{"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":"5cb87aa6-992c-5345-8ac2-c33704fc85df","task_key":"default--v0~2e1~2e0~5fhf--5cb87aa6-992c-5345-8ac2-c33704fc85df","task_revision_id":"2","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 5cb87aa6-992c-5345-8ac2-c33704fc85df","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import matplotlib.pyplot as plt\\nimport pandas as pd\\nimport seaborn as sns\\nimport numpy as np\\ndef task_func(data_url=\\\"http://lib.stat.cmu.edu/datasets/boston\\\", seed=42):\\n\",\"complete_prompt\":\"import matplotlib.pyplot as plt\\nimport pandas as pd\\nimport seaborn as sns\\nimport numpy as np\\n\\ndef task_func(data_url=\\\"http://lib.stat.cmu.edu/datasets/boston\\\", seed=42):\\n    \\\"\\\"\\\"\\n    Draw the correlation heatmap of the Boston Housing dataset using Seaborn, with an option to save it to a specified file.\\n\\n    Parameters:\\n        seed (int, optional): Random seed for reproducibility. Defaults to 42.\\n    The font should be in the family of sans-serif and Arial.\\n\\n    Returns:\\n        matplotlib.axes.Axes: The Axes object containing the heatmap plot.\\n\\n    Raises:\\n        ValueError: If an error occurs in generating or saving the plot.\\n\\n    Requirements:\\n        - matplotlib\\n        - os\\n        - pandas\\n        - seaborn\\n        - numpy \\n\\n    Example:\\n        >>> ax = task_func()\\n        >>> type(ax)\\n        <class 'matplotlib.axes._axes.Axes'>\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Draw the correlation heatmap of the Boston Housing dataset using Seaborn, with an option to save it to a specified file.\\nThe function should raise the exception for: ValueError: If an error occurs in generating or saving the plot.\\nThe function should output with:\\n    matplotlib.axes.Axes: The Axes object containing the heatmap plot.\\nYou should write self-contained code starting with:\\n```\\nimport matplotlib.pyplot as plt\\nimport pandas as pd\\nimport seaborn as sns\\nimport numpy as np\\ndef task_func(data_url=\\\"http://lib.stat.cmu.edu/datasets/boston\\\", seed=42):\\n```\",\"libs\":\"['pandas', 'numpy', 'matplotlib', 'seaborn']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"noindex","subproblems":[],"grids":[]}