# Licensed under a 3-clause BSD style license - see LICENSE.rst

import copy
import gc
import os
import pathlib
import pickle
import sys
from collections import OrderedDict
from io import StringIO

import numpy as np
import pytest
from numpy.testing import assert_allclose, assert_array_equal

from astropy import table
from astropy import units as u
from astropy.coordinates import SkyCoord
from astropy.io import fits
from astropy.table import (
    Column,
    MaskedColumn,
    QTable,
    Table,
    TableAttribute,
    TableReplaceWarning,
)
from astropy.tests.helper import assert_follows_unicode_guidelines
from astropy.time import Time, TimeDelta
from astropy.utils.compat import NUMPY_LT_1_25
from astropy.utils.compat.optional_deps import HAS_PANDAS
from astropy.utils.data import get_pkg_data_filename
from astropy.utils.exceptions import AstropyUserWarning
from astropy.utils.tests.test_metadata import MetaBaseTest

from .conftest import MIXIN_COLS, MaskedTable


@pytest.fixture
def home_is_tmpdir(monkeypatch, tmp_path):
    """
    Pytest fixture to run a test case with tilde-prefixed paths.

    In the tilde-path case, environment variables are temporarily
    modified so that '~' resolves to the temp directory.
    """
    # For Unix
    monkeypatch.setenv("HOME", str(tmp_path))
    # For Windows
    monkeypatch.setenv("USERPROFILE", str(tmp_path))


class SetupData:
    def _setup(self, table_types):
        self._table_type = table_types.Table
        self._column_type = table_types.Column

    @property
    def a(self):
        if self._column_type is not None:
            if not hasattr(self, "_a"):
                self._a = self._column_type(
                    [1, 2, 3], name="a", format="%d", meta={"aa": [0, 1, 2, 3, 4]}
                )
            return self._a

    @property
    def b(self):
        if self._column_type is not None:
            if not hasattr(self, "_b"):
                self._b = self._column_type(
                    [4, 5, 6], name="b", format="%d", meta={"aa": 1}
                )
            return self._b

    @property
    def c(self):
        if self._column_type is not None:
            if not hasattr(self, "_c"):
                self._c = self._column_type([7, 8, 9], "c")
            return self._c

    @property
    def d(self):
        if self._column_type is not None:
            if not hasattr(self, "_d"):
                self._d = self._column_type([7, 8, 7], "d")
            return self._d

    @property
    def obj(self):
        if self._column_type is not None:
            if not hasattr(self, "_obj"):
                self._obj = self._column_type([1, "string", 3], "obj", dtype="O")
            return self._obj

    @property
    def t(self):
        if self._table_type is not None:
            if not hasattr(self, "_t"):
                self._t = self._table_type([self.a, self.b])
            return self._t


@pytest.mark.usefixtures("table_types")
class TestSetTableColumn(SetupData):
    def test_set_row(self, table_types):
        """Set a row from a tuple of values"""
        self._setup(table_types)
        t = table_types.Table([self.a, self.b])
        t[1] = (20, 21)
        assert t["a"][0] == 1
        assert t["a"][1] == 20
        assert t["a"][2] == 3
        assert t["b"][0] == 4
        assert t["b"][1] == 21
        assert t["b"][2] == 6

    def test_set_row_existing(self, table_types):
        """Set a row from another existing row"""
        self._setup(table_types)
        t = table_types.Table([self.a, self.b])
        t[0] = t[1]
        assert t[0][0] == 2
        assert t[0][1] == 5

    def test_set_row_fail_1(self, table_types):
        """Set a row from an incorrectly-sized or typed set of values"""
        self._setup(table_types)
        t = table_types.Table([self.a, self.b])
        with pytest.raises(ValueError):
            t[1] = (20, 21, 22)
        with pytest.raises(ValueError):
            t[1] = 0

    def test_set_row_fail_2(self, table_types):
        """Set a row from an incorrectly-typed tuple of values"""
        self._setup(table_types)
        t = table_types.Table([self.a, self.b])
        with pytest.raises(ValueError):
            t[1] = ("abc", "def")

    def test_set_new_col_new_table(self, table_types):
        """Create a new column in empty table using the item access syntax"""
        self._setup(table_types)
        t = table_types.Table()
        t["aa"] = self.a
        # Test that the new column name is 'aa' and that the values match
        assert np.all(t["aa"] == self.a)
        assert t.colnames == ["aa"]

    def test_set_new_col_new_table_quantity(self, table_types):
        """Create a new column (from a quantity) in empty table using the item access syntax"""
        self._setup(table_types)
        t = table_types.Table()

        t["aa"] = np.array([1, 2, 3]) * u.m
        assert np.all(t["aa"] == np.array([1, 2, 3]))
        assert t["aa"].unit == u.m

        t["bb"] = 3 * u.m
        assert np.all(t["bb"] == 3)
        assert t["bb"].unit == u.m

    def test_set_new_col_existing_table(self, table_types):
        """Create a new column in an existing table using the item access syntax"""
        self._setup(table_types)
        t = table_types.Table([self.a])

        # Add a column
        t["bb"] = self.b
        assert np.all(t["bb"] == self.b)
        assert t.colnames == ["a", "bb"]
        assert t["bb"].meta == self.b.meta
        assert t["bb"].format == self.b.format

        # Add another column
        t["c"] = t["a"]
        assert np.all(t["c"] == t["a"])
        assert t.colnames == ["a", "bb", "c"]
        assert t["c"].meta == t["a"].meta
        assert t["c"].format == t["a"].format

        # Add a multi-dimensional column
        t["d"] = table_types.Column(np.arange(12).reshape(3, 2, 2))
        assert t["d"].shape == (3, 2, 2)
        assert t["d"][0, 0, 1] == 1

        # Add column from a list
        t["e"] = ["hello", "the", "world"]
        assert np.all(t["e"] == np.array(["hello", "the", "world"]))

        # Make sure setting existing column still works
        t["e"] = ["world", "hello", "the"]
        assert np.all(t["e"] == np.array(["world", "hello", "the"]))

        # Add a column via broadcasting
        t["f"] = 10
        assert np.all(t["f"] == 10)

        # Add a column from a Quantity
        t["g"] = np.array([1, 2, 3]) * u.m
        assert np.all(t["g"].data == np.array([1, 2, 3]))
        assert t["g"].unit == u.m

        # Add a column from a (scalar) Quantity
        t["g"] = 3 * u.m
        assert np.all(t["g"].data == 3)
        assert t["g"].unit == u.m

    def test_set_new_unmasked_col_existing_table(self, table_types):
        """Create a new column in an existing table using the item access syntax"""
        self._setup(table_types)
        t = table_types.Table([self.a])  # masked or unmasked
        b = table.Column(name="b", data=[1, 2, 3])  # unmasked
        t["b"] = b
        assert np.all(t["b"] == b)

    def test_set_new_masked_col_existing_table(self, table_types):
        """Create a new column in an existing table using the item access syntax"""
        self._setup(table_types)
        t = table_types.Table([self.a])  # masked or unmasked
        b = table.MaskedColumn(name="b", data=[1, 2, 3])  # masked
        t["b"] = b
        assert np.all(t["b"] == b)

    def test_set_new_col_existing_table_fail(self, table_types):
        """Generate failure when creating a new column using the item access syntax"""
        self._setup(table_types)
        t = table_types.Table([self.a])
        # Wrong size
        with pytest.raises(ValueError):
            t["b"] = [1, 2]


@pytest.mark.usefixtures("table_types")
class TestEmptyData:
    def test_1(self, table_types):
        t = table_types.Table()
        t.add_column(table_types.Column(name="a", dtype=int, length=100))
        assert len(t["a"]) == 100

    def test_2(self, table_types):
        t = table_types.Table()
        t.add_column(table_types.Column(name="a", dtype=int, shape=(3,), length=100))
        assert len(t["a"]) == 100

    def test_3(self, table_types):
        t = table_types.Table()  # length is not given
        t.add_column(table_types.Column(name="a", dtype=int))
        assert len(t["a"]) == 0

    def test_4(self, table_types):
        t = table_types.Table()  # length is not given
        t.add_column(table_types.Column(name="a", dtype=int, shape=(3, 4)))
        assert len(t["a"]) == 0

    def test_5(self, table_types):
        t = table_types.Table()
        t.add_column(table_types.Column(name="a"))  # dtype is not specified
        assert len(t["a"]) == 0

    def test_scalar(self, table_types):
        """Test related to #3811 where setting empty tables to scalar values
        should raise an error instead of having an error raised when accessing
        the table."""
        t = table_types.Table()
        with pytest.raises(
            TypeError, match="Empty table cannot have column set to scalar value"
        ):
            t.add_column(0)

    def test_add_via_setitem_and_slice(self, table_types):
        """Test related to #3023 where a MaskedColumn is created with name=None
        and then gets changed to name='a'.  After PR #2790 this test fails
        without the #3023 fix."""
        t = table_types.Table()
        t["a"] = table_types.Column([1, 2, 3])
        t2 = t[:]
        assert t2.colnames == t.colnames


@pytest.mark.usefixtures("table_types")
class TestNewFromColumns:
    def test_simple(self, table_types):
        cols = [
            table_types.Column(name="a", data=[1, 2, 3]),
            table_types.Column(name="b", data=[4, 5, 6], dtype=np.float32),
        ]
        t = table_types.Table(cols)
        assert np.all(t["a"].data == np.array([1, 2, 3]))
        assert np.all(t["b"].data == np.array([4, 5, 6], dtype=np.float32))
        assert type(t["b"][1]) is np.float32

    def test_from_np_array(self, table_types):
        cols = [
            table_types.Column(
                name="a", data=np.array([1, 2, 3], dtype=np.int64), dtype=np.float64
            ),
            table_types.Column(name="b", data=np.array([4, 5, 6], dtype=np.float32)),
        ]
        t = table_types.Table(cols)
        assert np.all(t["a"] == np.array([1, 2, 3], dtype=np.float64))
        assert np.all(t["b"] == np.array([4, 5, 6], dtype=np.float32))
        assert type(t["a"][1]) is np.float64
        assert type(t["b"][1]) is np.float32

    def test_size_mismatch(self, table_types):
        cols = [
            table_types.Column(name="a", data=[1, 2, 3]),
            table_types.Column(name="b", data=[4, 5, 6, 7]),
        ]
        with pytest.raises(ValueError):
            table_types.Table(cols)

    def test_name_none(self, table_types):
        """Column with name=None can init a table whether or not names are supplied"""
        c = table_types.Column(data=[1, 2], name="c")
        d = table_types.Column(data=[3, 4])
        t = table_types.Table([c, d], names=(None, "d"))
        assert t.colnames == ["c", "d"]
        t = table_types.Table([c, d])
        assert t.colnames == ["c", "col1"]


@pytest.mark.usefixtures("table_types")
class TestReverse:
    def test_reverse(self, table_types):
        t = table_types.Table(
            [
                [1, 2, 3],
                ["a", "b", "cc"],
            ]
        )
        t.reverse()
        assert np.all(t["col0"] == np.array([3, 2, 1]))
        assert np.all(t["col1"] == np.array(["cc", "b", "a"]))

        t2 = table_types.Table(t, copy=False)
        assert np.all(t2["col0"] == np.array([3, 2, 1]))
        assert np.all(t2["col1"] == np.array(["cc", "b", "a"]))

        t2 = table_types.Table(t, copy=True)
        assert np.all(t2["col0"] == np.array([3, 2, 1]))
        assert np.all(t2["col1"] == np.array(["cc", "b", "a"]))

        t2.sort("col0")
        assert np.all(t2["col0"] == np.array([1, 2, 3]))
        assert np.all(t2["col1"] == np.array(["a", "b", "cc"]))

    def test_reverse_big(self, table_types):
        x = np.arange(10000)
        y = x + 1
        t = table_types.Table([x, y], names=("x", "y"))
        t.reverse()
        assert np.all(t["x"] == x[::-1])
        assert np.all(t["y"] == y[::-1])

    def test_reverse_mixin(self):
        """Test reverse for a mixin with no item assignment, fix for #9836"""
        sc = SkyCoord([1, 2], [3, 4], unit="deg")
        t = Table([[2, 1], sc], names=["a", "sc"])
        t.reverse()
        assert np.all(t["a"] == [1, 2])
        assert np.allclose(t["sc"].ra.to_value("deg"), [2, 1])


@pytest.mark.usefixtures("table_types")
class TestRound:
    def test_round_int(self, table_types):
        t = table_types.Table(
            [
                ["a", "b", "c"],
                [1.11, 2.3, 3.0],
                [1.123456, 2.9876, 3.901],
            ]
        )
        t.round()
        assert np.all(t["col0"] == ["a", "b", "c"])
        assert np.all(t["col1"] == [1.0, 2.0, 3.0])
        assert np.all(t["col2"] == [1.0, 3.0, 4.0])

    def test_round_dict(self, table_types):
        t = table_types.Table(
            [
                ["a", "b", "c"],
                [1.5, 2.5, 3.0111],
                [1.123456, 2.9876, 3.901],
            ]
        )

        t.round({"col1": 0, "col2": 3})
        assert np.all(t["col0"] == ["a", "b", "c"])
        assert np.all(t["col1"] == [2.0, 2.0, 3.0])
        assert np.all(t["col2"] == [1.123, 2.988, 3.901])

    def test_round_invalid(self, table_types):
        t = table_types.Table([[1, 2, 3]])
        with pytest.raises(
            ValueError, match="'decimals' argument must be an int or a dict"
        ):
            t.round(0.5)

    def test_round_kind(self, table_types):
        for typecode in "bBhHiIlLqQpPefdgFDG":  # AllInteger, AllFloat
            arr = np.array([4, 16], dtype=typecode)
            t = Table([arr])
            col0 = t["col0"]
            t.round(decimals=-1)  # Round to nearest 10
            assert np.all(t["col0"] == [0, 20])
            assert t["col0"] is col0


@pytest.mark.usefixtures("table_types")
class TestColumnAccess:
    def test_1(self, table_types):
        t = table_types.Table()
        with pytest.raises(KeyError):
            t["a"]

    def test_2(self, table_types):
        t = table_types.Table()
        t.add_column(table_types.Column(name="a", data=[1, 2, 3]))
        assert np.all(t["a"] == np.array([1, 2, 3]))
        with pytest.raises(KeyError):
            t["b"]  # column does not exist

    def test_itercols(self, table_types):
        names = ["a", "b", "c"]
        t = table_types.Table([[1], [2], [3]], names=names)
        for name, col in zip(names, t.itercols()):
            assert name == col.name
            assert isinstance(col, table_types.Column)


