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HumanEval

Code

HumanEval asks for a Python function body from a docstring and signature, checked by hidden unit tests. It is the original functional-correctness benchmark for code generation.

humaneval

Full text164 tasksProblems imported

Official source

Full text: eligible public problems include text, images and discussion.

Browse the problems Open a random one Problems awaiting a first attempt

Reference links

Issues

Dataset discussions

Paper

arXiv:2107.03374

Dataset

Source dataset

At a glance

Size: 164 problems imported from the openai_humaneval / test selection, with a source-row limit of 200.
License: mit (declared on the source)
Released: Dataset published on Hugging Face 2022-03
Maintainer: openai (source organisation)
Answer access: Columns outside the prompt allowlist, including any answer or reference solution, are separated into restricted storage and never rendered.

What a problem looks like

A Python function signature and docstring in prompt, with the entry point named. The reference solution and the tests are kept out of the prompt.

Read an actual problem

How it is scored

For the 164 imported problems, every column outside the prompt is separated into restricted storage, but the converter does not interpret it, so this catalogue does not claim a usable answer key exists.

Why it is hard

Correctness is decided by execution, not by resemblance to a reference: a plausible-looking function that fails one edge case scores zero.

Cite

@misc{chen2021evaluating,
      title={Evaluating Large Language Models Trained on Code},
      author={Mark Chen and Jerry Tworek and Heewoo Jun and Qiming Yuan and Henrique Ponde de Oliveira Pinto and Jared Kaplan and Harri Edwards and Yuri Burda and Nicholas Joseph and Greg Brockman and Alex Ray and Raul Puri and Gretchen Krueger and Michael Petrov and Heidy Khlaaf and Girish Sastry and Pamela Mishkin and Brooke Chan and Scott Gray and Nick Ryder and Mikhail Pavlov and Alethea Power and Lukasz Kaiser and Mohammad Bavarian and Clemens Winter and Philippe Tillet and Felipe Petroski Such and Dave Cummings and Matthias Plappert and Fotios Chantzis and Elizabeth Barnes and Ariel Herbert-Voss and William Hebgen Guss and Alex Nichol and Alex Paino and Nikolas Tezak and Jie Tang and Igor Babuschkin and Suchir Balaji and Shantanu Jain and William Saunders and Christopher Hesse and Andrew N. Carr and Jan Leike and Josh Achiam and Vedant Misra and Evan Morikawa and Alec Radford and Matthew Knight and Miles Brundage and Mira Murati and Katie Mayer and Peter Welinder and Bob McGrew and Dario Amodei and Sam McCandlish and Ilya Sutskever and Wojciech Zaremba},
      year={2021},
      eprint={2107.03374},
      archivePrefix={arXiv},
      primaryClass={cs.LG}
}

Discussion

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Discussion

Tasks

Whole public benchmark.

Public problems: 164
Formats: text (164)
Problems with images: 0
Answer availability: Answer availability not recorded (164)
Configs: openai_humaneval (164)
Splits: test (164)
Awaiting a first discussion: 164
Problems with a discussion: 0
Public contributions: 0

Provenance and terms

Pinned source revisions, newest first:

7dce6050a7d6d172f3cc5c32aa97f52fa1a2e544 · acquired 2026-09-11 · release 143d6b426d5d

Licence: Not recorded. This catalogue has not verified redistribution terms.
Redistribution terms: Not recorded. This catalogue has not verified redistribution terms.
Publisher requests: Not recorded. This catalogue has not verified redistribution terms.
Terms last checked: Never

FIX = """
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def count_nums(arr):
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def correct_bracketing(brackets: str):
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def sort_third(l: list):
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from typing import List
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def solution(lst):
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def below_threshold(l: list, t: int):
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def fix_spaces(text):
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def largest_smallest_integers(lst):
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def sort_array(arr):
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def flip_case(string: str) -> str:
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import math
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def tri(n):
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def solve(s):
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def triangle_area(a, b, c):
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def words_in_sentence(sentence):
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from typing import List
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from typing import List
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def fruit_distribution(s,n):
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def sort_even(l: list):
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def get_closest_vowel(word):
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from typing import List
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def pairs_sum_to_zero(l):
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def derivative(xs: list):
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def median(l: list):
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from typing import List
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def check_dict_case(dict):
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from typing import List
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def add_elements(arr, k):
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def hex_key(num):
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def iscube(a):
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def numerical_letter_grade(grades):
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def rounded_avg(n, m):
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def is_bored(S):
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def prime_fib(n: int):
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def how_many_times(string: str, substring: str) -> int:
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def right_angle_triangle(a, b, c):
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def is_nested(string):
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def will_it_fly(q,w):
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from typing import List
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def prime_length(string):
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from typing import List
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def generate_integers(a, b):
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def string_to_md5(text):
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def max_element(l: list):
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def is_happy(s):
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def encode_shift(s: str):
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def unique_digits(x):
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def get_positive(l: list):
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def strlen(string: str) -> int:
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