"""
Tests for ndarray-like method on the base Index class
"""
import pytest

import pandas as pd
from pandas import Index
import pandas._testing as tm


class TestReshape:
    def test_repeat(self):
        repeats = 2
        index = pd.Index([1, 2, 3])
        expected = pd.Index([1, 1, 2, 2, 3, 3])

        result = index.repeat(repeats)
        tm.assert_index_equal(result, expected)

    def test_insert(self):

        # GH 7256
        # validate neg/pos inserts
        result = Index(["b", "c", "d"])

        # test 0th element
        tm.assert_index_equal(Index(["a", "b", "c", "d"]), result.insert(0, "a"))

        # test Nth element that follows Python list behavior
        tm.assert_index_equal(Index(["b", "c", "e", "d"]), result.insert(-1, "e"))

        # test loc +/- neq (0, -1)
        tm.assert_index_equal(result.insert(1, "z"), result.insert(-2, "z"))

        # test empty
        null_index = Index([])
        tm.assert_index_equal(Index(["a"]), null_index.insert(0, "a"))

    @pytest.mark.parametrize(
        "pos,expected",
        [
            (0, Index(["b", "c", "d"], name="index")),
            (-1, Index(["a", "b", "c"], name="index")),
        ],
    )
    def test_delete(self, pos, expected):
        index = Index(["a", "b", "c", "d"], name="index")
        result = index.delete(pos)
        tm.assert_index_equal(result, expected)
        assert result.name == expected.name

    def test_append_multiple(self):
        index = Index(["a", "b", "c", "d", "e", "f"])

        foos = [index[:2], index[2:4], index[4:]]
        result = foos[0].append(foos[1:])
        tm.assert_index_equal(result, index)

        # empty
        result = index.append([])
        tm.assert_index_equal(result, index)