[{'role': 'system', 'content': "You are an expert in machine learning and your task is to classify the code snippets into categories from the provided list of categories. List of categories: ['helper_functions', 'load_data', 'data_exploration', 'data_preprocessing', 'evaluation', 'modelling', 'prediction', 'result_visualization', 'save_results', 'comment_only']"}, {'role': 'user', 'content': 'Identify to which category the provided code belongs and assign the code snippet to at least 1 but up to 5 categories based on the probabilities, ignore if the probability of the category is negligible. Strictly provide your response as a list. Avoid providing any additional information, commentary, or personal opinions.\\nPython Code:METADATA = [ \'version\', \'changeset\', \'timestamp\', \'user\', \'uid\', \'id\']\n\'\'\'\nReference:  Udacity\n\'\'\'\ndef get_user(elem, users):\nif elem.tag == "node":\nuid = elem.get(\'user\')\nif uid not in users and uid != None:\nusers.add(uid)\nreturn users\ndef user_contributors(filename):\nusers = set()\nfor _, elem in xET.iterparse(filename):\nuser = get_user(elem, users)\nreturn users\ndef get_user_contributors():\nusers = user_contributors(SAMPLE_NAME)\nprint(\'Total Users: \', len(users))\nprint(users)\nget_user_contributors()'}, {'role': 'assistant', 'content': "['data_exploration']"}]