"""Unit tests for demographics logic layer."""

from unittest import mock
from unittest.mock import MagicMock

from analytics.connectors import redis
from analytics.logic import demographics as demographics_logic
from analytics.models import demographics as demographics_models


def test_response_for_analytics_frontend(monkeypatch):
    """Convert cohorts list to response for analytics frontend."""
    monkeypatch.setattr(redis.client, 'get', MagicMock(return_value=None))
    monkeypatch.setattr(redis.client, 'set', MagicMock())

    data = [demographics_models.Cohort(**cohort_data)
            for cohort_data in (
        {
            'gender': 'men',
            'age_group': '18-50',
            'streams': 500,
        },
        {
            'gender': 'women',
            'age_group': '18-50',
            'streams': 400,
        },
        {
            'gender': 'unknown',
            'age_group': '18-50',
            'streams': 100,
        },
    )]

    response = demographics_logic.format_response_for_analytics_frontend(data)
    assert response == {
        'age_breakdown': [{
            'age_group': '18-50',
            'all_percentage': 100,
            'all_streams_number': 1000,
            'men_percentage': 50,
            'men_streams_number': 500,
            'women_percentage': 40,
            'women_streams_number': 400,
        }],
        'gender_breakdown': {
            'streams_number': 1000,
            'women_percentage': 40,
            'women_streams_number': 400,
            'men_percentage': 50,
            'men_streams_number': 500,
            'unknown_percentage': 10,
            'unknown_streams_number': 100,
        },
        'top_audiences': [
            {
                'age_group': '18-50',
                'gender': 'men',
                'percentage': 50,
                'total_streams_number': 500
            },
            {
                'age_group': '18-50',
                'gender': 'women',
                'percentage': 40,
                'total_streams_number': 400
            },
            {
                'age_group': '18-50',
                'gender': 'unknown',
                'percentage': 10,
                'total_streams_number': 100
            },
        ],
    }


def test_empty_response_for_analytics_frontend(monkeypatch):
    """Check format_response_for_analytics_frontend works with empty data."""
    monkeypatch.setattr(redis.client, 'get', MagicMock(return_value=None))
    monkeypatch.setattr(redis.client, 'set', MagicMock())

    assert demographics_logic.format_response_for_analytics_frontend([]) == {
        'age_breakdown': [],
        'gender_breakdown': {
            'streams_number': 0,
            'men_streams_number': 0,
            'men_percentage': 0,
            'unknown_streams_number': 0,
            'unknown_percentage': 0,
            'women_streams_number': 0,
            'women_percentage': 0
        },
        'top_audiences': [],
    }


def test_get_demographic_insights_no_content(monkeypatch):
    """Test logic returns 204 response when no data is found."""
    mock_get_cohorts = mock.Mock()
    mock_get_cohorts.return_value = mock.Mock(status=204)

    monkeypatch.setattr(demographics_models, 'get_cohorts', mock_get_cohorts)

    response = demographics_logic.get_demographic_insights(
        store_ids={286}, feed_ids=[1, 2], start_date='2017-01-01',
        end_date='2017-10-01', account_type='L', account_id=7123,
        distributors=['theorchard'])

    assert response.status == 204