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DiegoAlbertoTorres opened this issue May 28, 2020 · 11 comments
Open
24 of 32 tasks

TRACKER: milestones #44

DiegoAlbertoTorres opened this issue May 28, 2020 · 11 comments

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@DiegoAlbertoTorres
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DiegoAlbertoTorres commented May 28, 2020 •
edited by jreback
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In order in which we should tackle them:
@jreback
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jreback commented Jun 3, 2020

@jreback
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jreback commented Aug 13, 2020

@mroeschke added 14. above, but i think should be straightforward, if you can work on this when you have a chance.

@RhysU
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RhysU commented Aug 19, 2020

@mroeschke, below please find some sample code that can be used to exercise pandas-dev#35690. Apologies for the inline-- couldn't get an attachment up on this tracker even applying some obvious trickery. Stick this into, say, foo.py and run with python -m unittest foo.py -v:

## Implementation file
import datetime
import numbers
import typing

import pandas as pd


T = typing.TypeVar("T")
U = typing.TypeVar("U")


def half_open(df: T, start: typing.Optional[U], stop: typing.Optional[U]) -> T:
    """
    Return the portion of df within the half-open interval [start, stop).

    See half_open_slice(...) for how DatetimeIndex-related slicing is handled.
    """
    # Multiple lines to make stack traces more informative
    slyce = half_open_slice(df=df, s=slice(start, stop, None))
    subset = df[slyce]
    return subset


# The following is an altogether unpleasant function hiding many gotchas
# See https://github.com/pandas-dev/pandas/issues/35690 for some dragons
def half_open_slice(df: typing.Union[pd.DataFrame, pd.Series], s: slice) -> slice:
    """
    Return slice(start, stop, step) matching [s.start, s.stop) within df.

    When the DataFrame has a DatetimeIndex-like index with non-None tzinfo,
    this routine infers the UTC timezone for any slice start or stop
    value that lacks tzinfo entirely or that has tzinfo is None.
    This UTC-inference allows pre-1.0 Pandas logic to work unchanged post-1.0.
    """
    # Check incoming df then grab the index for brevity
    assert isinstance(df, pd.DataFrame) or isinstance(df, pd.Series), type(df)
    index = df.index

    # Unpack incoming s for brevity and retain original s in local variables
    assert isinstance(s, slice), type(s)
    start, stop, step = s.start, s.stop, s.step

    # Additional start/stop coercion for only DatetimeIndex-like indices
    # Use Timestamps due to https://github.com/pandas-dev/pandas/issues/35690
    # TODO After #35690 fixed, converting start/stop to Timestamp may not be needed
    attr_tz = "tzinfo"
    if hasattr(index, attr_tz):
        # Below, calls to pd.Timestamp(...) surprisingly interpret integers.
        # Refuse ambiguous requests to reduce likelihood for surprising bugs.
        if isinstance(start, numbers.Number) or isinstance(stop, numbers.Number):
            raise TypeError(
                f"{type(start)}, {type(stop)} prohibited: {start}, {stop}."
                f' Strings like "20200817" can succinctly express dates.'
                f" Supply pandas.Timestamps to express fine-grained times like"
                f" Timestamp('1970-01-01 00:00:00.020200817+0000', tz='UTC')."
            )
        index_has_tz = index.tzinfo is not None
        infer_start = index_has_tz and getattr(start, attr_tz, None) is None
        infer_stop = index_has_tz and getattr(stop, attr_tz, None) is None
        if start is not None:
            start = pd.Timestamp(
                start, tz=datetime.timezone.utc if infer_start else None
            )
        if stop is not None:
            stop = pd.Timestamp(stop, tz=datetime.timezone.utc if infer_stop else None)

    # Convert start to Optional[int]-valued index location start_idx
    # Clipping sidesteps https://github.com/pandas-dev/pandas/issues/35690
    # When below index.min() return 0 as if index.get_slice_bound(...) ran
    # TODO After #35690 fixed, may not need start < index.min() clause.
    # TODO After #35690 fixed, may not need start > index.max() clause.
    if start is None:
        start_idx = None
    elif start < index.min():
        start_idx = 0
    elif start > index.max():  # TODO Branch not unit tested below
        start_idx = len(df)
    else:
        start_idx = index.get_slice_bound(start, side="left", kind="ix")

    # Convert stop to Optional[int]-valued index location stop_idx
    # Clipping sidesteps https://github.com/pandas-dev/pandas/issues/35690
    # When above index.max() return len as if index.get_slice_bound(...) ran
    # TODO After #35690 fixed, may not need stop < index.min() clause.
    # TODO After #35690 fixed, may not need stop > index.max() clause.
    if stop is None:
        stop_idx = None
    elif stop < index.min():  # TODO Branch not unit tested below
        stop_idx = 0
    elif stop > index.max():
        stop_idx = len(df)
    else:
        stop_idx = index.get_slice_bound(stop, side="left", kind="ix")

    # Return the requested half-open slice
    return slice(start_idx, stop_idx, step)


## Test file
import datetime
import unittest
import typing

import numpy as np
import numpy.testing as npt
import pandas as pd
import pandas.util.testing as put  # Later, pandas.testing!
import pytz


# MAINTAINERS:
#
#   First, understand the contract implied by TZ_PAIRS_ACCEPTED/REJECTED.
#   Second, make the routine test_series_with_datetimeindex_accepted pass.
#   If that is not working, say after a Pandas upgrade, nothing else will.
#   After that, proceed down the file in the order tests are written.
#
# Beefy coverage due to https://github.com/pandas-dev/pandas/issues/35690
class HalfOpen(unittest.TestCase):
    """Test half_open(...) and half_open_slice(...)."""

