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HumanEval/0
from typing import List def yakin_iki_sayi_var_mi(sayilar: List[float], esik_deger: float) -> bool: """ Verilen sayi listesinde, verilen esik degerden birbirine daha yakin olan herhangi iki sayi olup olmadigini kontrol edin. >>> yakin_iki_sayi_var_mi([1.0, 2.0, 3.0], 0.5) False >>> yakin_iki_sayi_var_...
yakin_iki_sayi_var_mi
sorted_numbers = sorted(sayilar) for i in range(len(sorted_numbers) - 1): if sorted_numbers[i + 1] - sorted_numbers[i] < esik_deger: return True return False
METADATA = { 'author': 'jt', 'dataset': 'test' } def check(candidate): assert candidate([1.0, 2.0, 3.9, 4.0, 5.0, 2.2], 0.3) == True assert candidate([1.0, 2.0, 3.9, 4.0, 5.0, 2.2], 0.05) == False assert candidate([1.0, 2.0, 5.9, 4.0, 5.0], 0.95) == True assert candidate([1.0, 2.0, 5.9, 4.0,...
assert isinstance(esik_deger, float) and esik_deger > 0, "invalid inputs" # $_CONTRACT_$ assert isinstance(sayilar, list), "invalid inputs" # $_CONTRACT_$ assert all([isinstance(v, (int, float)) for v in sayilar]), "invalid inputs" # $_CONTRACT_$
[[[1.0, 2.0, 3.9, 4.0, 5.0, 2.2], 0.3], [[1.0, 2.0, 3.9, 4.0, 5.0, 2.2], 0.05], [[1.0, 2.0, 5.9, 4.0, 5.0], 0.95], [[1.0, 2.0, 5.9, 4.0, 5.0], 0.8], [[1.0, 2.0, 3.0, 4.0, 5.0, 2.0], 0.1], [[1.1, 2.2, 3.1, 4.1, 5.1], 1.0], [[1.1, 2.2, 3.1, 4.1, 5.1], 0.5]]
[[[1.0, 2.5, 3.0, 4.5, 5.0, 6.5], 0.4], [[1.0, 2.0, 3.0, 2.9, 5.0, 6.0], 0.1], [[0.5, 0.6, 0.7, 0.8, 0.9], 0.05], [[10.5, 20.5, 30.5, 25.5, 40.5], 4.0], [[1.1, 2.2, 3.3, 4.4, 5.5, 6.6, 7.7], 0.2], [[0.1, 0.5, 1.0, 1.5, 2.0], 0.1], [[1.2, 2.4, 3.6, 4.8], 0.8], [[-1.0, -0.5, 0.0, 0.5, 1.0], 0.3], [[-2.0, 2.0, 3.0, 4.0], ...
0
from typing import List def has_close_elements(numbers: List[float], threshold: float) -> bool: """ Check if in given list of numbers, are any two numbers closer to each other than given threshold. >>> has_close_elements([1.0, 2.0, 3.0], 0.5) False >>> has_close_elements([1.0, 2.8, 3.0, 4.0, 5.0, ...
has_close_elements
{"has_close_elements": "yakin_iki_sayi_var_mi", "numbers": "sayilar", "threshold": "esik_deger"}
HumanEval/1
from typing import List def ayir_parantez_gruplari(parantez_metni: str) -> List[str]: """ Input bu fonksiyona icinde birden fazla parantez grubu iceren bir dizgi verir. Amaciniz bu gruplari ayri dizgilere ayirmak ve bu dizgilerin listesini donmektir. Ayri gruplar dengelidir (her acilma parantezi uygun sek...
ayir_parantez_gruplari
cnt, group, results = 0, "", [] for ch in parantez_metni: if ch == "(": cnt += 1 if ch == ")": cnt -= 1 if ch != " ": group += ch if cnt == 0: if group != "": results.append(group) group = "" return results
METADATA = { 'author': 'jt', 'dataset': 'test' } def check(candidate): assert candidate('(()()) ((())) () ((())()())') == [ '(()())', '((()))', '()', '((())()())' ] assert candidate('() (()) ((())) (((())))') == [ '()', '(())', '((()))', '(((())))' ] assert candidate('(()...
assert type(parantez_metni) == str, "invalid inputs" # $_CONTRACT_$ cnt = 0 # $_CONTRACT_$ for ch in parantez_metni: # $_CONTRACT_$ assert ch in ["(", ")", " "], "invalid inputs" # $_CONTRACT_$ if ch == "(": cnt += 1 # $_CONTRACT_$ if ch == ")": cnt -= 1 # $_CONTRACT_$ asse...
