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BigCodeBench / BigCodeBench v0.1.0_hf 36d2ef90-3024-566d-bd00-2ccf5e06667c

Problem

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

complete prompt

import numpy as np
import random
from difflib import SequenceMatcher

def task_func(s, min_length, max_length, letters):
    """
    Generates a random string of length between `min_length` and `max_length`, inclusive,
    using characters from `letters`, and evaluates its similarity to the provided string `s`.
    A similarity score of 0.5 or higher considered 'similar'.

    Parameters:
    s (str): The string to which the generated string's similarity is evaluated.
    min_length (int): The minimum length for the generated string.
    max_length (int): The maximum length for the generated string.
    letters (str): A string of characters from which the random string is generated.

    Returns:
    tuple: A tuple containing the generated string and a boolean indicating whether it's
           considered similar to `s` based on the similarity threshold.
           
    Requirements:
    - numpy
    - random
    - difflib.SequenceMatcher

    Examples:
    >>> s = 'apple'
    >>> min_length = 5
    >>> max_length = 10
    >>> letters = 'abcdefghijklmnopqrstuvwxyz'
    >>> generated_s, is_similar = task_func(s, min_length, max_length, letters)
    >>> len(generated_s) >= min_length and len(generated_s) <= max_length
    True
    >>> isinstance(is_similar, bool)
    True
    """

instruct prompt

Generates a random string of length between `min_length` and `max_length`, inclusive, using characters from `letters`, and evaluates its similarity to the provided string `s`. A similarity score of 0.5 or higher considered 'similar'.
The function should output with:
    tuple: A tuple containing the generated string and a boolean indicating whether it's
    considered similar to `s` based on the similarity threshold.
You should write self-contained code starting with:

Code

import numpy as np
import random
from difflib import SequenceMatcher
def task_func(s, min_length, max_length, letters):

code prompt

Code

import numpy as np
import random
from difflib import SequenceMatcher
def task_func(s, min_length, max_length, letters):

entry point

task_func

libs

  • difflib
  • numpy
  • random

Discussion

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Source and history

task_id
36d2ef90-3024-566d-bd00-2ccf5e06667c
task_key
default--v0~2e1~2e0~5fhf--36d2ef90-3024-566d-bd00-2ccf5e06667c
task_revision_id
1
config / split
default / v0.1.0_hf

Official source

initial import