    # Which pairs of timezones should run to completion without raising?
    # "Europe/Amsterdam" is a stand-in for something very different from UTC.
    # "Etc/Greenwich" is chosen as tzinfos UTC != Greenwich but times align.
    # In particular, times aligning eases reusing the same tests/assertions.
    TZ_PAIRS_ACCEPTED = (
        # No timezone information in either the Pandas Index or slicing
        (None, None),
        # UTC information in both the Index and slicing
        ("UTC", "utc"),
        # Something other than UTC in both spots
        ("Europe/Amsterdam", "Europe/Amsterdam"),
        # UTC in the Pandas Index and None slicing implies UTC slicing
        ("utc", None),
        # Two different timezones with UTC on the DatetimeIndex
        ("UTC", "Etc/Greenwich"),
        # Two different timezones with Greenwich on the DatetimeIndex
        ("Etc/Greenwich", "utc"),
        # Greenwich in the Pandas Index and None slicing implies UTC slicing
        ("Etc/Greenwich", None),
    )

    # Which pairs of timezones should be confirmed as raising errors?
    TZ_PAIRS_REJECTED = (
        # No timezone on the Pandas index but UTC slicing
        (None, "utc"),
        # No timezone on the Pandas index but Amsterdam slicing
        (None, "Europe/Amsterdam"),
        # No timezone on the Pandas index but Greenwich slicing
        (None, "Etc/Greenwich"),
    )

    def series_with_datetimeindex(self, index_tz: str) -> pd.DataFrame:
        """Construct Series with multiple entries per index Timestamp."""
        # Construct sample with multiple entries per index Timestamp
        # Then defensively confirm construction is as expected.
        s = pd.concat(
            [
                put.makeTimeSeries(nper=10, freq="B"),
                put.makeTimeSeries(nper=10, freq="B"),
            ]
        ).sort_index()
        s = self.localize(s, index_tz)
        self.assertEqual(s.index[+0], pd.Timestamp("2000-01-03", tz=index_tz))
        self.assertEqual(s.index[-1], pd.Timestamp("2000-01-14", tz=index_tz))
        return s

    def localize(self, df, tz):
        """Ensure DataFrame or Series is appropriately tz-localized."""
        self.assertIsNone(df.index.tzinfo)
        if tz is not None:
            self.assertIsInstance(tz, str)
            df = df.tz_localize(tz)
            self.assertEqual(df.index.tzinfo, pytz.timezone(tz))
        return df

    def test_series_with_datetimeindex_accepted(self):
        """Confirm [start, stop) successfully slices a Series."""
        for index_tz, tz in self.TZ_PAIRS_ACCEPTED:
            with self.subTest(index_tz=index_tz, tz=tz):
                # Prepare the sample Series
                s = self.series_with_datetimeindex(index_tz=index_tz)

                # Degenerate slices retrieve all information
                a1 = half_open(s, start=None, stop=None)
                a2 = half_open(
                    s, start=pd.Timestamp("1970-01-01", tz=tz), stop=None
                )
                a3 = half_open(
                    s, start=None, stop=pd.Timestamp("2038-01-01", tz=tz)
                )
                a4 = half_open(
                    s,
                    start=pd.Timestamp("1970-01-01", tz=tz),
                    stop=pd.Timestamp("2038-01-01", tz=tz),
                )
                put.assert_series_equal(a1, s)
                put.assert_series_equal(a2, s)
                put.assert_series_equal(a3, s)
                put.assert_series_equal(a4, s)

                # Degenerate slices retrieve no information
                # TODO Test start > s.index.max()
                # TODO Test stop < s.index.min()

                # Half-open with left boundary both finite and internal
                b = half_open(
                    s, start=pd.Timestamp("2000-01-04", tz=tz), stop=None
                )
                put.assert_series_equal(b, s.iloc[+2:])

                # Half-open with right boundary both finite and internal
                c = half_open(
                    s, start=None, stop=pd.Timestamp("2000-01-14", tz=tz)
                )
                put.assert_series_equal(c, s.iloc[:-2])

                # Half-open with both boundaries finite and internal
                d = half_open(
                    s,
                    start=pd.Timestamp("2000-01-04", tz=tz),
                    stop=pd.Timestamp("2000-01-14", tz=tz),
                )
                put.assert_series_equal(d, s.iloc[+2:-2])

    def test_series_with_datetimeindex_no_number_footcannons(self):
        """Confirm [start, stop) is rejected whenever an integer is given."""
        # Both Pandas and half_open_slice(...) can emit TypeErrors
        # A regex ensures the ones below are raised by half_open_slice(...).
        regex = " prohibited"