[["(()()) ((())) () ((())()())"], ["() (()) ((())) (((())))"], ["(()(())((())))"], ["( ) (( )) (( )( ))"]]
[["()"], ["(())"], ["((()))()"], ["()()()"], ["()(()())()"], ["(((()()((())))))"], ["((()()))(())"], ["()(()()((())))"], ["()()()(((()())))()(())"], ["(((())))()((()()))"], ["(((())))()(((())))()((()()))((()()))"], ["((((((())))()(((())))()((()()))((()())))()))(())"], ["()(()())()(()()((())))()"], ["()(()()((()))(((()(...
0
from typing import List def separate_paren_groups(paren_string: str) -> List[str]: """ Input to this function is a string containing multiple groups of nested parentheses. Your goal is to separate those group into separate strings and return the list of those. Separate groups are balanced (each open brace...
separate_paren_groups
{"separate_paren_groups": "ayir_parantez_gruplari", "paren_string": "parantez_metni"}
HumanEval/2
def ondalik_bolum(sayi: float) -> float: """ Pozitif bir kayan nokta sayi verildiginde, bu sayi tam bir bolum (verilen sayidan kucuk en buyuk tam sayi) ve ondalik kisimlarina (her zaman 1'den kucuk kalan kisim) ayrilabilir. Sayinin ondalik kismini dondurun. >>> ondalik_bolum(3.5) 0.5 """
ondalik_bolum
return sayi - int(sayi)
METADATA = { 'author': 'jt', 'dataset': 'test' } def check(candidate): assert candidate(3.5) == 0.5 assert abs(candidate(1.33) - 0.33) < 1e-6 assert abs(candidate(123.456) - 0.456) < 1e-6
assert sayi > 0, "invalid inputs" # $_CONTRACT_$ assert isinstance(sayi, float), "invalid inputs" # $_CONTRACT_$ assert sayi != float("+inf"), "invalid inputs" # $_CONTRACT_$
[[3.5], [1.33], [123.456]]
[[999.99999], [0.3333333], [1.0], [1.5], [0.5], [0.999999], [500.00678], [11.11], [0.25], [5.99], [1.284163165748358], [1.8517611088029418], [0.7713842427275083], [3.1842364304976463], [1.0738831860229472], [0.04320870526393539], [1.1369261836552624], [1.0630407193724771], [10.291122396192739], [1.7558893686701653], [0...
0.000001
def truncate_number(number: float) -> float: """ Given a positive floating point number, it can be decomposed into and integer part (largest integer smaller than given number) and decimals (leftover part always smaller than 1). Return the decimal part of the number. >>> truncate_number(3.5) 0...
truncate_number
{"truncate_number": "ondalik_bolum", "number": "sayi"}
HumanEval/3
from typing import List def sifir_altti(islemler: List[int]) -> bool: """ Sifir bakiye ile baslayan bir banka hesabina yapilan para yatirma ve para cekme islemlerinin listesini alirsiniz. Goreviniz, herhangi bir anda hesap bakiyesinin sifir altina dusup dusmedigini tespit etmektir. Bakiye sifir altina dusuldugund...
sifir_altti
account = 0 for operation in islemler: account += operation if account < 0: return True return False
METADATA = { 'author': 'jt', 'dataset': 'test' } def check(candidate): assert candidate([]) == False assert candidate([1, 2, -3, 1, 2, -3]) == False assert candidate([1, 2, -4, 5, 6]) == True assert candidate([1, -1, 2, -2, 5, -5, 4, -4]) == False assert candidate([1, -1, 2, -2, 5, -5, 4...
