
_check2d(frame, self.results[method], method=method, axis=axis)

@pytest.mark.parametrize(
"method,exp", [("dense",
[[1., 1., 1.],
[1., 0.5, 2. / 3],
[1., 0.5, 1. / 3]]),
("min",
[[1. / 3, 1., 1.],
[1. / 3, 1. / 3, 2. / 3],
[1. / 3, 1. / 3, 1. / 3]]),
("max",
[[1., 1., 1.],
[1., 2. / 3, 2. / 3],
[1., 2. / 3, 1. / 3]]),
("average",
[[2. / 3, 1., 1.],
[2. / 3, 0.5, 2. / 3],
[2. / 3, 0.5, 1. / 3]]),
("first",
[[1. / 3, 1., 1.],
[2. / 3, 1. / 3, 2. / 3],
[3. / 3, 2. / 3, 1. / 3]])])
def test_rank_pct_true(self, method, exp):
# see gh-15630.

df = DataFrame([[2012, 66, 3], [2012, 65, 2], [2012, 65, 1]])
result = df.rank(method=method, pct=True)

expected = DataFrame(exp)
tm.assert_frame_equal(result, expected)
7 changes: 4 additions & 3 deletions pandas/tests/groupby/test_function.py
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Expand Up @@ -778,9 +778,10 @@ def test_frame_describe_unstacked_format():
# nunique
# --------------------------------

@pytest.mark.parametrize("n, m", cart_product(10 ** np.arange(2, 6),
(10, 100, 1000)))
@pytest.mark.parametrize("sort, dropna", cart_product((False, True), repeat=2))
@pytest.mark.parametrize('n', 10 ** np.arange(2, 6))
@pytest.mark.parametrize('m', [10, 100, 1000])
@pytest.mark.parametrize('sort', [False, True])
@pytest.mark.parametrize('dropna', [False, True])
def test_series_groupby_nunique(n, m, sort, dropna):

def check_nunique(df, keys, as_index=True):
Expand Down
12 changes: 5 additions & 7 deletions pandas/tests/groupby/test_whitelist.py
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Original file line number Diff line number Diff line change
Expand Up @@ -8,7 +8,6 @@
import numpy as np
from pandas import DataFrame, Series, compat, date_range, Index, MultiIndex
from pandas.util import testing as tm
from pandas.compat import lrange, product

AGG_FUNCTIONS = ['sum', 'prod', 'min', 'max', 'median', 'mean', 'skew',
'mad', 'std', 'var', 'sem']
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this should be a fixture (future PR)

Expand Down Expand Up @@ -175,12 +174,11 @@ def raw_frame():
return raw_frame


@pytest.mark.parametrize(
"op, level, axis, skipna, sort",
product(AGG_FUNCTIONS,
lrange(2), lrange(2),
[True, False],
[True, False]))
@pytest.mark.parametrize('op', AGG_FUNCTIONS)
@pytest.mark.parametrize('level', [0, 1])
@pytest.mark.parametrize('axis', [0, 1])
@pytest.mark.parametrize('skipna', [True, False])
@pytest.mark.parametrize('sort', [True, False])
def test_regression_whitelist_methods(
raw_frame, op, level,
axis, skipna, sort):
Expand Down
11 changes: 6 additions & 5 deletions pandas/tests/reshape/test_concat.py
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Original file line number Diff line number Diff line change
@@ -1,5 +1,5 @@
from warnings import catch_warnings
from itertools import combinations, product
from itertools import combinations

import datetime as dt
import dateutil
Expand Down Expand Up @@ -941,10 +941,11 @@ def test_append_different_columns_types(self, df_columns, series_index):
columns=combined_columns)
assert_frame_equal(result, expected)

@pytest.mark.parametrize(
"index_can_append, index_cannot_append_with_other",
product(indexes_can_append, indexes_cannot_append_with_other),
ids=lambda x: x.__class__.__name__)
@pytest.mark.parametrize('index_can_append', indexes_can_append,
ids=lambda x: x.__class__.__name__)
@pytest.mark.parametrize('index_cannot_append_with_other',
indexes_cannot_append_with_other,
ids=lambda x: x.__class__.__name__)
def test_append_different_columns_types_raises(
self, index_can_append, index_cannot_append_with_other):
# GH18359
Expand Down
20 changes: 9 additions & 11 deletions pandas/tests/sparse/series/test_series.py
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Original file line number Diff line number Diff line change
Expand Up @@ -23,8 +23,6 @@
from pandas.core.sparse.api import SparseSeries
from pandas.tests.series.test_api import SharedWithSparse

from itertools import product


def _test_data1():
# nan-based
Expand Down Expand Up @@ -985,16 +983,16 @@ def test_combine_first(self):
tm.assert_sp_series_equal(result, result2)
tm.assert_sp_series_equal(result, expected)

