Dataset Viewer
source
stringclasses 1
value | prompt
stringlengths 281
1.53k
| ability
stringclasses 1
value | reward_model
dict | starter_code
null | extra_info
dict |
|---|---|---|---|---|---|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
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, 2.0], 0.3)
True
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {\\n 'author': 'jt',\\n 'dataset': 'test'\\n}\\n\\n\\ndef check(candidate):\\n assert candidate([1.0, 2.0, 3.9, 4.0, 5.0, 2.2], 0.3) == True\\n assert candidate([1.0, 2.0, 3.9, 4.0, 5.0, 2.2], 0.05) == False\\n assert candidate([1.0, 2.0, 5.9, 4.0, 5.0], 0.95) == True\\n assert candidate([1.0, 2.0, 5.9, 4.0, 5.0], 0.8) == False\\n assert candidate([1.0, 2.0, 3.0, 4.0, 5.0, 2.0], 0.1) == True\\n assert candidate([1.1, 2.2, 3.1, 4.1, 5.1], 1.0) == True\\n assert candidate([1.1, 2.2, 3.1, 4.1, 5.1], 0.5) == False\\n\\n\\n\\ncheck(has_close_elements)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 0,
"original": "from typing import List\n\n\ndef has_close_elements(numbers: List[float], threshold: float) -> bool:\n \"\"\" Check if in given list of numbers, are any two numbers closer to each other than\n given threshold.\n >>> has_close_elements([1.0, 2.0, 3.0], 0.5)\n False\n >>> has_close_elements([1.0, 2.8, 3.0, 4.0, 5.0, 2.0], 0.3)\n True\n \"\"\"\n",
"reference": " for idx, elem in enumerate(numbers):\n for idx2, elem2 in enumerate(numbers):\n if idx != idx2:\n distance = abs(elem - elem2)\n if distance < threshold:\n return True\n\n return False\n",
"split": "test",
"task_id": "HumanEval/0"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
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 is properly closed) and not nested within each other
Ignore any spaces in the input string.
>>> separate_paren_groups('( ) (( )) (( )( ))')
['()', '(())', '(()())']
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {\\n 'author': 'jt',\\n 'dataset': 'test'\\n}\\n\\n\\ndef check(candidate):\\n assert candidate('(()()) ((())) () ((())()())') == [\\n '(()())', '((()))', '()', '((())()())'\\n ]\\n assert candidate('() (()) ((())) (((())))') == [\\n '()', '(())', '((()))', '(((())))'\\n ]\\n assert candidate('(()(())((())))') == [\\n '(()(())((())))'\\n ]\\n assert candidate('( ) (( )) (( )( ))') == ['()', '(())', '(()())']\\n\\n\\ncheck(separate_paren_groups)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 1,
"original": "from typing import List\n\n\ndef separate_paren_groups(paren_string: str) -> List[str]:\n \"\"\" Input to this function is a string containing multiple groups of nested parentheses. Your goal is to\n separate those group into separate strings and return the list of those.\n Separate groups are balanced (each open brace is properly closed) and not nested within each other\n Ignore any spaces in the input string.\n >>> separate_paren_groups('( ) (( )) (( )( ))')\n ['()', '(())', '(()())']\n \"\"\"\n",
"reference": " result = []\n current_string = []\n current_depth = 0\n\n for c in paren_string:\n if c == '(':\n current_depth += 1\n current_string.append(c)\n elif c == ')':\n current_depth -= 1\n current_string.append(c)\n\n if current_depth == 0:\n result.append(''.join(current_string))\n current_string.clear()\n\n return result\n",
"split": "test",
"task_id": "HumanEval/1"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
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)
0.5
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {\\n 'author': 'jt',\\n 'dataset': 'test'\\n}\\n\\n\\ndef check(candidate):\\n assert candidate(3.5) == 0.5\\n assert abs(candidate(1.33) - 0.33) < 1e-6\\n assert abs(candidate(123.456) - 0.456) < 1e-6\\n\\n\\ncheck(truncate_number)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 2,
"original": "\n\ndef truncate_number(number: float) -> float:\n \"\"\" Given a positive floating point number, it can be decomposed into\n and integer part (largest integer smaller than given number) and decimals\n (leftover part always smaller than 1).\n\n Return the decimal part of the number.\n >>> truncate_number(3.5)\n 0.5\n \"\"\"\n",
"reference": " return number % 1.0\n",
"split": "test",
"task_id": "HumanEval/2"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
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 True. Otherwise it should return False.
>>> below_zero([1, 2, 3])
False
>>> below_zero([1, 2, -4, 5])
True
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {\\n 'author': 'jt',\\n 'dataset': 'test'\\n}\\n\\n\\ndef check(candidate):\\n assert candidate([]) == False\\n assert candidate([1, 2, -3, 1, 2, -3]) == False\\n assert candidate([1, 2, -4, 5, 6]) == True\\n assert candidate([1, -1, 2, -2, 5, -5, 4, -4]) == False\\n assert candidate([1, -1, 2, -2, 5, -5, 4, -5]) == True\\n assert candidate([1, -2, 2, -2, 5, -5, 4, -4]) == True\\n\\n\\ncheck(below_zero)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 3,
"original": "from typing import List\n\n\ndef below_zero(operations: List[int]) -> bool:\n \"\"\" You're given a list of deposit and withdrawal operations on a bank account that starts with\n zero balance. Your task is to detect if at any point the balance of account fallls below zero, and\n at that point function should return True. Otherwise it should return False.\n >>> below_zero([1, 2, 3])\n False\n >>> below_zero([1, 2, -4, 5])\n True\n \"\"\"\n",
"reference": " balance = 0\n\n for op in operations:\n balance += op\n if balance < 0:\n return True\n\n return False\n",
"split": "test",
"task_id": "HumanEval/3"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
from typing import List
def mean_absolute_deviation(numbers: List[float]) -> float:
""" For a given list of input numbers, calculate Mean Absolute Deviation
around the mean of this dataset.
Mean Absolute Deviation is the average absolute difference between each
element and a centerpoint (mean in this case):
MAD = average | x - x_mean |
>>> mean_absolute_deviation([1.0, 2.0, 3.0, 4.0])
1.0
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {\\n 'author': 'jt',\\n 'dataset': 'test'\\n}\\n\\n\\ndef check(candidate):\\n assert abs(candidate([1.0, 2.0, 3.0]) - 2.0/3.0) < 1e-6\\n assert abs(candidate([1.0, 2.0, 3.0, 4.0]) - 1.0) < 1e-6\\n assert abs(candidate([1.0, 2.0, 3.0, 4.0, 5.0]) - 6.0/5.0) < 1e-6\\n\\n\\n\\ncheck(mean_absolute_deviation)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 4,
"original": "from typing import List\n\n\ndef mean_absolute_deviation(numbers: List[float]) -> float:\n \"\"\" For a given list of input numbers, calculate Mean Absolute Deviation\n around the mean of this dataset.\n Mean Absolute Deviation is the average absolute difference between each\n element and a centerpoint (mean in this case):\n MAD = average | x - x_mean |\n >>> mean_absolute_deviation([1.0, 2.0, 3.0, 4.0])\n 1.0\n \"\"\"\n",
"reference": " mean = sum(numbers) / len(numbers)\n return sum(abs(x - mean) for x in numbers) / len(numbers)\n",
"split": "test",
"task_id": "HumanEval/4"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
from typing import List
def intersperse(numbers: List[int], delimeter: int) -> List[int]:
""" Insert a number 'delimeter' between every two consecutive elements of input list `numbers'
>>> intersperse([], 4)
[]
>>> intersperse([1, 2, 3], 4)
[1, 4, 2, 4, 3]
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {\\n 'author': 'jt',\\n 'dataset': 'test'\\n}\\n\\n\\ndef check(candidate):\\n assert candidate([], 7) == []\\n assert candidate([5, 6, 3, 2], 8) == [5, 8, 6, 8, 3, 8, 2]\\n assert candidate([2, 2, 2], 2) == [2, 2, 2, 2, 2]\\n\\n\\ncheck(intersperse)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 5,
"original": "from typing import List\n\n\ndef intersperse(numbers: List[int], delimeter: int) -> List[int]:\n \"\"\" Insert a number 'delimeter' between every two consecutive elements of input list `numbers'\n >>> intersperse([], 4)\n []\n >>> intersperse([1, 2, 3], 4)\n [1, 4, 2, 4, 3]\n \"\"\"\n",
"reference": " if not numbers:\n return []\n\n result = []\n\n for n in numbers[:-1]:\n result.append(n)\n result.append(delimeter)\n\n result.append(numbers[-1])\n\n return result\n",
"split": "test",
"task_id": "HumanEval/5"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
from typing import List
def parse_nested_parens(paren_string: str) -> List[int]:
""" Input to this function is a string represented multiple groups for nested parentheses separated by spaces.
For each of the group, output the deepest level of nesting of parentheses.
E.g. (()()) has maximum two levels of nesting while ((())) has three.
>>> parse_nested_parens('(()()) ((())) () ((())()())')
[2, 3, 1, 3]
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {\\n 'author': 'jt',\\n 'dataset': 'test'\\n}\\n\\n\\ndef check(candidate):\\n assert candidate('(()()) ((())) () ((())()())') == [2, 3, 1, 3]\\n assert candidate('() (()) ((())) (((())))') == [1, 2, 3, 4]\\n assert candidate('(()(())((())))') == [4]\\n\\n\\ncheck(parse_nested_parens)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 6,
"original": "from typing import List\n\n\ndef parse_nested_parens(paren_string: str) -> List[int]:\n \"\"\" Input to this function is a string represented multiple groups for nested parentheses separated by spaces.\n For each of the group, output the deepest level of nesting of parentheses.\n E.g. (()()) has maximum two levels of nesting while ((())) has three.\n\n >>> parse_nested_parens('(()()) ((())) () ((())()())')\n [2, 3, 1, 3]\n \"\"\"\n",
"reference": " def parse_paren_group(s):\n depth = 0\n max_depth = 0\n for c in s:\n if c == '(':\n depth += 1\n max_depth = max(depth, max_depth)\n else:\n depth -= 1\n\n return max_depth\n\n return [parse_paren_group(x) for x in paren_string.split(' ') if x]\n",
"split": "test",
"task_id": "HumanEval/6"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
from typing import List
def filter_by_substring(strings: List[str], substring: str) -> List[str]:
""" Filter an input list of strings only for ones that contain given substring
>>> filter_by_substring([], 'a')
[]
>>> filter_by_substring(['abc', 'bacd', 'cde', 'array'], 'a')
['abc', 'bacd', 'array']
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {\\n 'author': 'jt',\\n 'dataset': 'test'\\n}\\n\\n\\ndef check(candidate):\\n assert candidate([], 'john') == []\\n assert candidate(['xxx', 'asd', 'xxy', 'john doe', 'xxxAAA', 'xxx'], 'xxx') == ['xxx', 'xxxAAA', 'xxx']\\n assert candidate(['xxx', 'asd', 'aaaxxy', 'john doe', 'xxxAAA', 'xxx'], 'xx') == ['xxx', 'aaaxxy', 'xxxAAA', 'xxx']\\n assert candidate(['grunt', 'trumpet', 'prune', 'gruesome'], 'run') == ['grunt', 'prune']\\n\\n\\ncheck(filter_by_substring)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 7,
"original": "from typing import List\n\n\ndef filter_by_substring(strings: List[str], substring: str) -> List[str]:\n \"\"\" Filter an input list of strings only for ones that contain given substring\n >>> filter_by_substring([], 'a')\n []\n >>> filter_by_substring(['abc', 'bacd', 'cde', 'array'], 'a')\n ['abc', 'bacd', 'array']\n \"\"\"\n",
"reference": " return [x for x in strings if substring in x]\n",
"split": "test",
"task_id": "HumanEval/7"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
from typing import List, Tuple
def sum_product(numbers: List[int]) -> Tuple[int, int]:
""" For a given list of integers, return a tuple consisting of a sum and a product of all the integers in a list.
Empty sum should be equal to 0 and empty product should be equal to 1.
>>> sum_product([])
(0, 1)
>>> sum_product([1, 2, 3, 4])
(10, 24)
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {\\n 'author': 'jt',\\n 'dataset': 'test'\\n}\\n\\n\\ndef check(candidate):\\n assert candidate([]) == (0, 1)\\n assert candidate([1, 1, 1]) == (3, 1)\\n assert candidate([100, 0]) == (100, 0)\\n assert candidate([3, 5, 7]) == (3 + 5 + 7, 3 * 5 * 7)\\n assert candidate([10]) == (10, 10)\\n\\n\\ncheck(sum_product)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 8,
"original": "from typing import List, Tuple\n\n\ndef sum_product(numbers: List[int]) -> Tuple[int, int]:\n \"\"\" For a given list of integers, return a tuple consisting of a sum and a product of all the integers in a list.\n Empty sum should be equal to 0 and empty product should be equal to 1.\n >>> sum_product([])\n (0, 1)\n >>> sum_product([1, 2, 3, 4])\n (10, 24)\n \"\"\"\n",
"reference": " sum_value = 0\n prod_value = 1\n\n for n in numbers:\n sum_value += n\n prod_value *= n\n return sum_value, prod_value\n",
"split": "test",
"task_id": "HumanEval/8"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
from typing import List, Tuple
def rolling_max(numbers: List[int]) -> List[int]:
""" From a given list of integers, generate a list of rolling maximum element found until given moment
in the sequence.
>>> rolling_max([1, 2, 3, 2, 3, 4, 2])
[1, 2, 3, 3, 3, 4, 4]
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {\\n 'author': 'jt',\\n 'dataset': 'test'\\n}\\n\\n\\ndef check(candidate):\\n assert candidate([]) == []\\n assert candidate([1, 2, 3, 4]) == [1, 2, 3, 4]\\n assert candidate([4, 3, 2, 1]) == [4, 4, 4, 4]\\n assert candidate([3, 2, 3, 100, 3]) == [3, 3, 3, 100, 100]\\n\\n\\ncheck(rolling_max)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 9,
"original": "from typing import List, Tuple\n\n\ndef rolling_max(numbers: List[int]) -> List[int]:\n \"\"\" From a given list of integers, generate a list of rolling maximum element found until given moment\n in the sequence.\n >>> rolling_max([1, 2, 3, 2, 3, 4, 2])\n [1, 2, 3, 3, 3, 4, 4]\n \"\"\"\n",
"reference": " running_max = None\n result = []\n\n for n in numbers:\n if running_max is None:\n running_max = n\n else:\n running_max = max(running_max, n)\n\n result.append(running_max)\n\n return result\n",
"split": "test",
"task_id": "HumanEval/9"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def is_palindrome(string: str) -> bool:
""" Test if given string is a palindrome """
return string == string[::-1]
def make_palindrome(string: str) -> str:
""" Find the shortest palindrome that begins with a supplied string.
Algorithm idea is simple:
- Find the longest postfix of supplied string that is a palindrome.
- Append to the end of the string reverse of a string prefix that comes before the palindromic suffix.
>>> make_palindrome('')
''
>>> make_palindrome('cat')
'catac'
>>> make_palindrome('cata')
'catac'
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {\\n 'author': 'jt',\\n 'dataset': 'test'\\n}\\n\\n\\ndef check(candidate):\\n assert candidate('') == ''\\n assert candidate('x') == 'x'\\n assert candidate('xyz') == 'xyzyx'\\n assert candidate('xyx') == 'xyx'\\n assert candidate('jerry') == 'jerryrrej'\\n\\n\\ncheck(make_palindrome)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 10,
"original": "\n\ndef is_palindrome(string: str) -> bool:\n \"\"\" Test if given string is a palindrome \"\"\"\n return string == string[::-1]\n\n\ndef make_palindrome(string: str) -> str:\n \"\"\" Find the shortest palindrome that begins with a supplied string.\n Algorithm idea is simple:\n - Find the longest postfix of supplied string that is a palindrome.\n - Append to the end of the string reverse of a string prefix that comes before the palindromic suffix.\n >>> make_palindrome('')\n ''\n >>> make_palindrome('cat')\n 'catac'\n >>> make_palindrome('cata')\n 'catac'\n \"\"\"\n",
"reference": " if not string:\n return ''\n\n beginning_of_suffix = 0\n\n while not is_palindrome(string[beginning_of_suffix:]):\n beginning_of_suffix += 1\n\n return string + string[:beginning_of_suffix][::-1]\n",
"split": "test",
"task_id": "HumanEval/10"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
from typing import List
def string_xor(a: str, b: str) -> str:
""" Input are two strings a and b consisting only of 1s and 0s.
Perform binary XOR on these inputs and return result also as a string.
>>> string_xor('010', '110')
'100'
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {\\n 'author': 'jt',\\n 'dataset': 'test'\\n}\\n\\n\\ndef check(candidate):\\n assert candidate('111000', '101010') == '010010'\\n assert candidate('1', '1') == '0'\\n assert candidate('0101', '0000') == '0101'\\n\\n\\ncheck(string_xor)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 11,
"original": "from typing import List\n\n\ndef string_xor(a: str, b: str) -> str:\n \"\"\" Input are two strings a and b consisting only of 1s and 0s.\n Perform binary XOR on these inputs and return result also as a string.\n >>> string_xor('010', '110')\n '100'\n \"\"\"\n",
"reference": " def xor(i, j):\n if i == j:\n return '0'\n else:\n return '1'\n\n return ''.join(xor(x, y) for x, y in zip(a, b))\n",
"split": "test",
"task_id": "HumanEval/11"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
from typing import List, Optional
def longest(strings: List[str]) -> Optional[str]:
""" Out of list of strings, return the longest one. Return the first one in case of multiple
strings of the same length. Return None in case the input list is empty.
>>> longest([])
>>> longest(['a', 'b', 'c'])
'a'
>>> longest(['a', 'bb', 'ccc'])
'ccc'
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {\\n 'author': 'jt',\\n 'dataset': 'test'\\n}\\n\\n\\ndef check(candidate):\\n assert candidate([]) == None\\n assert candidate(['x', 'y', 'z']) == 'x'\\n assert candidate(['x', 'yyy', 'zzzz', 'www', 'kkkk', 'abc']) == 'zzzz'\\n\\n\\ncheck(longest)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 12,
"original": "from typing import List, Optional\n\n\ndef longest(strings: List[str]) -> Optional[str]:\n \"\"\" Out of list of strings, return the longest one. Return the first one in case of multiple\n strings of the same length. Return None in case the input list is empty.\n >>> longest([])\n\n >>> longest(['a', 'b', 'c'])\n 'a'\n >>> longest(['a', 'bb', 'ccc'])\n 'ccc'\n \"\"\"\n",
"reference": " if not strings:\n return None\n\n maxlen = max(len(x) for x in strings)\n for s in strings:\n if len(s) == maxlen:\n return s\n",
"split": "test",
"task_id": "HumanEval/12"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def greatest_common_divisor(a: int, b: int) -> int:
""" Return a greatest common divisor of two integers a and b
>>> greatest_common_divisor(3, 5)
1
>>> greatest_common_divisor(25, 15)
5
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {\\n 'author': 'jt',\\n 'dataset': 'test'\\n}\\n\\n\\ndef check(candidate):\\n assert candidate(3, 7) == 1\\n assert candidate(10, 15) == 5\\n assert candidate(49, 14) == 7\\n assert candidate(144, 60) == 12\\n\\n\\ncheck(greatest_common_divisor)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 13,
"original": "\n\ndef greatest_common_divisor(a: int, b: int) -> int:\n \"\"\" Return a greatest common divisor of two integers a and b\n >>> greatest_common_divisor(3, 5)\n 1\n >>> greatest_common_divisor(25, 15)\n 5\n \"\"\"\n",
"reference": " while b:\n a, b = b, a % b\n return a\n",
"split": "test",
"task_id": "HumanEval/13"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
from typing import List
def all_prefixes(string: str) -> List[str]:
""" Return list of all prefixes from shortest to longest of the input string
>>> all_prefixes('abc')
['a', 'ab', 'abc']
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {\\n 'author': 'jt',\\n 'dataset': 'test'\\n}\\n\\n\\ndef check(candidate):\\n assert candidate('') == []\\n assert candidate('asdfgh') == ['a', 'as', 'asd', 'asdf', 'asdfg', 'asdfgh']\\n assert candidate('WWW') == ['W', 'WW', 'WWW']\\n\\n\\ncheck(all_prefixes)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 14,
"original": "from typing import List\n\n\ndef all_prefixes(string: str) -> List[str]:\n \"\"\" Return list of all prefixes from shortest to longest of the input string\n >>> all_prefixes('abc')\n ['a', 'ab', 'abc']\n \"\"\"\n",
"reference": " result = []\n\n for i in range(len(string)):\n result.append(string[:i+1])\n return result\n",
"split": "test",
"task_id": "HumanEval/14"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def string_sequence(n: int) -> str:
""" Return a string containing space-delimited numbers starting from 0 upto n inclusive.
