How to use the investpy.get_stock_historical_data function in investpy

'interval': ['error']
        },
        {
            'stock': 'BBVA',
            'country': 'spain',
            'from_date': '01/01/2019',
            'to_date': '01/03/2019',
            'as_json': False,
            'order': 'ascending',
            'interval': 'error'
        },
    ]

    for param in params:
        try:
            investpy.get_stock_historical_data(stock=param['stock'],
                                               country=param['country'],
                                               from_date=param['from_date'],
                                               to_date=param['to_date'],
                                               as_json=param['as_json'],
                                               order=param['order'],
                                               interval=param['interval'])
        except:
            pass

    params = [
        {
            'stock': None,
            'country': 'spain',
            'language': 'spanish'
        },
        {

'order': 'descending',
        },
        {
            'as_json': False,
            'order': 'descending',
        },
    ]

    for param in params:
        investpy.get_stock_recent_data(stock='BBVA',
                                       country='spain',
                                       as_json=param['as_json'],
                                       order=param['order'],
                                       interval='Daily')

        investpy.get_stock_historical_data(stock='BBVA',
                                           country='spain',
                                           from_date='01/01/1990',
                                           to_date='01/01/2019',
                                           as_json=param['as_json'],
                                           order=param['order'],
                                           interval='Daily')

    for value in ['spanish', 'english']:
        investpy.get_stock_company_profile(stock='BBVA',
                                           country='spain',
                                           language=value)

    params = [
        {
            'stock': 'bbva',
            'country': 'spain',

country=param['country'],
                                from_date=param['from_date'],
                                to_date=param['to_date'],
                                window_size=param['window_size'],
                                trend_limit=param['trend_limit'],
                                labels=param['labels'],
                                identify=param['identify'])

        trendet.identify_all_trends(stock=param['stock'],
                                    country=param['country'],
                                    from_date=param['from_date'],
                                    to_date=param['to_date'],
                                    window_size=param['window_size'],
                                    identify=param['identify'])

    df = get_stock_historical_data(stock='REP',
                                   country='Spain',
                                   from_date='01/01/2018',
                                   to_date='01/01/2019')

    params = [
        {
            'column': 'Close',
            'window_size': 5,
            'identify': 'both'
        },
        {
            'column': 'Close',
            'window_size': 5,
            'identify': 'up'
        },
        {

labels=param['labels'],
                                    identify=param['identify'])
        except:
            pass

        try:
            trendet.identify_all_trends(stock=param['stock'],
                                        country=param['country'],
                                        from_date=param['from_date'],
                                        to_date=param['to_date'],
                                        window_size=param['window_size'],
                                        identify=param['identify'])
        except:
            pass

    df = get_stock_historical_data(stock='REP',
                                   country='Spain',
                                   from_date='01/01/2018',
                                   to_date='01/01/2019')

    df['error'] = 'error'

    params = [
        {
            'df': None,
            'column': 'Close',
            'window_size': 5,
            'identify': 'both'
        },
        {
            'df': ['error'],
            'column': 'Close',

if labels is not None and isinstance(labels, list) and isinstance(trend_limit, int):
        if len(labels) != trend_limit:
            raise ValueError('if labels is not None and a `list`, it must have the same length as the trend_limit!')

    if labels is not None and not isinstance(labels, list):
        raise ValueError('labels is neither None or a `list`!')

    if not isinstance(identify, str):
        raise ValueError('identify should be a `str` contained in [both, up, down]!')

    if isinstance(identify, str) and identify not in ['both', 'up', 'down']:
        raise ValueError('identify should be a `str` contained in [both, up, down]!')

    try:
        df = get_stock_historical_data(stock=stock,
                                       country=country,
                                       from_date=from_date,
                                       to_date=to_date)
    except Exception as e:
        raise RuntimeError(f'investpy function call failed with Exception: {e}!')

    objs = list()

    up_trend = {
        'name': 'Up Trend',
        'element': np.negative(df['Close'])
    }

    down_trend = {
        'name': 'Down Trend',
        'element': df['Close']

raise ValueError("to_date should be greater than from_date, both formatted as 'dd/mm/yyyy'.")

    if not isinstance(window_size, int):
        raise ValueError('window_size must be an `int`')

    if isinstance(window_size, int) and window_size < 3:
        raise ValueError('window_size must be an `int` equal or higher than 3!')

    if not isinstance(identify, str):
        raise ValueError('identify should be a `str` contained in [both, up, down]!')

    if isinstance(identify, str) and identify not in ['both', 'up', 'down']:
        raise ValueError('identify should be a `str` contained in [both, up, down]!')

    try:
        df = get_stock_historical_data(stock=stock,
                                       country=country,
                                       from_date=from_date,
                                       to_date=to_date)
    except Exception as e:
        raise RuntimeError(f'investpy function call failed with Exception: {e}!')

    objs = list()

    up_trend = {
        'name': 'Up Trend',
        'element': np.negative(df['Close'])
    }

    down_trend = {
        'name': 'Down Trend',
        'element': df['Close']