"""Tests for XLSX to Pandas module."""

# import test_track_list
from types import SimpleNamespace
from unittest.mock import patch, MagicMock
from integration_scripts.xlsx_to_pandas_s3 import convert_all_xlsx_to_csv_s3, \
    convert_all_csv_to_xlsx_s3, get_files_from_s3_bucket, \
    convert_dataframe_to_csv_file, convert_dataframe_to_csv_s3, \
    convert_dataframe_to_xlsx_s3


@patch('integration_scripts.xlsx_to_pandas_s3.s3_utils.filter_file_keys')
@patch('integration_scripts.xlsx_to_pandas_s3.read_xlsx_to_dataframe_s3')
@patch('integration_scripts.xlsx_to_pandas_s3.s3_resource')
def test_convert_all_xlsx_to_csv(
        mock_resource, mock_df, mock_filter, test_track_list_xlsx):
    source_folder_key = 'source_key'
    output_folder_key = 'output_key'
    mock_filter.return_value = test_track_list_xlsx
    mock_df.head = MagicMock
    mock_df.to_csv = MagicMock
    mock_resource.Object = MagicMock
    mock_resource.Object.put = MagicMock

    convert_all_xlsx_to_csv_s3(source_folder_key, output_folder_key)

    # TODO: Test sorting is performed

    assert mock_df.call_count == 3


@patch('pandas.core.frame.DataFrame')
@patch('builtins.open')
def test_convert_dataframe_to_csv_file(mock_open, mock_df):
    """Test converting all CSV files in an s3 bucket to XLSX. """
    # if not output_folder_key:
    #     output_folder_key = source_folder_key
    #
    # converted_list = list()
    # mock_filter.return_value = test_s3_track_list_clean
    # mock_read_csv.return_value = mock_df
    mock_dropna = MagicMock()
    mock_df.dropna.return_value = mock_dropna
    mock_dropna.to_csv.return_value = MagicMock()

    filename = 'bucket/path/test_filename.csv'

    # open_name = 'builtins.open'
    # with patch('{}.open'.format(__name__), create=True) as mock_open:
    with patch('__main__.open', mock_open()):
        convert_dataframe_to_csv_file(mock_df, filename)

    # open_ = mock_open()
    # with patch.object('builtins', 'open', open_):

    assert mock_df.dropna.call_count == 1
    assert mock_dropna.to_csv.call_count == 1


@patch('integration_scripts.xlsx_to_pandas_s3.s3_utils.filter_backoff')
@patch('integration_scripts.xlsx_to_pandas_s3.s3_utils.get_object_backoff')
@patch('pandas.core.frame.DataFrame')
@patch('integration_scripts.xlsx_to_pandas_s3.pd.read_csv')
@patch('integration_scripts.xlsx_to_pandas_s3.s3_resource')
@patch('integration_scripts.xlsx_to_pandas_s3.convert_dataframe_to_xlsx_s3')
def test_convert_all_csv_to_xlsx_s3(
        mock_to_excel, mock_resource, mock_read_csv, mock_df,
        mock_get_object, mock_filter, test_s3_track_list_clean,
        test_to_excel_return_values, test_to_excel_results):

    output_folder_key = 'output_key'

    mock_filter.return_value = test_s3_track_list_clean
    mock_read_csv.return_value = mock_df
    mock_to_excel.side_effect = test_to_excel_return_values
    mock_resource.Object = MagicMock
    mock_resource.Object.put = MagicMock

    check_value = convert_all_csv_to_xlsx_s3(output_folder_key)

    assert mock_to_excel.call_count == 3
    assert check_value == test_to_excel_results
    assert mock_read_csv.call_count == 3
    assert mock_get_object.call_count == 0


@patch('integration_scripts.xlsx_to_pandas_s3.s3_utils.filter_backoff')
def test_get_files_from_s3_bucket(mock_filter,
                                  test_s3_track_list_clean,
                                  test_s3_track_list_mixed):
    """Test files are parsed from S3 key."""

    # Case 1 - all good
    mock_filter.return_value = test_s3_track_list_clean

    filter_response_1 = {
        'path1': [
            SimpleNamespace(key='bucket/path1/file_1.csv'),
            SimpleNamespace(key='bucket/path1/file_2.csv')
        ],
        'path2': [
            SimpleNamespace(key='bucket/path2/file_3.csv')
        ]
    }

    response = get_files_from_s3_bucket('folder_key')

    assert response == filter_response_1

    # Case 2 - mixed
    mock_filter.return_value = test_s3_track_list_mixed

    filter_response_2 = {
        'path2': [
            SimpleNamespace(key='bucket/path2/file_2.csv')
        ],
        'path3': [
            SimpleNamespace(key='bucket/path2/path3/file_4.csv')
        ]
    }

    response = get_files_from_s3_bucket('folder_key')

    assert response == filter_response_2

    # Case 3 - empty
    mock_filter.return_value = []

    filter_response_3 = {}

    response = get_files_from_s3_bucket('folder_key')

    assert response == filter_response_3


@patch('pandas.core.frame.DataFrame')
@patch('integration_scripts.xlsx_to_pandas_s3.s3_resource')
def test_convert_dataframe_to_xlsx_s3(mock_s3_resource,
                                      mock_dframe):
    """Test converting dataframe to excel doc."""
    # Check default case
    df_result = MagicMock()

    mock_dframe.dropna.return_value = df_result

    mock_s3_resource.Object = MagicMock
    mock_s3_resource.Object.put = MagicMock

    output_path_and_file = 'test_file_name'

    source_key, target_key = convert_dataframe_to_xlsx_s3(
        mock_dframe, output_path_and_file)

    assert mock_dframe.dropna.call_count == 1
    assert source_key == 'test_file_name.csv'
    assert target_key == 'test_file_name.xlsx'
    mock_dframe.dropna.assert_called_with(axis='rows', how='all')
    df_result.to_excel.assert_called_once()

    # Check added drop_by case
    drop_by = 'test'

    convert_dataframe_to_xlsx_s3(mock_dframe, output_path_and_file, drop_by)

    mock_dframe.dropna.assert_called_with(
        axis='rows', how='all', subset=[drop_by])


@patch('pandas.core.frame.DataFrame')
@patch('integration_scripts.xlsx_to_pandas_s3.s3_resource')
def test_convert_dataframe_to_csv_s3(mock_s3_resource,
                                     mock_dframe):
    """Convert a DataFrame to an CSV file and save it to an S3 object."""
    df_result = MagicMock()

    mock_dframe.dropna.return_value = df_result

    mock_s3_resource.Object = MagicMock
    mock_s3_resource.Object.put = MagicMock

    output_path_and_file = 'test_file_name'

    target_key = convert_dataframe_to_csv_s3(mock_dframe, output_path_and_file)

    assert mock_dframe.dropna.call_count == 1
    assert target_key == 'test_file_name.csv'
    mock_dframe.dropna.assert_called_with(axis='index', how='all')
    df_result.to_csv.assert_called_once()


# TODO: More tests.