{"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":"928b7690-12c4-55d8-b105-2764fd953712","task_key":"default--v0~2e1~2e0~5fhf--928b7690-12c4-55d8-b105-2764fd953712","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 928b7690-12c4-55d8-b105-2764fd953712","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import pandas as pd\\nfrom datetime import datetime, timedelta\\nimport random\\ndef task_func(epoch_milliseconds, seed=0):\\n\",\"complete_prompt\":\"import pandas as pd\\nfrom datetime import datetime, timedelta\\nimport random\\n\\n\\ndef task_func(epoch_milliseconds, seed=0):\\n    \\\"\\\"\\\"\\n    Generate user activity logs from a given epoch time to the current time.\\n\\n    This function iterates from the starting epoch time to the current system\\n    time, incrementally increasing the time by a random number of seconds (an\\n    integer in [1, 10]) between each log entry. Each log entry records a user\\n    performing an activity at a specific time.\\n\\n    Parameters:\\n    - epoch_milliseconds (int): Starting epoch time in milliseconds. Must be in\\n                                the past compared to current system time.\\n    - seed (int): random seed for reproducibility. Defaults to 0.\\n\\n    Returns:\\n    - pd.DataFrame: A DataFrame containing logs of user activities, with columns:\\n        - 'User':   User names, randomly chosen from a predefined list of users,\\n                    ['user1', 'user2', 'user3', 'user4', 'user5'].\\n        - 'Activity': Activities performed by the users, randomly chosen from a\\n                      predefined list of activities, ['login', 'logout', 'browse',\\n                      'search', 'purchase'].\\n        - 'Time': The timestamp of when the activity occurred, incrementally\\n                  increasing from the starting epoch time to the current time.\\n\\n    Raises:\\n    - ValueError: If the start time is after the current system time.\\n    \\n    Requirements:\\n    - pandas\\n    - datetime.datetime.fromtimestamp\\n    - datetime.timedelta\\n    - random\\n\\n    Example:\\n    >>> log = task_func(1615168051807)\\n    >>> type(log)\\n    <class 'pandas.core.frame.DataFrame'>\\n    >>> log.iloc[0]\\n    User                             user4\\n    Activity                        search\\n    Time        2021-03-08 12:47:31.807000\\n    Name: 0, dtype: object\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Generate user activity logs from a given epoch time to the current time. This function iterates from the starting epoch time to the current system time, incrementally increasing the time by a random number of seconds (an integer in [1, 10]) between each log entry. Each log entry records a user performing an activity at a specific time.\\nThe function should raise the exception for: ValueError: If the start time is after the current system time.\\nThe function should output with:\\n    pd.DataFrame: A DataFrame containing logs of user activities, with columns:\\n    'User':   User names, randomly chosen from a predefined list of users,\\n    ['user1', 'user2', 'user3', 'user4', 'user5'].\\n    'Activity': Activities performed by the users, randomly chosen from a\\n    predefined list of activities, ['login', 'logout', 'browse',\\n    'search', 'purchase'].\\n    'Time': The timestamp of when the activity occurred, incrementally\\n    increasing from the starting epoch time to the current time.\\nYou should write self-contained code starting with:\\n```\\nimport pandas as pd\\nfrom datetime import datetime, timedelta\\nimport random\\ndef task_func(epoch_milliseconds, seed=0):\\n```\",\"libs\":\"['pandas', 'datetime', 'random']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}