>>> string_sequence(0)
'0'
>>> string_sequence(5)
'0 1 2 3 4 5'
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {\\n 'author': 'jt',\\n 'dataset': 'test'\\n}\\n\\n\\ndef check(candidate):\\n assert candidate(0) == '0'\\n assert candidate(3) == '0 1 2 3'\\n assert candidate(10) == '0 1 2 3 4 5 6 7 8 9 10'\\n\\n\\ncheck(string_sequence)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 15,
"original": "\n\ndef string_sequence(n: int) -> str:\n \"\"\" Return a string containing space-delimited numbers starting from 0 upto n inclusive.\n >>> string_sequence(0)\n '0'\n >>> string_sequence(5)\n '0 1 2 3 4 5'\n \"\"\"\n",
"reference": " return ' '.join([str(x) for x in range(n + 1)])\n",
"split": "test",
"task_id": "HumanEval/15"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def count_distinct_characters(string: str) -> int:
""" Given a string, find out how many distinct characters (regardless of case) does it consist of
>>> count_distinct_characters('xyzXYZ')
3
>>> count_distinct_characters('Jerry')
4
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {\\n 'author': 'jt',\\n 'dataset': 'test'\\n}\\n\\n\\ndef check(candidate):\\n assert candidate('') == 0\\n assert candidate('abcde') == 5\\n assert candidate('abcde' + 'cade' + 'CADE') == 5\\n assert candidate('aaaaAAAAaaaa') == 1\\n assert candidate('Jerry jERRY JeRRRY') == 5\\n\\n\\ncheck(count_distinct_characters)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 16,
"original": "\n\ndef count_distinct_characters(string: str) -> int:\n \"\"\" Given a string, find out how many distinct characters (regardless of case) does it consist of\n >>> count_distinct_characters('xyzXYZ')\n 3\n >>> count_distinct_characters('Jerry')\n 4\n \"\"\"\n",
"reference": " return len(set(string.lower()))\n",
"split": "test",
"task_id": "HumanEval/16"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
from typing import List
def parse_music(music_string: str) -> List[int]:
""" Input to this function is a string representing musical notes in a special ASCII format.
Your task is to parse this string and return list of integers corresponding to how many beats does each
not last.
Here is a legend:
'o' - whole note, lasts four beats
'o|' - half note, lasts two beats
'.|' - quater note, lasts one beat
>>> parse_music('o o| .| o| o| .| .| .| .| o o')
[4, 2, 1, 2, 2, 1, 1, 1, 1, 4, 4]
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {\\n 'author': 'jt',\\n 'dataset': 'test'\\n}\\n\\n\\ndef check(candidate):\\n assert candidate('') == []\\n assert candidate('o o o o') == [4, 4, 4, 4]\\n assert candidate('.| .| .| .|') == [1, 1, 1, 1]\\n assert candidate('o| o| .| .| o o o o') == [2, 2, 1, 1, 4, 4, 4, 4]\\n assert candidate('o| .| o| .| o o| o o|') == [2, 1, 2, 1, 4, 2, 4, 2]\\n\\n\\ncheck(parse_music)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 17,
"original": "from typing import List\n\n\ndef parse_music(music_string: str) -> List[int]:\n \"\"\" Input to this function is a string representing musical notes in a special ASCII format.\n Your task is to parse this string and return list of integers corresponding to how many beats does each\n not last.\n\n Here is a legend:\n 'o' - whole note, lasts four beats\n 'o|' - half note, lasts two beats\n '.|' - quater note, lasts one beat\n\n >>> parse_music('o o| .| o| o| .| .| .| .| o o')\n [4, 2, 1, 2, 2, 1, 1, 1, 1, 4, 4]\n \"\"\"\n",
"reference": " note_map = {'o': 4, 'o|': 2, '.|': 1}\n return [note_map[x] for x in music_string.split(' ') if x]\n",
"split": "test",
"task_id": "HumanEval/17"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def how_many_times(string: str, substring: str) -> int:
""" Find how many times a given substring can be found in the original string. Count overlaping cases.
>>> how_many_times('', 'a')
0
>>> how_many_times('aaa', 'a')
3
>>> how_many_times('aaaa', 'aa')
3
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {\\n 'author': 'jt',\\n 'dataset': 'test'\\n}\\n\\n\\ndef check(candidate):\\n assert candidate('', 'x') == 0\\n assert candidate('xyxyxyx', 'x') == 4\\n assert candidate('cacacacac', 'cac') == 4\\n assert candidate('john doe', 'john') == 1\\n\\n\\ncheck(how_many_times)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 18,
"original": "\n\ndef how_many_times(string: str, substring: str) -> int:\n \"\"\" Find how many times a given substring can be found in the original string. Count overlaping cases.\n >>> how_many_times('', 'a')\n 0\n >>> how_many_times('aaa', 'a')\n 3\n >>> how_many_times('aaaa', 'aa')\n 3\n \"\"\"\n",
"reference": " times = 0\n\n for i in range(len(string) - len(substring) + 1):\n if string[i:i+len(substring)] == substring:\n times += 1\n\n return times\n",
"split": "test",
"task_id": "HumanEval/18"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
from typing import List
def sort_numbers(numbers: str) -> str:
""" Input is a space-delimited string of numberals from 'zero' to 'nine'.
Valid choices are 'zero', 'one', 'two', 'three', 'four', 'five', 'six', 'seven', 'eight' and 'nine'.
Return the string with numbers sorted from smallest to largest
>>> sort_numbers('three one five')
'one three five'
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {\\n 'author': 'jt',\\n 'dataset': 'test'\\n}\\n\\n\\ndef check(candidate):\\n assert candidate('') == ''\\n assert candidate('three') == 'three'\\n assert candidate('three five nine') == 'three five nine'\\n assert candidate('five zero four seven nine eight') == 'zero four five seven eight nine'\\n assert candidate('six five four three two one zero') == 'zero one two three four five six'\\n\\n\\ncheck(sort_numbers)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 19,
"original": "from typing import List\n\n\ndef sort_numbers(numbers: str) -> str:\n \"\"\" Input is a space-delimited string of numberals from 'zero' to 'nine'.\n Valid choices are 'zero', 'one', 'two', 'three', 'four', 'five', 'six', 'seven', 'eight' and 'nine'.\n Return the string with numbers sorted from smallest to largest\n >>> sort_numbers('three one five')\n 'one three five'\n \"\"\"\n",
"reference": " value_map = {\n 'zero': 0,\n 'one': 1,\n 'two': 2,\n 'three': 3,\n 'four': 4,\n 'five': 5,\n 'six': 6,\n 'seven': 7,\n 'eight': 8,\n 'nine': 9\n }\n return ' '.join(sorted([x for x in numbers.split(' ') if x], key=lambda x: value_map[x]))\n",
"split": "test",
"task_id": "HumanEval/19"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
from typing import List, Tuple
def find_closest_elements(numbers: List[float]) -> Tuple[float, float]:
""" From a supplied list of numbers (of length at least two) select and return two that are the closest to each
other and return them in order (smaller number, larger number).
>>> find_closest_elements([1.0, 2.0, 3.0, 4.0, 5.0, 2.2])
(2.0, 2.2)
>>> find_closest_elements([1.0, 2.0, 3.0, 4.0, 5.0, 2.0])
(2.0, 2.0)
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {\\n 'author': 'jt',\\n 'dataset': 'test'\\n}\\n\\n\\ndef check(candidate):\\n assert candidate([1.0, 2.0, 3.9, 4.0, 5.0, 2.2]) == (3.9, 4.0)\\n assert candidate([1.0, 2.0, 5.9, 4.0, 5.0]) == (5.0, 5.9)\\n assert candidate([1.0, 2.0, 3.0, 4.0, 5.0, 2.2]) == (2.0, 2.2)\\n assert candidate([1.0, 2.0, 3.0, 4.0, 5.0, 2.0]) == (2.0, 2.0)\\n assert candidate([1.1, 2.2, 3.1, 4.1, 5.1]) == (2.2, 3.1)\\n\\n\\n\\ncheck(find_closest_elements)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 20,
"original": "from typing import List, Tuple\n\n\ndef find_closest_elements(numbers: List[float]) -> Tuple[float, float]:\n \"\"\" From a supplied list of numbers (of length at least two) select and return two that are the closest to each\n other and return them in order (smaller number, larger number).\n >>> find_closest_elements([1.0, 2.0, 3.0, 4.0, 5.0, 2.2])\n (2.0, 2.2)\n >>> find_closest_elements([1.0, 2.0, 3.0, 4.0, 5.0, 2.0])\n (2.0, 2.0)\n \"\"\"\n",
"reference": " closest_pair = None\n distance = None\n\n for idx, elem in enumerate(numbers):\n for idx2, elem2 in enumerate(numbers):\n if idx != idx2:\n if distance is None:\n distance = abs(elem - elem2)\n closest_pair = tuple(sorted([elem, elem2]))\n else:\n new_distance = abs(elem - elem2)\n if new_distance < distance:\n distance = new_distance\n closest_pair = tuple(sorted([elem, elem2]))\n\n return closest_pair\n",
"split": "test",
"task_id": "HumanEval/20"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
from typing import List
def rescale_to_unit(numbers: List[float]) -> List[float]:
""" Given list of numbers (of at least two elements), apply a linear transform to that list,
such that the smallest number will become 0 and the largest will become 1
>>> rescale_to_unit([1.0, 2.0, 3.0, 4.0, 5.0])
[0.0, 0.25, 0.5, 0.75, 1.0]
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {\\n 'author': 'jt',\\n 'dataset': 'test'\\n}\\n\\n\\ndef check(candidate):\\n assert candidate([2.0, 49.9]) == [0.0, 1.0]\\n assert candidate([100.0, 49.9]) == [1.0, 0.0]\\n assert candidate([1.0, 2.0, 3.0, 4.0, 5.0]) == [0.0, 0.25, 0.5, 0.75, 1.0]\\n assert candidate([2.0, 1.0, 5.0, 3.0, 4.0]) == [0.25, 0.0, 1.0, 0.5, 0.75]\\n assert candidate([12.0, 11.0, 15.0, 13.0, 14.0]) == [0.25, 0.0, 1.0, 0.5, 0.75]\\n\\n\\ncheck(rescale_to_unit)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 21,
"original": "from typing import List\n\n\ndef rescale_to_unit(numbers: List[float]) -> List[float]:\n \"\"\" Given list of numbers (of at least two elements), apply a linear transform to that list,\n such that the smallest number will become 0 and the largest will become 1\n >>> rescale_to_unit([1.0, 2.0, 3.0, 4.0, 5.0])\n [0.0, 0.25, 0.5, 0.75, 1.0]\n \"\"\"\n",
"reference": " min_number = min(numbers)\n max_number = max(numbers)\n return [(x - min_number) / (max_number - min_number) for x in numbers]\n",
"split": "test",
"task_id": "HumanEval/21"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
from typing import List, Any
def filter_integers(values: List[Any]) -> List[int]:
""" Filter given list of any python values only for integers
>>> filter_integers(['a', 3.14, 5])
[5]
>>> filter_integers([1, 2, 3, 'abc', {}, []])
[1, 2, 3]
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {\\n 'author': 'jt',\\n 'dataset': 'test'\\n}\\n\\n\\ndef check(candidate):\\n assert candidate([]) == []\\n assert candidate([4, {}, [], 23.2, 9, 'adasd']) == [4, 9]\\n assert candidate([3, 'c', 3, 3, 'a', 'b']) == [3, 3, 3]\\n\\n\\ncheck(filter_integers)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 22,
"original": "from typing import List, Any\n\n\ndef filter_integers(values: List[Any]) -> List[int]:\n \"\"\" Filter given list of any python values only for integers\n >>> filter_integers(['a', 3.14, 5])\n [5]\n >>> filter_integers([1, 2, 3, 'abc', {}, []])\n [1, 2, 3]\n \"\"\"\n",
"reference": " return [x for x in values if isinstance(x, int)]\n",
"split": "test",
"task_id": "HumanEval/22"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def strlen(string: str) -> int:
""" Return length of given string
>>> strlen('')
0
>>> strlen('abc')
3
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {\\n 'author': 'jt',\\n 'dataset': 'test'\\n}\\n\\n\\ndef check(candidate):\\n assert candidate('') == 0\\n assert candidate('x') == 1\\n assert candidate('asdasnakj') == 9\\n\\n\\ncheck(strlen)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 23,
"original": "\n\ndef strlen(string: str) -> int:\n \"\"\" Return length of given string\n >>> strlen('')\n 0\n >>> strlen('abc')\n 3\n \"\"\"\n",
"reference": " return len(string)\n",
"split": "test",
"task_id": "HumanEval/23"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def largest_divisor(n: int) -> int:
""" For a given number n, find the largest number that divides n evenly, smaller than n
>>> largest_divisor(15)
5
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {\\n 'author': 'jt',\\n 'dataset': 'test'\\n}\\n\\n\\ndef check(candidate):\\n assert candidate(3) == 1\\n assert candidate(7) == 1\\n assert candidate(10) == 5\\n assert candidate(100) == 50\\n assert candidate(49) == 7\\n\\n\\ncheck(largest_divisor)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 24,
"original": "\n\ndef largest_divisor(n: int) -> int:\n \"\"\" For a given number n, find the largest number that divides n evenly, smaller than n\n >>> largest_divisor(15)\n 5\n \"\"\"\n",
"reference": " for i in reversed(range(n)):\n if n % i == 0:\n return i\n",
"split": "test",
"task_id": "HumanEval/24"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
from typing import List
def factorize(n: int) -> List[int]:
""" Return list of prime factors of given integer in the order from smallest to largest.
Each of the factors should be listed number of times corresponding to how many times it appeares in factorization.
Input number should be equal to the product of all factors
>>> factorize(8)
[2, 2, 2]
>>> factorize(25)
[5, 5]
>>> factorize(70)
[2, 5, 7]
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {\\n 'author': 'jt',\\n 'dataset': 'test'\\n}\\n\\n\\ndef check(candidate):\\n assert candidate(2) == [2]\\n assert candidate(4) == [2, 2]\\n assert candidate(8) == [2, 2, 2]\\n assert candidate(3 * 19) == [3, 19]\\n assert candidate(3 * 19 * 3 * 19) == [3, 3, 19, 19]\\n assert candidate(3 * 19 * 3 * 19 * 3 * 19) == [3, 3, 3, 19, 19, 19]\\n assert candidate(3 * 19 * 19 * 19) == [3, 19, 19, 19]\\n assert candidate(3 * 2 * 3) == [2, 3, 3]\\n\\n\\ncheck(factorize)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 25,
"original": "from typing import List\n\n\ndef factorize(n: int) -> List[int]:\n \"\"\" Return list of prime factors of given integer in the order from smallest to largest.\n Each of the factors should be listed number of times corresponding to how many times it appeares in factorization.\n Input number should be equal to the product of all factors\n >>> factorize(8)\n [2, 2, 2]\n >>> factorize(25)\n [5, 5]\n >>> factorize(70)\n [2, 5, 7]\n \"\"\"\n",
"reference": " import math\n fact = []\n i = 2\n while i <= int(math.sqrt(n) + 1):\n if n % i == 0:\n fact.append(i)\n n //= i\n else:\n i += 1\n\n if n > 1:\n fact.append(n)\n return fact\n",
"split": "test",
"task_id": "HumanEval/25"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
from typing import List
def remove_duplicates(numbers: List[int]) -> List[int]:
""" From a list of integers, remove all elements that occur more than once.
Keep order of elements left the same as in the input.
>>> remove_duplicates([1, 2, 3, 2, 4])
[1, 3, 4]
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {\\n 'author': 'jt',\\n 'dataset': 'test'\\n}\\n\\n\\ndef check(candidate):\\n assert candidate([]) == []\\n assert candidate([1, 2, 3, 4]) == [1, 2, 3, 4]\\n assert candidate([1, 2, 3, 2, 4, 3, 5]) == [1, 4, 5]\\n\\n\\ncheck(remove_duplicates)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 26,
"original": "from typing import List\n\n\ndef remove_duplicates(numbers: List[int]) -> List[int]:\n \"\"\" From a list of integers, remove all elements that occur more than once.\n Keep order of elements left the same as in the input.\n >>> remove_duplicates([1, 2, 3, 2, 4])\n [1, 3, 4]\n \"\"\"\n",
"reference": " import collections\n c = collections.Counter(numbers)\n return [n for n in numbers if c[n] <= 1]\n",
"split": "test",
"task_id": "HumanEval/26"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def flip_case(string: str) -> str:
""" For a given string, flip lowercase characters to uppercase and uppercase to lowercase.
>>> flip_case('Hello')
'hELLO'
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {\\n 'author': 'jt',\\n 'dataset': 'test'\\n}\\n\\n\\ndef check(candidate):\\n assert candidate('') == ''\\n assert candidate('Hello!') == 'hELLO!'\\n assert candidate('These violent delights have violent ends') == 'tHESE VIOLENT DELIGHTS HAVE VIOLENT ENDS'\\n\\n\\ncheck(flip_case)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 27,
"original": "\n\ndef flip_case(string: str) -> str:\n \"\"\" For a given string, flip lowercase characters to uppercase and uppercase to lowercase.\n >>> flip_case('Hello')\n 'hELLO'\n \"\"\"\n",
"reference": " return string.swapcase()\n",
"split": "test",
"task_id": "HumanEval/27"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
from typing import List
def concatenate(strings: List[str]) -> str:
""" Concatenate list of strings into a single string
>>> concatenate([])
''
>>> concatenate(['a', 'b', 'c'])
'abc'
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {\\n 'author': 'jt',\\n 'dataset': 'test'\\n}\\n\\n\\ndef check(candidate):\\n assert candidate([]) == ''\\n assert candidate(['x', 'y', 'z']) == 'xyz'\\n assert candidate(['x', 'y', 'z', 'w', 'k']) == 'xyzwk'\\n\\n\\ncheck(concatenate)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 28,
"original": "from typing import List\n\n\ndef concatenate(strings: List[str]) -> str:\n \"\"\" Concatenate list of strings into a single string\n >>> concatenate([])\n ''\n >>> concatenate(['a', 'b', 'c'])\n 'abc'\n \"\"\"\n",
"reference": " return ''.join(strings)\n",
"split": "test",
"task_id": "HumanEval/28"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
from typing import List
def filter_by_prefix(strings: List[str], prefix: str) -> List[str]:
""" Filter an input list of strings only for ones that start with a given prefix.
