{"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":"6fe61e42-d2d8-513f-a3ba-18ba0dc7d9a5","task_key":"default--v0~2e1~2e0~5fhf--6fe61e42-d2d8-513f-a3ba-18ba0dc7d9a5","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 6fe61e42-d2d8-513f-a3ba-18ba0dc7d9a5","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import numpy as np\\nimport matplotlib.pyplot as plt\\ndef task_func(n_points=100, random_seed=None):\\n\",\"complete_prompt\":\"import numpy as np\\nimport matplotlib.pyplot as plt\\n\\n\\ndef task_func(n_points=100, random_seed=None):\\n    \\\"\\\"\\\"\\n    Generate an array of random 3D dots in the range [0, 1) for each dimension\\n    and draw them in a 3D scatter plot.\\n\\n    Parameters:\\n    n_points (int): The number of points to generate and plot. Default is 100.\\n    random_seed (int, optional): Seed for the random number generator. Default is None.\\n\\n    Returns:\\n    tuple: A tuple containing:\\n        - points (ndarray): A numpy ndarray of shape (n_points, 3) with the coordinates of the points.\\n        - plot (Axes3D): A 3D scatter plot of the generated points.\\n\\n    Requirements:\\n    - numpy\\n    - matplotlib.pyplot\\n\\n    Example:\\n    >>> points, plot = task_func(200, random_seed=42)\\n    >>> type(points)\\n    <class 'numpy.ndarray'>\\n    >>> type(plot)\\n    <class 'mpl_toolkits.mplot3d.axes3d.Axes3D'>\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Generate an array of random 3D dots in the range [0, 1) for each dimension and draw them in a 3D scatter plot.\\nThe function should output with:\\n    tuple: A tuple containing:\\n    points (ndarray): A numpy ndarray of shape (n_points, 3) with the coordinates of the points.\\n    plot (Axes3D): A 3D scatter plot of the generated points.\\nYou should write self-contained code starting with:\\n```\\nimport numpy as np\\nimport matplotlib.pyplot as plt\\ndef task_func(n_points=100, random_seed=None):\\n```\",\"libs\":\"['numpy', 'matplotlib']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}