{"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":"72610b29-06fe-533c-9b71-94689016a92d","task_key":"default--v0~2e1~2e0~5fhf--72610b29-06fe-533c-9b71-94689016a92d","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 72610b29-06fe-533c-9b71-94689016a92d","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import string\\nimport random\\nimport pandas as pd\\nimport numpy as np\\n# Constants\\nNUM_SAMPLES = 1000  # Number of samples\\ndef task_func():\\n\",\"complete_prompt\":\"import string\\nimport random\\nimport pandas as pd\\nimport numpy as np\\n\\n# Constants\\nNUM_SAMPLES = 1000  # Number of samples\\n\\n\\ndef task_func():\\n    \\\"\\\"\\\"\\n    Generates a DataFrame with two columns: a string field and a float field.\\n    The string field contains randomly generated strings of 10 ASCII letters.\\n    The float field contains randomly generated numbers between 0 and 10000,\\n    formatted with two decimal places and a comma as the thousands separator.\\n\\n    Parameters:\\n    - None\\n\\n    Returns:\\n        DataFrame: A pandas DataFrame with NUM_SAMPLES rows. Each row contains a\\n        random string in the 'String Field' column and a formatted float in the\\n        'Float Field' column.\\n\\n    Requirements:\\n    - string\\n    - random\\n    - pandas\\n    - numpy\\n\\n    Example:\\n    >>> random.seed(0)\\n    >>> np.random.seed(0)\\n    >>> dataset = task_func()\\n    >>> print(dataset.head(1))\\n      String Field Float Field\\n    0   RNvnAvOpyE    5,488.14\\n\\n    Note: The exact values in the dataset will vary as they are randomly generated.\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Generates a DataFrame with two columns: a string field and a float field. The string field contains randomly generated strings of 10 ASCII letters. The float field contains randomly generated numbers between 0 and 10000, formatted with two decimal places and a comma as the thousands separator.\\nNote that: The exact values in the dataset will vary as they are randomly generated.\\nThe function should output with:\\n    DataFrame: A pandas DataFrame with NUM_SAMPLES rows. Each row contains a\\n    random string in the 'String Field' column and a formatted float in the\\n    'Float Field' column.\\nYou should write self-contained code starting with:\\n```\\nimport string\\nimport random\\nimport pandas as pd\\nimport numpy as np\\n# Constants\\nNUM_SAMPLES = 1000  # Number of samples\\ndef task_func():\\n```\",\"libs\":\"['pandas', 'numpy', 'random', 'string']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}