def put_one_record(key, val): ''' save one record into mongodb ''' DATABASE.smlog.insert({ 'func_name': key, 'created_at': val.get('created_at'), 'server_name': get_server_name(), 'file_path': val['file_path'], 'file_line': val['file_line'], 'message': val['message'], 'content': val['content'], })
def put_one_record(key, val): ''' save one record into mongodb ''' DATABASE.smlog.update( { 'created_at': val['created_at'], 'func_name': key, 'server_name': get_server_name(), }, { '$set': { 'func_count': val['count'], 'file_path': val['file_path'], 'file_line': val['file_line'], 'message': val['message'], 'content': val['content'], } }, safe=True, upsert=True, )
# Store class frequencies results class_frequency_file_name = 'Top{0}/Top{0}_class_frequency_of_'.format( K) + prediction_file.split('.')[0] write.save_obj( novel, prediction_files_path + class_frequency_file_name) res = dict( sorted(novel.items(), key=itemgetter(1), reverse=True)[:N]) res = { str(k)[:class_str_length]: v / N_USERS for k, v in res.items() } keys = res.keys() values = res.values() ordered = pd.DataFrame(list(zip(keys, values)), columns=['x', 'y' ]).sort_values(by=['y'], ascending=False) print('\nExperiment Name: {0}'.format(prediction_file)) print(ordered) f.writelines('\nExperiment Name: {0}'.format(prediction_file)) f.writelines(ordered.to_string()) sendmail('Elaborate Predictions on {0}'.format(get_server_name()), 'Amazon Women')