        # Generate sample data
        index_tz, _ = self.TZ_PAIRS_ACCEPTED[0]
        s = self.series_with_datetimeindex(index_tz=index_tz)

        # An number in either or both slots should raise
        with self.assertRaisesRegex(TypeError, regex):
            half_open(s, start=123, stop=None)
        with self.assertRaisesRegex(TypeError, regex):
            half_open(s, start=None, stop=456)
        with self.assertRaisesRegex(TypeError, regex):
            half_open(s, start=123.0, stop=456.0)

    def test_slicing_with_int64index(self):
        """
        half_open_slice(...) must work for integer-valued, non-unique indices.

        Generally, the method will be used on DatetimeIndex-es, but it
        should turn off cleanly when some other index type is supplied.
        Additionally, non-None slice steps are tested here.
        """
        # Create an index with duplicates like [0, 0, 1, 1, ..., 4, 4].
        df = pd.concat(
            (pd.DataFrame(data=list("abcde")), pd.DataFrame(data=list("abcde"))), axis=0
        )
        df.sort_index(inplace=True)
        self.assertEqual(10, len(df))
        self.assertEqual("int64", df.index.dtype.name)

        # Degenerate slices retrieve the entire range
        for step in (None, 1, 3, -2):
            self.assertEqual(
                slice(None, None, step),
                half_open_slice(df, slice(None, None, step)),
            )
            self.assertEqual(
                slice(0, None, step),
                half_open_slice(df, slice(-999999, None, step)),
            )
            self.assertEqual(
                slice(None, 10, step),
                half_open_slice(df, slice(None, +999999, step)),
            )
            self.assertEqual(
                slice(0, 10, step),
                half_open_slice(df, slice(-999999, +999999, step)),
            )

        # Degenerate slices retrieve no information
        # TODO Test start > s.index.max()
        # TODO Test stop < s.index.min()

        # Half-open with left boundary both finite and internal
        for step in (None, 1, 3, -2):
            self.assertEqual(
                slice(2, None, step), half_open_slice(df, slice(1, None, step))
            )

        # Half-open with right boundary both finite and internal
        for step in (None, 1, 3, -2):
            self.assertEqual(
                slice(None, 6, step), half_open_slice(df, slice(None, 3, step))
            )

        # Half-open with both boundaries finite and internal
        for step in (None, 1, 3, -2):
            self.assertEqual(
                slice(4, 8, step), half_open_slice(df, slice(2, 4, step))
            )

        # Defend against off-by-one coding mistakes at the left boundary
        self.assertEqual(slice(0, None), half_open_slice(df, slice(-1, None)))
        self.assertEqual(slice(0, None), half_open_slice(df, slice(+0, None)))
        self.assertEqual(slice(2, None), half_open_slice(df, slice(+1, None)))

        # Defend against off-by-one coding mistakes at the right boundary
        self.assertEqual(slice(None, 8), half_open_slice(df, slice(None, +4)))
        self.assertEqual(slice(None, 10), half_open_slice(df, slice(None, +5)))
        self.assertEqual(slice(None, 10), half_open_slice(df, slice(None, +6)))

    def test_slicing_with_object(self):
        """
        half_open_slice(...) must work for string-valued keys.

        Generally, the method will be used on DatetimeIndex-es, but it
        should turn off cleanly when some other index type is supplied.
        In particular, keys like "2020-01-01" should be dates for
        DatetimeIndex-es but they should be strings for other indices.
        """
        # Create an index like ["b", "c", "d", "e", "f"]
        df = pd.DataFrame(index=list("bcdef"), data=(0, 1, 2, 3, 4))
        self.assertEqual(5, len(df))
        self.assertEqual("object", df.index.dtype.name)

        # Degenerate slices retrieve the entire range
        self.assertEqual(
            slice(None, None), half_open_slice(df, slice(None, None))
        )
        self.assertEqual(slice(0, None), half_open_slice(df, slice("a", None)))
        self.assertEqual(slice(None, 5), half_open_slice(df, slice(None, "g")))
        self.assertEqual(slice(0, 5), half_open_slice(df, slice("a", "g")))

        # Degenerate slices retrieve no information
        # TODO Test start > s.index.max()
        # TODO Test stop < s.index.min()

        # Date-ish strings are treated lexicographically for this index
        self.assertEqual(
            slice(0, 0), half_open_slice(df, slice("2020-08-13", "2020-08-14"))
        )

        # Half-open with left boundary both finite and internal
        self.assertEqual(slice(2, None), half_open_slice(df, slice("d", None)))

        # Half-open with right boundary both finite and internal
        self.assertEqual(slice(None, 4), half_open_slice(df, slice(None, "f")))

