{"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":"a1b227ca-8afb-51ff-8073-7ffbcf5dae3b","task_key":"default--v0~2e1~2e0~5fhf--a1b227ca-8afb-51ff-8073-7ffbcf5dae3b","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf a1b227ca-8afb-51ff-8073-7ffbcf5dae3b","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import urllib.request\\nfrom pyquery import PyQuery as pq\\nfrom datetime import datetime\\nimport pandas as pd\\ndef task_func(url):\\n\",\"complete_prompt\":\"import urllib.request\\nfrom pyquery import PyQuery as pq\\nfrom datetime import datetime\\nimport pandas as pd\\n\\ndef task_func(url):\\n    \\\"\\\"\\\"\\n    Extracts the text and href attributes of all anchor tags from a given URL's HTML content, \\n    and returns this data in a pandas DataFrame along with the time of data extraction.\\n\\n    Parameters:\\n    url (str): The URL from which to fetch the HTML content.\\n\\n    Returns:\\n    pandas.DataFrame: A DataFrame with columns 'text', 'href', and 'fetch_time'. Each row \\n                      corresponds to an anchor tag in the HTML, with 'text' and 'href' containing \\n                      the text and the hyperlink reference of the anchor tag, respectively. \\n                      'fetch_time' contains the timestamp of when the data was fetched in the format\\n                        'YYYY-MM-DD HH:MM:SS'.\\n\\n    Raises:\\n    ValueError: If the provided URL is invalid or empty.\\n    URLError: If there is an issue with network connectivity or the server.\\n\\n    Requirements:\\n    - urllib.request\\n    - pyquery\\n    - datime\\n    - pandas\\n    - urllib.error\\n\\n    Example:\\n    >>> df = task_func('https://en.wikibooks.org/wiki/Main_Page')\\n\\n    Note:\\n    The function requires internet connectivity to fetch HTML content.\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Extracts the text and href attributes of all anchor tags from a given URL's HTML content, and returns this data in a pandas DataFrame along with the time of data extraction.\\nNote that: The function requires internet connectivity to fetch HTML content.\\nThe function should raise the exception for: ValueError: If the provided URL is invalid or empty. URLError: If there is an issue with network connectivity or the server.\\nThe function should output with:\\n    pandas.DataFrame: A DataFrame with columns 'text', 'href', and 'fetch_time'. Each row\\n    corresponds to an anchor tag in the HTML, with 'text' and 'href' containing\\n    the text and the hyperlink reference of the anchor tag, respectively.\\n    'fetch_time' contains the timestamp of when the data was fetched in the format\\n    'YYYY-MM-DD HH:MM:SS'.\\nYou should write self-contained code starting with:\\n```\\nimport urllib.request\\nfrom pyquery import PyQuery as pq\\nfrom datetime import datetime\\nimport pandas as pd\\ndef task_func(url):\\n```\",\"libs\":\"['pandas', 'urllib', 'datetime', 'pyquery']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}