{"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":"9a5bacbb-0420-52b4-a0c7-19915ac80a86","task_key":"default--v0~2e1~2e0~5fhf--9a5bacbb-0420-52b4-a0c7-19915ac80a86","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 9a5bacbb-0420-52b4-a0c7-19915ac80a86","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import itertools\\nfrom typing import Any\\nfrom scipy import stats\\ndef task_func(input_list: list, repetitions: int) -> Any:\\n\",\"complete_prompt\":\"import itertools\\nfrom typing import Any\\nfrom scipy import stats\\n\\n\\ndef task_func(input_list: list, repetitions: int) -> Any:\\n    \\\"\\\"\\\"\\n    Calculate the mode of a list of elements with multiple repetitions of the original list.\\n    \\n    Functionality: \\n    - Takes a list and a repetition count as input.\\n    - Flattens the list with multiple repetitions.\\n    - Calculates the mode of the flattened list.\\n    \\n    Parameters:\\n    - input_list (list): A list containing elements (can be of any hashable type).\\n    - repetitions (int): The number of times the original list should be repeated.\\n\\n    Requirements:\\n    - typing\\n    - itertools\\n    - scipy\\n\\n    Returns:\\n    - scipy.stats.ModeResult: An object containing the mode(s) and count(s) of the most frequently occurring element(s) in the flattened list.\\n    \\n    Examples:\\n    >>> task_func(['A', 'B', 'C'], 10)\\n    ModeResult(mode=array(['A'], dtype='<U1'), count=array([10]))\\n    \\n    >>> task_func([1, 2, 3], 5)\\n    ModeResult(mode=array([1]), count=array([5]))\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Calculate the mode of a list of elements with multiple repetitions of the original list. Functionality: - Takes a list and a repetition count as input. - Flattens the list with multiple repetitions. - Calculates the mode of the flattened list. >>> task_func([1, 2, 3], 5) ModeResult(mode=array([1]), count=array([5]))\\nThe function should output with:\\n    scipy.stats.ModeResult: An object containing the mode(s) and count(s) of the most frequently occurring element(s) in the flattened list.\\nYou should write self-contained code starting with:\\n```\\nimport itertools\\nfrom typing import Any\\nfrom scipy import stats\\ndef task_func(input_list: list, repetitions: int) -> Any:\\n```\",\"libs\":\"['typing', 'itertools', 'scipy']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}