{"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":"noindex","profile":{"resources":[],"task_format":"","scoring":"","metric":"","size":"","answer_access":"","license":"","citation":"","maintainer":"","released":"","why_hard":"","related":[]}},"task_id":"69343341-9c6f-5d73-8a8b-204161936c7c","task_key":"default--v0~2e1~2e0~5fhf--69343341-9c6f-5d73-8a8b-204161936c7c","task_revision_id":"2","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 69343341-9c6f-5d73-8a8b-204161936c7c","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import numpy as np\\nfrom sklearn.preprocessing import MinMaxScaler\\ndef task_func(my_dict):\\n\",\"complete_prompt\":\"import numpy as np\\nfrom sklearn.preprocessing import MinMaxScaler\\n\\ndef task_func(my_dict):\\n    \\\"\\\"\\\"\\n    Updates a dictionary by adding a normalized version of a numpy array found under the 'array' key.\\n    The normalization is performed using MinMaxScaler, scaling each value to fall between 0 and 1.\\n\\n    Parameters:\\n        my_dict (dict): A dictionary containing a key 'array' with a numpy array as its value.\\n\\n    Returns:\\n        dict: The dictionary after adding a key 'normalized_array' with the normalized values.\\n\\n    Notes:\\n        The function modifies the dictionary in-place and does not create a new dictionary.\\n        The function assumes that 'array' key exists and its value is a numpy array.\\n\\n    Raises:\\n        TypeError if the value of the 'array' key in my_dict is not a numpy array\\n        \\n    Requirements:\\n    - numpy\\n    - sklearn.preprocessing.MinMaxScaler\\n\\n    Examples:\\n    >>> example_dict = {'array': np.array([1, 2, 3, 4, 5])}\\n    >>> result = task_func(example_dict)\\n    >>> 'normalized_array' in result\\n    True\\n    >>> isinstance(result['normalized_array'], np.ndarray)\\n    True\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Updates a dictionary by adding a normalized version of a numpy array found under the 'array' key. The normalization is performed using MinMaxScaler, scaling each value to fall between 0 and 1.\\nNote that: Notes: The function modifies the dictionary in-place and does not create a new dictionary. The function assumes that 'array' key exists and its value is a numpy array.\\nThe function should raise the exception for: TypeError if the value of the 'array' key in my_dict is not a numpy array\\nThe function should output with:\\n    dict: The dictionary after adding a key 'normalized_array' with the normalized values.\\nYou should write self-contained code starting with:\\n```\\nimport numpy as np\\nfrom sklearn.preprocessing import MinMaxScaler\\ndef task_func(my_dict):\\n```\",\"libs\":\"['numpy', 'sklearn']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"noindex","subproblems":[],"grids":[]}