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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def get_dimensions(js_dict, naming):
 """Get dimensions from input data. Args: js_dict (dict):
 dictionary containing dataset data and metadata. naming (string, optional):
 dimension naming. Possible values: 'label' \ or 'id'. Returns: dimensions (list):
 list of pandas data frames with dimension \ category data. dim_names (list):
 list of strings with dimension names. """


    dimensions = []
    dim_names = []
    if check_version_2(js_dict):
        dimension_dict = js_dict
    else:
        dimension_dict = js_dict['dimension']
    for dim in dimension_dict['id']:
        dim_name = js_dict['dimension'][dim]['label']
        if not dim_name:
            dim_name = dim
        if naming == 'label':
            dim_label = get_dim_label(js_dict, dim)
            dimensions.append(dim_label)
            dim_names.append(dim_name)
        else:
            dim_index = get_dim_index(js_dict, dim)
            dimensions.append(dim_index)
            dim_names.append(dim)
    return dimensions, dim_names