@pytest.mark.usefixtures("table_types")
class TestAddLength(SetupData):
    def test_right_length(self, table_types):
        self._setup(table_types)
        t = table_types.Table([self.a])
        t.add_column(self.b)

    def test_too_long(self, table_types):
        self._setup(table_types)
        t = table_types.Table([self.a])
        with pytest.raises(ValueError):
            t.add_column(
                table_types.Column(name="b", data=[4, 5, 6, 7])
            )  # data too long

    def test_too_short(self, table_types):
        self._setup(table_types)
        t = table_types.Table([self.a])
        with pytest.raises(ValueError):
            t.add_column(table_types.Column(name="b", data=[4, 5]))  # data too short


@pytest.mark.usefixtures("table_types")
class TestAddPosition(SetupData):
    def test_1(self, table_types):
        self._setup(table_types)
        t = table_types.Table()
        t.add_column(self.a, 0)

    def test_2(self, table_types):
        self._setup(table_types)
        t = table_types.Table()
        t.add_column(self.a, 1)

    def test_3(self, table_types):
        self._setup(table_types)
        t = table_types.Table()
        t.add_column(self.a, -1)

    def test_5(self, table_types):
        self._setup(table_types)
        t = table_types.Table()
        with pytest.raises(ValueError):
            t.index_column("b")

    def test_6(self, table_types):
        self._setup(table_types)
        t = table_types.Table()
        t.add_column(self.a)
        t.add_column(self.b)
        assert t.colnames == ["a", "b"]

    def test_7(self, table_types):
        self._setup(table_types)
        t = table_types.Table([self.a])
        t.add_column(self.b, t.index_column("a"))
        assert t.colnames == ["b", "a"]

    def test_8(self, table_types):
        self._setup(table_types)
        t = table_types.Table([self.a])
        t.add_column(self.b, t.index_column("a") + 1)
        assert t.colnames == ["a", "b"]

    def test_9(self, table_types):
        self._setup(table_types)
        t = table_types.Table()
        t.add_column(self.a)
        t.add_column(self.b, t.index_column("a") + 1)
        t.add_column(self.c, t.index_column("b"))
        assert t.colnames == ["a", "c", "b"]

    def test_10(self, table_types):
        self._setup(table_types)
        t = table_types.Table()
        t.add_column(self.a)
        ia = t.index_column("a")
        t.add_column(self.b, ia + 1)
        t.add_column(self.c, ia)
        assert t.colnames == ["c", "a", "b"]


@pytest.mark.usefixtures("table_types")
class TestAddName(SetupData):
    def test_override_name(self, table_types):
        self._setup(table_types)
        t = table_types.Table()

        # Check that we can override the name of the input column in the Table
        t.add_column(self.a, name="b")
        t.add_column(self.b, name="a")
        assert t.colnames == ["b", "a"]
        # Check that we did not change the name of the input column
        assert self.a.info.name == "a"
        assert self.b.info.name == "b"

        # Now test with an input column from another table
        t2 = table_types.Table()
        t2.add_column(t["a"], name="c")
        assert t2.colnames == ["c"]
        # Check that we did not change the name of the input column
        assert t.colnames == ["b", "a"]

        # Check that we can give a name if none was present
        col = table_types.Column([1, 2, 3])
        t.add_column(col, name="c")
        assert t.colnames == ["b", "a", "c"]

    def test_default_name(self, table_types):
        t = table_types.Table()
        col = table_types.Column([1, 2, 3])
        t.add_column(col)
        assert t.colnames == ["col0"]


@pytest.mark.usefixtures("table_types")
class TestInitFromTable(SetupData):
    def test_from_table_cols(self, table_types):
        """Ensure that using cols from an existing table gives
        a clean copy.
        """
        self._setup(table_types)
        t = self.t
        cols = t.columns
        # Construct Table with cols via Table._new_from_cols
        t2a = table_types.Table([cols["a"], cols["b"], self.c])

        # Construct with add_column
        t2b = table_types.Table()
        t2b.add_column(cols["a"])
        t2b.add_column(cols["b"])
        t2b.add_column(self.c)

        t["a"][1] = 20
        t["b"][1] = 21
        for t2 in [t2a, t2b]:
            t2["a"][2] = 10
            t2["b"][2] = 11
            t2["c"][2] = 12
            t2.columns["a"].meta["aa"][3] = 10
            assert np.all(t["a"] == np.array([1, 20, 3]))
            assert np.all(t["b"] == np.array([4, 21, 6]))
            assert np.all(t2["a"] == np.array([1, 2, 10]))
            assert np.all(t2["b"] == np.array([4, 5, 11]))
            assert np.all(t2["c"] == np.array([7, 8, 12]))
            assert t2["a"].name == "a"
            assert t2.columns["a"].meta["aa"][3] == 10
            assert t.columns["a"].meta["aa"][3] == 3


@pytest.mark.usefixtures("table_types")
class TestAddColumns(SetupData):
    def test_add_columns1(self, table_types):
        self._setup(table_types)
        t = table_types.Table()
        t.add_columns([self.a, self.b, self.c])
        assert t.colnames == ["a", "b", "c"]

    def test_add_columns2(self, table_types):
        self._setup(table_types)
        t = table_types.Table([self.a, self.b])
        t.add_columns([self.c, self.d])
        assert t.colnames == ["a", "b", "c", "d"]
        assert np.all(t["c"] == np.array([7, 8, 9]))

    def test_add_columns3(self, table_types):
        self._setup(table_types)
        t = table_types.Table([self.a, self.b])
        t.add_columns([self.c, self.d], indexes=[1, 0])
        assert t.colnames == ["d", "a", "c", "b"]

    def test_add_columns4(self, table_types):
        self._setup(table_types)
        t = table_types.Table([self.a, self.b])
        t.add_columns([self.c, self.d], indexes=[0, 0])
        assert t.colnames == ["c", "d", "a", "b"]

    def test_add_columns5(self, table_types):
        self._setup(table_types)
        t = table_types.Table([self.a, self.b])
        t.add_columns([self.c, self.d], indexes=[2, 2])
        assert t.colnames == ["a", "b", "c", "d"]

    def test_add_columns6(self, table_types):
        """Check that we can override column names."""
        self._setup(table_types)
        t = table_types.Table()
        t.add_columns([self.a, self.b, self.c], names=["b", "c", "a"])
        assert t.colnames == ["b", "c", "a"]

    def test_add_columns7(self, table_types):
        """Check that default names are used when appropriate."""
        t = table_types.Table()
        col0 = table_types.Column([1, 2, 3])
        col1 = table_types.Column([4, 5, 3])
        t.add_columns([col0, col1])
        assert t.colnames == ["col0", "col1"]

    def test_add_duplicate_column(self, table_types):
        self._setup(table_types)
        t = table_types.Table()
        t.add_column(self.a)
        with pytest.raises(ValueError):
            t.add_column(table_types.Column(name="a", data=[0, 1, 2]))
        t.add_column(
            table_types.Column(name="a", data=[0, 1, 2]), rename_duplicate=True
        )
        t.add_column(self.b)
        t.add_column(self.c)
        assert t.colnames == ["a", "a_1", "b", "c"]
        t.add_column(
            table_types.Column(name="a", data=[0, 1, 2]), rename_duplicate=True
        )
        assert t.colnames == ["a", "a_1", "b", "c", "a_2"]

        # test adding column from a separate Table
        t1 = table_types.Table()
        t1.add_column(self.a)
        with pytest.raises(ValueError):
            t.add_column(t1["a"])
        t.add_column(t1["a"], rename_duplicate=True)

        t1["a"][0] = 100  # Change original column
        assert t.colnames == ["a", "a_1", "b", "c", "a_2", "a_3"]
        assert t1.colnames == ["a"]

        # Check new column didn't change (since name conflict forced a copy)
        assert t["a_3"][0] == self.a[0]

        # Check that rename_duplicate=True is ok if there are no duplicates
        t.add_column(
            table_types.Column(name="q", data=[0, 1, 2]), rename_duplicate=True
        )
        assert t.colnames == ["a", "a_1", "b", "c", "a_2", "a_3", "q"]

    def test_add_duplicate_columns(self, table_types):
        self._setup(table_types)
        t = table_types.Table([self.a, self.b, self.c])
        with pytest.raises(ValueError):
            t.add_columns(
                [
                    table_types.Column(name="a", data=[0, 1, 2]),
                    table_types.Column(name="b", data=[0, 1, 2]),
                ]
            )
        t.add_columns(
            [
                table_types.Column(name="a", data=[0, 1, 2]),
                table_types.Column(name="b", data=[0, 1, 2]),
            ],
            rename_duplicate=True,
        )
        t.add_column(self.d)
        assert t.colnames == ["a", "b", "c", "a_1", "b_1", "d"]


@pytest.mark.usefixtures("table_types")
class TestAddRow(SetupData):
    @property
    def b(self):
        if self._column_type is not None:
            if not hasattr(self, "_b"):
                self._b = self._column_type(name="b", data=[4.0, 5.1, 6.2])
            return self._b

    @property
    def c(self):
        if self._column_type is not None:
            if not hasattr(self, "_c"):
                self._c = self._column_type(name="c", data=["7", "8", "9"])
            return self._c

    @property
    def d(self):
        if self._column_type is not None:
            if not hasattr(self, "_d"):
                self._d = self._column_type(name="d", data=[[1, 2], [3, 4], [5, 6]])
            return self._d

    @property
    def t(self):
        if self._table_type is not None:
            if not hasattr(self, "_t"):
                self._t = self._table_type([self.a, self.b, self.c])
            return self._t

    def test_add_none_to_empty_table(self, table_types):
        self._setup(table_types)
        t = table_types.Table(names=("a", "b", "c"), dtype=("(2,)i", "S4", "O"))
        t.add_row()
        assert np.all(t["a"][0] == [0, 0])
        assert t["b"][0] == ""
        assert t["c"][0] == 0
        t.add_row()
        assert np.all(t["a"][1] == [0, 0])
        assert t["b"][1] == ""
        assert t["c"][1] == 0

    def test_add_stuff_to_empty_table(self, table_types):
        self._setup(table_types)
        t = table_types.Table(names=("a", "b", "obj"), dtype=("(2,)i", "S8", "O"))
        t.add_row([[1, 2], "hello", "world"])
        assert np.all(t["a"][0] == [1, 2])
        assert t["b"][0] == "hello"
        assert t["obj"][0] == "world"
        # Make sure it is not repeating last row but instead
        # adding zeros (as documented)
        t.add_row()
        assert np.all(t["a"][1] == [0, 0])
        assert t["b"][1] == ""
        assert t["obj"][1] == 0

    def test_add_table_row(self, table_types):
        self._setup(table_types)
        t = self.t
        t["d"] = self.d
        t2 = table_types.Table([self.a, self.b, self.c, self.d])
        t.add_row(t2[0])
        assert len(t) == 4
        assert np.all(t["a"] == np.array([1, 2, 3, 1]))
        assert np.allclose(t["b"], np.array([4.0, 5.1, 6.2, 4.0]))
        assert np.all(t["c"] == np.array(["7", "8", "9", "7"]))
        assert np.all(t["d"] == np.array([[1, 2], [3, 4], [5, 6], [1, 2]]))

    def test_add_table_row_obj(self, table_types):
        self._setup(table_types)
        t = table_types.Table([self.a, self.b, self.obj])
        t.add_row([1, 4.0, [10]])
        assert len(t) == 4
        assert np.all(t["a"] == np.array([1, 2, 3, 1]))
        assert np.allclose(t["b"], np.array([4.0, 5.1, 6.2, 4.0]))
        assert np.all(t["obj"] == np.array([1, "string", 3, [10]], dtype="O"))

    def test_add_qtable_row_multidimensional(self):
        q = [[1, 2], [3, 4]] * u.m
        qt = table.QTable([q])
        qt.add_row(([5, 6] * u.km,))
        assert np.all(qt["col0"] == [[1, 2], [3, 4], [5000, 6000]] * u.m)

    def test_add_with_tuple(self, table_types):
        self._setup(table_types)
        t = self.t
        t.add_row((4, 7.2, "1"))
        assert len(t) == 4
        assert np.all(t["a"] == np.array([1, 2, 3, 4]))
        assert np.allclose(t["b"], np.array([4.0, 5.1, 6.2, 7.2]))
        assert np.all(t["c"] == np.array(["7", "8", "9", "1"]))

    def test_add_with_list(self, table_types):
        self._setup(table_types)
        t = self.t
        t.add_row([4, 7.2, "10"])
        assert len(t) == 4
        assert np.all(t["a"] == np.array([1, 2, 3, 4]))
        assert np.allclose(t["b"], np.array([4.0, 5.1, 6.2, 7.2]))
        assert np.all(t["c"] == np.array(["7", "8", "9", "10"]))

    def test_add_with_dict(self, table_types):
        self._setup(table_types)
        t = self.t
        t.add_row({"a": 4, "b": 7.2})
        assert len(t) == 4
        assert np.all(t["a"] == np.array([1, 2, 3, 4]))
        assert np.allclose(t["b"], np.array([4.0, 5.1, 6.2, 7.2]))
        if t.masked:
            assert np.all(t["c"] == np.array(["7", "8", "9", "7"]))
        else:
            assert np.all(t["c"] == np.array(["7", "8", "9", ""]))

    def test_add_with_none(self, table_types):
        self._setup(table_types)
        t = self.t
        t.add_row()
        assert len(t) == 4
        assert np.all(t["a"].data == np.array([1, 2, 3, 0]))
        assert np.allclose(t["b"], np.array([4.0, 5.1, 6.2, 0.0]))
        assert np.all(t["c"].data == np.array(["7", "8", "9", ""]))

    def test_add_missing_column(self, table_types):
        self._setup(table_types)
        t = self.t
        with pytest.raises(ValueError):
            t.add_row({"bad_column": 1})

    def test_wrong_size_tuple(self, table_types):
        self._setup(table_types)
        t = self.t
        with pytest.raises(ValueError):
            t.add_row((1, 2))

    def test_wrong_vals_type(self, table_types):
        self._setup(table_types)
        t = self.t
        with pytest.raises(TypeError):
            t.add_row(1)

    def test_add_row_failures(self, table_types):
        self._setup(table_types)
        t = self.t
        t_copy = table_types.Table(t, copy=True)
        # Wrong number of columns
        try:
            t.add_row([1, 2, 3, 4])
        except ValueError:
            pass
        assert len(t) == 3
        assert np.all(t.as_array() == t_copy.as_array())
        # Wrong data type
        try:
            t.add_row(["one", 2, 3])
        except ValueError:
            pass
        assert len(t) == 3
        assert np.all(t.as_array() == t_copy.as_array())

    def test_insert_table_row(self, table_types):
        """
        Light testing of Table.insert_row() method.  The deep testing is done via
        the add_row() tests which calls insert_row(index=len(self), ...), so
        here just test that the added index parameter is handled correctly.
        """
        self._setup(table_types)
        row = (10, 40.0, "x", [10, 20])
        for index in range(-3, 4):
            indices = np.insert(np.arange(3), index, 3)
            t = table_types.Table([self.a, self.b, self.c, self.d])
            t2 = t.copy()
            t.add_row(row)  # By now we know this works
            t2.insert_row(index, row)
            for name in t.colnames:
                if t[name].dtype.kind == "f":
                    assert np.allclose(t[name][indices], t2[name])
                else:
                    assert np.all(t[name][indices] == t2[name])

        for index in (-4, 4):
            t = table_types.Table([self.a, self.b, self.c, self.d])
            with pytest.raises(IndexError):
                t.insert_row(index, row)