        # Half-open with both boundaries finite and internal
        self.assertEqual(slice(1, 4), half_open_slice(df, slice("c", "f")))

    def dataframe_with_datetimeindex(self, index_tz: str) -> pd.DataFrame:
        """Construct DataFrame with multiple entries per index Timestamp."""
        df = []
        for tid in (3, 5, 7):
            df.append(put.makeTimeDataFrame(nper=10, freq="B"))
            df[-1]["tid"] = tid
        df = pd.concat(df).sort_index()
        df = self.localize(df, index_tz)
        self.assertEqual(df.index[+0], pd.Timestamp("2000-01-03", tz=index_tz))
        self.assertEqual(df.index[-1], pd.Timestamp("2000-01-14", tz=index_tz))
        return df

    @staticmethod
    def constructors(
        tz: str
    ) -> typing.Iterable[
        typing.Tuple[str, typing.Callable[[int, int, int], typing.Any]]
    ]:
        """
        An iterable of named, date-like object *constructors* for testing.

        Some of the test cases below iterate across these various objects.
        The names allow self.subTest(...) can identify specific constructors.
        """
        # Pandas' Timestamp object.  Nothing below will pass if this does not.
        yield (
            "Timestamp",
            lambda y, m, d: pd.Timestamp(datetime.date(year=y, month=m, day=d), tz=tz),
        )

        # The Python standard datetime.datetime using pytz for tzinfo
        #
        # Beware that datetime.datetime(..., tzinfo=...) is misleading per
        # https://typesandtimes.net/2019/05/royal-astronomical-society-python.
        #
        # Beware also pd.to_datetime(...) standardizes timezones in ways that
        # pd.Timestamp(...) does not.  In particular, "fixing" the API above.
        yield (
            "datetime",
            (
                lambda y, m, d: datetime.datetime(year=y, month=m, day=d)
                if tz is None
                else pytz.timezone(tz).localize(
                    datetime.datetime(year=y, month=m, day=d)
                )
            ),
        )

        # A datetime.date cannot possess a timezone so only test when possible
        if tz is None:
            yield ("date", lambda y, m, d: datetime.date(y, m, d))

        # A str can specify a timezone but here restrict to the case without
        if tz is None:
            yield ("str1", lambda y, m, d: f"{y:d}-{m:02d}-{d:02d}")  # Hypens
            yield ("str2", lambda y, m, d: f"{y:d}{m:02d}{d:02d}")  # None

        # A str that may contain a timezone specification
        # For example, "2020-01-04T00:00:00+01:00"
        yield (
            "isoformat",
            lambda y, m, d: pd.Timestamp(
                datetime.date(year=y, month=m, day=d), tz=tz
            ).isoformat(),
        )

    def test_dataframe_with_datetimeindex_accepted(self):
        """Confirm [start, stop) successfully slices a DataFrame."""
        for index_tz, tz in self.TZ_PAIRS_ACCEPTED:
            for name, constructor in self.constructors(tz):
                with self.subTest(index_tz=index_tz, tz=tz, name=name):
                    # Prepare the sample Dataframe
                    df = self.dataframe_with_datetimeindex(index_tz=index_tz)

                    # Degenerate slices retrieve all information
                    a1 = half_open(df, start=None, stop=None)
                    a2 = half_open(df, start=constructor(1970, 1, 1), stop=None)
                    a3 = half_open(df, start=None, stop=constructor(2038, 1, 1))
                    a4 = half_open(
                        df, start=constructor(1970, 1, 1), stop=constructor(2038, 1, 1)
                    )
                    put.assert_frame_equal(a1, df)
                    put.assert_frame_equal(a2, df)
                    put.assert_frame_equal(a3, df)
                    put.assert_frame_equal(a4, df)

                    # Degenerate slices retrieve no information
                    # TODO Test start > s.index.max()
                    # TODO Test stop < s.index.min()

                    # Half-open with left boundary both finite and internal
                    b = half_open(df, start=constructor(2000, 1, 4), stop=None)
                    put.assert_frame_equal(b, df.iloc[+3:, :])

                    # Half-open with right boundary both finite and internal
                    c = half_open(df, start=None, stop=constructor(2000, 1, 14))
                    put.assert_frame_equal(c, df.iloc[:-3, :])

                    # Half-open with both boundaries finite and internal
                    d = half_open(
                        df, start=constructor(2000, 1, 4), stop=constructor(2000, 1, 14)
                    )
                    put.assert_frame_equal(d, df.iloc[+3:-3, :])

    # No Series variant of this function because underlying logic identical
    def test_dataframe_with_datetimeindex_rejected(self):
        """Confirm invalid timezone pairs are rejected."""
        for index_tz, tz in self.TZ_PAIRS_REJECTED:
            for name, constructor in self.constructors(tz):
                with self.subTest(index_tz=index_tz, tz=tz, name=name):
                    # Prepare the sample Dataframe
                    df = self.dataframe_with_datetimeindex(index_tz=index_tz)