@pytest.mark.parametrize('deep,fill_values', [([True, False],
[0, 1, np.nan, None])])
def test_memory_usage_deep(self, deep, fill_values):
for deep, fill_value in product(deep, fill_values):
sparse_series = SparseSeries(fill_values, fill_value=fill_value)
dense_series = Series(fill_values)
sparse_usage = sparse_series.memory_usage(deep=deep)
dense_usage = dense_series.memory_usage(deep=deep)
@pytest.mark.parametrize('deep', [True, False])
@pytest.mark.parametrize('fill_value', [0, 1, np.nan, None])
def test_memory_usage_deep(self, deep, fill_value):
values = [0, 1, np.nan, None]
sparse_series = SparseSeries(values, fill_value=fill_value)
dense_series = Series(values)
sparse_usage = sparse_series.memory_usage(deep=deep)
dense_usage = dense_series.memory_usage(deep=deep)

assert sparse_usage < dense_usage
assert sparse_usage < dense_usage


class TestSparseHandlingMultiIndexes(object):
Expand Down
80 changes: 40 additions & 40 deletions pandas/tests/test_multilevel.py
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Original file line number Diff line number Diff line change
Expand Up @@ -20,6 +20,9 @@
import pandas as pd
import pandas._libs.index as _index

AGG_FUNCTIONS = ['sum', 'prod', 'min', 'max', 'median', 'mean', 'skew', 'mad',
'std', 'var', 'sem']


class Base(object):

Expand Down Expand Up @@ -1389,60 +1392,57 @@ def test_count(self):
pytest.raises(KeyError, series.count, 'x')
pytest.raises(KeyError, frame.count, level='x')

AGG_FUNCTIONS = ['sum', 'prod', 'min', 'max', 'median', 'mean', 'skew',
'mad', 'std', 'var', 'sem']

@pytest.mark.parametrize('op', AGG_FUNCTIONS)
@pytest.mark.parametrize('level', [0, 1])
@pytest.mark.parametrize('skipna', [True, False])
@pytest.mark.parametrize('sort', [True, False])
def test_series_group_min_max(self, sort):
def test_series_group_min_max(self, op, level, skipna, sort):
# GH 17537
for op, level, skipna in cart_product(self.AGG_FUNCTIONS, lrange(2),
[False, True]):
grouped = self.series.groupby(level=level, sort=sort)
aggf = lambda x: getattr(x, op)(skipna=skipna)
# skipna=True
leftside = grouped.agg(aggf)
rightside = getattr(self.series, op)(level=level, skipna=skipna)
if sort:
rightside = rightside.sort_index(level=level)
tm.assert_series_equal(leftside, rightside)

grouped = self.series.groupby(level=level, sort=sort)
# skipna=True
leftside = grouped.agg(lambda x: getattr(x, op)(skipna=skipna))
rightside = getattr(self.series, op)(level=level, skipna=skipna)
if sort:
rightside = rightside.sort_index(level=level)
tm.assert_series_equal(leftside, rightside)

@pytest.mark.parametrize('op', AGG_FUNCTIONS)
@pytest.mark.parametrize('level', [0, 1])
@pytest.mark.parametrize('axis', [0, 1])
@pytest.mark.parametrize('skipna', [True, False])
@pytest.mark.parametrize('sort', [True, False])
def test_frame_group_ops(self, sort):
def test_frame_group_ops(self, op, level, axis, skipna, sort):
# GH 17537
self.frame.iloc[1, [1, 2]] = np.nan
self.frame.iloc[7, [0, 1]] = np.nan

for op, level, axis, skipna in cart_product(self.AGG_FUNCTIONS,
lrange(2), lrange(2),
[False, True]):

if axis == 0:
frame = self.frame
else:
frame = self.frame.T
if axis == 0:
frame = self.frame
else:
frame = self.frame.T

grouped = frame.groupby(level=level, axis=axis, sort=sort)
grouped = frame.groupby(level=level, axis=axis, sort=sort)

pieces = []
pieces = []

def aggf(x):
pieces.append(x)
return getattr(x, op)(skipna=skipna, axis=axis)
def aggf(x):
pieces.append(x)
return getattr(x, op)(skipna=skipna, axis=axis)

leftside = grouped.agg(aggf)
rightside = getattr(frame, op)(level=level, axis=axis,
skipna=skipna)
if sort:
rightside = rightside.sort_index(level=level, axis=axis)
frame = frame.sort_index(level=level, axis=axis)
leftside = grouped.agg(aggf)
rightside = getattr(frame, op)(level=level, axis=axis,
skipna=skipna)
if sort:
rightside = rightside.sort_index(level=level, axis=axis)
frame = frame.sort_index(level=level, axis=axis)

# for good measure, groupby detail
level_index = frame._get_axis(axis).levels[level]
# for good measure, groupby detail
level_index = frame._get_axis(axis).levels[level]

tm.assert_index_equal(leftside._get_axis(axis), level_index)
tm.assert_index_equal(rightside._get_axis(axis), level_index)
tm.assert_index_equal(leftside._get_axis(axis), level_index)
tm.assert_index_equal(rightside._get_axis(axis), level_index)

tm.assert_frame_equal(leftside, rightside)
tm.assert_frame_equal(leftside, rightside)

def test_stat_op_corner(self):
obj = Series([10.0], index=MultiIndex.from_tuples([(2, 3)]))
Expand Down
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