@pytest.mark.usefixtures("table_types")
class TestTableColumn(SetupData):
    def test_column_view(self, table_types):
        self._setup(table_types)
        t = self.t
        a = t.columns["a"]
        a[2] = 10
        assert t["a"][2] == 10


@pytest.mark.usefixtures("table_types")
class TestArrayColumns(SetupData):
    def test_1d(self, table_types):
        self._setup(table_types)
        b = table_types.Column(name="b", dtype=int, shape=(2,), length=3)
        t = table_types.Table([self.a])
        t.add_column(b)
        assert t["b"].shape == (3, 2)
        assert t["b"][0].shape == (2,)

    def test_2d(self, table_types):
        self._setup(table_types)
        b = table_types.Column(name="b", dtype=int, shape=(2, 4), length=3)
        t = table_types.Table([self.a])
        t.add_column(b)
        assert t["b"].shape == (3, 2, 4)
        assert t["b"][0].shape == (2, 4)

    def test_3d(self, table_types):
        self._setup(table_types)
        t = table_types.Table([self.a])
        b = table_types.Column(name="b", dtype=int, shape=(2, 4, 6), length=3)
        t.add_column(b)
        assert t["b"].shape == (3, 2, 4, 6)
        assert t["b"][0].shape == (2, 4, 6)


@pytest.mark.usefixtures("table_types")
class TestRemove(SetupData):
    @property
    def t(self):
        if self._table_type is not None:
            if not hasattr(self, "_t"):
                self._t = self._table_type([self.a])
            return self._t

    @property
    def t2(self):
        if self._table_type is not None:
            if not hasattr(self, "_t2"):
                self._t2 = self._table_type([self.a, self.b, self.c])
            return self._t2

    def test_1(self, table_types):
        self._setup(table_types)
        self.t.remove_columns("a")
        assert self.t.colnames == []
        assert self.t.as_array().size == 0
        # Regression test for gh-8640
        assert not self.t
        assert isinstance(self.t == None, np.ndarray)
        assert (self.t == None).size == 0

    def test_2(self, table_types):
        self._setup(table_types)
        self.t.add_column(self.b)
        self.t.remove_columns("a")
        assert self.t.colnames == ["b"]
        assert self.t.dtype.names == ("b",)
        assert np.all(self.t["b"] == np.array([4, 5, 6]))

    def test_3(self, table_types):
        """Check remove_columns works for a single column with a name of
        more than one character.  Regression test against #2699"""
        self._setup(table_types)
        self.t["new_column"] = self.t["a"]
        assert "new_column" in self.t.columns.keys()
        self.t.remove_columns("new_column")
        assert "new_column" not in self.t.columns.keys()

    def test_remove_nonexistent_row(self, table_types):
        self._setup(table_types)
        with pytest.raises(IndexError):
            self.t.remove_row(4)

    def test_remove_row_0(self, table_types):
        self._setup(table_types)
        self.t.add_column(self.b)
        self.t.add_column(self.c)
        self.t.remove_row(0)
        assert self.t.colnames == ["a", "b", "c"]
        assert np.all(self.t["b"] == np.array([5, 6]))

    def test_remove_row_1(self, table_types):
        self._setup(table_types)
        self.t.add_column(self.b)
        self.t.add_column(self.c)
        self.t.remove_row(1)
        assert self.t.colnames == ["a", "b", "c"]
        assert np.all(self.t["a"] == np.array([1, 3]))

    def test_remove_row_2(self, table_types):
        self._setup(table_types)
        self.t.add_column(self.b)
        self.t.add_column(self.c)
        self.t.remove_row(2)
        assert self.t.colnames == ["a", "b", "c"]
        assert np.all(self.t["c"] == np.array([7, 8]))

    def test_remove_row_slice(self, table_types):
        self._setup(table_types)
        self.t.add_column(self.b)
        self.t.add_column(self.c)
        self.t.remove_rows(slice(0, 2, 1))
        assert self.t.colnames == ["a", "b", "c"]
        assert np.all(self.t["c"] == np.array([9]))

    def test_remove_row_list(self, table_types):
        self._setup(table_types)
        self.t.add_column(self.b)
        self.t.add_column(self.c)
        self.t.remove_rows([0, 2])
        assert self.t.colnames == ["a", "b", "c"]
        assert np.all(self.t["c"] == np.array([8]))

    def test_remove_row_preserves_meta(self, table_types):
        self._setup(table_types)
        self.t.add_column(self.b)
        self.t.remove_rows([0, 2])
        assert self.t["a"].meta == {"aa": [0, 1, 2, 3, 4]}
        assert self.t.dtype == np.dtype([("a", "int"), ("b", "int")])

    def test_delitem_row(self, table_types):
        self._setup(table_types)
        self.t.add_column(self.b)
        self.t.add_column(self.c)
        del self.t[1]
        assert self.t.colnames == ["a", "b", "c"]
        assert np.all(self.t["a"] == np.array([1, 3]))

    @pytest.mark.parametrize("idx", [[0, 2], np.array([0, 2])])
    def test_delitem_row_list(self, table_types, idx):
        self._setup(table_types)
        self.t.add_column(self.b)
        self.t.add_column(self.c)
        del self.t[idx]
        assert self.t.colnames == ["a", "b", "c"]
        assert np.all(self.t["c"] == np.array([8]))

    def test_delitem_row_slice(self, table_types):
        self._setup(table_types)
        self.t.add_column(self.b)
        self.t.add_column(self.c)
        del self.t[0:2]
        assert self.t.colnames == ["a", "b", "c"]
        assert np.all(self.t["c"] == np.array([9]))

    def test_delitem_row_fail(self, table_types):
        self._setup(table_types)
        with pytest.raises(IndexError):
            del self.t[4]

    def test_delitem_row_float(self, table_types):
        self._setup(table_types)
        with pytest.raises(IndexError):
            del self.t[1.0]

    def test_delitem1(self, table_types):
        self._setup(table_types)
        del self.t["a"]
        assert self.t.colnames == []
        assert self.t.as_array().size == 0
        # Regression test for gh-8640
        assert not self.t
        assert isinstance(self.t == None, np.ndarray)
        assert (self.t == None).size == 0

    def test_delitem2(self, table_types):
        self._setup(table_types)
        del self.t2["b"]
        assert self.t2.colnames == ["a", "c"]

    def test_delitems(self, table_types):
        self._setup(table_types)
        del self.t2["a", "b"]
        assert self.t2.colnames == ["c"]

    def test_delitem_fail(self, table_types):
        self._setup(table_types)
        with pytest.raises(KeyError):
            del self.t["d"]


@pytest.mark.usefixtures("table_types")
class TestKeep(SetupData):
    def test_1(self, table_types):
        self._setup(table_types)
        t = table_types.Table([self.a, self.b])
        t.keep_columns([])
        assert t.colnames == []
        assert t.as_array().size == 0
        # Regression test for gh-8640
        assert not t
        assert isinstance(t == None, np.ndarray)
        assert (t == None).size == 0

    def test_2(self, table_types):
        self._setup(table_types)
        t = table_types.Table([self.a, self.b])
        t.keep_columns("b")
        assert t.colnames == ["b"]
        assert t.dtype.names == ("b",)
        assert np.all(t["b"] == np.array([4, 5, 6]))


@pytest.mark.usefixtures("table_types")
class TestRename(SetupData):
    def test_1(self, table_types):
        self._setup(table_types)
        t = table_types.Table([self.a])
        t.rename_column("a", "b")
        assert t.colnames == ["b"]
        assert t.dtype.names == ("b",)
        assert np.all(t["b"] == np.array([1, 2, 3]))

    def test_2(self, table_types):
        self._setup(table_types)
        t = table_types.Table([self.a, self.b])
        t.rename_column("a", "c")
        t.rename_column("b", "a")
        assert t.colnames == ["c", "a"]
        assert t.dtype.names == ("c", "a")
        if t.masked:
            assert t.mask.dtype.names == ("c", "a")
        assert np.all(t["c"] == np.array([1, 2, 3]))
        assert np.all(t["a"] == np.array([4, 5, 6]))

    def test_rename_by_attr(self, table_types):
        self._setup(table_types)
        t = table_types.Table([self.a, self.b])
        t["a"].name = "c"
        t["b"].name = "a"
        assert t.colnames == ["c", "a"]
        assert t.dtype.names == ("c", "a")
        assert np.all(t["c"] == np.array([1, 2, 3]))
        assert np.all(t["a"] == np.array([4, 5, 6]))

    def test_rename_columns(self, table_types):
        self._setup(table_types)
        t = table_types.Table([self.a, self.b, self.c])
        t.rename_columns(("a", "b", "c"), ("aa", "bb", "cc"))
        assert t.colnames == ["aa", "bb", "cc"]
        t.rename_columns(["bb", "cc"], ["b", "c"])
        assert t.colnames == ["aa", "b", "c"]
        with pytest.raises(TypeError):
            t.rename_columns("aa", ["a"])
        with pytest.raises(ValueError):
            t.rename_columns(["a"], ["b", "c"])


@pytest.mark.usefixtures("table_types")
class TestSort:
    def test_single(self, table_types):
        t = table_types.Table()
        t.add_column(table_types.Column(name="a", data=[2, 1, 3]))
        t.add_column(table_types.Column(name="b", data=[6, 5, 4]))
        t.add_column(
            table_types.Column(
                name="c",
                data=[
                    (1, 2),
                    (3, 4),
                    (4, 5),
                ],
            )
        )
        assert np.all(t["a"] == np.array([2, 1, 3]))
        assert np.all(t["b"] == np.array([6, 5, 4]))
        t.sort("a")
        assert np.all(t["a"] == np.array([1, 2, 3]))
        assert np.all(t["b"] == np.array([5, 6, 4]))
        assert np.all(
            t["c"]
            == np.array(
                [
                    [3, 4],
                    [1, 2],
                    [4, 5],
                ]
            )
        )
        t.sort("b")
        assert np.all(t["a"] == np.array([3, 1, 2]))
        assert np.all(t["b"] == np.array([4, 5, 6]))
        assert np.all(
            t["c"]
            == np.array(
                [
                    [4, 5],
                    [3, 4],
                    [1, 2],
                ]
            )
        )

    @pytest.mark.parametrize("create_index", [False, True])
    def test_single_reverse(self, table_types, create_index):
        t = table_types.Table()
        t.add_column(table_types.Column(name="a", data=[2, 1, 3]))
        t.add_column(table_types.Column(name="b", data=[6, 5, 4]))
        t.add_column(table_types.Column(name="c", data=[(1, 2), (3, 4), (4, 5)]))
        assert np.all(t["a"] == np.array([2, 1, 3]))
        assert np.all(t["b"] == np.array([6, 5, 4]))
        t.sort("a", reverse=True)
        assert np.all(t["a"] == np.array([3, 2, 1]))
        assert np.all(t["b"] == np.array([4, 6, 5]))
        assert np.all(t["c"] == np.array([[4, 5], [1, 2], [3, 4]]))
        t.sort("b", reverse=True)
        assert np.all(t["a"] == np.array([2, 1, 3]))
        assert np.all(t["b"] == np.array([6, 5, 4]))
        assert np.all(t["c"] == np.array([[1, 2], [3, 4], [4, 5]]))

    def test_single_big(self, table_types):
        """Sort a big-ish table with a non-trivial sort order"""
        x = np.arange(10000)
        y = np.sin(x)
        t = table_types.Table([x, y], names=("x", "y"))
        t.sort("y")
        idx = np.argsort(y)
        assert np.all(t["x"] == x[idx])
        assert np.all(t["y"] == y[idx])

