How to use the dtale.dtale.route function in dtale

@dtale.route('/update-settings/')
@swag_from('swagger/dtale/views/update-settings.yml')
def update_settings(data_id):
    """
    :class:`flask:flask.Flask` route which updates global SETTINGS for current port

    :param data_id: integer string identifier for a D-Tale process's data
    :type data_id: str
    :param settings: JSON string from flask.request.args['settings'] which gets decoded and stored in SETTINGS variable
    :return: JSON
    """
    try:
        global SETTINGS

        curr_settings = SETTINGS.get(data_id, {})
        updated_settings = dict_merge(curr_settings, json.loads(get_str_arg(request, 'settings', '{}')))
        SETTINGS[data_id] = updated_settings

@dtale.route('/correlations-ts/')
@swag_from('swagger/dtale/views/correlations-ts.yml')
def get_correlations_ts(data_id):
    """
    :class:`flask:flask.Flask` route which returns timeseries of Pearson correlations of two columns with numeric data
    using :meth:`pandas:pandas.DataFrame.corr`

    :param data_id: integer string identifier for a D-Tale process's data
    :type data_id: str
    :param query: string from flask.request.args['query'] which is applied to DATA using the query() function
    :param cols: comma-separated string from flask.request.args['cols'] containing names of two columns in dataframe
    :param dateCol: string from flask.request.args['dateCol'] with name of date-type column in dateframe for timeseries
    :returns: JSON {
        data: {:col1:col2: {data: [{corr: 0.99, date: 'YYYY-MM-DD'},...], max: 0.99, min: 0.99}
    } or {error: 'Exception message', traceback: 'Exception stacktrace'}
    """
    try:

@dtale.route('/data/')
@swag_from('swagger/dtale/views/data.yml')
def get_data(data_id):
    """
    :class:`flask:flask.Flask` route which returns current rows from DATA (based on scrollbar specs and saved settings)
    to front-end as JSON

    :param data_id: integer string identifier for a D-Tale process's data
    :type data_id: str
    :param ids: required dash separated string "START-END" stating a range of row indexes to be returned to the screen
    :param query: string from flask.request.args['query'] which is applied to DATA using the query() function
    :param sort: JSON string from flask.request.args['sort'] which is applied to DATA using the sort_values() or
                 sort_index() function.  Here is the JSON structure: [col1,dir1],[col2,dir2],....[coln,dirn]
    :return: JSON {
        results: [
            {dtale_index: 1, col1: val1_1, ...,colN: valN_1},
            ...,

@dtale.route('/main/')
@swag_from('swagger/dtale/views/main.yml')
def view_main(data_id):
    """
    :class:`flask:flask.Flask` route which serves up base jinja template housing JS files

    :param data_id: integer string identifier for a D-Tale process's data
    :type data_id: str
    :return: HTML
    """
    return _view_main(data_id)

@dtale.route('/test-filter/')
@swag_from('swagger/dtale/views/test-filter.yml')
def test_filter(data_id):
    """
    :class:`flask:flask.Flask` route which will test out pandas query before it gets applied to DATA and return
    exception information to the screen if there is any

    :param data_id: integer string identifier for a D-Tale process's data
    :type data_id: str
    :param query: string from flask.request.args['query'] which is applied to DATA using the query() function
    :return: JSON {success: True/False}
    """
    try:
        query = get_str_arg(request, 'query')
        _test_filter(DATA[data_id], query)
        return jsonify(dict(success=True))
    except BaseException as e:

@dtale.route('/describe//')
@swag_from('swagger/dtale/views/describe.yml')
def describe(data_id, column):
    """
    :class:`flask:flask.Flask` route which returns standard details about column data using
    :meth:`pandas:pandas.DataFrame.describe` to the front-end as JSON

    :param data_id: integer string identifier for a D-Tale process's data
    :type data_id: str
    :param column: required dash separated string "START-END" stating a range of row indexes to be returned
                   to the screen
    :return: JSON {
        describe: object representing output from :meth:`pandas:pandas.Series.describe`,
        unique_data: array of unique values when data has <= 100 unique values
        success: True/False
    }

@dtale.route('/processes')
@swag_from('swagger/dtale/views/processes.yml')
def get_processes():
    """
    :class:`flask:flask.Flask` route which returns list of running D-Tale processes within current python process

    :return: JSON {
        data: [
            {
                port: 1, name: 'name1', rows: 5, columns: 5, names: 'col1,...,col5', start: '2018-04-30 12:36:44',
                ts: 1525106204000
            },
            ...,
            {
                port: N, name: 'nameN', rows: 5, columns: 5, names: 'col1,...,col5', start: '2018-04-30 12:36:44',
                ts: 1525106204000
            }

@dtale.route('/iframe/')
@swag_from('swagger/dtale/views/main.yml')
def view_iframe(data_id):
    """
    :class:`flask:flask.Flask` route which serves up base jinja template housing JS files

    :param data_id: integer string identifier for a D-Tale process's data
    :type data_id: str
    :return: HTML
    """
    return _view_main(data_id, iframe=True)

@dtale.route('/scatter/')
@swag_from('swagger/dtale/views/scatter.yml')
def get_scatter(data_id):
    """
    :class:`flask:flask.Flask` route which returns data used in correlation of two columns for scatter chart

    :param data_id: integer string identifier for a D-Tale process's data
    :type data_id: str
    :param query: string from flask.request.args['query'] which is applied to DATA using the query() function
    :param cols: comma-separated string from flask.request.args['cols'] containing names of two columns in dataframe
    :param dateCol: string from flask.request.args['dateCol'] with name of date-type column in dateframe for timeseries
    :param date: string from flask.request.args['date'] date value in dateCol to filter dataframe to
    :returns: JSON {
        data: [{col1: 0.123, col2: 0.123, index: 1},...,{col1: 0.123, col2: 0.123, index: N}],
        stats: {
            correlated: 50,
            only_in_s0: 1,