>>> filter_by_prefix([], 'a')
[]
>>> filter_by_prefix(['abc', 'bcd', 'cde', 'array'], 'a')
['abc', 'array']
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {\\n 'author': 'jt',\\n 'dataset': 'test'\\n}\\n\\n\\ndef check(candidate):\\n assert candidate([], 'john') == []\\n assert candidate(['xxx', 'asd', 'xxy', 'john doe', 'xxxAAA', 'xxx'], 'xxx') == ['xxx', 'xxxAAA', 'xxx']\\n\\n\\ncheck(filter_by_prefix)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 29,
"original": "from typing import List\n\n\ndef filter_by_prefix(strings: List[str], prefix: str) -> List[str]:\n \"\"\" Filter an input list of strings only for ones that start with a given prefix.\n >>> filter_by_prefix([], 'a')\n []\n >>> filter_by_prefix(['abc', 'bcd', 'cde', 'array'], 'a')\n ['abc', 'array']\n \"\"\"\n",
"reference": " return [x for x in strings if x.startswith(prefix)]\n",
"split": "test",
"task_id": "HumanEval/29"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def get_positive(l: list):
"""Return only positive numbers in the list.
>>> get_positive([-1, 2, -4, 5, 6])
[2, 5, 6]
>>> get_positive([5, 3, -5, 2, -3, 3, 9, 0, 123, 1, -10])
[5, 3, 2, 3, 9, 123, 1]
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {}\\n\\n\\ndef check(candidate):\\n assert candidate([-1, -2, 4, 5, 6]) == [4, 5, 6]\\n assert candidate([5, 3, -5, 2, 3, 3, 9, 0, 123, 1, -10]) == [5, 3, 2, 3, 3, 9, 123, 1]\\n assert candidate([-1, -2]) == []\\n assert candidate([]) == []\\n\\n\\n\\ncheck(get_positive)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 30,
"original": "\n\ndef get_positive(l: list):\n \"\"\"Return only positive numbers in the list.\n >>> get_positive([-1, 2, -4, 5, 6])\n [2, 5, 6]\n >>> get_positive([5, 3, -5, 2, -3, 3, 9, 0, 123, 1, -10])\n [5, 3, 2, 3, 9, 123, 1]\n \"\"\"\n",
"reference": " return [e for e in l if e > 0]\n",
"split": "test",
"task_id": "HumanEval/30"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def is_prime(n):
"""Return true if a given number is prime, and false otherwise.
>>> is_prime(6)
False
>>> is_prime(101)
True
>>> is_prime(11)
True
>>> is_prime(13441)
True
>>> is_prime(61)
True
>>> is_prime(4)
False
>>> is_prime(1)
False
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {}\\n\\n\\ndef check(candidate):\\n assert candidate(6) == False\\n assert candidate(101) == True\\n assert candidate(11) == True\\n assert candidate(13441) == True\\n assert candidate(61) == True\\n assert candidate(4) == False\\n assert candidate(1) == False\\n assert candidate(5) == True\\n assert candidate(11) == True\\n assert candidate(17) == True\\n assert candidate(5 * 17) == False\\n assert candidate(11 * 7) == False\\n assert candidate(13441 * 19) == False\\n\\n\\n\\ncheck(is_prime)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 31,
"original": "\n\ndef is_prime(n):\n \"\"\"Return true if a given number is prime, and false otherwise.\n >>> is_prime(6)\n False\n >>> is_prime(101)\n True\n >>> is_prime(11)\n True\n >>> is_prime(13441)\n True\n >>> is_prime(61)\n True\n >>> is_prime(4)\n False\n >>> is_prime(1)\n False\n \"\"\"\n",
"reference": " if n < 2:\n return False\n for k in range(2, n - 1):\n if n % k == 0:\n return False\n return True\n",
"split": "test",
"task_id": "HumanEval/31"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
import math
def poly(xs: list, x: float):
"""
Evaluates polynomial with coefficients xs at point x.
return xs[0] + xs[1] * x + xs[1] * x^2 + .... xs[n] * x^n
"""
return sum([coeff * math.pow(x, i) for i, coeff in enumerate(xs)])
def find_zero(xs: list):
""" xs are coefficients of a polynomial.
find_zero find x such that poly(x) = 0.
find_zero returns only only zero point, even if there are many.
Moreover, find_zero only takes list xs having even number of coefficients
and largest non zero coefficient as it guarantees
a solution.
>>> round(find_zero([1, 2]), 2) # f(x) = 1 + 2x
-0.5
>>> round(find_zero([-6, 11, -6, 1]), 2) # (x - 1) * (x - 2) * (x - 3) = -6 + 11x - 6x^2 + x^3
1.0
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {}\\n\\n\\ndef check(candidate):\\n import math\\n import random\\n rng = random.Random(42)\\n import copy\\n for _ in range(100):\\n ncoeff = 2 * rng.randint(1, 4)\\n coeffs = []\\n for _ in range(ncoeff):\\n coeff = rng.randint(-10, 10)\\n if coeff == 0:\\n coeff = 1\\n coeffs.append(coeff)\\n solution = candidate(copy.deepcopy(coeffs))\\n assert math.fabs(poly(coeffs, solution)) < 1e-4\\n\\n\\n\\ncheck(find_zero)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 32,
"original": "import math\n\n\ndef poly(xs: list, x: float):\n \"\"\"\n Evaluates polynomial with coefficients xs at point x.\n return xs[0] + xs[1] * x + xs[1] * x^2 + .... xs[n] * x^n\n \"\"\"\n return sum([coeff * math.pow(x, i) for i, coeff in enumerate(xs)])\n\n\ndef find_zero(xs: list):\n \"\"\" xs are coefficients of a polynomial.\n find_zero find x such that poly(x) = 0.\n find_zero returns only only zero point, even if there are many.\n Moreover, find_zero only takes list xs having even number of coefficients\n and largest non zero coefficient as it guarantees\n a solution.\n >>> round(find_zero([1, 2]), 2) # f(x) = 1 + 2x\n -0.5\n >>> round(find_zero([-6, 11, -6, 1]), 2) # (x - 1) * (x - 2) * (x - 3) = -6 + 11x - 6x^2 + x^3\n 1.0\n \"\"\"\n",
"reference": " begin, end = -1., 1.\n while poly(xs, begin) * poly(xs, end) > 0:\n begin *= 2.0\n end *= 2.0\n while end - begin > 1e-10:\n center = (begin + end) / 2.0\n if poly(xs, center) * poly(xs, begin) > 0:\n begin = center\n else:\n end = center\n return begin\n",
"split": "test",
"task_id": "HumanEval/32"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def sort_third(l: list):
"""This function takes a list l and returns a list l' such that
l' is identical to l in the indicies that are not divisible by three, while its values at the indicies that are divisible by three are equal
to the values of the corresponding indicies of l, but sorted.
>>> sort_third([1, 2, 3])
[1, 2, 3]
>>> sort_third([5, 6, 3, 4, 8, 9, 2])
[2, 6, 3, 4, 8, 9, 5]
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {}\\n\\n\\ndef check(candidate):\\n assert tuple(candidate([1, 2, 3])) == tuple(sort_third([1, 2, 3]))\\n assert tuple(candidate([5, 3, -5, 2, -3, 3, 9, 0, 123, 1, -10])) == tuple(sort_third([5, 3, -5, 2, -3, 3, 9, 0, 123, 1, -10]))\\n assert tuple(candidate([5, 8, -12, 4, 23, 2, 3, 11, 12, -10])) == tuple(sort_third([5, 8, -12, 4, 23, 2, 3, 11, 12, -10]))\\n assert tuple(candidate([5, 6, 3, 4, 8, 9, 2])) == tuple([2, 6, 3, 4, 8, 9, 5])\\n assert tuple(candidate([5, 8, 3, 4, 6, 9, 2])) == tuple([2, 8, 3, 4, 6, 9, 5])\\n assert tuple(candidate([5, 6, 9, 4, 8, 3, 2])) == tuple([2, 6, 9, 4, 8, 3, 5])\\n assert tuple(candidate([5, 6, 3, 4, 8, 9, 2, 1])) == tuple([2, 6, 3, 4, 8, 9, 5, 1])\\n\\n\\n\\ncheck(sort_third)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 33,
"original": "\n\ndef sort_third(l: list):\n \"\"\"This function takes a list l and returns a list l' such that\n l' is identical to l in the indicies that are not divisible by three, while its values at the indicies that are divisible by three are equal\n to the values of the corresponding indicies of l, but sorted.\n >>> sort_third([1, 2, 3])\n [1, 2, 3]\n >>> sort_third([5, 6, 3, 4, 8, 9, 2])\n [2, 6, 3, 4, 8, 9, 5]\n \"\"\"\n",
"reference": " l = list(l)\n l[::3] = sorted(l[::3])\n return l\n",
"split": "test",
"task_id": "HumanEval/33"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def unique(l: list):
"""Return sorted unique elements in a list
>>> unique([5, 3, 5, 2, 3, 3, 9, 0, 123])
[0, 2, 3, 5, 9, 123]
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {}\\n\\n\\ndef check(candidate):\\n assert candidate([5, 3, 5, 2, 3, 3, 9, 0, 123]) == [0, 2, 3, 5, 9, 123]\\n\\n\\n\\ncheck(unique)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 34,
"original": "\n\ndef unique(l: list):\n \"\"\"Return sorted unique elements in a list\n >>> unique([5, 3, 5, 2, 3, 3, 9, 0, 123])\n [0, 2, 3, 5, 9, 123]\n \"\"\"\n",
"reference": " return sorted(list(set(l)))\n",
"split": "test",
"task_id": "HumanEval/34"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def max_element(l: list):
"""Return maximum element in the list.
>>> max_element([1, 2, 3])
3
>>> max_element([5, 3, -5, 2, -3, 3, 9, 0, 123, 1, -10])
123
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {}\\n\\n\\ndef check(candidate):\\n assert candidate([1, 2, 3]) == 3\\n assert candidate([5, 3, -5, 2, -3, 3, 9, 0, 124, 1, -10]) == 124\\n\\n\\ncheck(max_element)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 35,
"original": "\n\ndef max_element(l: list):\n \"\"\"Return maximum element in the list.\n >>> max_element([1, 2, 3])\n 3\n >>> max_element([5, 3, -5, 2, -3, 3, 9, 0, 123, 1, -10])\n 123\n \"\"\"\n",
"reference": " m = l[0]\n for e in l:\n if e > m:\n m = e\n return m\n",
"split": "test",
"task_id": "HumanEval/35"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def fizz_buzz(n: int):
"""Return the number of times the digit 7 appears in integers less than n which are divisible by 11 or 13.
>>> fizz_buzz(50)
0
>>> fizz_buzz(78)
2
>>> fizz_buzz(79)
3
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {}\\n\\n\\ndef check(candidate):\\n assert candidate(50) == 0\\n assert candidate(78) == 2\\n assert candidate(79) == 3\\n assert candidate(100) == 3\\n assert candidate(200) == 6\\n assert candidate(4000) == 192\\n assert candidate(10000) == 639\\n assert candidate(100000) == 8026\\n\\n\\n\\ncheck(fizz_buzz)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 36,
"original": "\n\ndef fizz_buzz(n: int):\n \"\"\"Return the number of times the digit 7 appears in integers less than n which are divisible by 11 or 13.\n >>> fizz_buzz(50)\n 0\n >>> fizz_buzz(78)\n 2\n >>> fizz_buzz(79)\n 3\n \"\"\"\n",
"reference": " ns = []\n for i in range(n):\n if i % 11 == 0 or i % 13 == 0:\n ns.append(i)\n s = ''.join(list(map(str, ns)))\n ans = 0\n for c in s:\n ans += (c == '7')\n return ans\n",
"split": "test",
"task_id": "HumanEval/36"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def sort_even(l: list):
"""This function takes a list l and returns a list l' such that
l' is identical to l in the odd indicies, while its values at the even indicies are equal
to the values of the even indicies of l, but sorted.
>>> sort_even([1, 2, 3])
[1, 2, 3]
>>> sort_even([5, 6, 3, 4])
[3, 6, 5, 4]
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {}\\n\\n\\ndef check(candidate):\\n assert tuple(candidate([1, 2, 3])) == tuple([1, 2, 3])\\n assert tuple(candidate([5, 3, -5, 2, -3, 3, 9, 0, 123, 1, -10])) == tuple([-10, 3, -5, 2, -3, 3, 5, 0, 9, 1, 123])\\n assert tuple(candidate([5, 8, -12, 4, 23, 2, 3, 11, 12, -10])) == tuple([-12, 8, 3, 4, 5, 2, 12, 11, 23, -10])\\n\\n\\n\\ncheck(sort_even)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 37,
"original": "\n\ndef sort_even(l: list):\n \"\"\"This function takes a list l and returns a list l' such that\n l' is identical to l in the odd indicies, while its values at the even indicies are equal\n to the values of the even indicies of l, but sorted.\n >>> sort_even([1, 2, 3])\n [1, 2, 3]\n >>> sort_even([5, 6, 3, 4])\n [3, 6, 5, 4]\n \"\"\"\n",
"reference": " evens = l[::2]\n odds = l[1::2]\n evens.sort()\n ans = []\n for e, o in zip(evens, odds):\n ans.extend([e, o])\n if len(evens) > len(odds):\n ans.append(evens[-1])\n return ans\n",
"split": "test",
"task_id": "HumanEval/37"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def encode_cyclic(s: str):
"""
returns encoded string by cycling groups of three characters.
"""
# split string to groups. Each of length 3.
groups = [s[(3 * i):min((3 * i + 3), len(s))] for i in range((len(s) + 2) // 3)]
# cycle elements in each group. Unless group has fewer elements than 3.
groups = [(group[1:] + group[0]) if len(group) == 3 else group for group in groups]
return "".join(groups)
def decode_cyclic(s: str):
"""
takes as input string encoded with encode_cyclic function. Returns decoded string.
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {}\\n\\n\\ndef check(candidate):\\n from random import randint, choice\\n import string\\n\\n letters = string.ascii_lowercase\\n for _ in range(100):\\n str = ''.join(choice(letters) for i in range(randint(10, 20)))\\n encoded_str = encode_cyclic(str)\\n assert candidate(encoded_str) == str\\n\\n\\n\\ncheck(decode_cyclic)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 38,
"original": "\n\ndef encode_cyclic(s: str):\n \"\"\"\n returns encoded string by cycling groups of three characters.\n \"\"\"\n # split string to groups. Each of length 3.\n groups = [s[(3 * i):min((3 * i + 3), len(s))] for i in range((len(s) + 2) // 3)]\n # cycle elements in each group. Unless group has fewer elements than 3.\n groups = [(group[1:] + group[0]) if len(group) == 3 else group for group in groups]\n return \"\".join(groups)\n\n\ndef decode_cyclic(s: str):\n \"\"\"\n takes as input string encoded with encode_cyclic function. Returns decoded string.\n \"\"\"\n",
"reference": " return encode_cyclic(encode_cyclic(s))\n",
"split": "test",
"task_id": "HumanEval/38"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def prime_fib(n: int):
"""
prime_fib returns n-th number that is a Fibonacci number and it's also prime.
>>> prime_fib(1)
2
>>> prime_fib(2)
3
>>> prime_fib(3)
5
>>> prime_fib(4)
13
>>> prime_fib(5)
89
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {}\\n\\n\\ndef check(candidate):\\n assert candidate(1) == 2\\n assert candidate(2) == 3\\n assert candidate(3) == 5\\n assert candidate(4) == 13\\n assert candidate(5) == 89\\n assert candidate(6) == 233\\n assert candidate(7) == 1597\\n assert candidate(8) == 28657\\n assert candidate(9) == 514229\\n assert candidate(10) == 433494437\\n\\n\\n\\ncheck(prime_fib)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 39,
"original": "\n\ndef prime_fib(n: int):\n \"\"\"\n prime_fib returns n-th number that is a Fibonacci number and it's also prime.\n >>> prime_fib(1)\n 2\n >>> prime_fib(2)\n 3\n >>> prime_fib(3)\n 5\n >>> prime_fib(4)\n 13\n >>> prime_fib(5)\n 89\n \"\"\"\n",
"reference": " import math\n\n def is_prime(p):\n if p < 2:\n return False\n for k in range(2, min(int(math.sqrt(p)) + 1, p - 1)):\n if p % k == 0:\n return False\n return True\n f = [0, 1]\n while True:\n f.append(f[-1] + f[-2])\n if is_prime(f[-1]):\n n -= 1\n if n == 0:\n return f[-1]\n",
"split": "test",
"task_id": "HumanEval/39"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def triples_sum_to_zero(l: list):
"""
triples_sum_to_zero takes a list of integers as an input.
it returns True if there are three distinct elements in the list that
sum to zero, and False otherwise.
>>> triples_sum_to_zero([1, 3, 5, 0])
False
>>> triples_sum_to_zero([1, 3, -2, 1])
True
>>> triples_sum_to_zero([1, 2, 3, 7])
False
>>> triples_sum_to_zero([2, 4, -5, 3, 9, 7])
True
>>> triples_sum_to_zero([1])
False
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {}\\n\\n\\ndef check(candidate):\\n assert candidate([1, 3, 5, 0]) == False\\n assert candidate([1, 3, 5, -1]) == False\\n assert candidate([1, 3, -2, 1]) == True\\n assert candidate([1, 2, 3, 7]) == False\\n assert candidate([1, 2, 5, 7]) == False\\n assert candidate([2, 4, -5, 3, 9, 7]) == True\\n assert candidate([1]) == False\\n assert candidate([1, 3, 5, -100]) == False\\n assert candidate([100, 3, 5, -100]) == False\\n\\n\\n\\ncheck(triples_sum_to_zero)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 40,
"original": "\n\ndef triples_sum_to_zero(l: list):\n \"\"\"\n triples_sum_to_zero takes a list of integers as an input.\n it returns True if there are three distinct elements in the list that\n sum to zero, and False otherwise.\n\n >>> triples_sum_to_zero([1, 3, 5, 0])\n False\n >>> triples_sum_to_zero([1, 3, -2, 1])\n True\n >>> triples_sum_to_zero([1, 2, 3, 7])\n False\n >>> triples_sum_to_zero([2, 4, -5, 3, 9, 7])\n True\n >>> triples_sum_to_zero([1])\n False\n \"\"\"\n",
"reference": " for i in range(len(l)):\n for j in range(i + 1, len(l)):\n for k in range(j + 1, len(l)):\n if l[i] + l[j] + l[k] == 0:\n return True\n return False\n",
"split": "test",
"task_id": "HumanEval/40"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def car_race_collision(n: int):
"""
Imagine a road that's a perfectly straight infinitely long line.
n cars are driving left to right; simultaneously, a different set of n cars
are driving right to left. The two sets of cars start out being very far from
each other. All cars move in the same speed. Two cars are said to collide
when a car that's moving left to right hits a car that's moving right to left.
However, the cars are infinitely sturdy and strong; as a result, they continue moving
in their trajectory as if they did not collide.
This function outputs the number of such collisions.