    @pytest.mark.parametrize("reverse", [True, False])
    def test_empty_reverse(self, table_types, reverse):
        t = table_types.Table([[], []], dtype=["f4", "U1"])
        t.sort("col1", reverse=reverse)

    def test_multiple(self, table_types):
        t = table_types.Table()
        t.add_column(table_types.Column(name="a", data=[2, 1, 3, 2, 3, 1]))
        t.add_column(table_types.Column(name="b", data=[6, 5, 4, 3, 5, 4]))
        assert np.all(t["a"] == np.array([2, 1, 3, 2, 3, 1]))
        assert np.all(t["b"] == np.array([6, 5, 4, 3, 5, 4]))
        t.sort(["a", "b"])
        assert np.all(t["a"] == np.array([1, 1, 2, 2, 3, 3]))
        assert np.all(t["b"] == np.array([4, 5, 3, 6, 4, 5]))
        t.sort(["b", "a"])
        assert np.all(t["a"] == np.array([2, 1, 3, 1, 3, 2]))
        assert np.all(t["b"] == np.array([3, 4, 4, 5, 5, 6]))
        t.sort(("a", "b"))
        assert np.all(t["a"] == np.array([1, 1, 2, 2, 3, 3]))
        assert np.all(t["b"] == np.array([4, 5, 3, 6, 4, 5]))

    def test_multiple_reverse(self, table_types):
        t = table_types.Table()
        t.add_column(table_types.Column(name="a", data=[2, 1, 3, 2, 3, 1]))
        t.add_column(table_types.Column(name="b", data=[6, 5, 4, 3, 5, 4]))
        assert np.all(t["a"] == np.array([2, 1, 3, 2, 3, 1]))
        assert np.all(t["b"] == np.array([6, 5, 4, 3, 5, 4]))
        t.sort(["a", "b"], reverse=True)
        assert np.all(t["a"] == np.array([3, 3, 2, 2, 1, 1]))
        assert np.all(t["b"] == np.array([5, 4, 6, 3, 5, 4]))
        t.sort(["b", "a"], reverse=True)
        assert np.all(t["a"] == np.array([2, 3, 1, 3, 1, 2]))
        assert np.all(t["b"] == np.array([6, 5, 5, 4, 4, 3]))
        t.sort(("a", "b"), reverse=True)
        assert np.all(t["a"] == np.array([3, 3, 2, 2, 1, 1]))
        assert np.all(t["b"] == np.array([5, 4, 6, 3, 5, 4]))

    def test_multiple_with_bytes(self, table_types):
        t = table_types.Table()
        t.add_column(
            table_types.Column(name="firstname", data=[b"Max", b"Jo", b"John"])
        )
        t.add_column(
            table_types.Column(name="name", data=[b"Miller", b"Miller", b"Jackson"])
        )
        t.add_column(table_types.Column(name="tel", data=[12, 15, 19]))
        t.sort(["name", "firstname"])
        assert np.all([t["firstname"] == np.array([b"John", b"Jo", b"Max"])])
        assert np.all([t["name"] == np.array([b"Jackson", b"Miller", b"Miller"])])
        assert np.all([t["tel"] == np.array([19, 15, 12])])

    def test_multiple_with_unicode(self, table_types):
        # Before Numpy 1.6.2, sorting with multiple column names
        # failed when a unicode column was present.
        t = table_types.Table()
        t.add_column(
            table_types.Column(
                name="firstname", data=[str(x) for x in ["Max", "Jo", "John"]]
            )
        )
        t.add_column(
            table_types.Column(
                name="name", data=[str(x) for x in ["Miller", "Miller", "Jackson"]]
            )
        )
        t.add_column(table_types.Column(name="tel", data=[12, 15, 19]))
        t.sort(["name", "firstname"])
        assert np.all(
            [t["firstname"] == np.array([str(x) for x in ["John", "Jo", "Max"]])]
        )
        assert np.all(
            [t["name"] == np.array([str(x) for x in ["Jackson", "Miller", "Miller"]])]
        )
        assert np.all([t["tel"] == np.array([19, 15, 12])])

    def test_argsort(self, table_types):
        t = table_types.Table()
        t.add_column(table_types.Column(name="a", data=[2, 1, 3, 2, 3, 1]))
        t.add_column(table_types.Column(name="b", data=[6, 5, 4, 3, 5, 4]))
        assert np.all(t.argsort() == t.as_array().argsort())
        i0 = t.argsort("a")
        i1 = t.as_array().argsort(order=["a"])
        assert np.all(t["a"][i0] == t["a"][i1])
        i0 = t.argsort(["a", "b"])
        i1 = t.as_array().argsort(order=["a", "b"])
        assert np.all(t["a"][i0] == t["a"][i1])
        assert np.all(t["b"][i0] == t["b"][i1])

    @pytest.mark.parametrize("add_index", [False, True])
    def test_argsort_reverse(self, table_types, add_index):
        t = table_types.Table()
        t.add_column(table_types.Column(name="a", data=[2, 1, 3, 2, 3, 1]))
        t.add_column(table_types.Column(name="b", data=[6, 5, 4, 3, 5, 4]))
        if add_index:
            t.add_index("a")
        assert np.all(t.argsort(reverse=True) == np.array([4, 2, 0, 3, 1, 5]))
        i0 = t.argsort("a", reverse=True)
        i1 = np.array([4, 2, 3, 0, 5, 1])
        assert np.all(t["a"][i0] == t["a"][i1])
        i0 = t.argsort(["a", "b"], reverse=True)
        i1 = np.array([4, 2, 0, 3, 1, 5])
        assert np.all(t["a"][i0] == t["a"][i1])
        assert np.all(t["b"][i0] == t["b"][i1])

    def test_argsort_bytes(self, table_types):
        t = table_types.Table()
        t.add_column(
            table_types.Column(name="firstname", data=[b"Max", b"Jo", b"John"])
        )
        t.add_column(
            table_types.Column(name="name", data=[b"Miller", b"Miller", b"Jackson"])
        )
        t.add_column(table_types.Column(name="tel", data=[12, 15, 19]))
        assert np.all(t.argsort(["name", "firstname"]) == np.array([2, 1, 0]))

    def test_argsort_unicode(self, table_types):
        # Before Numpy 1.6.2, sorting with multiple column names
        # failed when a unicode column was present.
        t = table_types.Table()
        t.add_column(
            table_types.Column(
                name="firstname", data=[str(x) for x in ["Max", "Jo", "John"]]
            )
        )
        t.add_column(
            table_types.Column(
                name="name", data=[str(x) for x in ["Miller", "Miller", "Jackson"]]
            )
        )
        t.add_column(table_types.Column(name="tel", data=[12, 15, 19]))
        assert np.all(t.argsort(["name", "firstname"]) == np.array([2, 1, 0]))

    def test_rebuild_column_view_then_rename(self, table_types):
        """
        Issue #2039 where renaming fails after any method that calls
        _rebuild_table_column_view (this includes sort and add_row).
        """
        t = table_types.Table([[1]], names=("a",))
        assert t.colnames == ["a"]
        assert t.dtype.names == ("a",)

        t.add_row((2,))
        assert t.colnames == ["a"]
        assert t.dtype.names == ("a",)

        t.rename_column("a", "b")
        assert t.colnames == ["b"]
        assert t.dtype.names == ("b",)

        t.sort("b")
        assert t.colnames == ["b"]
        assert t.dtype.names == ("b",)

        t.rename_column("b", "c")
        assert t.colnames == ["c"]
        assert t.dtype.names == ("c",)


@pytest.mark.parametrize("kwargs", [{}, {"kind": "stable"}, {"kind": "quicksort"}])
def test_sort_kind(kwargs):
    t = Table()
    t["a"] = [2, 1, 3, 2, 3, 1]
    t["b"] = [6, 5, 4, 3, 5, 4]
    t_struct = t.as_array()
    # Since sort calls Table.argsort this covers `kind` for both methods
    t.sort(["a", "b"], **kwargs)
    assert np.all(t.as_array() == np.sort(t_struct, **kwargs))


@pytest.mark.usefixtures("table_types")
class TestIterator:
    def test_iterator(self, table_types):
        d = np.array(
            [
                (2, 1),
                (3, 6),
                (4, 5),
            ],
            dtype=[("a", "i4"), ("b", "i4")],
        )
        t = table_types.Table(d)
        if t.masked:
            with pytest.raises(ValueError):
                t[0] == d[0]
        else:
            for row, np_row in zip(t, d):
                assert np.all(row == np_row)


@pytest.mark.usefixtures("table_types")
class TestSetMeta:
    def test_set_meta(self, table_types):
        d = table_types.Table(names=("a", "b"))
        d.meta["a"] = 1
        d.meta["b"] = 1
        d.meta["c"] = 1
        d.meta["d"] = 1
        assert list(d.meta.keys()) == ["a", "b", "c", "d"]


@pytest.mark.usefixtures("table_types")
class TestConvertNumpyArray:
    def test_convert_numpy_array(self, table_types):
        d = table_types.Table([[1, 2], [3, 4]], names=("a", "b"))

        np_data = np.array(d)
        if table_types.Table is not MaskedTable:
            assert np.all(np_data == d.as_array())
        assert np_data is not d.as_array()
        assert d.colnames == list(np_data.dtype.names)

        np_data = np.array(d, copy=False)
        if table_types.Table is not MaskedTable:
            assert np.all(np_data == d.as_array())
        assert d.colnames == list(np_data.dtype.names)

        with pytest.raises(ValueError):
            np_data = np.array(d, dtype=[("c", "i8"), ("d", "i8")])

    def test_as_array_byteswap(self, table_types):
        """Test for https://github.com/astropy/astropy/pull/4080"""

        byte_orders = (">", "<")
        native_order = byte_orders[sys.byteorder == "little"]

        for order in byte_orders:
            col = table_types.Column([1.0, 2.0], name="a", dtype=order + "f8")
            t = table_types.Table([col])
            arr = t.as_array()
            assert arr["a"].dtype.byteorder in (native_order, "=")
            arr = t.as_array(keep_byteorder=True)
            if order == native_order:
                assert arr["a"].dtype.byteorder in (order, "=")
            else:
                assert arr["a"].dtype.byteorder == order

    def test_byteswap_fits_array(self, table_types):
        """
        Test for https://github.com/astropy/astropy/pull/4080, demonstrating
        that FITS tables are converted to native byte order.
        """

        non_native_order = (">", "<")[sys.byteorder != "little"]

        filename = get_pkg_data_filename("data/tb.fits", "astropy.io.fits.tests")
        t = table_types.Table.read(filename)
        arr = t.as_array()

        for idx in range(len(arr.dtype)):
            assert arr.dtype[idx].byteorder != non_native_order

        with fits.open(filename, character_as_bytes=True) as hdul:
            data = hdul[1].data
            for colname in data.columns.names:
                assert np.all(data[colname] == arr[colname])

            arr2 = t.as_array(keep_byteorder=True)
            for colname in data.columns.names:
                assert data[colname].dtype.byteorder == arr2[colname].dtype.byteorder

    def test_convert_numpy_object_array(self, table_types):
        d = table_types.Table([[1, 2], [3, 4]], names=("a", "b"))

        # Single table
        np_d = np.array(d, dtype=object)
        assert isinstance(np_d, np.ndarray)
        assert np_d[()] is d

    def test_convert_list_numpy_object_array(self, table_types):
        d = table_types.Table([[1, 2], [3, 4]], names=("a", "b"))
        ds = [d, d, d]
        np_ds = np.array(ds, dtype=object)
        assert all(isinstance(t, table_types.Table) for t in np_ds)
        assert all(np.array_equal(t, d) for t in np_ds)


def _assert_copies(t, t2, deep=True):
    assert t.colnames == t2.colnames
    np.testing.assert_array_equal(t.as_array(), t2.as_array())
    assert t.meta == t2.meta

    for col, col2 in zip(t.columns.values(), t2.columns.values()):
        if deep:
            assert not np.may_share_memory(col, col2)
        else:
            assert np.may_share_memory(col, col2)


def test_copy():
    t = table.Table([[1, 2, 3], [2, 3, 4]], names=["x", "y"])
    t2 = t.copy()
    _assert_copies(t, t2)


def test_copy_masked():
    t = table.Table(
        [[1, 2, 3], [2, 3, 4]], names=["x", "y"], masked=True, meta={"name": "test"}
    )
    t["x"].mask == [True, False, True]
    t2 = t.copy()
    _assert_copies(t, t2)


def test_copy_protocol():
    t = table.Table([[1, 2, 3], [2, 3, 4]], names=["x", "y"])

    t2 = copy.copy(t)
    t3 = copy.deepcopy(t)

    _assert_copies(t, t2, deep=False)
    _assert_copies(t, t3)


def test_disallow_inequality_comparisons():
    """
    Regression test for #828 - disallow comparison operators on whole Table
    """

    t = table.Table()

    with pytest.raises(TypeError):
        t > 2

    with pytest.raises(TypeError):
        t < 1.1

    with pytest.raises(TypeError):
        t >= 5.5

    with pytest.raises(TypeError):
        t <= -1.1


def test_values_equal_part1():
    col1 = [1, 2]
    col2 = [1.0, 2.0]
    col3 = ["a", "b"]
    t1 = table.Table([col1, col2, col3], names=["a", "b", "c"])
    t2 = table.Table([col1, col2], names=["a", "b"])
    t3 = table.table_helpers.simple_table()
    tm = t1.copy()
    tm["time"] = Time([1, 2], format="cxcsec")
    tm1 = tm.copy()
    tm1["time"][0] = np.ma.masked

    tq = table.table_helpers.simple_table()
    tq["quantity"] = [1.0, 2.0, 3.0] * u.m

    tsk = table.table_helpers.simple_table()
    tsk["sk"] = SkyCoord(1, 2, unit="deg")
    eqsk = tsk.values_equal(tsk)
    for col in eqsk.itercols():
        assert np.all(col)

    with pytest.raises(
        ValueError, match="cannot compare tables with different column names"
    ):
        t2.values_equal(t1)

    with pytest.raises(ValueError, match="unable to compare column a"):
        # Shape mismatch
        t3.values_equal(t1)

    if NUMPY_LT_1_25:
        with pytest.raises(ValueError, match="unable to compare column c"):
            # Type mismatch in column c causes FutureWarning
            t1.values_equal(2)

        with pytest.raises(ValueError, match="unable to compare column c"):
            t1.values_equal([1, 2])
    else:
        eq = t2.values_equal(2)
        for col in eq.colnames:
            assert np.all(eq[col] == [False, True])

        eq = t2.values_equal([1, 2])
        for col in eq.colnames:
            assert np.all(eq[col] == [True, True])

    eq = t2.values_equal(t2)
    for col in eq.colnames:
        assert np.all(eq[col] == [True, True])

    eq1 = tm1.values_equal(tm)
    for col in eq1.colnames:
        assert np.all(eq1[col] == [True, True])

    eq2 = tq.values_equal(tq)
    for col in eq2.colnames:
        assert np.all(eq2[col] == [True, True, True])

    eq3 = t2.values_equal(2)
    for col in eq3.colnames:
        assert np.all(eq3[col] == [False, True])

    eq4 = t2.values_equal([1, 2])
    for col in eq4.colnames:
        assert np.all(eq4[col] == [True, True])

    # Compare table to its first row
    t = table.Table(rows=[(1, "a"), (1, "b")])
    eq = t.values_equal(t[0])
    assert np.all(eq["col0"] == [True, True])
    assert np.all(eq["col1"] == [True, False])


def test_rows_equal():
    t = table.Table.read(
        [
            " a b  c  d",
            " 2 c 7.0 0",
            " 2 b 5.0 1",
            " 2 b 6.0 2",
            " 2 a 4.0 3",
            " 0 a 0.0 4",
            " 1 b 3.0 5",
            " 1 a 2.0 6",
            " 1 a 1.0 7",
        ],
        format="ascii",
    )

