# -*- coding: utf-8 -*-
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements.  See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership.  The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License.  You may obtain a copy of the License at
#
#   http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied.  See the License for the
# specific language governing permissions and limitations
# under the License.

import pytest

import numpy as np
import pandas as pd

from pyarrow.compat import unittest, u, unicode_type
import pyarrow as pa


class TestScalars(unittest.TestCase):

    def test_null_singleton(self):
        with pytest.raises(Exception):
            pa.NAType()

    def test_bool(self):
        arr = pa.array([True, None, False, None])

        v = arr[0]
        assert isinstance(v, pa.BooleanValue)
        assert repr(v) == "True"
        assert str(v) == "True"
        assert v.as_py() is True

        assert arr[1] is pa.NA

    def test_int64(self):
        arr = pa.array([1, 2, None])

        v = arr[0]
        assert isinstance(v, pa.Int64Value)
        assert repr(v) == "1"
        assert str(v) == "1"
        assert v.as_py() == 1
        assert v == 1

        assert arr[2] is pa.NA

    def test_double(self):
        arr = pa.array([1.5, None, 3])

        v = arr[0]
        assert isinstance(v, pa.DoubleValue)
        assert repr(v) == "1.5"
        assert str(v) == "1.5"
        assert v.as_py() == 1.5
        assert v == 1.5

        assert arr[1] is pa.NA

        v = arr[2]
        assert v.as_py() == 3.0

    def test_half_float(self):
        arr = pa.array([np.float16(1.5), None], type=pa.float16())
        v = arr[0]
        assert isinstance(v, pa.HalfFloatValue)
        assert repr(v) == "1.5"
        assert str(v) == "1.5"
        assert v.as_py() == 1.5
        assert v == 1.5

        assert arr[1] is pa.NA

    def test_string_unicode(self):
        arr = pa.array([u'foo', None, u'mañana'])

        v = arr[0]
        assert isinstance(v, pa.StringValue)
        assert v.as_py() == u'foo'
        assert repr(v) == repr(u"foo")
        assert str(v) == str(u"foo")
        assert v == u'foo'
        # Assert that newly created values are equal to the previously created
        # one.
        assert v == arr[0]

        assert arr[1] is pa.NA

        v = arr[2].as_py()
        assert v == u'mañana'
        assert isinstance(v, unicode_type)

    def test_bytes(self):
        arr = pa.array([b'foo', None, u('bar')])

        v = arr[0]
        assert isinstance(v, pa.BinaryValue)
        assert v.as_py() == b'foo'
        assert str(v) == str(b"foo")
        assert repr(v) == repr(b"foo")
        assert v == b'foo'

        assert arr[1] is pa.NA

        v = arr[2].as_py()
        assert v == b'bar'
        assert isinstance(v, bytes)

    def test_fixed_size_bytes(self):
        data = [b'foof', None, b'barb']
        arr = pa.array(data, type=pa.binary(4))

        v = arr[0]
        assert isinstance(v, pa.FixedSizeBinaryValue)
        assert v.as_py() == b'foof'

        assert arr[1] is pa.NA

        v = arr[2].as_py()
        assert v == b'barb'
        assert isinstance(v, bytes)

    def test_list(self):
        arr = pa.array([['foo', None], None, ['bar'], []])

        v = arr[0]
        assert len(v) == 2
        assert isinstance(v, pa.ListValue)
        assert repr(v) == "['foo', None]"
        assert v.as_py() == ['foo', None]
        assert v[0].as_py() == 'foo'
        assert v[1] is pa.NA
        assert v[-1] == v[1]
        assert v[-2] == v[0]
        with pytest.raises(IndexError):
            v[-3]
        with pytest.raises(IndexError):
            v[2]

        assert arr[1] is pa.NA

        v = arr[3]
        assert len(v) == 0

    def test_timestamp(self):
        arr = pd.date_range('2000-01-01 12:34:56', periods=10).values

        units = ['ns', 'us', 'ms', 's']

        for i, unit in enumerate(units):
            dtype = 'datetime64[{0}]'.format(unit)
            arrow_arr = pa.Array.from_pandas(arr.astype(dtype))
            expected = pd.Timestamp('2000-01-01 12:34:56')

            assert arrow_arr[0].as_py() == expected
            assert arrow_arr[0].value * 1000**i == expected.value

            tz = 'America/New_York'
            arrow_type = pa.timestamp(unit, tz=tz)

            dtype = 'datetime64[{0}]'.format(unit)
            arrow_arr = pa.Array.from_pandas(arr.astype(dtype),
                                             type=arrow_type)
            expected = (pd.Timestamp('2000-01-01 12:34:56')
                        .tz_localize('utc')
                        .tz_convert(tz))

            assert arrow_arr[0].as_py() == expected
            assert arrow_arr[0].value * 1000**i == expected.value

    def test_dictionary(self):
        colors = ['red', 'green', 'blue']
        colors_dict = {'red': 0, 'green': 1, 'blue': 2}
        values = pd.Series(colors * 4)

        categorical = pd.Categorical(values, categories=colors)

        v = pa.DictionaryArray.from_arrays(categorical.codes,
                                           categorical.categories)
        for i, c in enumerate(values):
            assert v[i].as_py() == c
            assert v[i].dictionary_value == c
            assert v[i].index_value == colors_dict[c]

    def test_int_hash(self):
        # ARROW-640
        int_arr = pa.array([1, 1, 2, 1])
        assert hash(int_arr[0]) == hash(1)

    def test_float_hash(self):
        # ARROW-640
        float_arr = pa.array([1.4, 1.2, 2.5, 1.8])
        assert hash(float_arr[0]) == hash(1.4)

    def test_string_hash(self):
        # ARROW-640
        str_arr = pa.array(["foo", "bar"])
        assert hash(str_arr[1]) == hash("bar")

    def test_bytes_hash(self):
        # ARROW-640
        byte_arr = pa.array([b'foo', None, b'bar'])
        assert hash(byte_arr[2]) == hash(b"bar")

    def test_array_to_set(self):
        # ARROW-640
        arr = pa.array([1, 1, 2, 1])
        set_from_array = set(arr)
        assert isinstance(set_from_array, set)
        assert set_from_array == {1, 2}

    def test_struct_value_subscripting(self):
        ty = pa.struct([pa.field('x', pa.int16()),
                        pa.field('y', pa.float32())])
        arr = pa.array([(1, 2.5), (3, 4.5), (5, 6.5)], type=ty)

        assert arr[0]['x'] == 1
        assert arr[0]['y'] == 2.5
        assert arr[1]['x'] == 3
        assert arr[1]['y'] == 4.5
        assert arr[2]['x'] == 5
        assert arr[2]['y'] == 6.5

        with pytest.raises(IndexError):
            arr[4]['non-existent']

        with pytest.raises(KeyError):
            arr[0]['non-existent']
