Skip to content

Collect tslibs test, organize PeriodIndex tests #19627

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.

Sign up for GitHub

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

Closed
wants to merge 10 commits into from
Closed

Collect tslibs test, organize PeriodIndex tests #19627

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
10 commits
Select commit Hold shift + click to select a range
afb3271
move test_parsing to tests.tslibs
jbrockmendel Feb 10, 2018
c2befed
move array_to_datetime and other tslib tests to test_tslib
jbrockmendel Feb 10, 2018
b1a7c57
move libfreqs and liboffsets tests to tests.tslibs
jbrockmendel Feb 10, 2018
0a7025c
move tslibs-specific tests from test_timezones
jbrockmendel Feb 10, 2018
8bc158f
move astype and shift_months tests to their appropriate spots
jbrockmendel Feb 10, 2018
6c68691
put astype test in the right place
jbrockmendel Feb 10, 2018
6ccc960
move non-Index tests to test_period_helper
jbrockmendel Feb 10, 2018
cfe771e
implement test_scalar_compat, move shift test
jbrockmendel Feb 10, 2018
471cbf0
fixup typo
jbrockmendel Feb 10, 2018
f73dc2b
two more test_shift tests
jbrockmendel Feb 10, 2018
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
15 changes: 15 additions & 0 deletions pandas/tests/indexes/datetimes/test_arithmetic.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -2,6 +2,7 @@
import warnings
from datetime import datetime, timedelta
import operator
from itertools import product

import pytest

Expand All @@ -15,6 +16,7 @@
DatetimeIndex, TimedeltaIndex,
date_range)
from pandas._libs import tslib
from pandas._libs.tslibs.offsets import shift_months


@pytest.fixture(params=[None, 'UTC', 'Asia/Tokyo',
Expand Down Expand Up @@ -933,3 +935,16 @@ def test_datetime64_with_DateOffset(klass, assert_func):
Timestamp('2000-02-29', tz='US/Central')], name='a')
assert_func(result, exp)
assert_func(result2, exp)


@pytest.mark.parametrize('years,months', product([-1, 0, 1], [-2, 0, 2]))
Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

If you parametrize years & months separately, pytest will handle the product

i.e. @pytest.mark.parametrize(('years',[-1, 0, 1]), ('months', [-2, 0, 2]))

def test_shift_months(years, months):
s = DatetimeIndex([Timestamp('2000-01-05 00:15:00'),
Timestamp('2000-01-31 00:23:00'),
Timestamp('2000-01-01'),
Timestamp('2000-02-29'),
Timestamp('2000-12-31')])
actual = DatetimeIndex(shift_months(s.asi8, years * 12 + months))
expected = DatetimeIndex([x + pd.offsets.DateOffset(
years=years, months=months) for x in s])
tm.assert_index_equal(actual, expected)
42 changes: 42 additions & 0 deletions pandas/tests/indexes/datetimes/test_astype.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -138,6 +138,48 @@ def test_astype_object(self):
tm.assert_index_equal(casted, Index(exp_values, dtype=np.object_))
assert casted.tolist() == exp_values

idx = pd.date_range(start='2013-01-01', periods=4, freq='M',
Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

can you avoid duplication of lots of code and just parameterize over the tz.

name='idx')
expected_list = [Timestamp('2013-01-31'),
Timestamp('2013-02-28'),
Timestamp('2013-03-31'),
Timestamp('2013-04-30')]
expected = pd.Index(expected_list, dtype=object, name='idx')
result = idx.astype(object)
assert isinstance(result, Index)

assert result.dtype == object
tm.assert_index_equal(result, expected)
assert result.name == expected.name
assert idx.tolist() == expected_list

idx = pd.date_range(start='2013-01-01', periods=4, freq='M',
name='idx', tz='Asia/Tokyo')
expected_list = [Timestamp('2013-01-31', tz='Asia/Tokyo'),
Timestamp('2013-02-28', tz='Asia/Tokyo'),
Timestamp('2013-03-31', tz='Asia/Tokyo'),
Timestamp('2013-04-30', tz='Asia/Tokyo')]
expected = pd.Index(expected_list, dtype=object, name='idx')
result = idx.astype(object)
assert isinstance(result, Index)
assert result.dtype == object
tm.assert_index_equal(result, expected)
assert result.name == expected.name
assert idx.tolist() == expected_list