    # All rows are equal
    assert np.all(t == t)

    # Assert no rows are different
    assert not np.any(t != t)

    # Check equality result for a given row
    assert np.all((t == t[3]) == np.array([0, 0, 0, 1, 0, 0, 0, 0], dtype=bool))

    # Check inequality result for a given row
    assert np.all((t != t[3]) == np.array([1, 1, 1, 0, 1, 1, 1, 1], dtype=bool))

    t2 = table.Table.read(
        [
            " a b  c  d",
            " 2 c 7.0 0",
            " 2 b 5.0 1",
            " 3 b 6.0 2",
            " 2 a 4.0 3",
            " 0 a 1.0 4",
            " 1 b 3.0 5",
            " 1 c 2.0 6",
            " 1 a 1.0 7",
        ],
        format="ascii",
    )

    # In the above cases, Row.__eq__ gets called, but now need to make sure
    # Table.__eq__ also gets called.
    assert np.all((t == t2) == np.array([1, 1, 0, 1, 0, 1, 0, 1], dtype=bool))
    assert np.all((t != t2) == np.array([0, 0, 1, 0, 1, 0, 1, 0], dtype=bool))

    # Check that comparing to a structured array works
    assert np.all(
        (t == t2.as_array()) == np.array([1, 1, 0, 1, 0, 1, 0, 1], dtype=bool)
    )
    assert np.all(
        (t.as_array() == t2) == np.array([1, 1, 0, 1, 0, 1, 0, 1], dtype=bool)
    )


def test_equality_masked():
    t = table.Table.read(
        [
            " a b  c  d",
            " 2 c 7.0 0",
            " 2 b 5.0 1",
            " 2 b 6.0 2",
            " 2 a 4.0 3",
            " 0 a 0.0 4",
            " 1 b 3.0 5",
            " 1 a 2.0 6",
            " 1 a 1.0 7",
        ],
        format="ascii",
    )

    # Make into masked table
    t = table.Table(t, masked=True)

    # All rows are equal
    assert np.all(t == t)

    # Assert no rows are different
    assert not np.any(t != t)

    # Check equality result for a given row
    assert np.all((t == t[3]) == np.array([0, 0, 0, 1, 0, 0, 0, 0], dtype=bool))

    # Check inequality result for a given row
    assert np.all((t != t[3]) == np.array([1, 1, 1, 0, 1, 1, 1, 1], dtype=bool))

    t2 = table.Table.read(
        [
            " a b  c  d",
            " 2 c 7.0 0",
            " 2 b 5.0 1",
            " 3 b 6.0 2",
            " 2 a 4.0 3",
            " 0 a 1.0 4",
            " 1 b 3.0 5",
            " 1 c 2.0 6",
            " 1 a 1.0 7",
        ],
        format="ascii",
    )

    # In the above cases, Row.__eq__ gets called, but now need to make sure
    # Table.__eq__ also gets called.
    assert np.all((t == t2) == np.array([1, 1, 0, 1, 0, 1, 0, 1], dtype=bool))
    assert np.all((t != t2) == np.array([0, 0, 1, 0, 1, 0, 1, 0], dtype=bool))

    # Check that masking a value causes the row to differ
    t.mask["a"][0] = True
    assert np.all((t == t2) == np.array([0, 1, 0, 1, 0, 1, 0, 1], dtype=bool))
    assert np.all((t != t2) == np.array([1, 0, 1, 0, 1, 0, 1, 0], dtype=bool))

    # Check that comparing to a structured array works
    assert np.all(
        (t == t2.as_array()) == np.array([0, 1, 0, 1, 0, 1, 0, 1], dtype=bool)
    )


@pytest.mark.xfail
def test_equality_masked_bug():
    """
    This highlights a Numpy bug. Once it works, it can be moved into the
    test_equality_masked test. Related Numpy bug report:

      https://github.com/numpy/numpy/issues/3840
    """

    t = table.Table.read(
        [
            " a b  c  d",
            " 2 c 7.0 0",
            " 2 b 5.0 1",
            " 2 b 6.0 2",
            " 2 a 4.0 3",
            " 0 a 0.0 4",
            " 1 b 3.0 5",
            " 1 a 2.0 6",
            " 1 a 1.0 7",
        ],
        format="ascii",
    )

    t = table.Table(t, masked=True)

    t2 = table.Table.read(
        [
            " a b  c  d",
            " 2 c 7.0 0",
            " 2 b 5.0 1",
            " 3 b 6.0 2",
            " 2 a 4.0 3",
            " 0 a 1.0 4",
            " 1 b 3.0 5",
            " 1 c 2.0 6",
            " 1 a 1.0 7",
        ],
        format="ascii",
    )

    assert np.all(
        (t.as_array() == t2) == np.array([0, 1, 0, 1, 0, 1, 0, 1], dtype=bool)
    )


# Check that the meta descriptor is working as expected. The MetaBaseTest class
# takes care of defining all the tests, and we simply have to define the class
# and any minimal set of args to pass.


class TestMetaTable(MetaBaseTest):
    test_class = table.Table
    args = ()


def test_unicode_content():
    # If we don't have unicode literals then return
    if isinstance("", bytes):
        return

    # Define unicode literals
    string_a = "астрономическая питона"
    string_b = "миллиарды световых лет"

    a = table.Table([[string_a, 2], [string_b, 3]], names=("a", "b"))

    assert string_a in str(a)
    # This only works because the coding of this file is utf-8, which
    # matches the default encoding of Table.__str__
    assert string_a.encode("utf-8") in bytes(a)


def test_unicode_policy():
    t = table.Table.read(
        [
            " a b  c  d",
            " 2 c 7.0 0",
            " 2 b 5.0 1",
            " 2 b 6.0 2",
            " 2 a 4.0 3",
            " 0 a 0.0 4",
            " 1 b 3.0 5",
            " 1 a 2.0 6",
            " 1 a 1.0 7",
        ],
        format="ascii",
    )
    assert_follows_unicode_guidelines(t)


@pytest.mark.parametrize("uni", ["питона", "ascii"])
def test_unicode_bytestring_conversion(table_types, uni):
    """
    Test converting columns to all unicode or all bytestring.  This
    makes two columns, one which is unicode (str in Py3) and one which
    is bytes (UTF-8 encoded).  There are two code paths in the conversions,
    a faster one where the data are actually ASCII and a slower one where
    UTF-8 conversion is required.  This tests both via the ``uni`` param.
    """
    byt = uni.encode("utf-8")
    t = table_types.Table([[byt], [uni], [1]], dtype=("S", "U", "i"))
    assert t["col0"].dtype.kind == "S"
    assert t["col1"].dtype.kind == "U"
    assert t["col2"].dtype.kind == "i"
    t["col0"].description = "col0"
    t["col1"].description = "col1"
    t["col0"].meta["val"] = "val0"
    t["col1"].meta["val"] = "val1"

    # Unicode to bytestring
    t1 = t.copy()
    t1.convert_unicode_to_bytestring()
    assert t1["col0"].dtype.kind == "S"
    assert t1["col1"].dtype.kind == "S"
    assert t1["col2"].dtype.kind == "i"

    # Meta made it through
    assert t1["col0"].description == "col0"
    assert t1["col1"].description == "col1"
    assert t1["col0"].meta["val"] == "val0"
    assert t1["col1"].meta["val"] == "val1"

    # Need to de-fang the automatic unicode sandwiching of Table
    assert np.array(t1["col0"])[0] == byt
    assert np.array(t1["col1"])[0] == byt
    assert np.array(t1["col2"])[0] == 1

    # Bytestring to unicode
    t1 = t.copy()
    t1.convert_bytestring_to_unicode()
    assert t1["col0"].dtype.kind == "U"
    assert t1["col1"].dtype.kind == "U"
    assert t1["col2"].dtype.kind == "i"

    # Meta made it through
    assert t1["col0"].description == "col0"
    assert t1["col1"].description == "col1"
    assert t1["col0"].meta["val"] == "val0"
    assert t1["col1"].meta["val"] == "val1"

    # No need to de-fang the automatic unicode sandwiching of Table here, but
    # do just for consistency to prove things are working.
    assert np.array(t1["col0"])[0] == uni
    assert np.array(t1["col1"])[0] == uni
    assert np.array(t1["col2"])[0] == 1


def test_table_deletion():
    """
    Regression test for the reference cycle discussed in
    https://github.com/astropy/astropy/issues/2877
    """

    deleted = set()

    # A special table subclass which leaves a record when it is finalized
    class TestTable(table.Table):
        def __del__(self):
            deleted.add(id(self))

    t = TestTable({"a": [1, 2, 3]})
    the_id = id(t)
    assert t["a"].parent_table is t

    del t

    # Cleanup
    gc.collect()

    assert the_id in deleted


def test_nested_iteration():
    """
    Regression test for issue 3358 where nested iteration over a single table fails.
    """
    t = table.Table([[0, 1]], names=["a"])
    out = []
    for r1 in t:
        for r2 in t:
            out.append((r1["a"], r2["a"]))
    assert out == [(0, 0), (0, 1), (1, 0), (1, 1)]


def test_table_init_from_degenerate_arrays(table_types):
    t = table_types.Table(np.array([]))
    assert len(t.columns) == 0

    with pytest.raises(ValueError):
        t = table_types.Table(np.array(0))

    t = table_types.Table(np.array([1, 2, 3]))
    assert len(t.columns) == 3


@pytest.mark.skipif(not HAS_PANDAS, reason="requires pandas")
class TestPandas:
    def test_simple(self):
        t = table.Table()

        for endian in ["<", ">", "="]:
            for kind in ["f", "i"]:
                for byte in ["2", "4", "8"]:
                    dtype = np.dtype(endian + kind + byte)
                    x = np.array([1, 2, 3], dtype=dtype)
                    t[endian + kind + byte] = x.newbyteorder(endian)

        t["u"] = ["a", "b", "c"]
        t["s"] = ["a", "b", "c"]

        d = t.to_pandas()

        for column in t.columns:
            if column == "u":
                assert np.all(t["u"] == np.array(["a", "b", "c"]))
                assert d[column].dtype == np.dtype("O")  # upstream feature of pandas
            elif column == "s":
                assert np.all(t["s"] == np.array(["a", "b", "c"]))
                assert d[column].dtype == np.dtype("O")  # upstream feature of pandas
            else:
                # We should be able to compare exact values here
                assert np.all(t[column] == d[column])
                if t[column].dtype.isnative:
                    assert d[column].dtype == t[column].dtype
                else:
                    assert d[column].dtype == t[column].byteswap().newbyteorder().dtype

        # Regression test for astropy/astropy#1156 - the following code gave a
        # ValueError: Big-endian buffer not supported on little-endian
        # compiler. We now automatically swap the endian-ness to native order
        # upon adding the arrays to the data frame.
        # Explicitly testing little/big/native endian separately -
        # regression for a case in astropy/astropy#11286 not caught by #3729.
        d[["<i4", ">i4"]]
        d[["<f4", ">f4"]]

        t2 = table.Table.from_pandas(d)

        for column in t.columns:
            if column in ("u", "s"):
                assert np.all(t[column] == t2[column])
            else:
                assert_allclose(t[column], t2[column])
            if t[column].dtype.isnative:
                assert t[column].dtype == t2[column].dtype
            else:
                assert t[column].byteswap().newbyteorder().dtype == t2[column].dtype

    @pytest.mark.parametrize("unsigned", ["u", ""])
    @pytest.mark.parametrize("bits", [8, 16, 32, 64])
    def test_nullable_int(self, unsigned, bits):
        np_dtype = f"{unsigned}int{bits}"
        c = MaskedColumn([1, 2], mask=[False, True], dtype=np_dtype)
        t = Table([c])
        df = t.to_pandas()
        pd_dtype = np_dtype.replace("i", "I").replace("u", "U")
        assert str(df["col0"].dtype) == pd_dtype
        t2 = Table.from_pandas(df)
        assert str(t2["col0"].dtype) == np_dtype
        assert np.all(t2["col0"].mask == [False, True])
        assert np.all(t2["col0"] == c)

    def test_2d(self):
        t = table.Table()
        t["a"] = [1, 2, 3]
        t["b"] = np.ones((3, 2))

        with pytest.raises(
            ValueError, match="Cannot convert a table with multidimensional columns"
        ):
            t.to_pandas()

    def test_mixin_pandas(self):
        t = table.QTable()
        for name in sorted(MIXIN_COLS):
            if not name.startswith("ndarray"):
                t[name] = MIXIN_COLS[name]

        t["dt"] = TimeDelta([0, 2, 4, 6], format="sec")

        tp = t.to_pandas()
        t2 = table.Table.from_pandas(tp)

        assert np.allclose(t2["quantity"], [0, 1, 2, 3])
        assert np.allclose(t2["longitude"], [0.0, 1.0, 5.0, 6.0])
        assert np.allclose(t2["latitude"], [5.0, 6.0, 10.0, 11.0])
        assert np.allclose(t2["skycoord.ra"], [0, 1, 2, 3])
        assert np.allclose(t2["skycoord.dec"], [0, 1, 2, 3])
        assert np.allclose(t2["arraywrap"], [0, 1, 2, 3])
        assert np.allclose(t2["arrayswap"], [0, 1, 2, 3])
        assert np.allclose(
            t2["earthlocation.y"], [0, 110708, 547501, 654527], rtol=0, atol=1
        )

        # For pandas, Time, TimeDelta are the mixins that round-trip the class
        assert isinstance(t2["time"], Time)
        assert np.allclose(t2["time"].jyear, [2000, 2001, 2002, 2003])
        assert np.all(
            t2["time"].isot
            == [
                "2000-01-01T12:00:00.000",
                "2000-12-31T18:00:00.000",
                "2002-01-01T00:00:00.000",
                "2003-01-01T06:00:00.000",
            ]
        )
        assert t2["time"].format == "isot"

        # TimeDelta
        assert isinstance(t2["dt"], TimeDelta)
        assert np.allclose(t2["dt"].value, [0, 2, 4, 6])
        assert t2["dt"].format == "sec"

    @pytest.mark.parametrize("use_IndexedTable", [False, True])
    def test_to_pandas_index(self, use_IndexedTable):
        """Test to_pandas() with different indexing options.