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {}\\n\\n\\ndef check(candidate):\\n assert candidate(2) == 4\\n assert candidate(3) == 9\\n assert candidate(4) == 16\\n assert candidate(8) == 64\\n assert candidate(10) == 100\\n\\n\\n\\ncheck(car_race_collision)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 41,
"original": "\n\ndef car_race_collision(n: int):\n \"\"\"\n Imagine a road that's a perfectly straight infinitely long line.\n n cars are driving left to right; simultaneously, a different set of n cars\n are driving right to left. The two sets of cars start out being very far from\n each other. All cars move in the same speed. Two cars are said to collide\n when a car that's moving left to right hits a car that's moving right to left.\n However, the cars are infinitely sturdy and strong; as a result, they continue moving\n in their trajectory as if they did not collide.\n\n This function outputs the number of such collisions.\n \"\"\"\n",
"reference": " return n**2\n",
"split": "test",
"task_id": "HumanEval/41"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def incr_list(l: list):
"""Return list with elements incremented by 1.
>>> incr_list([1, 2, 3])
[2, 3, 4]
>>> incr_list([5, 3, 5, 2, 3, 3, 9, 0, 123])
[6, 4, 6, 3, 4, 4, 10, 1, 124]
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {}\\n\\n\\ndef check(candidate):\\n assert candidate([]) == []\\n assert candidate([3, 2, 1]) == [4, 3, 2]\\n assert candidate([5, 2, 5, 2, 3, 3, 9, 0, 123]) == [6, 3, 6, 3, 4, 4, 10, 1, 124]\\n\\n\\n\\ncheck(incr_list)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 42,
"original": "\n\ndef incr_list(l: list):\n \"\"\"Return list with elements incremented by 1.\n >>> incr_list([1, 2, 3])\n [2, 3, 4]\n >>> incr_list([5, 3, 5, 2, 3, 3, 9, 0, 123])\n [6, 4, 6, 3, 4, 4, 10, 1, 124]\n \"\"\"\n",
"reference": " return [(e + 1) for e in l]\n",
"split": "test",
"task_id": "HumanEval/42"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def pairs_sum_to_zero(l):
"""
pairs_sum_to_zero takes a list of integers as an input.
it returns True if there are two distinct elements in the list that
sum to zero, and False otherwise.
>>> pairs_sum_to_zero([1, 3, 5, 0])
False
>>> pairs_sum_to_zero([1, 3, -2, 1])
False
>>> pairs_sum_to_zero([1, 2, 3, 7])
False
>>> pairs_sum_to_zero([2, 4, -5, 3, 5, 7])
True
>>> pairs_sum_to_zero([1])
False
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {}\\n\\n\\ndef check(candidate):\\n assert candidate([1, 3, 5, 0]) == False\\n assert candidate([1, 3, -2, 1]) == False\\n assert candidate([1, 2, 3, 7]) == False\\n assert candidate([2, 4, -5, 3, 5, 7]) == True\\n assert candidate([1]) == False\\n\\n assert candidate([-3, 9, -1, 3, 2, 30]) == True\\n assert candidate([-3, 9, -1, 3, 2, 31]) == True\\n assert candidate([-3, 9, -1, 4, 2, 30]) == False\\n assert candidate([-3, 9, -1, 4, 2, 31]) == False\\n\\n\\n\\ncheck(pairs_sum_to_zero)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 43,
"original": "\n\ndef pairs_sum_to_zero(l):\n \"\"\"\n pairs_sum_to_zero takes a list of integers as an input.\n it returns True if there are two distinct elements in the list that\n sum to zero, and False otherwise.\n >>> pairs_sum_to_zero([1, 3, 5, 0])\n False\n >>> pairs_sum_to_zero([1, 3, -2, 1])\n False\n >>> pairs_sum_to_zero([1, 2, 3, 7])\n False\n >>> pairs_sum_to_zero([2, 4, -5, 3, 5, 7])\n True\n >>> pairs_sum_to_zero([1])\n False\n \"\"\"\n",
"reference": " for i, l1 in enumerate(l):\n for j in range(i + 1, len(l)):\n if l1 + l[j] == 0:\n return True\n return False\n",
"split": "test",
"task_id": "HumanEval/43"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def change_base(x: int, base: int):
"""Change numerical base of input number x to base.
return string representation after the conversion.
base numbers are less than 10.
>>> change_base(8, 3)
'22'
>>> change_base(8, 2)
'1000'
>>> change_base(7, 2)
'111'
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {}\\n\\n\\ndef check(candidate):\\n assert candidate(8, 3) == \\\"22\\\"\\n assert candidate(9, 3) == \\\"100\\\"\\n assert candidate(234, 2) == \\\"11101010\\\"\\n assert candidate(16, 2) == \\\"10000\\\"\\n assert candidate(8, 2) == \\\"1000\\\"\\n assert candidate(7, 2) == \\\"111\\\"\\n for x in range(2, 8):\\n assert candidate(x, x + 1) == str(x)\\n\\n\\n\\ncheck(change_base)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 44,
"original": "\n\ndef change_base(x: int, base: int):\n \"\"\"Change numerical base of input number x to base.\n return string representation after the conversion.\n base numbers are less than 10.\n >>> change_base(8, 3)\n '22'\n >>> change_base(8, 2)\n '1000'\n >>> change_base(7, 2)\n '111'\n \"\"\"\n",
"reference": " ret = \"\"\n while x > 0:\n ret = str(x % base) + ret\n x //= base\n return ret\n",
"split": "test",
"task_id": "HumanEval/44"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def triangle_area(a, h):
"""Given length of a side and high return area for a triangle.
>>> triangle_area(5, 3)
7.5
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {}\\n\\n\\ndef check(candidate):\\n assert candidate(5, 3) == 7.5\\n assert candidate(2, 2) == 2.0\\n assert candidate(10, 8) == 40.0\\n\\n\\n\\ncheck(triangle_area)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 45,
"original": "\n\ndef triangle_area(a, h):\n \"\"\"Given length of a side and high return area for a triangle.\n >>> triangle_area(5, 3)\n 7.5\n \"\"\"\n",
"reference": " return a * h / 2.0\n",
"split": "test",
"task_id": "HumanEval/45"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def fib4(n: int):
"""The Fib4 number sequence is a sequence similar to the Fibbonacci sequnece that's defined as follows:
fib4(0) -> 0
fib4(1) -> 0
fib4(2) -> 2
fib4(3) -> 0
fib4(n) -> fib4(n-1) + fib4(n-2) + fib4(n-3) + fib4(n-4).
Please write a function to efficiently compute the n-th element of the fib4 number sequence. Do not use recursion.
>>> fib4(5)
4
>>> fib4(6)
8
>>> fib4(7)
14
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {}\\n\\n\\ndef check(candidate):\\n assert candidate(5) == 4\\n assert candidate(8) == 28\\n assert candidate(10) == 104\\n assert candidate(12) == 386\\n\\n\\n\\ncheck(fib4)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 46,
"original": "\n\ndef fib4(n: int):\n \"\"\"The Fib4 number sequence is a sequence similar to the Fibbonacci sequnece that's defined as follows:\n fib4(0) -> 0\n fib4(1) -> 0\n fib4(2) -> 2\n fib4(3) -> 0\n fib4(n) -> fib4(n-1) + fib4(n-2) + fib4(n-3) + fib4(n-4).\n Please write a function to efficiently compute the n-th element of the fib4 number sequence. Do not use recursion.\n >>> fib4(5)\n 4\n >>> fib4(6)\n 8\n >>> fib4(7)\n 14\n \"\"\"\n",
"reference": " results = [0, 0, 2, 0]\n if n < 4:\n return results[n]\n\n for _ in range(4, n + 1):\n results.append(results[-1] + results[-2] + results[-3] + results[-4])\n results.pop(0)\n\n return results[-1]\n",
"split": "test",
"task_id": "HumanEval/46"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def median(l: list):
"""Return median of elements in the list l.
>>> median([3, 1, 2, 4, 5])
3
>>> median([-10, 4, 6, 1000, 10, 20])
15.0
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {}\\n\\n\\ndef check(candidate):\\n assert candidate([3, 1, 2, 4, 5]) == 3\\n assert candidate([-10, 4, 6, 1000, 10, 20]) == 8.0\\n assert candidate([5]) == 5\\n assert candidate([6, 5]) == 5.5\\n assert candidate([8, 1, 3, 9, 9, 2, 7]) == 7 \\n\\n\\n\\ncheck(median)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 47,
"original": "\n\ndef median(l: list):\n \"\"\"Return median of elements in the list l.\n >>> median([3, 1, 2, 4, 5])\n 3\n >>> median([-10, 4, 6, 1000, 10, 20])\n 15.0\n \"\"\"\n",
"reference": " l = sorted(l)\n if len(l) % 2 == 1:\n return l[len(l) // 2]\n else:\n return (l[len(l) // 2 - 1] + l[len(l) // 2]) / 2.0\n",
"split": "test",
"task_id": "HumanEval/47"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def is_palindrome(text: str):
"""
Checks if given string is a palindrome
>>> is_palindrome('')
True
>>> is_palindrome('aba')
True
>>> is_palindrome('aaaaa')
True
>>> is_palindrome('zbcd')
False
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {}\\n\\n\\ndef check(candidate):\\n assert candidate('') == True\\n assert candidate('aba') == True\\n assert candidate('aaaaa') == True\\n assert candidate('zbcd') == False\\n assert candidate('xywyx') == True\\n assert candidate('xywyz') == False\\n assert candidate('xywzx') == False\\n\\n\\n\\ncheck(is_palindrome)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 48,
"original": "\n\ndef is_palindrome(text: str):\n \"\"\"\n Checks if given string is a palindrome\n >>> is_palindrome('')\n True\n >>> is_palindrome('aba')\n True\n >>> is_palindrome('aaaaa')\n True\n >>> is_palindrome('zbcd')\n False\n \"\"\"\n",
"reference": " for i in range(len(text)):\n if text[i] != text[len(text) - 1 - i]:\n return False\n return True\n",
"split": "test",
"task_id": "HumanEval/48"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def modp(n: int, p: int):
"""Return 2^n modulo p (be aware of numerics).
>>> modp(3, 5)
3
>>> modp(1101, 101)
2
>>> modp(0, 101)
1
>>> modp(3, 11)
8
>>> modp(100, 101)
1
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {}\\n\\n\\ndef check(candidate):\\n assert candidate(3, 5) == 3\\n assert candidate(1101, 101) == 2\\n assert candidate(0, 101) == 1\\n assert candidate(3, 11) == 8\\n assert candidate(100, 101) == 1\\n assert candidate(30, 5) == 4\\n assert candidate(31, 5) == 3\\n\\n\\n\\ncheck(modp)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 49,
"original": "\n\ndef modp(n: int, p: int):\n \"\"\"Return 2^n modulo p (be aware of numerics).\n >>> modp(3, 5)\n 3\n >>> modp(1101, 101)\n 2\n >>> modp(0, 101)\n 1\n >>> modp(3, 11)\n 8\n >>> modp(100, 101)\n 1\n \"\"\"\n",
"reference": " ret = 1\n for i in range(n):\n ret = (2 * ret) % p\n return ret\n",
"split": "test",
"task_id": "HumanEval/49"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def encode_shift(s: str):
"""
returns encoded string by shifting every character by 5 in the alphabet.
"""
return "".join([chr(((ord(ch) + 5 - ord("a")) % 26) + ord("a")) for ch in s])
def decode_shift(s: str):
"""
takes as input string encoded with encode_shift function. Returns decoded string.
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {}\\n\\n\\ndef check(candidate):\\n from random import randint, choice\\n import copy\\n import string\\n\\n letters = string.ascii_lowercase\\n for _ in range(100):\\n str = ''.join(choice(letters) for i in range(randint(10, 20)))\\n encoded_str = encode_shift(str)\\n assert candidate(copy.deepcopy(encoded_str)) == str\\n\\n\\n\\ncheck(decode_shift)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 50,
"original": "\n\ndef encode_shift(s: str):\n \"\"\"\n returns encoded string by shifting every character by 5 in the alphabet.\n \"\"\"\n return \"\".join([chr(((ord(ch) + 5 - ord(\"a\")) % 26) + ord(\"a\")) for ch in s])\n\n\ndef decode_shift(s: str):\n \"\"\"\n takes as input string encoded with encode_shift function. Returns decoded string.\n \"\"\"\n",
"reference": " return \"\".join([chr(((ord(ch) - 5 - ord(\"a\")) % 26) + ord(\"a\")) for ch in s])\n",
"split": "test",
"task_id": "HumanEval/50"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def remove_vowels(text):
"""
remove_vowels is a function that takes string and returns string without vowels.
>>> remove_vowels('')
''
>>> remove_vowels("abcdef\nghijklm")
'bcdf\nghjklm'
>>> remove_vowels('abcdef')
'bcdf'
>>> remove_vowels('aaaaa')
''
>>> remove_vowels('aaBAA')
'B'
>>> remove_vowels('zbcd')
'zbcd'
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {}\\n\\n\\ndef check(candidate):\\n assert candidate('') == ''\\n assert candidate(\\\"abcdef\\\\nghijklm\\\") == 'bcdf\\\\nghjklm'\\n assert candidate('fedcba') == 'fdcb'\\n assert candidate('eeeee') == ''\\n assert candidate('acBAA') == 'cB'\\n assert candidate('EcBOO') == 'cB'\\n assert candidate('ybcd') == 'ybcd'\\n\\n\\n\\ncheck(remove_vowels)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 51,
"original": "\n\ndef remove_vowels(text):\n \"\"\"\n remove_vowels is a function that takes string and returns string without vowels.\n >>> remove_vowels('')\n ''\n >>> remove_vowels(\"abcdef\\nghijklm\")\n 'bcdf\\nghjklm'\n >>> remove_vowels('abcdef')\n 'bcdf'\n >>> remove_vowels('aaaaa')\n ''\n >>> remove_vowels('aaBAA')\n 'B'\n >>> remove_vowels('zbcd')\n 'zbcd'\n \"\"\"\n",
"reference": " return \"\".join([s for s in text if s.lower() not in [\"a\", \"e\", \"i\", \"o\", \"u\"]])\n",
"split": "test",
"task_id": "HumanEval/51"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def below_threshold(l: list, t: int):
"""Return True if all numbers in the list l are below threshold t.
>>> below_threshold([1, 2, 4, 10], 100)
True
>>> below_threshold([1, 20, 4, 10], 5)
False
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {}\\n\\n\\ndef check(candidate):\\n assert candidate([1, 2, 4, 10], 100)\\n assert not candidate([1, 20, 4, 10], 5)\\n assert candidate([1, 20, 4, 10], 21)\\n assert candidate([1, 20, 4, 10], 22)\\n assert candidate([1, 8, 4, 10], 11)\\n assert not candidate([1, 8, 4, 10], 10)\\n\\n\\n\\ncheck(below_threshold)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 52,
"original": "\n\ndef below_threshold(l: list, t: int):\n \"\"\"Return True if all numbers in the list l are below threshold t.\n >>> below_threshold([1, 2, 4, 10], 100)\n True\n >>> below_threshold([1, 20, 4, 10], 5)\n False\n \"\"\"\n",
"reference": " for e in l:\n if e >= t:\n return False\n return True\n",
"split": "test",
"task_id": "HumanEval/52"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def add(x: int, y: int):
"""Add two numbers x and y
>>> add(2, 3)
5
>>> add(5, 7)
12
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {}\\n\\n\\ndef check(candidate):\\n import random\\n\\n assert candidate(0, 1) == 1\\n assert candidate(1, 0) == 1\\n assert candidate(2, 3) == 5\\n assert candidate(5, 7) == 12\\n assert candidate(7, 5) == 12\\n\\n for i in range(100):\\n x, y = random.randint(0, 1000), random.randint(0, 1000)\\n assert candidate(x, y) == x + y\\n\\n\\n\\ncheck(add)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 53,
"original": "\n\ndef add(x: int, y: int):\n \"\"\"Add two numbers x and y\n >>> add(2, 3)\n 5\n >>> add(5, 7)\n 12\n \"\"\"\n",
"reference": " return x + y\n",
"split": "test",
"task_id": "HumanEval/53"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def same_chars(s0: str, s1: str):
"""
Check if two words have the same characters.
>>> same_chars('eabcdzzzz', 'dddzzzzzzzddeddabc')
True
>>> same_chars('abcd', 'dddddddabc')
True
>>> same_chars('dddddddabc', 'abcd')
True
>>> same_chars('eabcd', 'dddddddabc')
False
>>> same_chars('abcd', 'dddddddabce')
False
>>> same_chars('eabcdzzzz', 'dddzzzzzzzddddabc')
False
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {}\\n\\n\\ndef check(candidate):\\n assert candidate('eabcdzzzz', 'dddzzzzzzzddeddabc') == True\\n assert candidate('abcd', 'dddddddabc') == True\\n assert candidate('dddddddabc', 'abcd') == True\\n assert candidate('eabcd', 'dddddddabc') == False\\n assert candidate('abcd', 'dddddddabcf') == False\\n assert candidate('eabcdzzzz', 'dddzzzzzzzddddabc') == False\\n assert candidate('aabb', 'aaccc') == False\\n\\n\\n\\ncheck(same_chars)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 54,
"original": "\n\ndef same_chars(s0: str, s1: str):\n \"\"\"\n Check if two words have the same characters.\n >>> same_chars('eabcdzzzz', 'dddzzzzzzzddeddabc')\n True\n >>> same_chars('abcd', 'dddddddabc')\n True\n >>> same_chars('dddddddabc', 'abcd')\n True\n >>> same_chars('eabcd', 'dddddddabc')\n False\n >>> same_chars('abcd', 'dddddddabce')\n False\n >>> same_chars('eabcdzzzz', 'dddzzzzzzzddddabc')\n False\n \"\"\"\n",
"reference": " return set(s0) == set(s1)\n",
"split": "test",
"task_id": "HumanEval/54"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def fib(n: int):
"""Return n-th Fibonacci number.
>>> fib(10)
55
>>> fib(1)
1
>>> fib(8)
21
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {}\\n\\n\\ndef check(candidate):\\n assert candidate(10) == 55\\n assert candidate(1) == 1\\n assert candidate(8) == 21\\n assert candidate(11) == 89\\n assert candidate(12) == 144\\n\\n\\n\\ncheck(fib)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 55,
"original": "\n\ndef fib(n: int):\n \"\"\"Return n-th Fibonacci number.\n >>> fib(10)\n 55\n >>> fib(1)\n 1\n >>> fib(8)\n 21\n \"\"\"\n",
"reference": " if n == 0:\n return 0\n if n == 1:\n return 1\n return fib(n - 1) + fib(n - 2)\n",
"split": "test",
"task_id": "HumanEval/55"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def correct_bracketing(brackets: str):
""" brackets is a string of "<" and ">".
return True if every opening bracket has a corresponding closing bracket.
>>> correct_bracketing("<")
False
>>> correct_bracketing("<>")
True
>>> correct_bracketing("<<><>>")
True
>>> correct_bracketing("><<>")
False
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {}\\n\\n\\ndef check(candidate):\\n assert candidate(\\\"<>\\\")\\n assert candidate(\\\"<<><>>\\\")\\n assert candidate(\\\"<><><<><>><>\\\")\\n assert candidate(\\\"<><><<<><><>><>><<><><<>>>\\\")\\n assert not candidate(\\\"<<<><>>>>\\\")\\n assert not candidate(\\\"><<>\\\")\\n assert not candidate(\\\"<\\\")\\n assert not candidate(\\\"<<<<\\\")\\n assert not candidate(\\\">\\\")\\n assert not candidate(\\\"<<>\\\")\\n assert not candidate(\\\"<><><<><>><>><<>\\\")\\n assert not candidate(\\\"<><><<><>><>>><>\\\")\\n\\n\\n\\ncheck(correct_bracketing)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 56,
"original": "\n\ndef correct_bracketing(brackets: str):\n \"\"\" brackets is a string of \"<\" and \">\".\n return True if every opening bracket has a corresponding closing bracket.\n\n >>> correct_bracketing(\"<\")\n False\n >>> correct_bracketing(\"<>\")\n True\n >>> correct_bracketing(\"<<><>>\")\n True\n >>> correct_bracketing(\"><<>\")\n False\n \"\"\"\n",
"reference": " depth = 0\n for b in brackets:\n if b == \"<\":\n depth += 1\n else:\n depth -= 1\n if depth < 0:\n return False\n return depth == 0\n",
"split": "test",
"task_id": "HumanEval/56"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def monotonic(l: list):
"""Return True is list elements are monotonically increasing or decreasing.
