{"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":"6c62b406-0b21-5d8d-980e-62d33af2b5ad","task_key":"default--v0~2e1~2e0~5fhf--6c62b406-0b21-5d8d-980e-62d33af2b5ad","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 6c62b406-0b21-5d8d-980e-62d33af2b5ad","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import random\\nfrom datetime import datetime\\nimport matplotlib.pyplot as plt\\ndef task_func(epoch_milliseconds, seed=None):\\n\",\"complete_prompt\":\"import random\\nfrom datetime import datetime\\nimport matplotlib.pyplot as plt\\n\\ndef task_func(epoch_milliseconds, seed=None):\\n    \\\"\\\"\\\"\\n    Generate and draw a sales trend for different categories from a particular epoch milliseconds\\n    to the current UTC time.\\n\\n    The function selects category from ['Electronics', 'Clothing', 'Home', 'Books', 'Sports'].\\n    Each day's sales are randomly determined between 10 and 50 units for each category.\\n    The plot's x-axis represents 'Days since (the start date)', and the y-axis represents 'Sales' units.\\n\\n    Parameters:\\n    - epoch_milliseconds (int): Start time. Must be positive and before current time.\\n    - seed (int, optional): Seed for random number generation. Default is None (no seed).\\n\\n    Returns:\\n    - sales_data (dict): Sales data for different categories over days.\\n    - ax (plt.Axes): The plot depicting the sales trend.\\n\\n    Raises:\\n    - ValueError: If the start time is negative or after the current time.\\n    \\n    Requirements:\\n    - random\\n    - datetime.datetime\\n    - matplotlib\\n\\n    Example:\\n    >>> random.seed(42)\\n    >>> sales_data, ax = task_func(1236472051807, seed=42)\\n    >>> type(sales_data)\\n    <class 'dict'>\\n    >>> list(sales_data['Electronics'])[:3]\\n    [50, 24, 47]\\n    >>> type(ax)\\n    <class 'matplotlib.axes._axes.Axes'>\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Generate and draw a sales trend for different categories from a particular epoch milliseconds to the current UTC time. The function selects category from ['Electronics', 'Clothing', 'Home', 'Books', 'Sports']. Each day's sales are randomly determined between 10 and 50 units for each category. The plot's x-axis represents 'Days since (the start date)', and the y-axis represents 'Sales' units.\\nThe function should raise the exception for: ValueError: If the start time is negative or after the current time.\\nThe function should output with:\\n    sales_data (dict): Sales data for different categories over days.\\n    ax (plt.Axes): The plot depicting the sales trend.\\nYou should write self-contained code starting with:\\n```\\nimport random\\nfrom datetime import datetime\\nimport matplotlib.pyplot as plt\\ndef task_func(epoch_milliseconds, seed=None):\\n```\",\"libs\":\"['datetime', 'random', 'matplotlib']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}