{"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":"460978f0-7289-5263-9760-88e016bcb41b","task_key":"default--v0~2e1~2e0~5fhf--460978f0-7289-5263-9760-88e016bcb41b","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 460978f0-7289-5263-9760-88e016bcb41b","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import itertools\\nimport seaborn as sns\\nimport matplotlib.pyplot as plt\\n# Constants\\nSHAPES = [\\n    \\\"Circle\\\",\\n    \\\"Square\\\",\\n    \\\"Triangle\\\",\\n    \\\"Rectangle\\\",\\n    \\\"Pentagon\\\",\\n    \\\"Hexagon\\\",\\n    \\\"Heptagon\\\",\\n    \\\"Octagon\\\",\\n    \\\"Nonagon\\\",\\n    \\\"Decagon\\\",\\n]\\nCOLORS = [\\n    \\\"Red\\\",\\n    \\\"Blue\\\",\\n    \\\"Green\\\",\\n    \\\"Yellow\\\",\\n    \\\"Black\\\",\\n    \\\"White\\\",\\n    \\\"Purple\\\",\\n    \\\"Orange\\\",\\n    \\\"Pink\\\",\\n    \\\"Brown\\\",\\n]\\ndef task_func(num_pairs=10):\\n\",\"complete_prompt\":\"import itertools\\nimport seaborn as sns\\nimport matplotlib.pyplot as plt\\n\\n# Constants\\nSHAPES = [\\n    \\\"Circle\\\",\\n    \\\"Square\\\",\\n    \\\"Triangle\\\",\\n    \\\"Rectangle\\\",\\n    \\\"Pentagon\\\",\\n    \\\"Hexagon\\\",\\n    \\\"Heptagon\\\",\\n    \\\"Octagon\\\",\\n    \\\"Nonagon\\\",\\n    \\\"Decagon\\\",\\n]\\nCOLORS = [\\n    \\\"Red\\\",\\n    \\\"Blue\\\",\\n    \\\"Green\\\",\\n    \\\"Yellow\\\",\\n    \\\"Black\\\",\\n    \\\"White\\\",\\n    \\\"Purple\\\",\\n    \\\"Orange\\\",\\n    \\\"Pink\\\",\\n    \\\"Brown\\\",\\n]\\n\\n\\ndef task_func(num_pairs=10):\\n    \\\"\\\"\\\"\\n    Generate and display a countplot of predefined shape-color pairs.\\n\\n    This function creates a visual representation of a specified number of unique shape-color combinations,\\n    each displayed as a bar in the countplot. The shape-color pairs are selected from a predefined list.\\n\\n    Parameters:\\n    - num_pairs (int): The number of unique shape-color pairs to be displayed in the countplot.\\n                       Default is 10. If the requested number is less than 1 or greater than the total\\n                       possible unique combinations (100), it is adjusted to the valid range (1 to 100).\\n\\n    Returns:\\n    - ax (matplotlib.axes._axes.Axes): The Axes object of the countplot, which can be used for\\n                                                  further customizations or to retrieve information about the plot.\\n\\n    Requirements:\\n    - itertools\\n    - seaborn\\n    - matplotlib\\n\\n    Example:\\n    >>> ax = task_func(10)\\n    >>> [tick.get_text() for tick in ax.get_xticklabels()]\\n    ['Circle:Red', 'Circle:Blue', 'Circle:Green', 'Circle:Yellow', 'Circle:Black', 'Circle:White', 'Circle:Purple', 'Circle:Orange', 'Circle:Pink', 'Circle:Brown']\\n    >>> ax = task_func(9)\\n    >>> [tick.get_text() for tick in ax.get_xticklabels()]\\n    ['Circle:Red', 'Circle:Blue', 'Circle:Green', 'Circle:Yellow', 'Circle:Black', 'Circle:White', 'Circle:Purple', 'Circle:Orange', 'Circle:Pink', 'Circle:Brown']\\n    >>> ax = task_func(8)\\n    >>> [tick.get_text() for tick in ax.get_xticklabels()]\\n    ['Circle:Red', 'Circle:Blue', 'Circle:Green', 'Circle:Yellow', 'Circle:Black', 'Circle:White', 'Circle:Purple', 'Circle:Orange', 'Circle:Pink', 'Circle:Brown']\\n    >>> ax = task_func(7)\\n    >>> [tick.get_text() for tick in ax.get_xticklabels()]\\n    ['Circle:Red', 'Circle:Blue', 'Circle:Green', 'Circle:Yellow', 'Circle:Black', 'Circle:White', 'Circle:Purple', 'Circle:Orange', 'Circle:Pink', 'Circle:Brown']\\n    >>> ax = task_func(6)\\n    >>> [tick.get_text() for tick in ax.get_xticklabels()]\\n    ['Circle:Red', 'Circle:Blue', 'Circle:Green', 'Circle:Yellow', 'Circle:Black', 'Circle:White', 'Circle:Purple', 'Circle:Orange', 'Circle:Pink', 'Circle:Brown']\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Generate and display a countplot of predefined shape-color pairs. This function creates a visual representation of a specified number of unique shape-color combinations, each displayed as a bar in the countplot. The shape-color pairs are selected from a predefined list.\\nThe function should output with:\\n    ax (matplotlib.axes._axes.Axes): The Axes object of the countplot, which can be used for\\n    further customizations or to retrieve information about the plot.\\nYou should write self-contained code starting with:\\n```\\nimport itertools\\nimport seaborn as sns\\nimport matplotlib.pyplot as plt\\n# Constants\\nSHAPES = [\\n    \\\"Circle\\\",\\n    \\\"Square\\\",\\n    \\\"Triangle\\\",\\n    \\\"Rectangle\\\",\\n    \\\"Pentagon\\\",\\n    \\\"Hexagon\\\",\\n    \\\"Heptagon\\\",\\n    \\\"Octagon\\\",\\n    \\\"Nonagon\\\",\\n    \\\"Decagon\\\",\\n]\\nCOLORS = [\\n    \\\"Red\\\",\\n    \\\"Blue\\\",\\n    \\\"Green\\\",\\n    \\\"Yellow\\\",\\n    \\\"Black\\\",\\n    \\\"White\\\",\\n    \\\"Purple\\\",\\n    \\\"Orange\\\",\\n    \\\"Pink\\\",\\n    \\\"Brown\\\",\\n]\\ndef task_func(num_pairs=10):\\n```\",\"libs\":\"['matplotlib', 'itertools', 'seaborn']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}