                    # Finite slices outside the bounds of the DatetimeIndex
                    with self.assertRaises(TypeError):
                        half_open(df, start=constructor(1970, 1, 1), stop=None)
                    with self.assertRaises(TypeError):
                        half_open(df, start=None, stop=constructor(2038, 1, 1))
                    with self.assertRaises(TypeError):
                        half_open(
                            df,
                            start=constructor(1970, 1, 1),
                            stop=constructor(2038, 1, 1),
                        )

                    # Degenerate slices retrieve no information
                    # TODO Test start > s.index.max()
                    # TODO Test stop < s.index.min()

                    # Half-open with left boundary both finite and internal
                    with self.assertRaises(TypeError):
                        half_open(df, start=constructor(2000, 1, 4), stop=None)

                    # Half-open with right boundary both finite and internal
                    with self.assertRaises(TypeError):
                        half_open(df, start=None, stop=constructor(2000, 1, 14))

                    # Half-open with both boundaries finite and internal
                    with self.assertRaises(TypeError):
                        half_open(
                            df,
                            start=constructor(2000, 1, 4),
                            stop=constructor(2000, 1, 14),
                        )

@mroeschke
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@RhysU I have a PR in the pandas repo that addresses the get_slice_bound bugs: pandas-dev#35848

It passed your unit tests on my branch; I adapted some of the tests you had there in my PR

@RhysU
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RhysU commented Aug 22, 2020 •
edited
Loading

@mroeschke, thank you. I pulled down pandas-dev#35848. I confirm that it passes the unit tests from above after I change my kind="ix" to kind="loc".

I then modified my half_open_slice(...) logic to remove the start < index.min()-like workarounds as follows and re-tested:

diff --git a/foo.py b/foo.py
index 3666ce3..6a2e55e 100644
--- a/foo.py
+++ b/foo.py
@@ -68,30 +68,18 @@ def half_open_slice(df: typing.Union[pd.DataFrame, pd.Series], s: slice) -> slic
     # Convert start to Optional[int]-valued index location start_idx
     # Clipping sidesteps https://github.com/pandas-dev/pandas/issues/35690
     # When below index.min() return 0 as if index.get_slice_bound(...) ran
-    # TODO After #35690 fixed, may not need start < index.min() clause.
-    # TODO After #35690 fixed, may not need start > index.max() clause.
     if start is None:
         start_idx = None
-    elif start < index.min():
-        start_idx = 0
-    elif start > index.max():  # TODO Branch not unit tested below
-        start_idx = len(df)
     else:
-        start_idx = index.get_slice_bound(start, side="left", kind="ix")
+        start_idx = index.get_slice_bound(start, side="left", kind="loc")
 
     # Convert stop to Optional[int]-valued index location stop_idx
     # Clipping sidesteps https://github.com/pandas-dev/pandas/issues/35690
     # When above index.max() return len as if index.get_slice_bound(...) ran
-    # TODO After #35690 fixed, may not need stop < index.min() clause.
-    # TODO After #35690 fixed, may not need stop > index.max() clause.
     if stop is None:
         stop_idx = None
-    elif stop < index.min():  # TODO Branch not unit tested below
-        stop_idx = 0
-    elif stop > index.max():
-        stop_idx = len(df)
     else:
-        stop_idx = index.get_slice_bound(stop, side="left", kind="ix")
+        stop_idx = index.get_slice_bound(stop, side="left", kind="loc")
 
     # Return the requested half-open slice
     return slice(start_idx, stop_idx, step)

I observe that when the DatetimeIndex.tzinfo is None the changes in pandas-dev#35848 do not raise TypeErrors when the location includes a non-None tzinfo. There are 6 failures in the above test suite then, and they all look like:

======================================================================
FAIL: test_dataframe_with_datetimeindex_rejected (foo.HalfOpen) (index_tz=None, tz='utc', name='Timestamp')
Confirm invalid timezone pairs are rejected.
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/home/rhys/tmp/foo.py", line 471, in test_dataframe_with_datetimeindex_rejected
    half_open(df, start=constructor(2000, 1, 4), stop=None)
AssertionError: TypeError not raised

This behavior goes to some of my uncertainty in pandas-dev#35690. My tests assert that a TypeError arises when questions are asked about index.tzinfo is None using a pd.Timestamp.tzinfo is not None because I don't believe there's a well-defined answer. That said, pandas may have some coercion policy of which I'm not aware.

@mroeschke
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Looks like pandas currently allows indexing a tz-naive index with a tz-aware argument but with the implicit assumption to index the tz-naive index "as UTC"

In [11]: df = pd.DataFrame(range(3), pd.date_range('2020', freq='D', periods=3))

In [12]: df
Out[12]:
            0
2020-01-01  0
2020-01-02  1
2020-01-03  2

In [13]: df.loc[pd.Timestamp('2020-01-01', tz='UTC'), 0]
Out[13]: 0

In [14]: df.loc['2020-01-01 00:00:00+00:00', 0]
Out[14]: 0

In [15]: df.loc[pd.Timestamp('2019-12-31 16:00:00', tz='US/Pacific'), 0]
Out[15]: 0

So given this behavior, I would say is okay to have get_slice_bounds accept a tz-aware Timestamp when the index is a tz-naive DatetimeIndex

@RhysU
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RhysU commented Aug 24, 2020 •
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'Evening @mroeschke.

