{"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":"0377950f-9922-580d-be8b-70acb78ebda1","task_key":"default--v0~2e1~2e0~5fhf--0377950f-9922-580d-be8b-70acb78ebda1","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 0377950f-9922-580d-be8b-70acb78ebda1","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import collections\\nimport json\\nimport os\\ndef task_func(data, json_file_name='data.json'):\\n\",\"complete_prompt\":\"import collections\\nimport json\\nimport os\\n\\n\\ndef task_func(data, json_file_name='data.json'):\\n    \\\"\\\"\\\"\\n    Add a new key \\\"a\\\" with the value 1 to the input dictionary, calculate the frequency of its values, and save the updated dictionary along with its frequency distribution to a JSON file. The dictionary is saved under the key 'data' and the frequency distribution under the key 'freq'.\\n\\n    Parameters:\\n    data (dict): The input data as a dictionary.\\n    json_file_name (str): The name of the JSON file to be saved.\\n\\n    Returns:\\n    str: The path of the JSON file.\\n\\n    Requirements:\\n    - collections\\n    - re\\n    - json\\n    - os\\n\\n    Example:\\n    >>> import tempfile\\n    >>> json_file = tempfile.NamedTemporaryFile(delete=False)\\n    >>> data = {'key1': 'value1', 'key2': 'value2', 'key3': 'value1'}\\n    >>> task_func(data, json_file.name) is not None\\n    True\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Add a new key \\\"a\\\" with the value 1 to the input dictionary, calculate the frequency of its values, and save the updated dictionary along with its frequency distribution to a JSON file. The dictionary is saved under the key 'data' and the frequency distribution under the key 'freq'.\\nThe function should output with:\\n    str: The path of the JSON file.\\nYou should write self-contained code starting with:\\n```\\nimport collections\\nimport json\\nimport os\\ndef task_func(data, json_file_name='data.json'):\\n```\",\"libs\":\"['json', 'collections', 'os']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}