>>> monotonic([1, 2, 4, 20])
True
>>> monotonic([1, 20, 4, 10])
False
>>> monotonic([4, 1, 0, -10])
True
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {}\\n\\n\\ndef check(candidate):\\n assert candidate([1, 2, 4, 10]) == True\\n assert candidate([1, 2, 4, 20]) == True\\n assert candidate([1, 20, 4, 10]) == False\\n assert candidate([4, 1, 0, -10]) == True\\n assert candidate([4, 1, 1, 0]) == True\\n assert candidate([1, 2, 3, 2, 5, 60]) == False\\n assert candidate([1, 2, 3, 4, 5, 60]) == True\\n assert candidate([9, 9, 9, 9]) == True\\n\\n\\n\\ncheck(monotonic)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 57,
"original": "\n\ndef monotonic(l: list):\n \"\"\"Return True is list elements are monotonically increasing or decreasing.\n >>> monotonic([1, 2, 4, 20])\n True\n >>> monotonic([1, 20, 4, 10])\n False\n >>> monotonic([4, 1, 0, -10])\n True\n \"\"\"\n",
"reference": " if l == sorted(l) or l == sorted(l, reverse=True):\n return True\n return False\n",
"split": "test",
"task_id": "HumanEval/57"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def common(l1: list, l2: list):
"""Return sorted unique common elements for two lists.
>>> common([1, 4, 3, 34, 653, 2, 5], [5, 7, 1, 5, 9, 653, 121])
[1, 5, 653]
>>> common([5, 3, 2, 8], [3, 2])
[2, 3]
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {}\\n\\n\\ndef check(candidate):\\n assert candidate([1, 4, 3, 34, 653, 2, 5], [5, 7, 1, 5, 9, 653, 121]) == [1, 5, 653]\\n assert candidate([5, 3, 2, 8], [3, 2]) == [2, 3]\\n assert candidate([4, 3, 2, 8], [3, 2, 4]) == [2, 3, 4]\\n assert candidate([4, 3, 2, 8], []) == []\\n\\n\\n\\ncheck(common)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 58,
"original": "\n\ndef common(l1: list, l2: list):\n \"\"\"Return sorted unique common elements for two lists.\n >>> common([1, 4, 3, 34, 653, 2, 5], [5, 7, 1, 5, 9, 653, 121])\n [1, 5, 653]\n >>> common([5, 3, 2, 8], [3, 2])\n [2, 3]\n\n \"\"\"\n",
"reference": " ret = set()\n for e1 in l1:\n for e2 in l2:\n if e1 == e2:\n ret.add(e1)\n return sorted(list(ret))\n",
"split": "test",
"task_id": "HumanEval/58"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def largest_prime_factor(n: int):
"""Return the largest prime factor of n. Assume n > 1 and is not a prime.
>>> largest_prime_factor(13195)
29
>>> largest_prime_factor(2048)
2
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {}\\n\\n\\ndef check(candidate):\\n assert candidate(15) == 5\\n assert candidate(27) == 3\\n assert candidate(63) == 7\\n assert candidate(330) == 11\\n assert candidate(13195) == 29\\n\\n\\n\\ncheck(largest_prime_factor)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 59,
"original": "\n\ndef largest_prime_factor(n: int):\n \"\"\"Return the largest prime factor of n. Assume n > 1 and is not a prime.\n >>> largest_prime_factor(13195)\n 29\n >>> largest_prime_factor(2048)\n 2\n \"\"\"\n",
"reference": " def is_prime(k):\n if k < 2:\n return False\n for i in range(2, k - 1):\n if k % i == 0:\n return False\n return True\n largest = 1\n for j in range(2, n + 1):\n if n % j == 0 and is_prime(j):\n largest = max(largest, j)\n return largest\n",
"split": "test",
"task_id": "HumanEval/59"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def sum_to_n(n: int):
"""sum_to_n is a function that sums numbers from 1 to n.
>>> sum_to_n(30)
465
>>> sum_to_n(100)
5050
>>> sum_to_n(5)
15
>>> sum_to_n(10)
55
>>> sum_to_n(1)
1
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {}\\n\\n\\ndef check(candidate):\\n assert candidate(1) == 1\\n assert candidate(6) == 21\\n assert candidate(11) == 66\\n assert candidate(30) == 465\\n assert candidate(100) == 5050\\n\\n\\n\\ncheck(sum_to_n)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 60,
"original": "\n\ndef sum_to_n(n: int):\n \"\"\"sum_to_n is a function that sums numbers from 1 to n.\n >>> sum_to_n(30)\n 465\n >>> sum_to_n(100)\n 5050\n >>> sum_to_n(5)\n 15\n >>> sum_to_n(10)\n 55\n >>> sum_to_n(1)\n 1\n \"\"\"\n",
"reference": " return sum(range(n + 1))\n",
"split": "test",
"task_id": "HumanEval/60"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def correct_bracketing(brackets: str):
""" brackets is a string of "(" and ")".
return True if every opening bracket has a corresponding closing bracket.
>>> correct_bracketing("(")
False
>>> correct_bracketing("()")
True
>>> correct_bracketing("(()())")
True
>>> correct_bracketing(")(()")
False
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {}\\n\\n\\ndef check(candidate):\\n assert candidate(\\\"()\\\")\\n assert candidate(\\\"(()())\\\")\\n assert candidate(\\\"()()(()())()\\\")\\n assert candidate(\\\"()()((()()())())(()()(()))\\\")\\n assert not candidate(\\\"((()())))\\\")\\n assert not candidate(\\\")(()\\\")\\n assert not candidate(\\\"(\\\")\\n assert not candidate(\\\"((((\\\")\\n assert not candidate(\\\")\\\")\\n assert not candidate(\\\"(()\\\")\\n assert not candidate(\\\"()()(()())())(()\\\")\\n assert not candidate(\\\"()()(()())()))()\\\")\\n\\n\\n\\ncheck(correct_bracketing)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 61,
"original": "\n\ndef correct_bracketing(brackets: str):\n \"\"\" brackets is a string of \"(\" and \")\".\n return True if every opening bracket has a corresponding closing bracket.\n\n >>> correct_bracketing(\"(\")\n False\n >>> correct_bracketing(\"()\")\n True\n >>> correct_bracketing(\"(()())\")\n True\n >>> correct_bracketing(\")(()\")\n False\n \"\"\"\n",
"reference": " depth = 0\n for b in brackets:\n if b == \"(\":\n depth += 1\n else:\n depth -= 1\n if depth < 0:\n return False\n return depth == 0\n",
"split": "test",
"task_id": "HumanEval/61"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def derivative(xs: list):
""" xs represent coefficients of a polynomial.
xs[0] + xs[1] * x + xs[2] * x^2 + ....
Return derivative of this polynomial in the same form.
>>> derivative([3, 1, 2, 4, 5])
[1, 4, 12, 20]
>>> derivative([1, 2, 3])
[2, 6]
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {}\\n\\n\\ndef check(candidate):\\n assert candidate([3, 1, 2, 4, 5]) == [1, 4, 12, 20]\\n assert candidate([1, 2, 3]) == [2, 6]\\n assert candidate([3, 2, 1]) == [2, 2]\\n assert candidate([3, 2, 1, 0, 4]) == [2, 2, 0, 16]\\n assert candidate([1]) == []\\n\\n\\n\\ncheck(derivative)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 62,
"original": "\n\ndef derivative(xs: list):\n \"\"\" xs represent coefficients of a polynomial.\n xs[0] + xs[1] * x + xs[2] * x^2 + ....\n Return derivative of this polynomial in the same form.\n >>> derivative([3, 1, 2, 4, 5])\n [1, 4, 12, 20]\n >>> derivative([1, 2, 3])\n [2, 6]\n \"\"\"\n",
"reference": " return [(i * x) for i, x in enumerate(xs)][1:]\n",
"split": "test",
"task_id": "HumanEval/62"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def fibfib(n: int):
"""The FibFib number sequence is a sequence similar to the Fibbonacci sequnece that's defined as follows:
fibfib(0) == 0
fibfib(1) == 0
fibfib(2) == 1
fibfib(n) == fibfib(n-1) + fibfib(n-2) + fibfib(n-3).
Please write a function to efficiently compute the n-th element of the fibfib number sequence.
>>> fibfib(1)
0
>>> fibfib(5)
4
>>> fibfib(8)
24
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"\\n\\nMETADATA = {}\\n\\n\\ndef check(candidate):\\n assert candidate(2) == 1\\n assert candidate(1) == 0\\n assert candidate(5) == 4\\n assert candidate(8) == 24\\n assert candidate(10) == 81\\n assert candidate(12) == 274\\n assert candidate(14) == 927\\n\\n\\n\\ncheck(fibfib)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 63,
"original": "\n\ndef fibfib(n: int):\n \"\"\"The FibFib number sequence is a sequence similar to the Fibbonacci sequnece that's defined as follows:\n fibfib(0) == 0\n fibfib(1) == 0\n fibfib(2) == 1\n fibfib(n) == fibfib(n-1) + fibfib(n-2) + fibfib(n-3).\n Please write a function to efficiently compute the n-th element of the fibfib number sequence.\n >>> fibfib(1)\n 0\n >>> fibfib(5)\n 4\n >>> fibfib(8)\n 24\n \"\"\"\n",
"reference": " if n == 0:\n return 0\n if n == 1:\n return 0\n if n == 2:\n return 1\n return fibfib(n - 1) + fibfib(n - 2) + fibfib(n - 3)\n",
"split": "test",
"task_id": "HumanEval/63"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
FIX = """
Add more test cases.
"""
def vowels_count(s):
"""Write a function vowels_count which takes a string representing
a word as input and returns the number of vowels in the string.
Vowels in this case are 'a', 'e', 'i', 'o', 'u'. Here, 'y' is also a
vowel, but only when it is at the end of the given word.
Example:
>>> vowels_count("abcde")
2
>>> vowels_count("ACEDY")
3
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"def check(candidate):\\n\\n # Check some simple cases\\n assert candidate(\\\"abcde\\\") == 2, \\\"Test 1\\\"\\n assert candidate(\\\"Alone\\\") == 3, \\\"Test 2\\\"\\n assert candidate(\\\"key\\\") == 2, \\\"Test 3\\\"\\n assert candidate(\\\"bye\\\") == 1, \\\"Test 4\\\"\\n assert candidate(\\\"keY\\\") == 2, \\\"Test 5\\\"\\n assert candidate(\\\"bYe\\\") == 1, \\\"Test 6\\\"\\n assert candidate(\\\"ACEDY\\\") == 3, \\\"Test 7\\\"\\n\\n # Check some edge cases that are easy to work out by hand.\\n assert True, \\\"This prints if this assert fails 2 (also good for debugging!)\\\"\\n\\n\\n\\ncheck(vowels_count)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 64,
"original": "\nFIX = \"\"\"\nAdd more test cases.\n\"\"\"\n\ndef vowels_count(s):\n \"\"\"Write a function vowels_count which takes a string representing\n a word as input and returns the number of vowels in the string.\n Vowels in this case are 'a', 'e', 'i', 'o', 'u'. Here, 'y' is also a\n vowel, but only when it is at the end of the given word.\n\n Example:\n >>> vowels_count(\"abcde\")\n 2\n >>> vowels_count(\"ACEDY\")\n 3\n \"\"\"\n",
"reference": " vowels = \"aeiouAEIOU\"\n n_vowels = sum(c in vowels for c in s)\n if s[-1] == 'y' or s[-1] == 'Y':\n n_vowels += 1\n return n_vowels\n",
"split": "test",
"task_id": "HumanEval/64"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def circular_shift(x, shift):
"""Circular shift the digits of the integer x, shift the digits right by shift
and return the result as a string.
If shift > number of digits, return digits reversed.
>>> circular_shift(12, 1)
"21"
>>> circular_shift(12, 2)
"12"
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"def check(candidate):\\n\\n # Check some simple cases\\n assert candidate(100, 2) == \\\"001\\\"\\n assert candidate(12, 2) == \\\"12\\\"\\n assert candidate(97, 8) == \\\"79\\\"\\n assert candidate(12, 1) == \\\"21\\\", \\\"This prints if this assert fails 1 (good for debugging!)\\\"\\n\\n # Check some edge cases that are easy to work out by hand.\\n assert candidate(11, 101) == \\\"11\\\", \\\"This prints if this assert fails 2 (also good for debugging!)\\\"\\n\\n\\n\\ncheck(circular_shift)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 65,
"original": "\ndef circular_shift(x, shift):\n \"\"\"Circular shift the digits of the integer x, shift the digits right by shift\n and return the result as a string.\n If shift > number of digits, return digits reversed.\n >>> circular_shift(12, 1)\n \"21\"\n >>> circular_shift(12, 2)\n \"12\"\n \"\"\"\n",
"reference": " s = str(x)\n if shift > len(s):\n return s[::-1]\n else:\n return s[len(s) - shift:] + s[:len(s) - shift]\n",
"split": "test",
"task_id": "HumanEval/65"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def digitSum(s):
"""Task
Write a function that takes a string as input and returns the sum of the upper characters only'
ASCII codes.
Examples:
digitSum("") => 0
digitSum("abAB") => 131
digitSum("abcCd") => 67
digitSum("helloE") => 69
digitSum("woArBld") => 131
digitSum("aAaaaXa") => 153
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"def check(candidate):\\n\\n # Check some simple cases\\n assert True, \\\"This prints if this assert fails 1 (good for debugging!)\\\"\\n assert candidate(\\\"\\\") == 0, \\\"Error\\\"\\n assert candidate(\\\"abAB\\\") == 131, \\\"Error\\\"\\n assert candidate(\\\"abcCd\\\") == 67, \\\"Error\\\"\\n assert candidate(\\\"helloE\\\") == 69, \\\"Error\\\"\\n assert candidate(\\\"woArBld\\\") == 131, \\\"Error\\\"\\n assert candidate(\\\"aAaaaXa\\\") == 153, \\\"Error\\\"\\n\\n # Check some edge cases that are easy to work out by hand.\\n assert True, \\\"This prints if this assert fails 2 (also good for debugging!)\\\"\\n assert candidate(\\\" How are yOu?\\\") == 151, \\\"Error\\\"\\n assert candidate(\\\"You arE Very Smart\\\") == 327, \\\"Error\\\"\\n\\n\\n\\ncheck(digitSum)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 66,
"original": "\ndef digitSum(s):\n \"\"\"Task\n Write a function that takes a string as input and returns the sum of the upper characters only'\n ASCII codes.\n\n Examples:\n digitSum(\"\") => 0\n digitSum(\"abAB\") => 131\n digitSum(\"abcCd\") => 67\n digitSum(\"helloE\") => 69\n digitSum(\"woArBld\") => 131\n digitSum(\"aAaaaXa\") => 153\n \"\"\"\n",
"reference": " if s == \"\": return 0\n return sum(ord(char) if char.isupper() else 0 for char in s)\n",
"split": "test",
"task_id": "HumanEval/66"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def fruit_distribution(s,n):
"""
In this task, you will be given a string that represents a number of apples and oranges
that are distributed in a basket of fruit this basket contains
apples, oranges, and mango fruits. Given the string that represents the total number of
the oranges and apples and an integer that represent the total number of the fruits
in the basket return the number of the mango fruits in the basket.
for examble:
fruit_distribution("5 apples and 6 oranges", 19) ->19 - 5 - 6 = 8
fruit_distribution("0 apples and 1 oranges",3) -> 3 - 0 - 1 = 2
fruit_distribution("2 apples and 3 oranges", 100) -> 100 - 2 - 3 = 95
fruit_distribution("100 apples and 1 oranges",120) -> 120 - 100 - 1 = 19
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"def check(candidate):\\n\\n # Check some simple cases\\n assert candidate(\\\"5 apples and 6 oranges\\\",19) == 8\\n assert candidate(\\\"5 apples and 6 oranges\\\",21) == 10\\n assert candidate(\\\"0 apples and 1 oranges\\\",3) == 2\\n assert candidate(\\\"1 apples and 0 oranges\\\",3) == 2\\n assert candidate(\\\"2 apples and 3 oranges\\\",100) == 95\\n assert candidate(\\\"2 apples and 3 oranges\\\",5) == 0\\n assert candidate(\\\"1 apples and 100 oranges\\\",120) == 19\\n\\n\\ncheck(fruit_distribution)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 67,
"original": "\ndef fruit_distribution(s,n):\n \"\"\"\n In this task, you will be given a string that represents a number of apples and oranges \n that are distributed in a basket of fruit this basket contains \n apples, oranges, and mango fruits. Given the string that represents the total number of \n the oranges and apples and an integer that represent the total number of the fruits \n in the basket return the number of the mango fruits in the basket.\n for examble:\n fruit_distribution(\"5 apples and 6 oranges\", 19) ->19 - 5 - 6 = 8\n fruit_distribution(\"0 apples and 1 oranges\",3) -> 3 - 0 - 1 = 2\n fruit_distribution(\"2 apples and 3 oranges\", 100) -> 100 - 2 - 3 = 95\n fruit_distribution(\"100 apples and 1 oranges\",120) -> 120 - 100 - 1 = 19\n \"\"\"\n",
"reference": " lis = list()\n for i in s.split(' '):\n if i.isdigit():\n lis.append(int(i))\n return n - sum(lis)\n",
"split": "test",
"task_id": "HumanEval/67"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def pluck(arr):
"""
"Given an array representing a branch of a tree that has non-negative integer nodes
your task is to pluck one of the nodes and return it.
The plucked node should be the node with the smallest even value.
If multiple nodes with the same smallest even value are found return the node that has smallest index.
The plucked node should be returned in a list, [ smalest_value, its index ],
If there are no even values or the given array is empty, return [].
Example 1:
Input: [4,2,3]
Output: [2, 1]
Explanation: 2 has the smallest even value, and 2 has the smallest index.
Example 2:
Input: [1,2,3]
Output: [2, 1]
Explanation: 2 has the smallest even value, and 2 has the smallest index.
Example 3:
Input: []
Output: []
Example 4:
Input: [5, 0, 3, 0, 4, 2]
Output: [0, 1]
Explanation: 0 is the smallest value, but there are two zeros,
so we will choose the first zero, which has the smallest index.