I don't disagree with your assessment but I'll note that there seems to be little consistency in inferring UTC for a None tzinfo:

>>> import pandas as pd
>>> a = pd.Timestamp('2020-01-01', tz='UTC')
>>> b = pd.Timestamp('2020-01-01', tz=None)
>>> a < b
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "pandas/_libs/tslibs/timestamps.pyx", line 255, in pandas._libs.tslibs.timestamps._Timestamp.__richcmp__
  File "pandas/_libs/tslibs/timestamps.pyx", line 303, in pandas._libs.tslibs.timestamps._Timestamp._assert_tzawareness_compat
TypeError: Cannot compare tz-naive and tz-aware timestamps

I see the same for a == b. That inconsistency in inferring UTC makes me think it'll cause odd edge cases. That looks out-of-scope for this ticket but it'll reappear below.

Returning to my original tests, if I understand your point correctly then I expect that all None/non-None pairs of timezones should work. Going back to the above file and applying the following diff is equivalent to saying that None/UTC, None/Greenwich, etc should pass my tests:

diff --git a/foo.py b/foo.py
index 3666ce3..0a278b1 100644
--- a/foo.py
+++ b/foo.py
@@ -68,30 +68,18 @@ def half_open_slice(df: typing.Union[pd.DataFrame, pd.Series], s: slice) -> slic
     # Convert start to Optional[int]-valued index location start_idx
     # Clipping sidesteps https://github.com/pandas-dev/pandas/issues/35690
     # When below index.min() return 0 as if index.get_slice_bound(...) ran
-    # TODO After #35690 fixed, may not need start < index.min() clause.
-    # TODO After #35690 fixed, may not need start > index.max() clause.
     if start is None:
         start_idx = None
-    elif start < index.min():
-        start_idx = 0
-    elif start > index.max():  # TODO Branch not unit tested below
-        start_idx = len(df)
     else:
-        start_idx = index.get_slice_bound(start, side="left", kind="ix")
+        start_idx = index.get_slice_bound(start, side="left", kind="loc")
 
     # Convert stop to Optional[int]-valued index location stop_idx
     # Clipping sidesteps https://github.com/pandas-dev/pandas/issues/35690
     # When above index.max() return len as if index.get_slice_bound(...) ran
-    # TODO After #35690 fixed, may not need stop < index.min() clause.
-    # TODO After #35690 fixed, may not need stop > index.max() clause.
     if stop is None:
         stop_idx = None
-    elif stop < index.min():  # TODO Branch not unit tested below
-        stop_idx = 0
-    elif stop > index.max():
-        stop_idx = len(df)
     else:
-        stop_idx = index.get_slice_bound(stop, side="left", kind="ix")
+        stop_idx = index.get_slice_bound(stop, side="left", kind="loc")
 
     # Return the requested half-open slice
     return slice(start_idx, stop_idx, step)
@@ -139,10 +127,6 @@ class HalfOpen(unittest.TestCase):
         ("Etc/Greenwich", "utc"),
         # Greenwich in the Pandas Index and None slicing implies UTC slicing
         ("Etc/Greenwich", None),
-    )
-
-    # Which pairs of timezones should be confirmed as raising errors?
-    TZ_PAIRS_REJECTED = (
         # No timezone on the Pandas index but UTC slicing
         (None, "utc"),
         # No timezone on the Pandas index but Amsterdam slicing
@@ -151,6 +135,10 @@ class HalfOpen(unittest.TestCase):
         (None, "Etc/Greenwich"),
     )
 
+    # Which pairs of timezones should be confirmed as raising errors?
+    TZ_PAIRS_REJECTED = (
+    )
+
     def series_with_datetimeindex(self, index_tz: str) -> pd.DataFrame:
         """Construct Series with multiple entries per index Timestamp."""
         # Construct sample with multiple entries per index Timestamp

That is, all TZ_PAIRS should be acceptable and len(TZ_PAIRS_REJECTED) == 0. (I have to remove the start < index.min() workarounds now because they run afoul of my a < b counterexample and get_slice_bound would otherwise not be invoked). Running with that edit, I observe:

ERROR: test_dataframe_with_datetimeindex_accepted (foo.HalfOpen) (index_tz=None, tz='utc', name='Timestamp')
Confirm [start, stop) successfully slices a DataFrame.
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/home/rhys/tmp/pandas/pandas/core/indexes/base.py", line 2876, in get_loc
    return self._engine.get_loc(casted_key)
  File "pandas/_libs/index.pyx", line 409, in pandas._libs.index.DatetimeEngine.get_loc
  File "pandas/_libs/index.pyx", line 437, in pandas._libs.index.DatetimeEngine.get_loc
  File "pandas/_libs/index.pyx", line 116, in pandas._libs.index.IndexEngine._get_loc_duplicates
KeyError: 0