assert type(islemler) == list, "invalid inputs" # $_CONTRACT_$ assert all([isinstance(v, int) for v in islemler]), "invalid inputs" # $_CONTRACT_$
[[[]], [[1, 2, -3, 1, 2, -3]], [[1, 2, -4, 5, 6]], [[1, -1, 2, -2, 5, -5, 4, -4]], [[1, -1, 2, -2, 5, -5, 4, -5]], [[1, -2, 2, -2, 5, -5, 4, -4]]]
[[[0]], [[0, 0, 0, 0]], [[1, 2, 3, -6]], [[-1, -2, -3, 6]], [[1, 2, 3, 4, -10, 5, 6, -15]], [[10, -20, 30, -40, 50, -60]], [[5, -10, 15, -20, 25, -30, 35, -40, 45, -50]], [[1, -1, 1, -1, 1, -1, 1, -1, 1, -1]], [[10, -15, 20, -25, 30, -35, 40, -45]], [[1, -2, 3, -4, 5, -6, 7, -8, 9, -10]], [[15, 2, 3, -6]], [[-1, -3, 6]...
0
from typing import List def below_zero(operations: List[int]) -> bool: """ You're given a list of deposit and withdrawal operations on a bank account that starts with zero balance. Your task is to detect if at any point the balance of account fallls below zero, and at that point function should return Tru...
below_zero
{"below_zero": "sifir_altti", "operations": "islemler"}
HumanEval/4
"from typing import List\n\n\ndef ortalama_mutlak_sapma(sayilar: List[float]) -> float:\n \"\"\" (...TRUNCATED)
ortalama_mutlak_sapma
"\n mean = sum(sayilar) / len(sayilar)\n return sum(abs(x - mean) for x in sayilar) / len(sayi(...TRUNCATED)
"\n\nMETADATA = {\n 'author': 'jt',\n 'dataset': 'test'\n}\n\n\ndef check(candidate):\n ass(...TRUNCATED)
"\n assert all(isinstance(x, float) for x in sayilar), \"invalid inputs\" # $_CONTRACT_$\n ass(...TRUNCATED)
[[[1.0, 2.0, 3.0]], [[1.0, 2.0, 3.0, 4.0]], [[1.0, 2.0, 3.0, 4.0, 5.0]]]
"[[[-1.0, 4.5, 0.0, 2.5, -3.0]], [[0.0, 0.0, 0.0, 0.0, 0.0]], [[-2.0, 2.0]], [[-1.0, -1.0, 1.0, 1.0](...TRUNCATED)
0.000001
"from typing import List\n\n\ndef mean_absolute_deviation(numbers: List[float]) -> float:\n \"\"\(...TRUNCATED)
mean_absolute_deviation
{"mean_absolute_deviation": "ortalama_mutlak_sapma", "numbers": "sayilar"}
HumanEval/5
"from typing import List\n\n\ndef aralarina_ekle(sayilar: List[int], ayirac: int) -> List[int]:\n (...TRUNCATED)
aralarina_ekle
"\n\n res = []\n for i in range(len(sayilar)):\n res.append(sayilar[i])\n if i !(...TRUNCATED)
"\n\nMETADATA = {\n 'author': 'jt',\n 'dataset': 'test'\n}\n\n\ndef check(candidate):\n ass(...TRUNCATED)
"\n assert all([isinstance(v, int) for v in sayilar]), \"invalid inputs\" # $_CONTRACT_$\n ass(...TRUNCATED)
[[[], 7], [[5, 6, 3, 2], 8], [[2, 2, 2], 2]]
"[[[1, 2, 3], 0], [[2, 4, 6, 8], 1], [[9, 9, 9, 9, 9, 9], 7], [[10], 5], [[5, 7], 2], [[1, 3, 5, 7],(...TRUNCATED)
0
"from typing import List\n\n\ndef intersperse(numbers: List[int], delimeter: int) -> List[int]:\n (...TRUNCATED)
intersperse
{"intersperse": "aralarina_ekle", "numbers": "sayilar", "delimeter": "ayirac"}
HumanEval/6
"from typing import List\n\n\ndef parantez_derinliklerini_bul(parantez_dizisi: str) -> List[int]:\n (...TRUNCATED)
parantez_derinliklerini_bul
"\n \n def count_depth(s: str) -> int:\n max_depth, cnt = 0, 0\n for ch in s:\n (...TRUNCATED)