idx = DatetimeIndex([datetime(2013, 1, 1), datetime(2013, 1, 2),
pd.NaT, datetime(2013, 1, 4)], name='idx')
expected_list = [Timestamp('2013-01-01'),
Timestamp('2013-01-02'), pd.NaT,
Timestamp('2013-01-04')]
expected = pd.Index(expected_list, dtype=object, name='idx')
result = idx.astype(object)
assert isinstance(result, Index)
assert result.dtype == object
tm.assert_index_equal(result, expected)
assert result.name == expected.name
assert idx.tolist() == expected_list

@pytest.mark.parametrize('dtype', [
float, 'timedelta64', 'timedelta64[ns]', 'datetime64',
'datetime64[D]'])
Expand Down
58 changes: 0 additions & 58 deletions pandas/tests/indexes/datetimes/test_ops.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -5,10 +5,8 @@
import numpy as np
from datetime import datetime

from itertools import product
import pandas as pd
import pandas._libs.tslib as tslib
from pandas._libs.tslibs.offsets import shift_months
import pandas.util.testing as tm
from pandas import (DatetimeIndex, PeriodIndex, Series, Timestamp,
date_range, _np_version_under1p10, Index,
Expand Down Expand Up @@ -51,49 +49,6 @@ def test_ops_properties_basic(self):
assert s.day == 10
pytest.raises(AttributeError, lambda: s.weekday)

def test_astype_object(self):
idx = pd.date_range(start='2013-01-01', periods=4, freq='M',
name='idx')
expected_list = [Timestamp('2013-01-31'),
Timestamp('2013-02-28'),
Timestamp('2013-03-31'),
Timestamp('2013-04-30')]
expected = pd.Index(expected_list, dtype=object, name='idx')
result = idx.astype(object)
assert isinstance(result, Index)

assert result.dtype == object
tm.assert_index_equal(result, expected)
assert result.name == expected.name
assert idx.tolist() == expected_list

idx = pd.date_range(start='2013-01-01', periods=4, freq='M',
name='idx', tz='Asia/Tokyo')
expected_list = [Timestamp('2013-01-31', tz='Asia/Tokyo'),
Timestamp('2013-02-28', tz='Asia/Tokyo'),
Timestamp('2013-03-31', tz='Asia/Tokyo'),
Timestamp('2013-04-30', tz='Asia/Tokyo')]
expected = pd.Index(expected_list, dtype=object, name='idx')
result = idx.astype(object)
assert isinstance(result, Index)
assert result.dtype == object
tm.assert_index_equal(result, expected)
assert result.name == expected.name
assert idx.tolist() == expected_list

idx = DatetimeIndex([datetime(2013, 1, 1), datetime(2013, 1, 2),
pd.NaT, datetime(2013, 1, 4)], name='idx')
expected_list = [Timestamp('2013-01-01'),
Timestamp('2013-01-02'), pd.NaT,
Timestamp('2013-01-04')]
expected = pd.Index(expected_list, dtype=object, name='idx')
result = idx.astype(object)
assert isinstance(result, Index)
assert result.dtype == object
tm.assert_index_equal(result, expected)
assert result.name == expected.name
assert idx.tolist() == expected_list

def test_minmax(self):
for tz in self.tz:
# monotonic
Expand Down Expand Up @@ -568,19 +523,6 @@ def test_equals(self):
assert not idx.equals(pd.Series(idx3))