Constraints:
* 1 <= nodes.length <= 10000
* 0 <= node.value
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"def check(candidate):\\n\\n # Check some simple cases\\n assert True, \\\"This prints if this assert fails 1 (good for debugging!)\\\"\\n assert candidate([4,2,3]) == [2, 1], \\\"Error\\\"\\n assert candidate([1,2,3]) == [2, 1], \\\"Error\\\"\\n assert candidate([]) == [], \\\"Error\\\"\\n assert candidate([5, 0, 3, 0, 4, 2]) == [0, 1], \\\"Error\\\"\\n\\n # Check some edge cases that are easy to work out by hand.\\n assert True, \\\"This prints if this assert fails 2 (also good for debugging!)\\\"\\n assert candidate([1, 2, 3, 0, 5, 3]) == [0, 3], \\\"Error\\\"\\n assert candidate([5, 4, 8, 4 ,8]) == [4, 1], \\\"Error\\\"\\n assert candidate([7, 6, 7, 1]) == [6, 1], \\\"Error\\\"\\n assert candidate([7, 9, 7, 1]) == [], \\\"Error\\\"\\n\\n\\n\\ncheck(pluck)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 68,
"original": "\ndef pluck(arr):\n \"\"\"\n \"Given an array representing a branch of a tree that has non-negative integer nodes\n your task is to pluck one of the nodes and return it.\n The plucked node should be the node with the smallest even value.\n If multiple nodes with the same smallest even value are found return the node that has smallest index.\n\n The plucked node should be returned in a list, [ smalest_value, its index ],\n If there are no even values or the given array is empty, return [].\n\n Example 1:\n Input: [4,2,3]\n Output: [2, 1]\n Explanation: 2 has the smallest even value, and 2 has the smallest index.\n\n Example 2:\n Input: [1,2,3]\n Output: [2, 1]\n Explanation: 2 has the smallest even value, and 2 has the smallest index. \n\n Example 3:\n Input: []\n Output: []\n \n Example 4:\n Input: [5, 0, 3, 0, 4, 2]\n Output: [0, 1]\n Explanation: 0 is the smallest value, but there are two zeros,\n so we will choose the first zero, which has the smallest index.\n\n Constraints:\n * 1 <= nodes.length <= 10000\n * 0 <= node.value\n \"\"\"\n",
"reference": " if(len(arr) == 0): return []\n evens = list(filter(lambda x: x%2 == 0, arr))\n if(evens == []): return []\n return [min(evens), arr.index(min(evens))]\n",
"split": "test",
"task_id": "HumanEval/68"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def search(lst):
'''
You are given a non-empty list of positive integers. Return the greatest integer that is greater than
zero, and has a frequency greater than or equal to the value of the integer itself.
The frequency of an integer is the number of times it appears in the list.
If no such a value exist, return -1.
Examples:
search([4, 1, 2, 2, 3, 1]) == 2
search([1, 2, 2, 3, 3, 3, 4, 4, 4]) == 3
search([5, 5, 4, 4, 4]) == -1
'''
|
codegen
|
{
"ground_truth": "{\"functional\": \"def check(candidate):\\n\\n # manually generated tests\\n assert candidate([5, 5, 5, 5, 1]) == 1\\n assert candidate([4, 1, 4, 1, 4, 4]) == 4\\n assert candidate([3, 3]) == -1\\n assert candidate([8, 8, 8, 8, 8, 8, 8, 8]) == 8\\n assert candidate([2, 3, 3, 2, 2]) == 2\\n\\n # automatically generated tests\\n assert candidate([2, 7, 8, 8, 4, 8, 7, 3, 9, 6, 5, 10, 4, 3, 6, 7, 1, 7, 4, 10, 8, 1]) == 1\\n assert candidate([3, 2, 8, 2]) == 2\\n assert candidate([6, 7, 1, 8, 8, 10, 5, 8, 5, 3, 10]) == 1\\n assert candidate([8, 8, 3, 6, 5, 6, 4]) == -1\\n assert candidate([6, 9, 6, 7, 1, 4, 7, 1, 8, 8, 9, 8, 10, 10, 8, 4, 10, 4, 10, 1, 2, 9, 5, 7, 9]) == 1\\n assert candidate([1, 9, 10, 1, 3]) == 1\\n assert candidate([6, 9, 7, 5, 8, 7, 5, 3, 7, 5, 10, 10, 3, 6, 10, 2, 8, 6, 5, 4, 9, 5, 3, 10]) == 5\\n assert candidate([1]) == 1\\n assert candidate([8, 8, 10, 6, 4, 3, 5, 8, 2, 4, 2, 8, 4, 6, 10, 4, 2, 1, 10, 2, 1, 1, 5]) == 4\\n assert candidate([2, 10, 4, 8, 2, 10, 5, 1, 2, 9, 5, 5, 6, 3, 8, 6, 4, 10]) == 2\\n assert candidate([1, 6, 10, 1, 6, 9, 10, 8, 6, 8, 7, 3]) == 1\\n assert candidate([9, 2, 4, 1, 5, 1, 5, 2, 5, 7, 7, 7, 3, 10, 1, 5, 4, 2, 8, 4, 1, 9, 10, 7, 10, 2, 8, 10, 9, 4]) == 4\\n assert candidate([2, 6, 4, 2, 8, 7, 5, 6, 4, 10, 4, 6, 3, 7, 8, 8, 3, 1, 4, 2, 2, 10, 7]) == 4\\n assert candidate([9, 8, 6, 10, 2, 6, 10, 2, 7, 8, 10, 3, 8, 2, 6, 2, 3, 1]) == 2\\n assert candidate([5, 5, 3, 9, 5, 6, 3, 2, 8, 5, 6, 10, 10, 6, 8, 4, 10, 7, 7, 10, 8]) == -1\\n assert candidate([10]) == -1\\n assert candidate([9, 7, 7, 2, 4, 7, 2, 10, 9, 7, 5, 7, 2]) == 2\\n assert candidate([5, 4, 10, 2, 1, 1, 10, 3, 6, 1, 8]) == 1\\n assert candidate([7, 9, 9, 9, 3, 4, 1, 5, 9, 1, 2, 1, 1, 10, 7, 5, 6, 7, 6, 7, 7, 6]) == 1\\n assert candidate([3, 10, 10, 9, 2]) == -1\\n\\n\\n\\ncheck(search)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 69,
"original": "\ndef search(lst):\n '''\n You are given a non-empty list of positive integers. Return the greatest integer that is greater than \n zero, and has a frequency greater than or equal to the value of the integer itself. \n The frequency of an integer is the number of times it appears in the list.\n If no such a value exist, return -1.\n Examples:\n search([4, 1, 2, 2, 3, 1]) == 2\n search([1, 2, 2, 3, 3, 3, 4, 4, 4]) == 3\n search([5, 5, 4, 4, 4]) == -1\n '''\n",
"reference": " frq = [0] * (max(lst) + 1)\n for i in lst:\n frq[i] += 1;\n\n ans = -1\n for i in range(1, len(frq)):\n if frq[i] >= i:\n ans = i\n \n return ans\n",
"split": "test",
"task_id": "HumanEval/69"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def strange_sort_list(lst):
'''
Given list of integers, return list in strange order.
Strange sorting, is when you start with the minimum value,
then maximum of the remaining integers, then minimum and so on.
Examples:
strange_sort_list([1, 2, 3, 4]) == [1, 4, 2, 3]
strange_sort_list([5, 5, 5, 5]) == [5, 5, 5, 5]
strange_sort_list([]) == []
'''
|
codegen
|
{
"ground_truth": "{\"functional\": \"def check(candidate):\\n\\n # Check some simple cases\\n assert candidate([1, 2, 3, 4]) == [1, 4, 2, 3]\\n assert candidate([5, 6, 7, 8, 9]) == [5, 9, 6, 8, 7]\\n assert candidate([1, 2, 3, 4, 5]) == [1, 5, 2, 4, 3]\\n assert candidate([5, 6, 7, 8, 9, 1]) == [1, 9, 5, 8, 6, 7]\\n assert candidate([5, 5, 5, 5]) == [5, 5, 5, 5]\\n assert candidate([]) == []\\n assert candidate([1,2,3,4,5,6,7,8]) == [1, 8, 2, 7, 3, 6, 4, 5]\\n assert candidate([0,2,2,2,5,5,-5,-5]) == [-5, 5, -5, 5, 0, 2, 2, 2]\\n assert candidate([111111]) == [111111]\\n\\n # Check some edge cases that are easy to work out by hand.\\n assert True\\n\\n\\n\\ncheck(strange_sort_list)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 70,
"original": "\ndef strange_sort_list(lst):\n '''\n Given list of integers, return list in strange order.\n Strange sorting, is when you start with the minimum value,\n then maximum of the remaining integers, then minimum and so on.\n\n Examples:\n strange_sort_list([1, 2, 3, 4]) == [1, 4, 2, 3]\n strange_sort_list([5, 5, 5, 5]) == [5, 5, 5, 5]\n strange_sort_list([]) == []\n '''\n",
"reference": " res, switch = [], True\n while lst:\n res.append(min(lst) if switch else max(lst))\n lst.remove(res[-1])\n switch = not switch\n return res\n",
"split": "test",
"task_id": "HumanEval/70"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def triangle_area(a, b, c):
'''
Given the lengths of the three sides of a triangle. Return the area of
the triangle rounded to 2 decimal points if the three sides form a valid triangle.
Otherwise return -1
Three sides make a valid triangle when the sum of any two sides is greater
than the third side.
Example:
triangle_area(3, 4, 5) == 6.00
triangle_area(1, 2, 10) == -1
'''
|
codegen
|
{
"ground_truth": "{\"functional\": \"def check(candidate):\\n\\n # Check some simple cases\\n assert candidate(3, 4, 5) == 6.00, \\\"This prints if this assert fails 1 (good for debugging!)\\\"\\n assert candidate(1, 2, 10) == -1\\n assert candidate(4, 8, 5) == 8.18\\n assert candidate(2, 2, 2) == 1.73\\n assert candidate(1, 2, 3) == -1\\n assert candidate(10, 5, 7) == 16.25\\n assert candidate(2, 6, 3) == -1\\n\\n # Check some edge cases that are easy to work out by hand.\\n assert candidate(1, 1, 1) == 0.43, \\\"This prints if this assert fails 2 (also good for debugging!)\\\"\\n assert candidate(2, 2, 10) == -1\\n\\n\\n\\ncheck(triangle_area)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 71,
"original": "\ndef triangle_area(a, b, c):\n '''\n Given the lengths of the three sides of a triangle. Return the area of\n the triangle rounded to 2 decimal points if the three sides form a valid triangle. \n Otherwise return -1\n Three sides make a valid triangle when the sum of any two sides is greater \n than the third side.\n Example:\n triangle_area(3, 4, 5) == 6.00\n triangle_area(1, 2, 10) == -1\n '''\n",
"reference": " if a + b <= c or a + c <= b or b + c <= a:\n return -1 \n s = (a + b + c)/2 \n area = (s * (s - a) * (s - b) * (s - c)) ** 0.5\n area = round(area, 2)\n return area\n",
"split": "test",
"task_id": "HumanEval/71"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def will_it_fly(q,w):
'''
Write a function that returns True if the object q will fly, and False otherwise.
The object q will fly if it's balanced (it is a palindromic list) and the sum of its elements is less than or equal the maximum possible weight w.
Example:
will_it_fly([1, 2], 5) ➞ False
# 1+2 is less than the maximum possible weight, but it's unbalanced.
will_it_fly([3, 2, 3], 1) ➞ False
# it's balanced, but 3+2+3 is more than the maximum possible weight.
will_it_fly([3, 2, 3], 9) ➞ True
# 3+2+3 is less than the maximum possible weight, and it's balanced.
will_it_fly([3], 5) ➞ True
# 3 is less than the maximum possible weight, and it's balanced.
'''
|
codegen
|
{
"ground_truth": "{\"functional\": \"def check(candidate):\\n\\n # Check some simple cases\\n assert candidate([3, 2, 3], 9) is True\\n assert candidate([1, 2], 5) is False\\n assert candidate([3], 5) is True\\n assert candidate([3, 2, 3], 1) is False\\n\\n\\n # Check some edge cases that are easy to work out by hand.\\n assert candidate([1, 2, 3], 6) is False\\n assert candidate([5], 5) is True\\n\\n\\n\\ncheck(will_it_fly)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 72,
"original": "\ndef will_it_fly(q,w):\n '''\n Write a function that returns True if the object q will fly, and False otherwise.\n The object q will fly if it's balanced (it is a palindromic list) and the sum of its elements is less than or equal the maximum possible weight w.\n\n Example:\n will_it_fly([1, 2], 5) ➞ False \n # 1+2 is less than the maximum possible weight, but it's unbalanced.\n\n will_it_fly([3, 2, 3], 1) ➞ False\n # it's balanced, but 3+2+3 is more than the maximum possible weight.\n\n will_it_fly([3, 2, 3], 9) ➞ True\n # 3+2+3 is less than the maximum possible weight, and it's balanced.\n\n will_it_fly([3], 5) ➞ True\n # 3 is less than the maximum possible weight, and it's balanced.\n '''\n",
"reference": " if sum(q) > w:\n return False\n\n i, j = 0, len(q)-1\n while i<j:\n if q[i] != q[j]:\n return False\n i+=1\n j-=1\n return True\n",
"split": "test",
"task_id": "HumanEval/72"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def smallest_change(arr):
"""
Given an array arr of integers, find the minimum number of elements that
need to be changed to make the array palindromic. A palindromic array is an array that
is read the same backwards and forwards. In one change, you can change one element to any other element.
For example:
smallest_change([1,2,3,5,4,7,9,6]) == 4
smallest_change([1, 2, 3, 4, 3, 2, 2]) == 1
smallest_change([1, 2, 3, 2, 1]) == 0
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"def check(candidate):\\n\\n # Check some simple cases\\n assert candidate([1,2,3,5,4,7,9,6]) == 4\\n assert candidate([1, 2, 3, 4, 3, 2, 2]) == 1\\n assert candidate([1, 4, 2]) == 1\\n assert candidate([1, 4, 4, 2]) == 1\\n\\n # Check some edge cases that are easy to work out by hand.\\n assert candidate([1, 2, 3, 2, 1]) == 0\\n assert candidate([3, 1, 1, 3]) == 0\\n assert candidate([1]) == 0\\n assert candidate([0, 1]) == 1\\n\\n\\n\\ncheck(smallest_change)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 73,
"original": "\ndef smallest_change(arr):\n \"\"\"\n Given an array arr of integers, find the minimum number of elements that\n need to be changed to make the array palindromic. A palindromic array is an array that\n is read the same backwards and forwards. In one change, you can change one element to any other element.\n\n For example:\n smallest_change([1,2,3,5,4,7,9,6]) == 4\n smallest_change([1, 2, 3, 4, 3, 2, 2]) == 1\n smallest_change([1, 2, 3, 2, 1]) == 0\n \"\"\"\n",
"reference": " ans = 0\n for i in range(len(arr) // 2):\n if arr[i] != arr[len(arr) - i - 1]:\n ans += 1\n return ans\n",
"split": "test",
"task_id": "HumanEval/73"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def total_match(lst1, lst2):
'''
Write a function that accepts two lists of strings and returns the list that has
total number of chars in the all strings of the list less than the other list.
if the two lists have the same number of chars, return the first list.
Examples
total_match([], []) ➞ []
total_match(['hi', 'admin'], ['hI', 'Hi']) ➞ ['hI', 'Hi']
total_match(['hi', 'admin'], ['hi', 'hi', 'admin', 'project']) ➞ ['hi', 'admin']
total_match(['hi', 'admin'], ['hI', 'hi', 'hi']) ➞ ['hI', 'hi', 'hi']
total_match(['4'], ['1', '2', '3', '4', '5']) ➞ ['4']
'''
|
codegen
|
{
"ground_truth": "{\"functional\": \"def check(candidate):\\n\\n # Check some simple cases\\n assert True, \\\"This prints if this assert fails 1 (good for debugging!)\\\"\\n assert candidate([], []) == []\\n assert candidate(['hi', 'admin'], ['hi', 'hi']) == ['hi', 'hi']\\n assert candidate(['hi', 'admin'], ['hi', 'hi', 'admin', 'project']) == ['hi', 'admin']\\n assert candidate(['4'], ['1', '2', '3', '4', '5']) == ['4']\\n assert candidate(['hi', 'admin'], ['hI', 'Hi']) == ['hI', 'Hi']\\n assert candidate(['hi', 'admin'], ['hI', 'hi', 'hi']) == ['hI', 'hi', 'hi']\\n assert candidate(['hi', 'admin'], ['hI', 'hi', 'hii']) == ['hi', 'admin']\\n\\n\\n # Check some edge cases that are easy to work out by hand.\\n assert True, \\\"This prints if this assert fails 2 (also good for debugging!)\\\"\\n assert candidate([], ['this']) == []\\n assert candidate(['this'], []) == []\\n\\n\\n\\ncheck(total_match)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 74,
"original": "\ndef total_match(lst1, lst2):\n '''\n Write a function that accepts two lists of strings and returns the list that has \n total number of chars in the all strings of the list less than the other list.\n\n if the two lists have the same number of chars, return the first list.\n\n Examples\n total_match([], []) ➞ []\n total_match(['hi', 'admin'], ['hI', 'Hi']) ➞ ['hI', 'Hi']\n total_match(['hi', 'admin'], ['hi', 'hi', 'admin', 'project']) ➞ ['hi', 'admin']\n total_match(['hi', 'admin'], ['hI', 'hi', 'hi']) ➞ ['hI', 'hi', 'hi']\n total_match(['4'], ['1', '2', '3', '4', '5']) ➞ ['4']\n '''\n",
"reference": " l1 = 0\n for st in lst1:\n l1 += len(st)\n \n l2 = 0\n for st in lst2:\n l2 += len(st)\n \n if l1 <= l2:\n return lst1\n else:\n return lst2\n",
"split": "test",
"task_id": "HumanEval/74"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def is_multiply_prime(a):
"""Write a function that returns true if the given number is the multiplication of 3 prime numbers
and false otherwise.
Knowing that (a) is less then 100.
Example:
is_multiply_prime(30) == True
30 = 2 * 3 * 5
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"def check(candidate):\\n\\n assert candidate(5) == False\\n assert candidate(30) == True\\n assert candidate(8) == True\\n assert candidate(10) == False\\n assert candidate(125) == True\\n assert candidate(3 * 5 * 7) == True\\n assert candidate(3 * 6 * 7) == False\\n assert candidate(9 * 9 * 9) == False\\n assert candidate(11 * 9 * 9) == False\\n assert candidate(11 * 13 * 7) == True\\n\\n\\n\\ncheck(is_multiply_prime)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 75,
"original": "\ndef is_multiply_prime(a):\n \"\"\"Write a function that returns true if the given number is the multiplication of 3 prime numbers\n and false otherwise.\n Knowing that (a) is less then 100. \n Example:\n is_multiply_prime(30) == True\n 30 = 2 * 3 * 5\n \"\"\"\n",
"reference": " def is_prime(n):\n for j in range(2,n):\n if n%j == 0:\n return False\n return True\n\n for i in range(2,101):\n if not is_prime(i): continue\n for j in range(2,101):\n if not is_prime(j): continue\n for k in range(2,101):\n if not is_prime(k): continue\n if i*j*k == a: return True\n return False\n",
"split": "test",
"task_id": "HumanEval/75"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def is_simple_power(x, n):
"""Your task is to write a function that returns true if a number x is a simple
power of n and false in other cases.
x is a simple power of n if n**int=x
For example:
is_simple_power(1, 4) => true
is_simple_power(2, 2) => true
is_simple_power(8, 2) => true
is_simple_power(3, 2) => false
is_simple_power(3, 1) => false
is_simple_power(5, 3) => false
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"def check(candidate):\\n\\n # Check some simple cases\\n assert candidate(16, 2)== True, \\\"This prints if this assert fails 1 (good for debugging!)\\\"\\n assert candidate(143214, 16)== False, \\\"This prints if this assert fails 1 (good for debugging!)\\\"\\n assert candidate(4, 2)==True, \\\"This prints if this assert fails 1 (good for debugging!)\\\"\\n assert candidate(9, 3)==True, \\\"This prints if this assert fails 1 (good for debugging!)\\\"\\n assert candidate(16, 4)==True, \\\"This prints if this assert fails 1 (good for debugging!)\\\"\\n assert candidate(24, 2)==False, \\\"This prints if this assert fails 1 (good for debugging!)\\\"\\n assert candidate(128, 4)==False, \\\"This prints if this assert fails 1 (good for debugging!)\\\"\\n assert candidate(12, 6)==False, \\\"This prints if this assert fails 1 (good for debugging!)\\\"\\n\\n # Check some edge cases that are easy to work out by hand.\\n assert candidate(1, 1)==True, \\\"This prints if this assert fails 2 (also good for debugging!)\\\"\\n assert candidate(1, 12)==True, \\\"This prints if this assert fails 2 (also good for debugging!)\\\"\\n\\n\\n\\ncheck(is_simple_power)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 76,
"original": "\ndef is_simple_power(x, n):\n \"\"\"Your task is to write a function that returns true if a number x is a simple\n power of n and false in other cases.\n x is a simple power of n if n**int=x\n For example:\n is_simple_power(1, 4) => true\n is_simple_power(2, 2) => true\n is_simple_power(8, 2) => true\n is_simple_power(3, 2) => false\n is_simple_power(3, 1) => false\n is_simple_power(5, 3) => false\n \"\"\"\n",
"reference": " if (n == 1): \n return (x == 1) \n power = 1\n while (power < x): \n power = power * n \n return (power == x) \n",
"split": "test",
"task_id": "HumanEval/76"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def iscube(a):
'''
Write a function that takes an integer a and returns True
if this ingeger is a cube of some integer number.