"\n\nMETADATA = {\n 'author': 'jt',\n 'dataset': 'test'\n}\n\n\ndef check(candidate):\n ass(...TRUNCATED)
"\n assert type(parantez_dizisi) == str, \"invalid inputs\" # $_CONTRACT_$\n cnt = 0 # $_CONTR(...TRUNCATED)
[["(()()) ((())) () ((())()())"], ["() (()) ((())) (((())))"], ["(()(())((())))"]]
"[[\"\"], [\"((()))\"], [\"(())(()())\"], [\"(())(()(()))((()()))\"], [\"(()()(((())))(()(())))()\"](...TRUNCATED)
0
"from typing import List\n\n\ndef parse_nested_parens(paren_string: str) -> List[int]:\n \"\"\" I(...TRUNCATED)
parse_nested_parens
{"parse_nested_parens": "parantez_derinliklerini_bul", "paren_string": "parantez_dizisi"}
HumanEval/7
"from typing import List\n\n\ndef alt_dizeye_gore_filtrele(dizeler: List[str], alt_dize: str) -> Lis(...TRUNCATED)
alt_dizeye_gore_filtrele
return list(filter(lambda s: alt_dize in s, dizeler))
"\n\nMETADATA = {\n 'author': 'jt',\n 'dataset': 'test'\n}\n\n\ndef check(candidate):\n ass(...TRUNCATED)
"\n assert type(dizeler) == list, \"invalid inputs\" # $_CONTRACT_$\n assert all(type(x) == st(...TRUNCATED)
"[[[], \"john\"], [[\"xxx\", \"asd\", \"xxy\", \"john doe\", \"xxxAAA\", \"xxx\"], \"xxx\"], [[\"xxx(...TRUNCATED)
"[[[\"banana\", \"apple\", \"kiwi\", \"peach\"], \"a\"], [[\"hello\", \"world\", \"python\", \"numpy(...TRUNCATED)
0
"from typing import List\n\n\ndef filter_by_substring(strings: List[str], substring: str) -> List[st(...TRUNCATED)
filter_by_substring
"{\"filter_by_substring\": \"alt_dizeye_gore_filtrele\", \"strings\": \"dizeler\", \"substring\": \"(...TRUNCATED)
HumanEval/8
"from typing import List, Tuple\n\n\ndef toplam_carpim(sayilar: List[int]) -> Tuple[int, int]:\n (...TRUNCATED)
toplam_carpim
"\n s, p = 0, 1\n for number in sayilar:\n s += number\n p *= number\n return(...TRUNCATED)
"\n\nMETADATA = {\n 'author': 'jt',\n 'dataset': 'test'\n}\n\n\ndef check(candidate):\n ass(...TRUNCATED)
assert all([isinstance(v, int) for v in sayilar]), "invalid inputs" # $_CONTRACT_$
[[[]], [[1, 1, 1]], [[100, 0]], [[3, 5, 7]], [[10]]]
"[[[2, 4, 6, 8, 10]], [[0, 1, 2, 3, 4, 5]], [[-1, 1, -2, 2, -3, 3]], [[2, 3, 5, 7, 11, 13]], [[1, 2,(...TRUNCATED)
0
"from typing import List, Tuple\n\n\ndef sum_product(numbers: List[int]) -> Tuple[int, int]:\n \"(...TRUNCATED)
sum_product
{"sum_product": "toplam_carpim", "numbers": "sayilar"}
HumanEval/9
"from typing import List, Tuple\n\n\ndef akiskan_maks(sayilar: List[int]) -> List[int]:\n \"\"\" (...TRUNCATED)
akiskan_maks
return [max(sayilar[:(i+1)]) for i in range(len(sayilar))]
"\n\nMETADATA = {\n 'author': 'jt',\n 'dataset': 'test'\n}\n\n\ndef check(candidate):\n ass(...TRUNCATED)
"\n assert isinstance(sayilar, list), \"invalid inputs\" # $_CONTRACT_$\n assert all([isinstan(...TRUNCATED)
[[[]], [[1, 2, 3, 4]], [[4, 3, 2, 1]], [[3, 2, 3, 100, 3]]]
"[[[1, 1, 1, 1, 1]], [[5, 4, 3, 2, 1]], [[1, 3, 2, 4, 3, 5, 4, 6]], [[10, 5, 20, 30, 25, 20, 15, 10](...TRUNCATED)
0
"from typing import List, Tuple\n\n\ndef rolling_max(numbers: List[int]) -> List[int]:\n \"\"\" F(...TRUNCATED)
rolling_max
{"rolling_max": "akiskan_maks", "numbers": "sayilar"}
End of preview. Expand in Data Studio