@pytest.mark.parametrize('years,months', product([-1, 0, 1], [-2, 0, 2]))
def test_shift_months(years, months):
s = DatetimeIndex([Timestamp('2000-01-05 00:15:00'),
Timestamp('2000-01-31 00:23:00'),
Timestamp('2000-01-01'),
Timestamp('2000-02-29'),
Timestamp('2000-12-31')])
actual = DatetimeIndex(shift_months(s.asi8, years * 12 + months))
expected = DatetimeIndex([x + pd.offsets.DateOffset(
years=years, months=months) for x in s])
tm.assert_index_equal(actual, expected)


class TestBusinessDatetimeIndex(object):

def setup_method(self, method):
Expand Down
196 changes: 20 additions & 176 deletions pandas/tests/indexes/datetimes/test_tools.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -8,7 +8,7 @@
import dateutil
import numpy as np
from dateutil.parser import parse
from datetime import datetime, date, time
from datetime import datetime, time
from distutils.version import LooseVersion

import pandas as pd
Expand All @@ -19,7 +19,6 @@

from pandas.errors import OutOfBoundsDatetime
from pandas.compat import lmap
from pandas.compat.numpy import np_array_datetime64_compat
from pandas.core.dtypes.common import is_datetime64_ns_dtype
from pandas.util import testing as tm
import pandas.util._test_decorators as td
Expand Down Expand Up @@ -1445,182 +1444,15 @@ def test_parsers_timezone_minute_offsets_roundtrip(self, cache):
converted_time = dt_time.tz_localize('UTC').tz_convert(tz)
assert dt_string_repr == repr(converted_time)

def test_parsers_iso8601(self):
# GH 12060
# test only the iso parser - flexibility to different
# separators and leadings 0s
# Timestamp construction falls back to dateutil
cases = {'2011-01-02': datetime(2011, 1, 2),
'2011-1-2': datetime(2011, 1, 2),
'2011-01': datetime(2011, 1, 1),
'2011-1': datetime(2011, 1, 1),
'2011 01 02': datetime(2011, 1, 2),
'2011.01.02': datetime(2011, 1, 2),
'2011/01/02': datetime(2011, 1, 2),
'2011\\01\\02': datetime(2011, 1, 2),
'2013-01-01 05:30:00': datetime(2013, 1, 1, 5, 30),
'2013-1-1 5:30:00': datetime(2013, 1, 1, 5, 30)}
for date_str, exp in compat.iteritems(cases):
actual = tslib._test_parse_iso8601(date_str)
assert actual == exp

# separators must all match - YYYYMM not valid
invalid_cases = ['2011-01/02', '2011^11^11',
'201401', '201111', '200101',
# mixed separated and unseparated
'2005-0101', '200501-01',
'20010101 12:3456', '20010101 1234:56',
# HHMMSS must have two digits in each component
# if unseparated
'20010101 1', '20010101 123', '20010101 12345',
'20010101 12345Z',
# wrong separator for HHMMSS
'2001-01-01 12-34-56']
for date_str in invalid_cases:
with pytest.raises(ValueError):
tslib._test_parse_iso8601(date_str)
# If no ValueError raised, let me know which case failed.
raise Exception(date_str)


class TestArrayToDatetime(object):
def test_parsing_valid_dates(self):
arr = np.array(['01-01-2013', '01-02-2013'], dtype=object)
tm.assert_numpy_array_equal(
tslib.array_to_datetime(arr),
np_array_datetime64_compat(
[
'2013-01-01T00:00:00.000000000-0000',
'2013-01-02T00:00:00.000000000-0000'
],
dtype='M8[ns]'
)
)

arr = np.array(['Mon Sep 16 2013', 'Tue Sep 17 2013'], dtype=object)
tm.assert_numpy_array_equal(
tslib.array_to_datetime(arr),
np_array_datetime64_compat(
[
'2013-09-16T00:00:00.000000000-0000',
'2013-09-17T00:00:00.000000000-0000'
],
dtype='M8[ns]'
)
)

def test_parsing_timezone_offsets(self):
# All of these datetime strings with offsets are equivalent
# to the same datetime after the timezone offset is added
dt_strings = [
'01-01-2013 08:00:00+08:00',
'2013-01-01T08:00:00.000000000+0800',
'2012-12-31T16:00:00.000000000-0800',
'12-31-2012 23:00:00-01:00'
]

expected_output = tslib.array_to_datetime(np.array(
['01-01-2013 00:00:00'], dtype=object))

for dt_string in dt_strings:
tm.assert_numpy_array_equal(
tslib.array_to_datetime(
np.array([dt_string], dtype=object)
),
expected_output
)

