{"kind":"task","effective_mode":"full","benchmark":{"kind":"benchmark","effective_mode":"full","slug":"bigcodebench","formal_name":"BigCodeBench","introduction":"BigCodeBench poses 1,140 function-level tasks drawn across 139 libraries. It tests whether a model can compose several real APIs correctly rather than write one self-contained function.","introduction_ja":"","introduction_en":"","category":"Category not supplied","task_count":null,"acquisition_status":"Acquisition status not supplied","official_url":"https://bigcode-bench.github.io/","indexing_mode":"index","profile":{"resources":[],"task_format":"","scoring":"","metric":"","size":"","answer_access":"","license":"","citation":"","maintainer":"","released":"","why_hard":"","related":[],"history":"","construction":"","limitations":"","saturation":"","scores":[]}},"task_id":"0ee7ad40-8807-5f0a-90b2-68a26c2644a5","task_key":"default--v0~2e1~2e0~5fhf--0ee7ad40-8807-5f0a-90b2-68a26c2644a5","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 0ee7ad40-8807-5f0a-90b2-68a26c2644a5","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import re\\nimport json\\nfrom collections import defaultdict\\nimport string\\ndef task_func(json_string):\\n\",\"complete_prompt\":\"import re\\nimport json\\nfrom collections import defaultdict\\nimport string\\n\\ndef task_func(json_string):\\n    \\\"\\\"\\\"\\n    Process a JSON string containing a \\\"text\\\" field: convert to lowercase, remove punctuation, and count word frequency.\\n\\n    This function takes a JSON string with a field named \\\"text\\\", and returns a dictionary with word counts. \\n    It processes the text by converting it to lowercase, removing all punctuation and non-alphanumeric characters \\n    (except spaces), and then counting the frequency of each word.\\n\\n    Parameters:\\n    - json_string (str): A JSON string with a \\\"text\\\" field to process.\\n\\n    Returns:\\n    - dict: A dictionary with words as keys and their frequency counts as values. If the \\\"text\\\" field is missing, \\n      returns an empty dictionary.\\n\\n    Requirements:\\n    - re\\n    - json\\n    - collections\\n    - string\\n\\n    Example:\\n    >>> json_input = '{\\\"text\\\": \\\"Hello world! Hello universe. World, meet universe.\\\"}'\\n    >>> task_func(json_input)\\n    {'hello': 2, 'world': 2, 'universe': 2, 'meet': 1}\\n\\n    Notes:\\n    - Punctuation is removed using the `string.punctuation` constant.\\n    - The function is case-insensitive and treats words like \\\"Hello\\\" and \\\"hello\\\" as the same word.\\n    - If the JSON string is malformed or the \\\"text\\\" field is missing, an empty dictionary is returned.\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Process a JSON string containing a \\\"text\\\" field: convert to lowercase, remove punctuation, and count word frequency. This function takes a JSON string with a field named \\\"text\\\", and returns a dictionary with word counts. It processes the text by converting it to lowercase, removing all punctuation and non-alphanumeric characters (except spaces), and then counting the frequency of each word.\\nNote that: Notes: Punctuation is removed using the `string.punctuation` constant. The function is case-insensitive and treats words like \\\"Hello\\\" and \\\"hello\\\" as the same word. If the JSON string is malformed or the \\\"text\\\" field is missing, an empty dictionary is returned.\\nThe function should output with:\\n    dict: A dictionary with words as keys and their frequency counts as values. If the \\\"text\\\" field is missing,\\n    returns an empty dictionary.\\nYou should write self-contained code starting with:\\n```\\nimport re\\nimport json\\nfrom collections import defaultdict\\nimport string\\ndef task_func(json_string):\\n```\",\"libs\":\"['collections', 'string', 're', 'json']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}