Note: you may assume the input is always valid.
Examples:
iscube(1) ==> True
iscube(2) ==> False
iscube(-1) ==> True
iscube(64) ==> True
iscube(0) ==> True
iscube(180) ==> False
'''
|
codegen
|
{
"ground_truth": "{\"functional\": \"def check(candidate):\\n\\n # Check some simple cases\\n assert candidate(1) == True, \\\"First test error: \\\" + str(candidate(1))\\n assert candidate(2) == False, \\\"Second test error: \\\" + str(candidate(2))\\n assert candidate(-1) == True, \\\"Third test error: \\\" + str(candidate(-1))\\n assert candidate(64) == True, \\\"Fourth test error: \\\" + str(candidate(64))\\n assert candidate(180) == False, \\\"Fifth test error: \\\" + str(candidate(180))\\n assert candidate(1000) == True, \\\"Sixth test error: \\\" + str(candidate(1000))\\n\\n\\n # Check some edge cases that are easy to work out by hand.\\n assert candidate(0) == True, \\\"1st edge test error: \\\" + str(candidate(0))\\n assert candidate(1729) == False, \\\"2nd edge test error: \\\" + str(candidate(1728))\\n\\n\\n\\ncheck(iscube)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 77,
"original": "\ndef iscube(a):\n '''\n Write a function that takes an integer a and returns True \n if this ingeger is a cube of some integer number.\n Note: you may assume the input is always valid.\n Examples:\n iscube(1) ==> True\n iscube(2) ==> False\n iscube(-1) ==> True\n iscube(64) ==> True\n iscube(0) ==> True\n iscube(180) ==> False\n '''\n",
"reference": " a = abs(a)\n return int(round(a ** (1. / 3))) ** 3 == a\n",
"split": "test",
"task_id": "HumanEval/77"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def hex_key(num):
"""You have been tasked to write a function that receives
a hexadecimal number as a string and counts the number of hexadecimal
digits that are primes (prime number, or a prime, is a natural number
greater than 1 that is not a product of two smaller natural numbers).
Hexadecimal digits are 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, A, B, C, D, E, F.
Prime numbers are 2, 3, 5, 7, 11, 13, 17,...
So you have to determine a number of the following digits: 2, 3, 5, 7,
B (=decimal 11), D (=decimal 13).
Note: you may assume the input is always correct or empty string,
and symbols A,B,C,D,E,F are always uppercase.
Examples:
For num = "AB" the output should be 1.
For num = "1077E" the output should be 2.
For num = "ABED1A33" the output should be 4.
For num = "123456789ABCDEF0" the output should be 6.
For num = "2020" the output should be 2.
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"def check(candidate):\\n\\n # Check some simple cases\\n assert candidate(\\\"AB\\\") == 1, \\\"First test error: \\\" + str(candidate(\\\"AB\\\")) \\n assert candidate(\\\"1077E\\\") == 2, \\\"Second test error: \\\" + str(candidate(\\\"1077E\\\")) \\n assert candidate(\\\"ABED1A33\\\") == 4, \\\"Third test error: \\\" + str(candidate(\\\"ABED1A33\\\")) \\n assert candidate(\\\"2020\\\") == 2, \\\"Fourth test error: \\\" + str(candidate(\\\"2020\\\")) \\n assert candidate(\\\"123456789ABCDEF0\\\") == 6, \\\"Fifth test error: \\\" + str(candidate(\\\"123456789ABCDEF0\\\")) \\n assert candidate(\\\"112233445566778899AABBCCDDEEFF00\\\") == 12, \\\"Sixth test error: \\\" + str(candidate(\\\"112233445566778899AABBCCDDEEFF00\\\")) \\n\\n\\n # Check some edge cases that are easy to work out by hand.\\n assert candidate([]) == 0\\n\\n\\n\\ncheck(hex_key)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 78,
"original": "\ndef hex_key(num):\n \"\"\"You have been tasked to write a function that receives \n a hexadecimal number as a string and counts the number of hexadecimal \n digits that are primes (prime number, or a prime, is a natural number \n greater than 1 that is not a product of two smaller natural numbers).\n Hexadecimal digits are 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, A, B, C, D, E, F.\n Prime numbers are 2, 3, 5, 7, 11, 13, 17,...\n So you have to determine a number of the following digits: 2, 3, 5, 7, \n B (=decimal 11), D (=decimal 13).\n Note: you may assume the input is always correct or empty string, \n and symbols A,B,C,D,E,F are always uppercase.\n Examples:\n For num = \"AB\" the output should be 1.\n For num = \"1077E\" the output should be 2.\n For num = \"ABED1A33\" the output should be 4.\n For num = \"123456789ABCDEF0\" the output should be 6.\n For num = \"2020\" the output should be 2.\n \"\"\"\n",
"reference": " primes = ('2', '3', '5', '7', 'B', 'D')\n total = 0\n for i in range(0, len(num)):\n if num[i] in primes:\n total += 1\n return total\n",
"split": "test",
"task_id": "HumanEval/78"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def decimal_to_binary(decimal):
"""You will be given a number in decimal form and your task is to convert it to
binary format. The function should return a string, with each character representing a binary
number. Each character in the string will be '0' or '1'.
There will be an extra couple of characters 'db' at the beginning and at the end of the string.
The extra characters are there to help with the format.
Examples:
decimal_to_binary(15) # returns "db1111db"
decimal_to_binary(32) # returns "db100000db"
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"def check(candidate):\\n\\n # Check some simple cases\\n assert candidate(0) == \\\"db0db\\\"\\n assert candidate(32) == \\\"db100000db\\\"\\n assert candidate(103) == \\\"db1100111db\\\"\\n assert candidate(15) == \\\"db1111db\\\", \\\"This prints if this assert fails 1 (good for debugging!)\\\"\\n\\n # Check some edge cases that are easy to work out by hand.\\n assert True, \\\"This prints if this assert fails 2 (also good for debugging!)\\\"\\n\\n\\n\\ncheck(decimal_to_binary)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 79,
"original": "\ndef decimal_to_binary(decimal):\n \"\"\"You will be given a number in decimal form and your task is to convert it to\n binary format. The function should return a string, with each character representing a binary\n number. Each character in the string will be '0' or '1'.\n\n There will be an extra couple of characters 'db' at the beginning and at the end of the string.\n The extra characters are there to help with the format.\n\n Examples:\n decimal_to_binary(15) # returns \"db1111db\"\n decimal_to_binary(32) # returns \"db100000db\"\n \"\"\"\n",
"reference": " return \"db\" + bin(decimal)[2:] + \"db\"\n",
"split": "test",
"task_id": "HumanEval/79"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def is_happy(s):
"""You are given a string s.
Your task is to check if the string is happy or not.
A string is happy if its length is at least 3 and every 3 consecutive letters are distinct
For example:
is_happy(a) => False
is_happy(aa) => False
is_happy(abcd) => True
is_happy(aabb) => False
is_happy(adb) => True
is_happy(xyy) => False
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"def check(candidate):\\n\\n # Check some simple cases\\n assert candidate(\\\"a\\\") == False , \\\"a\\\"\\n assert candidate(\\\"aa\\\") == False , \\\"aa\\\"\\n assert candidate(\\\"abcd\\\") == True , \\\"abcd\\\"\\n assert candidate(\\\"aabb\\\") == False , \\\"aabb\\\"\\n assert candidate(\\\"adb\\\") == True , \\\"adb\\\"\\n assert candidate(\\\"xyy\\\") == False , \\\"xyy\\\"\\n assert candidate(\\\"iopaxpoi\\\") == True , \\\"iopaxpoi\\\"\\n assert candidate(\\\"iopaxioi\\\") == False , \\\"iopaxioi\\\"\\n\\n\\ncheck(is_happy)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 80,
"original": "\ndef is_happy(s):\n \"\"\"You are given a string s.\n Your task is to check if the string is happy or not.\n A string is happy if its length is at least 3 and every 3 consecutive letters are distinct\n For example:\n is_happy(a) => False\n is_happy(aa) => False\n is_happy(abcd) => True\n is_happy(aabb) => False\n is_happy(adb) => True\n is_happy(xyy) => False\n \"\"\"\n",
"reference": " if len(s) < 3:\n return False\n\n for i in range(len(s) - 2):\n \n if s[i] == s[i+1] or s[i+1] == s[i+2] or s[i] == s[i+2]:\n return False\n return True\n",
"split": "test",
"task_id": "HumanEval/80"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def numerical_letter_grade(grades):
"""It is the last week of the semester and the teacher has to give the grades
to students. The teacher has been making her own algorithm for grading.
The only problem is, she has lost the code she used for grading.
She has given you a list of GPAs for some students and you have to write
a function that can output a list of letter grades using the following table:
GPA | Letter grade
4.0 A+
> 3.7 A
> 3.3 A-
> 3.0 B+
> 2.7 B
> 2.3 B-
> 2.0 C+
> 1.7 C
> 1.3 C-
> 1.0 D+
> 0.7 D
> 0.0 D-
0.0 E
Example:
grade_equation([4.0, 3, 1.7, 2, 3.5]) ==> ['A+', 'B', 'C-', 'C', 'A-']
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"def check(candidate):\\n\\n # Check some simple cases\\n assert candidate([4.0, 3, 1.7, 2, 3.5]) == ['A+', 'B', 'C-', 'C', 'A-']\\n assert candidate([1.2]) == ['D+']\\n assert candidate([0.5]) == ['D-']\\n assert candidate([0.0]) == ['E']\\n assert candidate([1, 0.3, 1.5, 2.8, 3.3]) == ['D', 'D-', 'C-', 'B', 'B+']\\n assert candidate([0, 0.7]) == ['E', 'D-']\\n\\n # Check some edge cases that are easy to work out by hand.\\n assert True\\n\\n\\n\\ncheck(numerical_letter_grade)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 81,
"original": "\ndef numerical_letter_grade(grades):\n \"\"\"It is the last week of the semester and the teacher has to give the grades\n to students. The teacher has been making her own algorithm for grading.\n The only problem is, she has lost the code she used for grading.\n She has given you a list of GPAs for some students and you have to write \n a function that can output a list of letter grades using the following table:\n GPA | Letter grade\n 4.0 A+\n > 3.7 A \n > 3.3 A- \n > 3.0 B+\n > 2.7 B \n > 2.3 B-\n > 2.0 C+\n > 1.7 C\n > 1.3 C-\n > 1.0 D+ \n > 0.7 D \n > 0.0 D-\n 0.0 E\n \n\n Example:\n grade_equation([4.0, 3, 1.7, 2, 3.5]) ==> ['A+', 'B', 'C-', 'C', 'A-']\n \"\"\"\n",
"reference": "\n \n letter_grade = []\n for gpa in grades:\n if gpa == 4.0:\n letter_grade.append(\"A+\")\n elif gpa > 3.7:\n letter_grade.append(\"A\")\n elif gpa > 3.3:\n letter_grade.append(\"A-\")\n elif gpa > 3.0:\n letter_grade.append(\"B+\")\n elif gpa > 2.7:\n letter_grade.append(\"B\")\n elif gpa > 2.3:\n letter_grade.append(\"B-\")\n elif gpa > 2.0:\n letter_grade.append(\"C+\")\n elif gpa > 1.7:\n letter_grade.append(\"C\")\n elif gpa > 1.3:\n letter_grade.append(\"C-\")\n elif gpa > 1.0:\n letter_grade.append(\"D+\")\n elif gpa > 0.7:\n letter_grade.append(\"D\")\n elif gpa > 0.0:\n letter_grade.append(\"D-\")\n else:\n letter_grade.append(\"E\")\n return letter_grade\n",
"split": "test",
"task_id": "HumanEval/81"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def prime_length(string):
"""Write a function that takes a string and returns True if the string
length is a prime number or False otherwise
Examples
prime_length('Hello') == True
prime_length('abcdcba') == True
prime_length('kittens') == True
prime_length('orange') == False
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"def check(candidate):\\n\\n # Check some simple cases\\n assert candidate('Hello') == True\\n assert candidate('abcdcba') == True\\n assert candidate('kittens') == True\\n assert candidate('orange') == False\\n assert candidate('wow') == True\\n assert candidate('world') == True\\n assert candidate('MadaM') == True\\n assert candidate('Wow') == True\\n assert candidate('') == False\\n assert candidate('HI') == True\\n assert candidate('go') == True\\n assert candidate('gogo') == False\\n assert candidate('aaaaaaaaaaaaaaa') == False\\n\\n # Check some edge cases that are easy to work out by hand.\\n assert candidate('Madam') == True\\n assert candidate('M') == False\\n assert candidate('0') == False\\n\\n\\n\\ncheck(prime_length)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 82,
"original": "\ndef prime_length(string):\n \"\"\"Write a function that takes a string and returns True if the string\n length is a prime number or False otherwise\n Examples\n prime_length('Hello') == True\n prime_length('abcdcba') == True\n prime_length('kittens') == True\n prime_length('orange') == False\n \"\"\"\n",
"reference": " l = len(string)\n if l == 0 or l == 1:\n return False\n for i in range(2, l):\n if l % i == 0:\n return False\n return True\n",
"split": "test",
"task_id": "HumanEval/82"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def starts_one_ends(n):
"""
Given a positive integer n, return the count of the numbers of n-digit
positive integers that start or end with 1.
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"def check(candidate):\\n\\n # Check some simple cases\\n assert True, \\\"This prints if this assert fails 1 (good for debugging!)\\\"\\n assert candidate(1) == 1\\n assert candidate(2) == 18\\n assert candidate(3) == 180\\n assert candidate(4) == 1800\\n assert candidate(5) == 18000\\n\\n # Check some edge cases that are easy to work out by hand.\\n assert True, \\\"This prints if this assert fails 2 (also good for debugging!)\\\"\\n\\n\\n\\ncheck(starts_one_ends)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 83,
"original": "\ndef starts_one_ends(n):\n \"\"\"\n Given a positive integer n, return the count of the numbers of n-digit\n positive integers that start or end with 1.\n \"\"\"\n",
"reference": " if n == 1: return 1\n return 18 * (10 ** (n - 2))\n",
"split": "test",
"task_id": "HumanEval/83"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def solve(N):
"""Given a positive integer N, return the total sum of its digits in binary.
Example
For N = 1000, the sum of digits will be 1 the output should be "1".
For N = 150, the sum of digits will be 6 the output should be "110".
For N = 147, the sum of digits will be 12 the output should be "1100".
Variables:
@N integer
Constraints: 0 ≤ N ≤ 10000.
Output:
a string of binary number
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"def check(candidate):\\n\\n # Check some simple cases\\n assert True, \\\"This prints if this assert fails 1 (good for debugging!)\\\"\\n assert candidate(1000) == \\\"1\\\", \\\"Error\\\"\\n assert candidate(150) == \\\"110\\\", \\\"Error\\\"\\n assert candidate(147) == \\\"1100\\\", \\\"Error\\\"\\n\\n # Check some edge cases that are easy to work out by hand.\\n assert True, \\\"This prints if this assert fails 2 (also good for debugging!)\\\"\\n assert candidate(333) == \\\"1001\\\", \\\"Error\\\"\\n assert candidate(963) == \\\"10010\\\", \\\"Error\\\"\\n\\n\\n\\ncheck(solve)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 84,
"original": "\ndef solve(N):\n \"\"\"Given a positive integer N, return the total sum of its digits in binary.\n \n Example\n For N = 1000, the sum of digits will be 1 the output should be \"1\".\n For N = 150, the sum of digits will be 6 the output should be \"110\".\n For N = 147, the sum of digits will be 12 the output should be \"1100\".\n \n Variables:\n @N integer\n Constraints: 0 ≤ N ≤ 10000.\n Output:\n a string of binary number\n \"\"\"\n",
"reference": " return bin(sum(int(i) for i in str(N)))[2:]\n",
"split": "test",
"task_id": "HumanEval/84"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def add(lst):
"""Given a non-empty list of integers lst. add the even elements that are at odd indices..
Examples:
add([4, 2, 6, 7]) ==> 2
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"def check(candidate):\\n\\n # Check some simple cases\\n assert candidate([4, 88]) == 88\\n assert candidate([4, 5, 6, 7, 2, 122]) == 122\\n assert candidate([4, 0, 6, 7]) == 0\\n assert candidate([4, 4, 6, 8]) == 12\\n\\n # Check some edge cases that are easy to work out by hand.\\n \\n\\n\\ncheck(add)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 85,
"original": "\ndef add(lst):\n \"\"\"Given a non-empty list of integers lst. add the even elements that are at odd indices..\n\n\n Examples:\n add([4, 2, 6, 7]) ==> 2 \n \"\"\"\n",
"reference": " return sum([lst[i] for i in range(1, len(lst), 2) if lst[i]%2 == 0])\n",
"split": "test",
"task_id": "HumanEval/85"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def anti_shuffle(s):
"""
Write a function that takes a string and returns an ordered version of it.
Ordered version of string, is a string where all words (separated by space)
are replaced by a new word where all the characters arranged in
ascending order based on ascii value.
Note: You should keep the order of words and blank spaces in the sentence.
For example:
anti_shuffle('Hi') returns 'Hi'
anti_shuffle('hello') returns 'ehllo'
anti_shuffle('Hello World!!!') returns 'Hello !!!Wdlor'
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"def check(candidate):\\n\\n # Check some simple cases\\n assert candidate('Hi') == 'Hi'\\n assert candidate('hello') == 'ehllo'\\n assert candidate('number') == 'bemnru'\\n assert candidate('abcd') == 'abcd'\\n assert candidate('Hello World!!!') == 'Hello !!!Wdlor'\\n assert candidate('') == ''\\n assert candidate('Hi. My name is Mister Robot. How are you?') == '.Hi My aemn is Meirst .Rboot How aer ?ouy'\\n # Check some edge cases that are easy to work out by hand.\\n assert True\\n\\n\\n\\ncheck(anti_shuffle)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 86,
"original": "\ndef anti_shuffle(s):\n \"\"\"\n Write a function that takes a string and returns an ordered version of it.\n Ordered version of string, is a string where all words (separated by space)\n are replaced by a new word where all the characters arranged in\n ascending order based on ascii value.\n Note: You should keep the order of words and blank spaces in the sentence.\n\n For example:\n anti_shuffle('Hi') returns 'Hi'\n anti_shuffle('hello') returns 'ehllo'\n anti_shuffle('Hello World!!!') returns 'Hello !!!Wdlor'\n \"\"\"\n",
"reference": " return ' '.join([''.join(sorted(list(i))) for i in s.split(' ')])\n",
"split": "test",
"task_id": "HumanEval/86"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def get_row(lst, x):
"""
You are given a 2 dimensional data, as a nested lists,
which is similar to matrix, however, unlike matrices,
each row may contain a different number of columns.