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/home/rhys/tmp/pandas/pandas/core/indexes/datetimes.py", line 589, in get_loc
    return Index.get_loc(self, key, method, tolerance)
  File "/home/rhys/tmp/pandas/pandas/core/indexes/base.py", line 2878, in get_loc
    raise KeyError(key) from err
KeyError: Timestamp('1970-01-01 00:00:00')

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/home/rhys/tmp/pandas/pandas/core/indexes/base.py", line 5059, in get_slice_bound
    slc = self.get_loc(label)
  File "/home/rhys/tmp/pandas/pandas/core/indexes/datetimes.py", line 591, in get_loc
    raise KeyError(orig_key) from err
KeyError: Timestamp('1970-01-01 00:00:00+0000', tz='UTC')

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/home/rhys/tmp/foo.py", line 416, in test_dataframe_with_datetimeindex_accepted
    a2 = half_open(df, start=constructor(1970, 1, 1), stop=None)
  File "/home/rhys/tmp/foo.py", line 20, in half_open
    slyce = half_open_slice(df=df, s=slice(start, stop, None))
  File "/home/rhys/tmp/foo.py", line 74, in half_open_slice
    start_idx = index.get_slice_bound(start, side="left", kind="loc")
  File "/home/rhys/tmp/pandas/pandas/core/indexes/base.py", line 5062, in get_slice_bound
    return self._searchsorted_monotonic(label, side)
  File "/home/rhys/tmp/pandas/pandas/core/indexes/base.py", line 5013, in _searchsorted_monotonic
    return self.searchsorted(label, side=side)
  File "/home/rhys/tmp/pandas/pandas/core/indexes/datetimelike.py", line 206, in searchsorted
    return self._data.searchsorted(value, side=side, sorter=sorter)
  File "/home/rhys/tmp/pandas/pandas/core/arrays/datetimelike.py", line 929, in searchsorted
    value = self._validate_searchsorted_value(value)
  File "/home/rhys/tmp/pandas/pandas/core/arrays/datetimelike.py", line 851, in _validate_searchsorted_value
    return self._unbox(value)
  File "/home/rhys/tmp/pandas/pandas/core/arrays/datetimelike.py", line 892, in _unbox
    other = self._unbox_scalar(other)
  File "/home/rhys/tmp/pandas/pandas/core/arrays/datetimes.py", line 451, in _unbox_scalar
    self._check_compatible_with(value)
  File "/home/rhys/tmp/pandas/pandas/core/arrays/datetimes.py", line 460, in _check_compatible_with
    self._assert_tzawareness_compat(other)
  File "/home/rhys/tmp/pandas/pandas/core/arrays/datetimes.py", line 644, in _assert_tzawareness_compat
    raise TypeError(
TypeError: Cannot compare tz-naive and tz-aware datetime-like objects.

where something down in the guts disagrees with the None/utc pair. It looks like my a < b counterexample is happening somewhere but it may not be the root cause.

@mroeschke
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Thanks for bring up that example and testing out my patch.

Taking a step back, I am not 100% sure where pandas lies today in regard to operations that involve an operation with a tz-naive and a tz-aware elements (indexing, comparisons, etc). Ideally it would be nice if there was consistency across all operations. I think there might be a push towards disallowing tz-naive and tz-aware objects from interacting, but that might need a larger discussion in pandas-dev#35690 or with the core team.

What would be your opinion if in get_slice_bound the timezones needed to match e.g.

print(index)
# DatetimeIndex(['2000-01-03 00:00:00+00:00', '2000-01-04 00:00:00+00:00',
#                ...
#                '2000-02-10 00:00:00+00:00', '2000-02-11 00:00:00+00:00'],
#               dtype='datetime64[ns, UTC]', freq='B')

Would raise: TypeError: Cannot compare tz-naive and tz-aware datetime-like objects.
index.get_slice_bounds(date.datetime(2020, 2, 10), ...)

Would raise: TypeError: Cannot compare tz-naive and tz-aware datetime-like objects.
index.get_slice_bounds(pd.Timestamp(2020, 2, 10), ...)

@RhysU
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RhysU commented Aug 25, 2020 •
edited
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@mroeschke, The timezones needing to match (in the sense that mixing tz-naive and tz-aware raises TypeError) in get_slice_bound is A-OK by me. So long as that implementation is consistent in its behavior, users can accomplish something else with a helper like my half_open(...).

@mroeschke
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Sorry for the delay @RhysU. I think my PR to fix get_slice_bound is pretty much ready to go. I think it will be easier if I address the interaction between tz-aware index and tz-naive argument in another PR where I can address other indexing methods like loc (since these methods share the same internal methods)

@RhysU
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RhysU commented Sep 2, 2020

Thank you for following-up @mroeschke. On the PR I now see consistency in index.get_slice_bound(...) in that the behavior is as I expect then the bound is before, internal, or after the data in the index. On the PR I now also see consistency in handling of Timestamps, datetimes, etc. I don't see rejection of mixing tz-naive and tz-aware data, but that's to be expected given your comments.