HumanEval+ TR

A full Turkish translation of HumanEval+ (EvalPlus v0.1.10), all 164 problems.

Most translated code benchmarks only translate the docstring. This one translates everything a model reads:

  • docstrings and comments
  • function names, parameter names and helper function names
  • function names inside the docstring examples

Only ASCII letters are used (c g i o s u instead of ç ğ ı ö ş ü), so identifiers stay valid, conventional Python names.

String literals, numbers, type hints and expected example outputs are left exactly as in the original, so the tests still apply.

Example

Original:

def has_close_elements(numbers: List[float], threshold: float) -> bool:
    """ Check if in given list of numbers, are any two numbers closer to each other than
    given threshold.
    >>> has_close_elements([1.0, 2.0, 3.0], 0.5)
    False
    """

Translated:

def yakin_elemanlar_var_mi(sayilar: List[float], sinir: float) -> bool:
    """ Verilen sayi listesinde, herhangi iki sayinin birbirine yakinligi verilen sinirdan daha kucuk olup olmadigini
    kontrol edin.
    >>> yakin_elemanlar_var_mi([1.0, 2.0, 3.0], 0.5)
    False
    """

How it was made

  1. Machine translation with Qwen3.6-35B-A3B (Q4, thinking on) running locally through llama.cpp.
  2. Automatic checks on every problem: same functions in the same order, no function body added to the stub, the entry point actually renamed, and the old name gone.
  3. Verified against the tests. The canonical solution was renamed with the same mapping, then run against the original solution on every base and plus input. All 164 produce identical outputs. Problems that failed any check were re-translated.
  4. Human reviewed by a native Turkish speaker.

21 of 164 problems needed a second translation attempt. The scripts used are in scripts/, and every raw model attempt (including rejected ones) is in raw/translation_attempts.jsonl.

Format

Two files with the same rows:

  • humanevalplus_tr.jsonl: the canonical file. Same schema as HumanEvalPlus.jsonl, so it works with EvalPlus tooling (for example through HUMANEVAL_OVERRIDE_PATH). This is the one BenchKit uses.
  • viewer/test.jsonl: the same data for the Hub viewer and datasets.load_dataset. base_input, plus_input and rename_map are stored as JSON strings, because their types differ from problem to problem. Use json.loads to get them back.

Columns (extra ones are for traceability):

column description
task_id original id, e.g. HumanEval/0
prompt translated function stub
entry_point translated function name
canonical_solution original solution with parameters and helper calls renamed
test, base_input, plus_input, atol unchanged from HumanEval+
contract input asserts, renamed to the new parameter names
original_prompt, original_entry_point the English source
rename_map English to Turkish name mapping used

Usage

It is built into BenchKit as humaneval-plus-tr:

uv run benchkit --headless --models MODEL --benchmarks humaneval-plus-tr

Credits and license

Based on HumanEval (MIT, OpenAI) and HumanEval+ / EvalPlus (Apache-2.0). This translation is released under Apache-2.0.

Made by Doğukan Ürker.

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