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BigCodeBench / BigCodeBench v0.1.0_hf 928b7690-12c4-55d8-b105-2764fd953712

Problem

Answer published by the source. Consult the official source to check your work against its answer.

complete prompt

import pandas as pd
from datetime import datetime, timedelta
import random


def task_func(epoch_milliseconds, seed=0):
    """
    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.

    Parameters:
    - epoch_milliseconds (int): Starting epoch time in milliseconds. Must be in
                                the past compared to current system time.
    - seed (int): random seed for reproducibility. Defaults to 0.

    Returns:
    - pd.DataFrame: A DataFrame containing logs of user activities, with columns:
        - 'User':   User names, randomly chosen from a predefined list of users,
                    ['user1', 'user2', 'user3', 'user4', 'user5'].
        - 'Activity': Activities performed by the users, randomly chosen from a
                      predefined list of activities, ['login', 'logout', 'browse',
                      'search', 'purchase'].
        - 'Time': The timestamp of when the activity occurred, incrementally
                  increasing from the starting epoch time to the current time.

    Raises:
    - ValueError: If the start time is after the current system time.
    
    Requirements:
    - pandas
    - datetime.datetime.fromtimestamp
    - datetime.timedelta
    - random

    Example:
    >>> log = task_func(1615168051807)
    >>> type(log)
    <class 'pandas.core.frame.DataFrame'>
    >>> log.iloc[0]
    User                             user4
    Activity                        search
    Time        2021-03-08 12:47:31.807000
    Name: 0, dtype: object
    """

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.
The function should raise the exception for: ValueError: If the start time is after the current system time.
The function should output with:
    pd.DataFrame: A DataFrame containing logs of user activities, with columns:
    'User':   User names, randomly chosen from a predefined list of users,
    ['user1', 'user2', 'user3', 'user4', 'user5'].
    'Activity': Activities performed by the users, randomly chosen from a
    predefined list of activities, ['login', 'logout', 'browse',
    'search', 'purchase'].
    'Time': The timestamp of when the activity occurred, incrementally
    increasing from the starting epoch time to the current time.
You should write self-contained code starting with:

Code

import pandas as pd
from datetime import datetime, timedelta
import random
def task_func(epoch_milliseconds, seed=0):

code prompt

Code

import pandas as pd
from datetime import datetime, timedelta
import random
def task_func(epoch_milliseconds, seed=0):

entry point

task_func

libs

  • pandas
  • datetime
  • random

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Source and history

task_id
928b7690-12c4-55d8-b105-2764fd953712
task_key
default--v0~2e1~2e0~5fhf--928b7690-12c4-55d8-b105-2764fd953712
task_revision_id
1
config / split
default / v0.1.0_hf

Official source

initial import