{"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":"6cbfe508-0389-5103-ab19-66a777fd879a","task_key":"default--v0~2e1~2e0~5fhf--6cbfe508-0389-5103-ab19-66a777fd879a","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 6cbfe508-0389-5103-ab19-66a777fd879a","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import pandas as pd\\nimport os\\nimport json\\nfrom collections import Counter\\ndef task_func(json_dir_path, word_count):\\n\",\"complete_prompt\":\"import pandas as pd\\nimport os\\nimport json\\nfrom collections import Counter\\n\\n\\ndef task_func(json_dir_path, word_count):\\n    \\\"\\\"\\\" \\n    Analyze text content in JSON files from a given directory and find the most common words.\\n    \\n    This function reads all the JSON files in the specified directory, extracts the text content from each file,\\n    and determines the most frequent words. It then returns a list of the specified number of the most common words \\n    and their respective counts.\\n    \\n    Parameters:\\n    json_dir_path (str): The directory path where JSON files are stored.\\n    word_count (int): The number of most common words to return.\\n\\n    Returns:\\n    list: A list of tuples with the most common words and their counts.\\n\\n    Requirements:\\n    - pandas\\n    - os\\n    - json\\n    - collections.Counter\\n\\n    Example:\\n    >>> import tempfile\\n    >>> fake_data_1 = {\\\"text\\\": \\\"Top visit morning price certainly indicate time. Figure add cold behind customer also.\\\"}\\n    >>> fake_data_2 = {\\\"text\\\": \\\"Itself to current listen. Cover add will feeling head. Perform family affect reduce political general.\\\"}\\n    >>> temp_dir = tempfile.TemporaryDirectory()\\n    >>> with open(f\\\"{temp_dir.name}/fake_data_1.json\\\", 'w') as f:\\n    ...     json.dump(fake_data_1, f)\\n    >>> with open(f\\\"{temp_dir.name}/fake_data_2.json\\\", 'w') as f:\\n    ...     json.dump(fake_data_2, f)\\n    >>> task_func(temp_dir.name, 2)\\n    [('add', 2), ('Top', 1)]\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Analyze text content in JSON files from a given directory and find the most common words. This function reads all the JSON files in the specified directory, extracts the text content from each file, and determines the most frequent words. It then returns a list of the specified number of the most common words and their respective counts.\\nThe function should output with:\\n    list: A list of tuples with the most common words and their counts.\\nYou should write self-contained code starting with:\\n```\\nimport pandas as pd\\nimport os\\nimport json\\nfrom collections import Counter\\ndef task_func(json_dir_path, word_count):\\n```\",\"libs\":\"['pandas', 'collections', 'json', 'os']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}