Concretely, with python -m unittest -v foo.py my prior tests now pass with the following diff:

diff --git a/foo.py b/foo.py
index 3666ce3..68481a0 100644
--- a/foo.py
+++ b/foo.py
@@ -43,7 +43,6 @@ def half_open_slice(df: typing.Union[pd.DataFrame, pd.Series], s: slice) -> slic
 
     # Additional start/stop coercion for only DatetimeIndex-like indices
     # Use Timestamps due to https://github.com/pandas-dev/pandas/issues/35690
-    # TODO After #35690 fixed, converting start/stop to Timestamp may not be needed
     attr_tz = "tzinfo"
     if hasattr(index, attr_tz):
         # Below, calls to pd.Timestamp(...) surprisingly interpret integers.
@@ -55,43 +54,22 @@ def half_open_slice(df: typing.Union[pd.DataFrame, pd.Series], s: slice) -> slic
                 f" Supply pandas.Timestamps to express fine-grained times like"
                 f" Timestamp('1970-01-01 00:00:00.020200817+0000', tz='UTC')."
             )
-        index_has_tz = index.tzinfo is not None
-        infer_start = index_has_tz and getattr(start, attr_tz, None) is None
-        infer_stop = index_has_tz and getattr(stop, attr_tz, None) is None
-        if start is not None:
-            start = pd.Timestamp(
-                start, tz=datetime.timezone.utc if infer_start else None
-            )
-        if stop is not None:
-            stop = pd.Timestamp(stop, tz=datetime.timezone.utc if infer_stop else None)
 
     # Convert start to Optional[int]-valued index location start_idx
     # Clipping sidesteps https://github.com/pandas-dev/pandas/issues/35690
     # When below index.min() return 0 as if index.get_slice_bound(...) ran
-    # TODO After #35690 fixed, may not need start < index.min() clause.
-    # TODO After #35690 fixed, may not need start > index.max() clause.
     if start is None:
         start_idx = None
-    elif start < index.min():
-        start_idx = 0
-    elif start > index.max():  # TODO Branch not unit tested below
-        start_idx = len(df)
     else:
-        start_idx = index.get_slice_bound(start, side="left", kind="ix")
+        start_idx = index.get_slice_bound(start, side="left", kind="loc")
 
     # Convert stop to Optional[int]-valued index location stop_idx
     # Clipping sidesteps https://github.com/pandas-dev/pandas/issues/35690
     # When above index.max() return len as if index.get_slice_bound(...) ran
-    # TODO After #35690 fixed, may not need stop < index.min() clause.
-    # TODO After #35690 fixed, may not need stop > index.max() clause.
     if stop is None:
         stop_idx = None
-    elif stop < index.min():  # TODO Branch not unit tested below
-        stop_idx = 0
-    elif stop > index.max():
-        stop_idx = len(df)
     else:
-        stop_idx = index.get_slice_bound(stop, side="left", kind="ix")
+        stop_idx = index.get_slice_bound(stop, side="left", kind="loc")
 
     # Return the requested half-open slice
     return slice(start_idx, stop_idx, step)
@@ -131,8 +109,6 @@ class HalfOpen(unittest.TestCase):
         ("UTC", "utc"),
         # Something other than UTC in both spots
         ("Europe/Amsterdam", "Europe/Amsterdam"),
-        # UTC in the Pandas Index and None slicing implies UTC slicing
-        ("utc", None),
         # Two different timezones with UTC on the DatetimeIndex
         ("UTC", "Etc/Greenwich"),
         # Two different timezones with Greenwich on the DatetimeIndex
@@ -142,14 +118,17 @@ class HalfOpen(unittest.TestCase):
     )
 
     # Which pairs of timezones should be confirmed as raising errors?
-    TZ_PAIRS_REJECTED = (
-        # No timezone on the Pandas index but UTC slicing
-        (None, "utc"),
-        # No timezone on the Pandas index but Amsterdam slicing
-        (None, "Europe/Amsterdam"),
-        # No timezone on the Pandas index but Greenwich slicing
-        (None, "Etc/Greenwich"),
-    )
+    TZ_PAIRS_REJECTED = tuple()
+    #TZ_PAIRS_REJECTED = (
+    #    # UTC in the Pandas Index and None slicing implies UTC slicing
+    #    ("utc", None),
+    #    # No timezone on the Pandas index but UTC slicing
+    #    (None, "utc"),
+    #    # No timezone on the Pandas index but Amsterdam slicing
+    #    (None, "Europe/Amsterdam"),
+    #    # No timezone on the Pandas index but Greenwich slicing
+    #    (None, "Etc/Greenwich"),
+    #)
 
     def series_with_datetimeindex(self, index_tz: str) -> pd.DataFrame:
         """Construct Series with multiple entries per index Timestamp."""

In any follow-on work, please do check that any ValueErrors are consistent across the various data types.

Appreciate all your effort here. Land away!

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4 participants
@RhysU @jreback @DiegoAlbertoTorres @mroeschke