        This also tests the fix for #12014. The exception seen there is
        reproduced here without the fix.
        """
        import pandas as pd

        class IndexedTable(table.QTable):
            """Always index the first column"""

            def __init__(self, *args, **kwargs):
                super().__init__(*args, **kwargs)
                self.add_index(self.colnames[0])

        row_index = pd.RangeIndex(0, 2, 1)
        tm_index = pd.DatetimeIndex(
            ["1998-01-01", "2002-01-01"], dtype="datetime64[ns]", name="tm", freq=None
        )

        tm = Time([1998, 2002], format="jyear")
        x = [1, 2]
        table_cls = IndexedTable if use_IndexedTable else table.QTable
        t = table_cls([tm, x], names=["tm", "x"])
        tp = t.to_pandas()

        if not use_IndexedTable:
            assert np.all(tp.index == row_index)
            tp = t.to_pandas(index="tm")
            assert np.all(tp.index == tm_index)
            t.add_index("tm")

        tp = t.to_pandas()
        assert np.all(tp.index == tm_index)
        # Make sure writing to pandas didn't hack the original table
        assert t["tm"].info.indices

        tp = t.to_pandas(index=True)
        assert np.all(tp.index == tm_index)

        tp = t.to_pandas(index=False)
        assert np.all(tp.index == row_index)

        with pytest.raises(ValueError) as err:
            t.to_pandas(index="not a column")
        assert "index must be None, False" in str(err.value)

    def test_mixin_pandas_masked(self):
        tm = Time([1, 2, 3], format="cxcsec")
        dt = TimeDelta([1, 2, 3], format="sec")
        tm[1] = np.ma.masked
        dt[1] = np.ma.masked
        t = table.QTable([tm, dt], names=["tm", "dt"])

        tp = t.to_pandas()
        assert np.all(tp["tm"].isnull() == [False, True, False])
        assert np.all(tp["dt"].isnull() == [False, True, False])

        t2 = table.Table.from_pandas(tp)

        assert np.all(t2["tm"].mask == tm.mask)
        assert np.ma.allclose(t2["tm"].jd, tm.jd, rtol=1e-14, atol=1e-14)

        assert np.all(t2["dt"].mask == dt.mask)
        assert np.ma.allclose(t2["dt"].jd, dt.jd, rtol=1e-14, atol=1e-14)

    def test_from_pandas_index(self):
        tm = Time([1998, 2002], format="jyear")
        x = [1, 2]
        t = table.Table([tm, x], names=["tm", "x"])
        tp = t.to_pandas(index="tm")

        t2 = table.Table.from_pandas(tp)
        assert t2.colnames == ["x"]

        t2 = table.Table.from_pandas(tp, index=True)
        assert t2.colnames == ["tm", "x"]
        assert np.allclose(t2["tm"].jyear, tm.jyear)

    @pytest.mark.parametrize("use_nullable_int", [True, False])
    def test_masking(self, use_nullable_int):
        t = table.Table(masked=True)

        t["a"] = [1, 2, 3]
        t["a"].mask = [True, False, True]

        t["b"] = [1.0, 2.0, 3.0]
        t["b"].mask = [False, False, True]

        t["u"] = ["a", "b", "c"]
        t["u"].mask = [False, True, False]

        t["s"] = ["a", "b", "c"]
        t["s"].mask = [False, True, False]

        # https://github.com/astropy/astropy/issues/7741
        t["Source"] = [2584290278794471936, 2584290038276303744, 2584288728310999296]
        t["Source"].mask = [False, False, False]

        if use_nullable_int:  # Default
            # No warning with the default use_nullable_int=True
            d = t.to_pandas(use_nullable_int=use_nullable_int)
        else:
            import pandas
            from packaging.version import Version

            PANDAS_LT_2_0 = Version(pandas.__version__) < Version("2.0dev")
            if PANDAS_LT_2_0:
                with pytest.warns(
                    TableReplaceWarning,
                    match=r"converted column 'a' from int(32|64) to float64",
                ):
                    d = t.to_pandas(use_nullable_int=use_nullable_int)
            else:
                from pandas.core.dtypes.cast import IntCastingNaNError

                with pytest.raises(
                    IntCastingNaNError,
                    match=r"Cannot convert non-finite values \(NA or inf\) to integer",
                ):
                    d = t.to_pandas(use_nullable_int=use_nullable_int)
                return  # Do not continue

        t2 = table.Table.from_pandas(d)

        for name, column in t.columns.items():
            assert np.all(column.data == t2[name].data)
            if hasattr(t2[name], "mask"):
                assert np.all(column.mask == t2[name].mask)

            if column.dtype.kind == "i":
                if np.any(column.mask) and not use_nullable_int:
                    assert t2[name].dtype.kind == "f"
                else:
                    assert t2[name].dtype.kind == "i"

                # This warning pops up when use_nullable_int is False
                # for pandas 1.5.2.
                with np.errstate(invalid="ignore"):
                    assert_array_equal(column.data, t2[name].data.astype(column.dtype))
            else:
                if column.dtype.byteorder in ("=", "|"):
                    assert column.dtype == t2[name].dtype
                else:
                    assert column.byteswap().newbyteorder().dtype == t2[name].dtype

    def test_units(self):
        import pandas as pd

        import astropy.units as u

        df = pd.DataFrame({"x": [1, 2, 3], "t": [1.3, 1.2, 1.8]})
        t = table.Table.from_pandas(df, units={"x": u.m, "t": u.s})

        assert t["x"].unit == u.m
        assert t["t"].unit == u.s

        # test error if not a mapping
        with pytest.raises(TypeError):
            table.Table.from_pandas(df, units=[u.m, u.s])

        # test warning is raised if additional columns in units dict
        with pytest.warns(UserWarning) as record:
            table.Table.from_pandas(df, units={"x": u.m, "t": u.s, "y": u.m})
        assert len(record) == 1
        assert "{'y'}" in record[0].message.args[0]

    def test_to_pandas_masked_int_data_with__index(self):
        data = {"data": [0, 1, 2], "index": [10, 11, 12]}
        t = table.Table(data=data, masked=True)

        t.add_index("index")
        t["data"].mask = [1, 1, 0]

        df = t.to_pandas()

        assert df["data"].iloc[-1] == 2


@pytest.mark.usefixtures("table_types")
class TestReplaceColumn(SetupData):
    def test_fail_replace_column(self, table_types):
        """Raise exception when trying to replace column via table.columns object"""
        self._setup(table_types)
        t = table_types.Table([self.a, self.b])

        with pytest.raises(
            ValueError,
            match=r"Cannot replace column 'a'.  Use " "Table.replace_column.. instead.",
        ):
            t.columns["a"] = [1, 2, 3]

        with pytest.raises(
            ValueError, match=r"column name not there is not in the table"
        ):
            t.replace_column("not there", [1, 2, 3])

        with pytest.raises(
            ValueError, match=r"length of new column must match table length"
        ):
            t.replace_column("a", [1, 2])

    def test_replace_column(self, table_types):
        """Replace existing column with a new column"""
        self._setup(table_types)
        t = table_types.Table([self.a, self.b])
        ta = t["a"]
        tb = t["b"]

        vals = [1.2, 3.4, 5.6]
        for col in (
            vals,
            table_types.Column(vals),
            table_types.Column(vals, name="a"),
            table_types.Column(vals, name="b"),
        ):
            t.replace_column("a", col)
            assert np.all(t["a"] == vals)
            assert t["a"] is not ta  # New a column
            assert t["b"] is tb  # Original b column unchanged
            assert t.colnames == ["a", "b"]
            assert t["a"].meta == {}
            assert t["a"].format is None

        # Special case: replacing the only column can resize table
        del t["b"]
        assert len(t) == 3
        t["a"] = [1, 2]
        assert len(t) == 2

    def test_replace_index_column(self, table_types):
        """Replace index column and generate expected exception"""
        self._setup(table_types)
        t = table_types.Table([self.a, self.b])
        t.add_index("a")

        with pytest.raises(ValueError) as err:
            t.replace_column("a", [1, 2, 3])
        assert err.value.args[0] == "cannot replace a table index column"

    def test_replace_column_no_copy(self):
        t = Table([[1, 2], [3, 4]], names=["a", "b"])
        a = np.array([1.5, 2.5])
        t.replace_column("a", a, copy=False)
        assert t["a"][0] == a[0]
        t["a"][0] = 10
        assert t["a"][0] == a[0]


class TestQTableColumnConversionCornerCases:
    def test_replace_with_masked_col_with_units_in_qtable(self):
        """This is a small regression from #8902"""
        t = QTable([[1, 2], [3, 4]], names=["a", "b"])
        t["a"] = MaskedColumn([5, 6], unit="m")
        assert isinstance(t["a"], u.Quantity)

    def test_do_not_replace_string_column_with_units_in_qtable(self):
        t = QTable([[1 * u.m]])
        with pytest.warns(AstropyUserWarning, match="convert it to Quantity failed"):
            t["a"] = Column(["a"], unit=u.m)
        assert isinstance(t["a"], Column)


class Test__Astropy_Table__:
    """
    Test initializing a Table subclass from a table-like object that
    implements the __astropy_table__ interface method.
    """

    class SimpleTable:
        def __init__(self):
            self.columns = [[1, 2, 3], [4, 5, 6], [7, 8, 9] * u.m]
            self.names = ["a", "b", "c"]
            self.meta = OrderedDict([("a", 1), ("b", 2)])

        def __astropy_table__(self, cls, copy, **kwargs):
            a, b, c = self.columns
            c.info.name = "c"
            cols = [table.Column(a, name="a"), table.MaskedColumn(b, name="b"), c]
            names = [col.info.name for col in cols]
            return cls(cols, names=names, copy=copy, meta=kwargs or self.meta)

    def test_simple_1(self):
        """Make a SimpleTable and convert to Table, QTable with copy=False, True"""
        for table_cls in (table.Table, table.QTable):
            col_c_class = u.Quantity if table_cls is table.QTable else table.Column
            for cpy in (False, True):
                st = self.SimpleTable()
                # Test putting in a non-native kwarg `extra_meta` to Table initializer
                t = table_cls(st, copy=cpy, extra_meta="extra!")
                assert t.colnames == ["a", "b", "c"]
                assert t.meta == {"extra_meta": "extra!"}
                assert np.all(t["a"] == st.columns[0])
                assert np.all(t["b"] == st.columns[1])
                vals = t["c"].value if table_cls is table.QTable else t["c"]
                assert np.all(st.columns[2].value == vals)

                assert isinstance(t["a"], table.Column)
                assert isinstance(t["b"], table.MaskedColumn)
                assert isinstance(t["c"], col_c_class)
                assert t["c"].unit is u.m
                assert type(t) is table_cls

                # Copy being respected?
                t["a"][0] = 10
                assert st.columns[0][0] == 1 if cpy else 10

    def test_simple_2(self):
        """Test converting a SimpleTable and changing column names and types"""
        st = self.SimpleTable()
        dtypes = [np.int32, np.float32, np.float16]
        names = ["a", "b", "c"]
        meta = OrderedDict([("c", 3)])
        t = table.Table(st, dtype=dtypes, names=names, meta=meta)
        assert t.colnames == names
        assert all(
            col.dtype.type is dtype for col, dtype in zip(t.columns.values(), dtypes)
        )

        # The supplied meta is overrides the existing meta.  Changed in astropy 3.2.
        assert t.meta != st.meta
        assert t.meta == meta

    def test_kwargs_exception(self):
        """If extra kwargs provided but without initializing with a table-like
        object, exception is raised"""
        with pytest.raises(TypeError) as err:
            table.Table([[1]], extra_meta="extra!")
        assert "__init__() got unexpected keyword argument" in str(err.value)


class TestUpdate:
    def _setup(self):
        self.a = Column((1, 2, 3), name="a")
        self.b = Column((4, 5, 6), name="b")
        self.c = Column((7, 8, 9), name="c")
        self.d = Column((10, 11, 12), name="d")

    def test_different_lengths(self):
        self._setup()
        t1 = Table([self.a])
        t2 = Table([self.b[:-1]])
        msg = "Inconsistent data column lengths"
        with pytest.raises(ValueError, match=msg):
            t1.update(t2)
        # If update didn't succeed then t1 and t2 should not have changed.
        assert t1.colnames == ["a"]
        assert np.all(t1["a"] == self.a)
        assert t2.colnames == ["b"]
        assert np.all(t2["b"] == self.b[:-1])

    def test_invalid_inputs(self):
        # If input is invalid then nothing should be modified.
        self._setup()
        t = Table([self.a])
        d = {"b": self.b, "c": [0]}
        msg = "Inconsistent data column lengths: {1, 3}"
        with pytest.raises(ValueError, match=msg):
            t.update(d)
        assert t.colnames == ["a"]
        assert np.all(t["a"] == self.a)
        assert d == {"b": self.b, "c": [0]}

    def test_metadata_conflict(self):
        self._setup()
        t1 = Table([self.a], meta={"a": 0, "b": [0], "c": True})
        t2 = Table([self.b], meta={"a": 1, "b": [1]})
        t2meta = copy.deepcopy(t2.meta)
        t1.update(t2)
        assert t1.meta == {"a": 1, "b": [0, 1], "c": True}
        # t2 metadata should not have changed.
        assert t2.meta == t2meta

    def test_update(self):
        self._setup()
        t1 = Table([self.a, self.b])
        t2 = Table([self.b, self.c])
        t2["b"] += 1
        t1.update(t2)
        assert t1.colnames == ["a", "b", "c"]
        assert np.all(t1["a"] == self.a)
        assert np.all(t1["b"] == self.b + 1)
        assert np.all(t1["c"] == self.c)
        # t2 should not have changed.
        assert t2.colnames == ["b", "c"]
        assert np.all(t2["b"] == self.b + 1)
        assert np.all(t2["c"] == self.c)

        d = {"b": list(self.b), "d": list(self.d)}
        dc = copy.deepcopy(d)
        t2.update(d)
        assert t2.colnames == ["b", "c", "d"]
        assert np.all(t2["b"] == self.b)
        assert np.all(t2["c"] == self.c)
        assert np.all(t2["d"] == self.d)
        # d should not have changed.
        assert d == dc

