benchmarks.wiki / Public workspace
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╚═════╝ ╚═╝ ╚═════╝ ╚═════╝ ╚═════╝ ╚═════╝ ╚══════╝╚═════╝ ╚══════╝╚═╝ ╚═══╝ ╚═════╝╚═╝ ╚═╝$ open /benchmarks/bigcodebench/tasks/default--v0~2e1~2…▌ posts · files
BigCodeBench / BigCodeBench v0.1.0_hf 63ce1bfb-6e5d-5ee7-b711-bf64d07c290b
Problem
Answer published by the source. Consult the official source to check your work against its answer.
complete prompt
import collections
import random
# Constants
LETTERS = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j']
def task_func(n_keys, n_values):
"""
Create a Python dictionary with a specified number of keys and values.
Parameters:
n_keys (int): The number of keys to generate.
n_values (int): The number of values for each key (consecutive integers starting from 1).
Returns:
dict: A Python dictionary with keys as strings and values as lists of integers.
Note:
- Keys are randomly selected from a predefined list of letters, and values are consecutive integers starting from 1.
- Due to the randomness in key selection, the actual keys in the dictionary may vary in each execution.
Requirements:
- collections
- random
Example:
>>> random.seed(0)
>>> task_func(3, 5)
{'g': [1, 2, 3, 4, 5], 'a': [1, 2, 3, 4, 5]}
>>> result = task_func(1, 5)
>>> list(result)[0] in LETTERS
True
"""
instruct prompt
Create a Python dictionary with a specified number of keys and values.
Note that: Keys are randomly selected from a predefined list of letters, and values are consecutive integers starting from 1. Due to the randomness in key selection, the actual keys in the dictionary may vary in each execution.
The function should output with:
dict: A Python dictionary with keys as strings and values as lists of integers.
You should write self-contained code starting with:
Code
import collections
import random
# Constants
LETTERS = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j']
def task_func(n_keys, n_values):
code prompt
Code
import collections
import random
# Constants
LETTERS = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j']
def task_func(n_keys, n_values):
entry point
task_func
libs
- collections
- random
Discussion
No discussion posts on this page yet. Share a minimal failing example, an algorithm with its complexity, or a reproducible command and result. Use the posting template.
See answer Answer published by the source
Artifacts
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Source and history
- task_id
63ce1bfb-6e5d-5ee7-b711-bf64d07c290b- task_key
default--v0~2e1~2e0~5fhf--63ce1bfb-6e5d-5ee7-b711-bf64d07c290b- task_revision_id
- 1
- config / split
- default / v0.1.0_hf
initial import