{"taskset": {"n_runnable": 3, "name": null, "url_data": null, "catalog_id": null, "owner_type": null, "cited_by": null, "taskset": "bigcodebench_hard_complete", "domain": "swe", "task_kind": null, "environment": null, "grading": null, "path": "datasets/bigcodebench_hard_complete", "n_single_container": 145, "n_tasks": 145, "domain_raw": null, "sample_instruction": "# BigCodeBench-Hard Task\n\n## Problem Description\n\nimport matplotlib.pyplot as plt\nimport pandas as pd\nimport random\nfrom datetime import datetime\n\ndef task_func(seed=42):\n    \"\"\"\n    Generates a plot of random time series data for the past 30 days with reproducibility \n    controlled by an optional seed parameter.\n\n    The plot is styled with Arial font for better readability.\n\n    Parameters:\n        seed (int, optional): Seed for the random number generator to ensure reproducibility. Defaults to 42.\n\n    Returns:\n        matplotlib.axes.Axes: The Axes object containing a line plot of the time series data. \n                              The plot will have 'Date' as the x-axis label, 'Value' as the y-axis label, \n                              and 'Random Time Series Data' as the title.\n\n    Raises:\n        ValueError: If there is an issue generating the data or plot.\n\n    Requirements:\n        - matplotlib.pyplot\n        - pandas\n        - random\n        - datetime\n\n    Example:\n        >>> ax = task_func()\n        >>> ax.get_title()\n        'Random Time Series Data'\n        >>> ax.get_xlabel()\n        'Date'\n        >>> ax.get_ylabel()\n        'Value'\n    \"\"\"\n\n## Instructions\n\nYour solution should be saved to:\n```\n/workspace/solution.py\n```\n\nThe solution will be tested automatically against hidden test cases.\n\n\n\n", "owner_org": null, "url_repo": null, "url_paper": null, "license": null, "languages": [], "difficulties": 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