        # Columns were copied, so changing t2 shouldn't have affected t1.
        assert t1.colnames == ["a", "b", "c"]
        assert np.all(t1["a"] == self.a)
        assert np.all(t1["b"] == self.b + 1)
        assert np.all(t1["c"] == self.c)

    def test_update_without_copy(self):
        self._setup()
        t1 = Table([self.a, self.b])
        t2 = Table([self.b, self.c])
        t1.update(t2, copy=False)
        t2["b"] -= 1
        assert t1.colnames == ["a", "b", "c"]
        assert np.all(t1["a"] == self.a)
        assert np.all(t1["b"] == self.b - 1)
        assert np.all(t1["c"] == self.c)

        d = {"b": np.array(self.b), "d": np.array(self.d)}
        t2.update(d, copy=False)
        d["b"] *= 2
        assert t2.colnames == ["b", "c", "d"]
        assert np.all(t2["b"] == 2 * self.b)
        assert np.all(t2["c"] == self.c)
        assert np.all(t2["d"] == self.d)

    def test_merge_operator(self):
        self._setup()
        t1 = Table([self.a, self.b])
        t2 = Table([self.b, self.c])
        with pytest.raises(TypeError):
            _ = 1 | t1
        with pytest.raises(TypeError):
            _ = t1 | 1

        t1_copy = t1.copy(True)
        t3 = t1 | t2
        assert t1.colnames == ["a", "b"]  # t1 should remain unchanged
        assert np.all(t1["a"] == self.a)
        assert np.all(t1["b"] == self.b)

        t1_copy.update(t2)
        assert t3.colnames == ["a", "b", "c"]
        assert np.all(t3["a"] == t1_copy["a"])
        assert np.all(t3["b"] == t1_copy["b"])
        assert np.all(t3["c"] == t1_copy["c"])

    def test_update_operator(self):
        self._setup()
        t1 = Table([self.a, self.b])
        t2 = Table([self.b, self.c])
        with pytest.raises(ValueError):
            t1 |= 1

        t1_copy = t1.copy(True)
        t1 |= t2
        t1_copy.update(t2)
        assert t1.colnames == ["a", "b", "c"]
        assert np.all(t1["a"] == t1_copy["a"])
        assert np.all(t1["b"] == t1_copy["b"])
        assert np.all(t1["c"] == t1_copy["c"])


def test_table_meta_copy():
    """
    Test no copy vs light (key) copy vs deep copy of table meta for different
    situations.  #8404.
    """
    t = table.Table([[1]])
    meta = {1: [1, 2]}

    # Assigning meta directly implies using direct object reference
    t.meta = meta
    assert t.meta is meta

    # Table slice implies key copy, so values are unchanged
    t2 = t[:]
    assert t2.meta is not t.meta  # NOT the same OrderedDict object but equal
    assert t2.meta == t.meta
    assert t2.meta[1] is t.meta[1]  # Value IS the list same object

    # Table init with copy=False implies key copy
    t2 = table.Table(t, copy=False)
    assert t2.meta is not t.meta  # NOT the same OrderedDict object but equal
    assert t2.meta == t.meta
    assert t2.meta[1] is t.meta[1]  # Value IS the same list object

    # Table init with copy=True implies deep copy
    t2 = table.Table(t, copy=True)
    assert t2.meta is not t.meta  # NOT the same OrderedDict object but equal
    assert t2.meta == t.meta
    assert t2.meta[1] is not t.meta[1]  # Value is NOT the same list object


def test_table_meta_copy_with_meta_arg():
    """
    Test no copy vs light (key) copy vs deep copy of table meta when meta is
    supplied as a table init argument.  #8404.
    """
    meta = {1: [1, 2]}
    meta2 = {2: [3, 4]}
    t = table.Table([[1]], meta=meta, copy=False)
    assert t.meta is meta

    t = table.Table([[1]], meta=meta)  # default copy=True
    assert t.meta is not meta
    assert t.meta == meta

    # Test initializing from existing table with meta with copy=False
    t2 = table.Table(t, meta=meta2, copy=False)
    assert t2.meta is meta2
    assert t2.meta != t.meta  # Change behavior in #8404

    # Test initializing from existing table with meta with default copy=True
    t2 = table.Table(t, meta=meta2)
    assert t2.meta is not meta2
    assert t2.meta != t.meta  # Change behavior in #8404

    # Table init with copy=True and empty dict meta gets that empty dict
    t2 = table.Table(t, copy=True, meta={})
    assert t2.meta == {}

    # Table init with copy=True and kwarg meta=None gets the original table dict.
    # This is a somewhat ambiguous case because it could be interpreted as the
    # user wanting NO meta set on the output.  This could be implemented by inspecting
    # call args.
    t2 = table.Table(t, copy=True, meta=None)
    assert t2.meta == t.meta

    # Test initializing empty table with meta with copy=False
    t = table.Table(meta=meta, copy=False)
    assert t.meta is meta
    assert t.meta[1] is meta[1]

    # Test initializing empty table with meta with default copy=True (deepcopy meta)
    t = table.Table(meta=meta)
    assert t.meta is not meta
    assert t.meta == meta
    assert t.meta[1] is not meta[1]


def test_replace_column_qtable():
    """Replace existing Quantity column with a new column in a QTable"""
    a = [1, 2, 3] * u.m
    b = [4, 5, 6]
    t = table.QTable([a, b], names=["a", "b"])

    ta = t["a"]
    tb = t["b"]
    ta.info.meta = {"aa": [0, 1, 2, 3, 4]}
    ta.info.format = "%f"

    t.replace_column("a", a.to("cm"))
    assert np.all(t["a"] == ta)
    assert t["a"] is not ta  # New a column
    assert t["b"] is tb  # Original b column unchanged
    assert t.colnames == ["a", "b"]
    assert t["a"].info.meta is None
    assert t["a"].info.format is None


def test_replace_update_column_via_setitem():
    """
    Test table update like ``t['a'] = value``.  This leverages off the
    already well-tested ``replace_column`` and in-place update
    ``t['a'][:] = value``, so this testing is fairly light.
    """
    a = [1, 2] * u.m
    b = [3, 4]
    t = table.QTable([a, b], names=["a", "b"])
    assert isinstance(t["a"], u.Quantity)

    # Inplace update
    ta = t["a"]
    t["a"] = 5 * u.m
    assert np.all(t["a"] == [5, 5] * u.m)
    assert t["a"] is ta

    # Replace
    t["a"] = [5, 6]
    assert np.all(t["a"] == [5, 6])
    assert isinstance(t["a"], table.Column)
    assert t["a"] is not ta


def test_replace_update_column_via_setitem_warnings_normal():
    """
    Test warnings related to table replace change in #5556:
    Normal warning-free replace
    """
    t = table.Table([[1, 2, 3], [4, 5, 6]], names=["a", "b"])
    with table.conf.set_temp("replace_warnings", ["refcount", "attributes", "slice"]):
        t["a"] = 0  # in-place update
        t["a"] = [10, 20, 30]  # replace column


def test_replace_update_column_via_setitem_warnings_slice():
    """
    Test warnings related to table replace change in #5556:
    Replace a slice, one warning.
    """
    t = table.Table([[1, 2, 3], [4, 5, 6]], names=["a", "b"])
    with table.conf.set_temp("replace_warnings", ["refcount", "attributes", "slice"]):
        t2 = t[:2]

        t2["a"] = 0  # in-place slice update
        assert np.all(t["a"] == [0, 0, 3])

        with pytest.warns(
            TableReplaceWarning,
            match="replaced column 'a' which looks like an array slice",
        ) as w:
            t2["a"] = [10, 20]  # replace slice
        assert len(w) == 1


def test_replace_update_column_via_setitem_warnings_attributes():
    """
    Test warnings related to table replace change in #5556:
    Lost attributes.
    """
    t = table.Table([[1, 2, 3], [4, 5, 6]], names=["a", "b"])
    t["a"].unit = "m"

    with pytest.warns(
        TableReplaceWarning,
        match=r"replaced column 'a' " r"and column attributes \['unit'\]",
    ) as w:
        with table.conf.set_temp(
            "replace_warnings", ["refcount", "attributes", "slice"]
        ):
            t["a"] = [10, 20, 30]
    assert len(w) == 1


def test_replace_update_column_via_setitem_warnings_refcount():
    """
    Test warnings related to table replace change in #5556:
    Reference count changes.
    """
    t = table.Table([[1, 2, 3], [4, 5, 6]], names=["a", "b"])
    ta = t["a"]  # Generate an extra reference to original column

    with pytest.warns(
        TableReplaceWarning, match="replaced column 'a' and the number of references"
    ) as w:
        with table.conf.set_temp(
            "replace_warnings", ["refcount", "attributes", "slice"]
        ):
            t["a"] = [10, 20, 30]
    assert len(w) == 1


def test_replace_update_column_via_setitem_warnings_always():
    """
    Test warnings related to table replace change in #5556:
    Test 'always' setting that raises warning for any replace.
    """
    from inspect import currentframe, getframeinfo

    t = table.Table([[1, 2, 3], [4, 5, 6]], names=["a", "b"])

    with table.conf.set_temp("replace_warnings", ["always"]):
        t["a"] = 0  # in-place slice update

        with pytest.warns(TableReplaceWarning, match="replaced column 'a'") as w:
            frameinfo = getframeinfo(currentframe())
            t["a"] = [10, 20, 30]  # replace column
        assert len(w) == 1

        # Make sure the warning points back to the user code line
        assert w[0].lineno == frameinfo.lineno + 1
        assert "test_table" in w[0].filename


def test_replace_update_column_via_setitem_replace_inplace():
    """
    Test the replace_inplace config option related to #5556.  In this
    case no replace is done.
    """
    t = table.Table([[1, 2, 3], [4, 5, 6]], names=["a", "b"])
    ta = t["a"]
    t["a"].unit = "m"

    with table.conf.set_temp("replace_inplace", True):
        with table.conf.set_temp(
            "replace_warnings", ["always", "refcount", "attributes", "slice"]
        ):
            t["a"] = 0  # in-place update
            assert ta is t["a"]

            t["a"] = [10, 20, 30]  # normally replaces column, but not now
            assert ta is t["a"]
            assert np.all(t["a"] == [10, 20, 30])


def test_primary_key_is_inherited():
    """Test whether a new Table inherits the primary_key attribute from
    its parent Table. Issue #4672"""

    t = table.Table([(2, 3, 2, 1), (8, 7, 6, 5)], names=("a", "b"))
    t.add_index("a")
    original_key = t.primary_key

    # can't test if tuples are equal, so just check content
    assert original_key[0] == "a"

    t2 = t[:]
    t3 = t.copy()
    t4 = table.Table(t)

    # test whether the reference is the same in the following
    assert original_key == t2.primary_key
    assert original_key == t3.primary_key
    assert original_key == t4.primary_key

    # just test one element, assume rest are equal if assert passes
    assert t.loc[1] == t2.loc[1]
    assert t.loc[1] == t3.loc[1]
    assert t.loc[1] == t4.loc[1]


def test_qtable_read_for_ipac_table_with_char_columns():
    """Test that a char column of a QTable is assigned no unit and not
    a dimensionless unit, otherwise conversion of reader output to
    QTable fails."""
    t1 = table.QTable([["A"]], names="B")
    out = StringIO()
    t1.write(out, format="ascii.ipac")
    t2 = table.QTable.read(out.getvalue(), format="ascii.ipac", guess=False)
    assert t2["B"].unit is None


def test_create_table_from_final_row():
    """Regression test for issue #8422: passing the last row of a table into
    Table should return a new table containing that row."""
    t1 = table.Table([(1, 2)], names=["col"])
    row = t1[-1]
    t2 = table.Table(row)["col"]
    assert t2[0] == 2


def test_key_values_in_as_array():
    # Test for checking column slicing using key_values in Table.as_array()
    data_rows = [(1, 2.0, "x"), (4, 5.0, "y"), (5, 8.2, "z")]
    # Creating a table with three columns
    t1 = table.Table(
        rows=data_rows,
        names=("a", "b", "c"),
        meta={"name": "first table"},
        dtype=("i4", "f8", "S1"),
    )
    # Values of sliced column a,b is stored in a numpy array
    a = np.array([(1, 2.0), (4, 5.0), (5, 8.2)], dtype=[("a", "<i4"), ("b", "<f8")])
    # Values for sliced column c is stored in a numpy array
    b = np.array([(b"x",), (b"y",), (b"z",)], dtype=[("c", "S1")])
    # Comparing initialised array with sliced array using Table.as_array()
    assert np.array_equal(a, t1.as_array(names=["a", "b"]))
    assert np.array_equal(b, t1.as_array(names=["c"]))


def test_tolist():
    t = table.Table(
        [[1, 2, 3], [1.1, 2.2, 3.3], [b"foo", b"bar", b"hello"]], names=("a", "b", "c")
    )
    assert t["a"].tolist() == [1, 2, 3]
    assert_array_equal(t["b"].tolist(), [1.1, 2.2, 3.3])
    assert t["c"].tolist() == ["foo", "bar", "hello"]

    assert isinstance(t["a"].tolist()[0], int)
    assert isinstance(t["b"].tolist()[0], float)
    assert isinstance(t["c"].tolist()[0], str)

    t = table.Table(
        [[[1, 2], [3, 4]], [[b"foo", b"bar"], [b"hello", b"world"]]], names=("a", "c")
    )

    assert t["a"].tolist() == [[1, 2], [3, 4]]
    assert t["c"].tolist() == [["foo", "bar"], ["hello", "world"]]
    assert isinstance(t["a"].tolist()[0][0], int)
    assert isinstance(t["c"].tolist()[0][0], str)


class MyTable(Table):
    foo = TableAttribute()
    bar = TableAttribute(default=[])
    baz = TableAttribute(default=1)


def test_table_attribute():
    assert repr(MyTable.baz) == "<TableAttribute name=baz default=1>"

    t = MyTable([[1, 2]])
    # __attributes__ created on the fly on the first access of an attribute
    # that has a non-None default.
    assert "__attributes__" not in t.meta
    assert t.foo is None
    assert "__attributes__" not in t.meta
    assert t.baz == 1
    assert "__attributes__" in t.meta
    t.bar.append(2.0)
    assert t.bar == [2.0]
    assert t.baz == 1

    t.baz = "baz"
    assert t.baz == "baz"

    # Table attributes round-trip through pickle
    tp = pickle.loads(pickle.dumps(t))
    assert tp.foo is None
    assert tp.baz == "baz"
    assert tp.bar == [2.0]

    # Allow initialization of attributes in table creation, with / without data
    for data in None, [[1, 2]]:
        t2 = MyTable(data, foo=3, bar="bar", baz="baz")
        assert t2.foo == 3
        assert t2.bar == "bar"
        assert t2.baz == "baz"

