def load_all_data_sources(): data = {} for k in config_dict: params = config_dict[k] load_func_name = params['load']['function'] st.subheader(k) if load_func_name == 'None': st.write('No load function') else: df = load_data.load_most_recent_loadable_data(params) data[k] = df # Mobility reports are too large for streamlit to handle if k != 'google_mobility_reports': st.write(df) return data
def export_non_aggregated_data(config_dict, export_path): for source in config_dict.keys(): config_dict[source]['export_path'] = export_path load_data.load_most_recent_loadable_data(config_dict[source]) print(config_dict.keys())
def export_non_aggregated_data(config_dict, export_path): print('export path (not used): ', export_path) for key in config_dict.keys(): load_data.load_most_recent_loadable_data(config_dict[key]) print(config_dict.keys())