def test_number_looking_strings_not_into_datetime(self):
# #4601
# These strings don't look like datetimes so they shouldn't be
# attempted to be converted
arr = np.array(['-352.737091', '183.575577'], dtype=object)
tm.assert_numpy_array_equal(
tslib.array_to_datetime(arr, errors='ignore'), arr)

arr = np.array(['1', '2', '3', '4', '5'], dtype=object)
tm.assert_numpy_array_equal(
tslib.array_to_datetime(arr, errors='ignore'), arr)

def test_coercing_dates_outside_of_datetime64_ns_bounds(self):
invalid_dates = [
date(1000, 1, 1),
datetime(1000, 1, 1),
'1000-01-01',
'Jan 1, 1000',
np.datetime64('1000-01-01'),
]

for invalid_date in invalid_dates:
pytest.raises(ValueError,
tslib.array_to_datetime,
np.array([invalid_date], dtype='object'),
errors='raise', )
tm.assert_numpy_array_equal(
tslib.array_to_datetime(
np.array([invalid_date], dtype='object'),
errors='coerce'),
np.array([tslib.iNaT], dtype='M8[ns]')
)

arr = np.array(['1/1/1000', '1/1/2000'], dtype=object)
tm.assert_numpy_array_equal(
tslib.array_to_datetime(arr, errors='coerce'),
np_array_datetime64_compat(
[
tslib.iNaT,
'2000-01-01T00:00:00.000000000-0000'
],
dtype='M8[ns]'
)
)

def test_coerce_of_invalid_datetimes(self):
arr = np.array(['01-01-2013', 'not_a_date', '1'], dtype=object)
def test_to_datetime_barely_out_of_bounds(self):
# GH#19529
# GH#19382 close enough to bounds that dropping nanos would result
# in an in-bounds datetime
arr = np.array(['2262-04-11 23:47:16.854775808'], dtype=object)

# Without coercing, the presence of any invalid dates prevents
# any values from being converted
tm.assert_numpy_array_equal(
tslib.array_to_datetime(arr, errors='ignore'), arr)

# With coercing, the invalid dates becomes iNaT
tm.assert_numpy_array_equal(
tslib.array_to_datetime(arr, errors='coerce'),
np_array_datetime64_compat(
[
'2013-01-01T00:00:00.000000000-0000',
tslib.iNaT,
tslib.iNaT
],
dtype='M8[ns]'
)
)

def test_to_datetime_barely_out_of_bounds(self):
# GH#19529
# GH#19382 close enough to bounds that dropping nanos would result
# in an in-bounds datetime
arr = np.array(['2262-04-11 23:47:16.854775808'], dtype=object)

with pytest.raises(OutOfBoundsDatetime):
to_datetime(arr)

with pytest.raises(OutOfBoundsDatetime):
# Essentially the same as above, but more directly calling
# the relevant function
tslib.array_to_datetime(arr)


def test_normalize_date():
value = date(2012, 9, 7)

result = tslib.normalize_date(value)
assert (result == datetime(2012, 9, 7))

value = datetime(2012, 9, 7, 12)

result = tslib.normalize_date(value)
assert (result == datetime(2012, 9, 7))
with pytest.raises(OutOfBoundsDatetime):
to_datetime(arr)


@pytest.fixture(params=['D', 's', 'ms', 'us', 'ns'])
Expand Down Expand Up @@ -1745,3 +1577,15 @@ def test_processing_order(self):
result = pd.to_datetime(300 * 365, unit='D', origin='1870-01-01')
expected = Timestamp('2169-10-20 00:00:00')
assert result == expected


def test_to_datetime1():
actual = pd.to_datetime(datetime(2008, 1, 15))
Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

can you add a refernce for this test (e.g. what is it testing)

can you put it near other tests that are similar

assert actual == datetime(2008, 1, 15)

actual = pd.to_datetime('20080115')
assert actual == datetime(2008, 1, 15)

# unparseable
s = 'Month 1, 1999'
assert pd.to_datetime(s, errors='ignore') == s
Loading