    # Initializing from an existing MyTable works, with and without kwarg attrs
    t3 = MyTable(t2)
    assert t3.foo == 3
    assert t3.bar == "bar"
    assert t3.baz == "baz"

    t3 = MyTable(t2, foo=5, bar="fubar")
    assert t3.foo == 5
    assert t3.bar == "fubar"
    assert t3.baz == "baz"

    # Deleting attributes removes it from attributes
    del t.baz
    assert "baz" not in t.meta["__attributes__"]
    del t.bar
    assert "__attributes__" not in t.meta


def test_table_attribute_ecsv():
    # Table attribute round-trip through ECSV
    t = MyTable([[1, 2]], bar=[2.0], baz="baz")
    out = StringIO()
    t.write(out, format="ascii.ecsv")
    t2 = MyTable.read(out.getvalue(), format="ascii.ecsv")
    assert t2.foo is None
    assert t2.bar == [2.0]
    assert t2.baz == "baz"


def test_table_attribute_fail():
    # Code raises ValueError(f'{attr} not allowed as TableAttribute') but in this
    # context it gets re-raised as a RuntimeError during class definition.
    with pytest.raises(RuntimeError, match="Error calling __set_name__"):

        class MyTable2(Table):
            descriptions = TableAttribute()  # Conflicts with init arg

    with pytest.raises(RuntimeError, match="Error calling __set_name__"):

        class MyTable3(Table):
            colnames = TableAttribute()  # Conflicts with built-in property


def test_set_units_fail():
    dat = [[1.0, 2.0], ["aa", "bb"]]
    with pytest.raises(
        ValueError, match="sequence of unit values must match number of columns"
    ):
        Table(dat, units=[u.m])
    with pytest.raises(
        ValueError, match="invalid column name c for setting unit attribute"
    ):
        Table(dat, units={"c": u.m})


def test_set_units():
    dat = [[1.0, 2.0], ["aa", "bb"], [3, 4]]
    exp_units = (u.m, None, None)
    for cls in Table, QTable:
        for units in ({"a": u.m, "c": ""}, exp_units):
            qt = cls(dat, units=units, names=["a", "b", "c"])
            if cls is QTable:
                assert isinstance(qt["a"], u.Quantity)
                assert isinstance(qt["b"], table.Column)
                assert isinstance(qt["c"], table.Column)
            for col, unit in zip(qt.itercols(), exp_units):
                assert col.info.unit is unit


def test_set_descriptions():
    dat = [[1.0, 2.0], ["aa", "bb"]]
    exp_descriptions = ("my description", None)
    for cls in Table, QTable:
        for descriptions in ({"a": "my description"}, exp_descriptions):
            qt = cls(dat, descriptions=descriptions, names=["a", "b"])
            for col, description in zip(qt.itercols(), exp_descriptions):
                assert col.info.description == description


def test_set_units_from_row():
    text = ["a,b", ",s", "1,2", "3,4"]
    units = Table.read(text, format="ascii", data_start=1, data_end=2)[0]
    t = Table.read(text, format="ascii", data_start=2, units=units)
    assert isinstance(units, table.Row)
    assert t["a"].info.unit is None
    assert t["b"].info.unit is u.s


def test_set_units_descriptions_read():
    """Test setting units and descriptions via Table.read.  The test here
    is less comprehensive because the implementation is exactly the same
    as for Table.__init__ (calling Table._set_column_attribute)"""
    for cls in Table, QTable:
        t = cls.read(
            ["a b", "1 2"],
            format="ascii",
            units=[u.m, u.s],
            descriptions=["hi", "there"],
        )
        assert t["a"].info.unit is u.m
        assert t["b"].info.unit is u.s
        assert t["a"].info.description == "hi"
        assert t["b"].info.description == "there"


def test_broadcasting_8933():
    """Explicitly check re-work of code related to broadcasting in #8933"""
    t = table.Table([[1, 2]])  # Length=2 table
    t["a"] = [[3, 4]]  # Can broadcast if ndim > 1 and shape[0] == 1
    t["b"] = 5
    t["c"] = [1]  # Treat as broadcastable scalar, not length=1 array (which would fail)
    assert np.all(t["a"] == [[3, 4], [3, 4]])
    assert np.all(t["b"] == [5, 5])
    assert np.all(t["c"] == [1, 1])

    # Test that broadcasted column is writeable
    t["c"][1] = 10
    assert np.all(t["c"] == [1, 10])


def test_custom_masked_column_in_nonmasked_table():
    """Test the refactor and change in column upgrades introduced
    in 95902650f.  This fixes a regression introduced by #8789
    (Change behavior of Table regarding masked columns)."""

    class MyMaskedColumn(table.MaskedColumn):
        pass

    class MySubMaskedColumn(MyMaskedColumn):
        pass

    class MyColumn(table.Column):
        pass

    class MySubColumn(MyColumn):
        pass

    class MyTable(table.Table):
        Column = MyColumn
        MaskedColumn = MyMaskedColumn

    a = table.Column([1])
    b = table.MaskedColumn([2], mask=[True])
    c = MyMaskedColumn([3], mask=[True])
    d = MySubColumn([4])
    e = MySubMaskedColumn([5], mask=[True])

    # Two different pathways for making table
    t1 = MyTable([a, b, c, d, e], names=["a", "b", "c", "d", "e"])
    t2 = MyTable()
    t2["a"] = a
    t2["b"] = b
    t2["c"] = c
    t2["d"] = d
    t2["e"] = e

    for t in (t1, t2):
        assert type(t["a"]) is MyColumn
        assert type(t["b"]) is MyMaskedColumn  # upgrade
        assert type(t["c"]) is MyMaskedColumn
        assert type(t["d"]) is MySubColumn
        assert type(t["e"]) is MySubMaskedColumn  # sub-class not downgraded


def test_sort_with_mutable_skycoord():
    """Test sorting a table that has a mutable column such as SkyCoord.

    In this case the sort is done in-place
    """
    t = Table([[2, 1], SkyCoord([4, 3], [6, 5], unit="deg,deg")], names=["a", "sc"])
    meta = {"a": [1, 2]}
    ta = t["a"]
    tsc = t["sc"]
    t["sc"].info.meta = meta
    t.sort("a")
    assert np.all(t["a"] == [1, 2])
    assert np.allclose(t["sc"].ra.to_value(u.deg), [3, 4])
    assert np.allclose(t["sc"].dec.to_value(u.deg), [5, 6])
    assert t["a"] is ta
    assert t["sc"] is tsc

    # Prior to astropy 4.1 this was a deep copy of SkyCoord column; after 4.1
    # it is a reference.
    t["sc"].info.meta["a"][0] = 100
    assert meta["a"][0] == 100


def test_sort_with_non_mutable():
    """Test sorting a table that has a non-mutable column."""
    t = Table([[2, 1], [3, 4]], names=["a", "b"])
    ta = t["a"]
    tb = t["b"]
    t["b"].setflags(write=False)
    meta = {"a": [1, 2]}
    t["b"].info.meta = meta
    t.sort("a")
    assert np.all(t["a"] == [1, 2])
    assert np.all(t["b"] == [4, 3])
    assert ta is t["a"]
    assert tb is not t["b"]

    # Prior to astropy 4.1 this was a deep copy of SkyCoord column; after 4.1
    # it is a reference.
    t["b"].info.meta["a"][0] = 100
    assert meta["a"][0] == 1


def test_init_with_list_of_masked_arrays():
    """Test the fix for #8977"""
    m0 = np.ma.array([0, 1, 2], mask=[True, False, True])
    m1 = np.ma.array([3, 4, 5], mask=[False, True, False])
    mc = [m0, m1]

    # Test _init_from_list
    t = table.Table([mc], names=["a"])

    # Test add_column
    t["b"] = [m1, m0]

    assert t["a"].shape == (2, 3)
    assert np.all(t["a"][0] == m0)
    assert np.all(t["a"][1] == m1)
    assert np.all(t["a"][0].mask == m0.mask)
    assert np.all(t["a"][1].mask == m1.mask)

    assert t["b"].shape == (2, 3)
    assert np.all(t["b"][0] == m1)
    assert np.all(t["b"][1] == m0)
    assert np.all(t["b"][0].mask == m1.mask)
    assert np.all(t["b"][1].mask == m0.mask)


def test_data_to_col_convert_strategy():
    """Test the update to how data_to_col works (#8972), using the regression
    example from #8971.
    """
    t = table.Table([[0, 1]])
    t["a"] = 1
    t["b"] = np.int64(2)  # Failed previously
    assert np.all(t["a"] == [1, 1])
    assert np.all(t["b"] == [2, 2])


def test_structured_masked_column():
    """Test that adding a masked ndarray with a structured dtype works"""
    dtype = np.dtype([("z", "f8"), ("x", "f8"), ("y", "i4")])
    t = Table()
    t["a"] = np.ma.array(
        [
            (1, 2, 3),
            (4, 5, 6),
        ],
        mask=[
            (False, False, True),
            (False, True, False),
        ],
        dtype=dtype,
    )
    assert np.all(t["a"]["z"].mask == [False, False])
    assert np.all(t["a"]["x"].mask == [False, True])
    assert np.all(t["a"]["y"].mask == [True, False])
    assert isinstance(t["a"], MaskedColumn)


def test_rows_with_mixins():
    """Test for #9165 to allow adding a list of mixin objects.
    Also test for fix to #9357 where group_by() failed due to
    mixin object not having info.indices set to [].
    """
    tm = Time([1, 2], format="cxcsec")
    q = [1, 2] * u.m
    mixed1 = [1 * u.m, 2]  # Mixed input, fails to convert to Quantity
    mixed2 = [2, 1 * u.m]  # Mixed input, not detected as potential mixin
    rows = [
        (1, q[0], tm[0]),
        (2, q[1], tm[1]),
    ]
    t = table.QTable(rows=rows)
    t["a"] = [q[0], q[1]]
    t["b"] = [tm[0], tm[1]]
    t["m1"] = mixed1
    t["m2"] = mixed2

    assert np.all(t["col1"] == q)
    assert np.all(t["col2"] == tm)
    assert np.all(t["a"] == q)
    assert np.all(t["b"] == tm)
    assert np.all(t["m1"][ii] == mixed1[ii] for ii in range(2))
    assert np.all(t["m2"][ii] == mixed2[ii] for ii in range(2))
    assert type(t["m1"]) is table.Column
    assert t["m1"].dtype is np.dtype(object)
    assert type(t["m2"]) is table.Column
    assert t["m2"].dtype is np.dtype(object)

    # Ensure group_by() runs without failing for sortable columns.
    # The columns 'm1', and 'm2' are object dtype and not sortable.
    for name in ["col0", "col1", "col2", "a", "b"]:
        t.group_by(name)

    # For good measure include exactly the failure in #9357 in which the
    # list of Time() objects is in the Table initializer.
    mjds = [Time(58000, format="mjd")]
    t = Table([mjds, ["gbt"]], names=("mjd", "obs"))
    t.group_by("obs")


def test_iterrows():
    dat = [
        (1, 2, 3),
        (4, 5, 6),
        (7, 8, 6),
    ]
    t = table.Table(rows=dat, names=("a", "b", "c"))
    c_s = []
    a_s = []
    for c, a in t.iterrows("c", "a"):
        a_s.append(a)
        c_s.append(c)
    assert np.all(t["a"] == a_s)
    assert np.all(t["c"] == c_s)

    rows = [row for row in t.iterrows()]
    assert rows == dat

    with pytest.raises(ValueError, match="d is not a valid column name"):
        t.iterrows("d")


def test_values_and_types():
    dat = [
        (1, 2, 3),
        (4, 5, 6),
        (7, 8, 6),
    ]
    t = table.Table(rows=dat, names=("a", "b", "c"))
    assert isinstance(t.values(), type(OrderedDict().values()))
    assert isinstance(t.columns.values(), type(OrderedDict().values()))
    assert isinstance(t.columns.keys(), type(OrderedDict().keys()))
    for i in t.values():
        assert isinstance(i, table.column.Column)


def test_items():
    dat = [
        (1, 2, 3),
        (4, 5, 6),
        (7, 8, 9),
    ]
    t = table.Table(rows=dat, names=("a", "b", "c"))

    assert isinstance(t.items(), type(OrderedDict({}).items()))

    for i in list(t.items()):
        assert isinstance(i, tuple)


def test_read_write_not_replaceable():
    t = table.Table()
    with pytest.raises(AttributeError):
        t.read = "fake_read"

    with pytest.raises(AttributeError):
        t.write = "fake_write"


def test_keep_columns_with_generator():
    # Regression test for #12529
    t = table.table_helpers.simple_table(1)
    t.keep_columns(col for col in t.colnames if col == "a")
    assert t.colnames == ["a"]


def test_remove_columns_with_generator():
    # Regression test for #12529
    t = table.table_helpers.simple_table(1)
    t.remove_columns(col for col in t.colnames if col == "a")
    assert t.colnames == ["b", "c"]


def test_keep_columns_invalid_names_messages():
    t = table.table_helpers.simple_table(1)
    with pytest.raises(KeyError, match='column "d" does not exist'):
        t.keep_columns(["c", "d"])
    with pytest.raises(KeyError, match="columns {'[de]', '[de]'} do not exist"):
        t.keep_columns(["c", "d", "e"])


def test_remove_columns_invalid_names_messages():
    t = table.table_helpers.simple_table(1)
    with pytest.raises(KeyError, match='column "d" does not exist'):
        t.remove_columns(["c", "d"])
    with pytest.raises(KeyError, match="columns {'[de]', '[de]'} do not exist"):
        t.remove_columns(["c", "d", "e"])


@pytest.mark.parametrize("path_type", ["str", "Path"])
def test_read_write_tilde_path(path_type, home_is_tmpdir):
    if path_type == "str":
        test_file = os.path.join("~", "test.csv")
    else:
        test_file = pathlib.Path("~", "test.csv")
    t1 = Table()
    t1["a"] = [1, 2, 3]
    t1.write(test_file)
    t2 = Table.read(test_file)
    assert np.all(t2["a"] == [1, 2, 3])
    # Ensure the data wasn't written to the literal tilde-prefixed path
    assert not os.path.exists(test_file)


def test_add_list_order():
    t = Table()
    names = list(map(str, range(20)))
    array = np.empty((20, 1))
    t.add_columns(array, names=names)
    assert t.colnames == names