Given lst, and integer x, find integers x in the list,
and return list of tuples, [(x1, y1), (x2, y2) ...] such that
each tuple is a coordinate - (row, columns), starting with 0.
Sort coordinates initially by rows in ascending order.
Also, sort coordinates of the row by columns in descending order.
Examples:
get_row([
[1,2,3,4,5,6],
[1,2,3,4,1,6],
[1,2,3,4,5,1]
], 1) == [(0, 0), (1, 4), (1, 0), (2, 5), (2, 0)]
get_row([], 1) == []
get_row([[], [1], [1, 2, 3]], 3) == [(2, 2)]
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"def check(candidate):\\n\\n # Check some simple cases\\n assert candidate([\\n [1,2,3,4,5,6],\\n [1,2,3,4,1,6],\\n [1,2,3,4,5,1]\\n ], 1) == [(0, 0), (1, 4), (1, 0), (2, 5), (2, 0)]\\n assert candidate([\\n [1,2,3,4,5,6],\\n [1,2,3,4,5,6],\\n [1,2,3,4,5,6],\\n [1,2,3,4,5,6],\\n [1,2,3,4,5,6],\\n [1,2,3,4,5,6]\\n ], 2) == [(0, 1), (1, 1), (2, 1), (3, 1), (4, 1), (5, 1)]\\n assert candidate([\\n [1,2,3,4,5,6],\\n [1,2,3,4,5,6],\\n [1,1,3,4,5,6],\\n [1,2,1,4,5,6],\\n [1,2,3,1,5,6],\\n [1,2,3,4,1,6],\\n [1,2,3,4,5,1]\\n ], 1) == [(0, 0), (1, 0), (2, 1), (2, 0), (3, 2), (3, 0), (4, 3), (4, 0), (5, 4), (5, 0), (6, 5), (6, 0)]\\n assert candidate([], 1) == []\\n assert candidate([[1]], 2) == []\\n assert candidate([[], [1], [1, 2, 3]], 3) == [(2, 2)]\\n\\n # Check some edge cases that are easy to work out by hand.\\n assert True\\n\\n\\n\\ncheck(get_row)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 87,
"original": "\ndef get_row(lst, x):\n \"\"\"\n You are given a 2 dimensional data, as a nested lists,\n which is similar to matrix, however, unlike matrices,\n each row may contain a different number of columns.\n Given lst, and integer x, find integers x in the list,\n and return list of tuples, [(x1, y1), (x2, y2) ...] such that\n each tuple is a coordinate - (row, columns), starting with 0.\n Sort coordinates initially by rows in ascending order.\n Also, sort coordinates of the row by columns in descending order.\n \n Examples:\n get_row([\n [1,2,3,4,5,6],\n [1,2,3,4,1,6],\n [1,2,3,4,5,1]\n ], 1) == [(0, 0), (1, 4), (1, 0), (2, 5), (2, 0)]\n get_row([], 1) == []\n get_row([[], [1], [1, 2, 3]], 3) == [(2, 2)]\n \"\"\"\n",
"reference": " coords = [(i, j) for i in range(len(lst)) for j in range(len(lst[i])) if lst[i][j] == x]\n return sorted(sorted(coords, key=lambda x: x[1], reverse=True), key=lambda x: x[0])\n",
"split": "test",
"task_id": "HumanEval/87"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def sort_array(array):
"""
Given an array of non-negative integers, return a copy of the given array after sorting,
you will sort the given array in ascending order if the sum( first index value, last index value) is odd,
or sort it in descending order if the sum( first index value, last index value) is even.
Note:
* don't change the given array.
Examples:
* sort_array([]) => []
* sort_array([5]) => [5]
* sort_array([2, 4, 3, 0, 1, 5]) => [0, 1, 2, 3, 4, 5]
* sort_array([2, 4, 3, 0, 1, 5, 6]) => [6, 5, 4, 3, 2, 1, 0]
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"def check(candidate):\\n\\n # Check some simple cases\\n assert True, \\\"This prints if this assert fails 1 (good for debugging!)\\\"\\n assert candidate([]) == [], \\\"Error\\\"\\n assert candidate([5]) == [5], \\\"Error\\\"\\n assert candidate([2, 4, 3, 0, 1, 5]) == [0, 1, 2, 3, 4, 5], \\\"Error\\\"\\n assert candidate([2, 4, 3, 0, 1, 5, 6]) == [6, 5, 4, 3, 2, 1, 0], \\\"Error\\\"\\n\\n # Check some edge cases that are easy to work out by hand.\\n assert True, \\\"This prints if this assert fails 2 (also good for debugging!)\\\"\\n assert candidate([2, 1]) == [1, 2], \\\"Error\\\"\\n assert candidate([15, 42, 87, 32 ,11, 0]) == [0, 11, 15, 32, 42, 87], \\\"Error\\\"\\n assert candidate([21, 14, 23, 11]) == [23, 21, 14, 11], \\\"Error\\\"\\n\\n\\n\\ncheck(sort_array)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 88,
"original": "\ndef sort_array(array):\n \"\"\"\n Given an array of non-negative integers, return a copy of the given array after sorting,\n you will sort the given array in ascending order if the sum( first index value, last index value) is odd,\n or sort it in descending order if the sum( first index value, last index value) is even.\n\n Note:\n * don't change the given array.\n\n Examples:\n * sort_array([]) => []\n * sort_array([5]) => [5]\n * sort_array([2, 4, 3, 0, 1, 5]) => [0, 1, 2, 3, 4, 5]\n * sort_array([2, 4, 3, 0, 1, 5, 6]) => [6, 5, 4, 3, 2, 1, 0]\n \"\"\"\n",
"reference": " return [] if len(array) == 0 else sorted(array, reverse= (array[0]+array[-1]) % 2 == 0) \n",
"split": "test",
"task_id": "HumanEval/88"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def encrypt(s):
"""Create a function encrypt that takes a string as an argument and
returns a string encrypted with the alphabet being rotated.
The alphabet should be rotated in a manner such that the letters
shift down by two multiplied to two places.
For example:
encrypt('hi') returns 'lm'
encrypt('asdfghjkl') returns 'ewhjklnop'
encrypt('gf') returns 'kj'
encrypt('et') returns 'ix'
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"def check(candidate):\\n\\n # Check some simple cases\\n assert candidate('hi') == 'lm', \\\"This prints if this assert fails 1 (good for debugging!)\\\"\\n assert candidate('asdfghjkl') == 'ewhjklnop', \\\"This prints if this assert fails 1 (good for debugging!)\\\"\\n assert candidate('gf') == 'kj', \\\"This prints if this assert fails 1 (good for debugging!)\\\"\\n assert candidate('et') == 'ix', \\\"This prints if this assert fails 1 (good for debugging!)\\\"\\n\\n assert candidate('faewfawefaewg')=='jeiajeaijeiak', \\\"This prints if this assert fails 1 (good for debugging!)\\\"\\n assert candidate('hellomyfriend')=='lippsqcjvmirh', \\\"This prints if this assert fails 2 (good for debugging!)\\\"\\n assert candidate('dxzdlmnilfuhmilufhlihufnmlimnufhlimnufhfucufh')=='hbdhpqrmpjylqmpyjlpmlyjrqpmqryjlpmqryjljygyjl', \\\"This prints if this assert fails 3 (good for debugging!)\\\"\\n\\n # Check some edge cases that are easy to work out by hand.\\n assert candidate('a')=='e', \\\"This prints if this assert fails 2 (also good for debugging!)\\\"\\n\\n\\n\\ncheck(encrypt)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 89,
"original": "\ndef encrypt(s):\n \"\"\"Create a function encrypt that takes a string as an argument and\n returns a string encrypted with the alphabet being rotated. \n The alphabet should be rotated in a manner such that the letters \n shift down by two multiplied to two places.\n For example:\n encrypt('hi') returns 'lm'\n encrypt('asdfghjkl') returns 'ewhjklnop'\n encrypt('gf') returns 'kj'\n encrypt('et') returns 'ix'\n \"\"\"\n",
"reference": " d = 'abcdefghijklmnopqrstuvwxyz'\n out = ''\n for c in s:\n if c in d:\n out += d[(d.index(c)+2*2) % 26]\n else:\n out += c\n return out\n",
"split": "test",
"task_id": "HumanEval/89"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def next_smallest(lst):
"""
You are given a list of integers.
Write a function next_smallest() that returns the 2nd smallest element of the list.
Return None if there is no such element.
next_smallest([1, 2, 3, 4, 5]) == 2
next_smallest([5, 1, 4, 3, 2]) == 2
next_smallest([]) == None
next_smallest([1, 1]) == None
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"def check(candidate):\\n\\n # Check some simple cases\\n assert candidate([1, 2, 3, 4, 5]) == 2\\n assert candidate([5, 1, 4, 3, 2]) == 2\\n assert candidate([]) == None\\n assert candidate([1, 1]) == None\\n assert candidate([1,1,1,1,0]) == 1\\n assert candidate([1, 0**0]) == None\\n assert candidate([-35, 34, 12, -45]) == -35\\n\\n # Check some edge cases that are easy to work out by hand.\\n assert True\\n\\n\\n\\ncheck(next_smallest)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 90,
"original": "\ndef next_smallest(lst):\n \"\"\"\n You are given a list of integers.\n Write a function next_smallest() that returns the 2nd smallest element of the list.\n Return None if there is no such element.\n \n next_smallest([1, 2, 3, 4, 5]) == 2\n next_smallest([5, 1, 4, 3, 2]) == 2\n next_smallest([]) == None\n next_smallest([1, 1]) == None\n \"\"\"\n",
"reference": " lst = sorted(set(lst))\n return None if len(lst) < 2 else lst[1]\n",
"split": "test",
"task_id": "HumanEval/90"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def is_bored(S):
"""
You'll be given a string of words, and your task is to count the number
of boredoms. A boredom is a sentence that starts with the word "I".
Sentences are delimited by '.', '?' or '!'.
For example:
>>> is_bored("Hello world")
0
>>> is_bored("The sky is blue. The sun is shining. I love this weather")
1
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"def check(candidate):\\n\\n # Check some simple cases\\n assert candidate(\\\"Hello world\\\") == 0, \\\"Test 1\\\"\\n assert candidate(\\\"Is the sky blue?\\\") == 0, \\\"Test 2\\\"\\n assert candidate(\\\"I love It !\\\") == 1, \\\"Test 3\\\"\\n assert candidate(\\\"bIt\\\") == 0, \\\"Test 4\\\"\\n assert candidate(\\\"I feel good today. I will be productive. will kill It\\\") == 2, \\\"Test 5\\\"\\n assert candidate(\\\"You and I are going for a walk\\\") == 0, \\\"Test 6\\\"\\n\\n # Check some edge cases that are easy to work out by hand.\\n assert True, \\\"This prints if this assert fails 2 (also good for debugging!)\\\"\\n\\n\\n\\ncheck(is_bored)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 91,
"original": "\ndef is_bored(S):\n \"\"\"\n You'll be given a string of words, and your task is to count the number\n of boredoms. A boredom is a sentence that starts with the word \"I\".\n Sentences are delimited by '.', '?' or '!'.\n \n For example:\n >>> is_bored(\"Hello world\")\n 0\n >>> is_bored(\"The sky is blue. The sun is shining. I love this weather\")\n 1\n \"\"\"\n",
"reference": " import re\n sentences = re.split(r'[.?!]\\s*', S)\n return sum(sentence[0:2] == 'I ' for sentence in sentences)\n",
"split": "test",
"task_id": "HumanEval/91"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def any_int(x, y, z):
'''
Create a function that takes 3 numbers.
Returns true if one of the numbers is equal to the sum of the other two, and all numbers are integers.
Returns false in any other cases.
Examples
any_int(5, 2, 7) ➞ True
any_int(3, 2, 2) ➞ False
any_int(3, -2, 1) ➞ True
any_int(3.6, -2.2, 2) ➞ False
'''
|
codegen
|
{
"ground_truth": "{\"functional\": \"def check(candidate):\\n\\n # Check some simple cases\\n assert candidate(2, 3, 1)==True, \\\"This prints if this assert fails 1 (good for debugging!)\\\"\\n assert candidate(2.5, 2, 3)==False, \\\"This prints if this assert fails 2 (good for debugging!)\\\"\\n assert candidate(1.5, 5, 3.5)==False, \\\"This prints if this assert fails 3 (good for debugging!)\\\"\\n assert candidate(2, 6, 2)==False, \\\"This prints if this assert fails 4 (good for debugging!)\\\"\\n assert candidate(4, 2, 2)==True, \\\"This prints if this assert fails 5 (good for debugging!)\\\"\\n assert candidate(2.2, 2.2, 2.2)==False, \\\"This prints if this assert fails 6 (good for debugging!)\\\"\\n assert candidate(-4, 6, 2)==True, \\\"This prints if this assert fails 7 (good for debugging!)\\\"\\n\\n # Check some edge cases that are easy to work out by hand.\\n assert candidate(2,1,1)==True, \\\"This prints if this assert fails 8 (also good for debugging!)\\\"\\n assert candidate(3,4,7)==True, \\\"This prints if this assert fails 9 (also good for debugging!)\\\"\\n assert candidate(3.0,4,7)==False, \\\"This prints if this assert fails 10 (also good for debugging!)\\\"\\n\\n\\n\\ncheck(any_int)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 92,
"original": "\ndef any_int(x, y, z):\n '''\n Create a function that takes 3 numbers.\n Returns true if one of the numbers is equal to the sum of the other two, and all numbers are integers.\n Returns false in any other cases.\n \n Examples\n any_int(5, 2, 7) ➞ True\n \n any_int(3, 2, 2) ➞ False\n\n any_int(3, -2, 1) ➞ True\n \n any_int(3.6, -2.2, 2) ➞ False\n \n\n \n '''\n",
"reference": " \n if isinstance(x,int) and isinstance(y,int) and isinstance(z,int):\n if (x+y==z) or (x+z==y) or (y+z==x):\n return True\n return False\n return False\n",
"split": "test",
"task_id": "HumanEval/92"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def encode(message):
"""
Write a function that takes a message, and encodes in such a
way that it swaps case of all letters, replaces all vowels in
the message with the letter that appears 2 places ahead of that
vowel in the english alphabet.
Assume only letters.
Examples:
>>> encode('test')
'TGST'
>>> encode('This is a message')
'tHKS KS C MGSSCGG'
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"def check(candidate):\\n\\n # Check some simple cases\\n assert candidate('TEST') == 'tgst', \\\"This prints if this assert fails 1 (good for debugging!)\\\"\\n assert candidate('Mudasir') == 'mWDCSKR', \\\"This prints if this assert fails 2 (good for debugging!)\\\"\\n assert candidate('YES') == 'ygs', \\\"This prints if this assert fails 3 (good for debugging!)\\\"\\n \\n # Check some edge cases that are easy to work out by hand.\\n assert candidate('This is a message') == 'tHKS KS C MGSSCGG', \\\"This prints if this assert fails 2 (also good for debugging!)\\\"\\n assert candidate(\\\"I DoNt KnOw WhAt tO WrItE\\\") == 'k dQnT kNqW wHcT Tq wRkTg', \\\"This prints if this assert fails 2 (also good for debugging!)\\\"\\n\\n\\n\\ncheck(encode)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 93,
"original": "\ndef encode(message):\n \"\"\"\n Write a function that takes a message, and encodes in such a \n way that it swaps case of all letters, replaces all vowels in \n the message with the letter that appears 2 places ahead of that \n vowel in the english alphabet. \n Assume only letters. \n \n Examples:\n >>> encode('test')\n 'TGST'\n >>> encode('This is a message')\n 'tHKS KS C MGSSCGG'\n \"\"\"\n",
"reference": " vowels = \"aeiouAEIOU\"\n vowels_replace = dict([(i, chr(ord(i) + 2)) for i in vowels])\n message = message.swapcase()\n return ''.join([vowels_replace[i] if i in vowels else i for i in message])\n",
"split": "test",
"task_id": "HumanEval/93"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def skjkasdkd(lst):
"""You are given a list of integers.
You need to find the largest prime value and return the sum of its digits.
Examples:
For lst = [0,3,2,1,3,5,7,4,5,5,5,2,181,32,4,32,3,2,32,324,4,3] the output should be 10
For lst = [1,0,1,8,2,4597,2,1,3,40,1,2,1,2,4,2,5,1] the output should be 25
For lst = [1,3,1,32,5107,34,83278,109,163,23,2323,32,30,1,9,3] the output should be 13
For lst = [0,724,32,71,99,32,6,0,5,91,83,0,5,6] the output should be 11
For lst = [0,81,12,3,1,21] the output should be 3
For lst = [0,8,1,2,1,7] the output should be 7
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"def check(candidate):\\n\\n # Check some simple cases\\n assert candidate([0,3,2,1,3,5,7,4,5,5,5,2,181,32,4,32,3,2,32,324,4,3]) == 10, \\\"This prints if this assert fails 1 (good for debugging!)\\\"\\n\\n # Check some edge cases that are easy to work out by hand.\\n assert candidate([1,0,1,8,2,4597,2,1,3,40,1,2,1,2,4,2,5,1]) == 25, \\\"This prints if this assert fails 2 (also good for debugging!)\\\"\\n\\n # Check some edge cases that are easy to work out by hand.\\n assert candidate([1,3,1,32,5107,34,83278,109,163,23,2323,32,30,1,9,3]) == 13, \\\"This prints if this assert fails 3 (also good for debugging!)\\\"\\n\\n # Check some edge cases that are easy to work out by hand.\\n assert candidate([0,724,32,71,99,32,6,0,5,91,83,0,5,6]) == 11, \\\"This prints if this assert fails 4 (also good for debugging!)\\\"\\n \\n # Check some edge cases that are easy to work out by hand.\\n assert candidate([0,81,12,3,1,21]) == 3, \\\"This prints if this assert fails 5 (also good for debugging!)\\\"\\n\\n # Check some edge cases that are easy to work out by hand.\\n assert candidate([0,8,1,2,1,7]) == 7, \\\"This prints if this assert fails 6 (also good for debugging!)\\\"\\n\\n assert candidate([8191]) == 19, \\\"This prints if this assert fails 7 (also good for debugging!)\\\"\\n assert candidate([8191, 123456, 127, 7]) == 19, \\\"This prints if this assert fails 8 (also good for debugging!)\\\"\\n assert candidate([127, 97, 8192]) == 10, \\\"This prints if this assert fails 9 (also good for debugging!)\\\"\\n\\n\\ncheck(skjkasdkd)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 94,
"original": "\n\ndef skjkasdkd(lst):\n \"\"\"You are given a list of integers.\n You need to find the largest prime value and return the sum of its digits.\n\n Examples:\n For lst = [0,3,2,1,3,5,7,4,5,5,5,2,181,32,4,32,3,2,32,324,4,3] the output should be 10\n For lst = [1,0,1,8,2,4597,2,1,3,40,1,2,1,2,4,2,5,1] the output should be 25\n For lst = [1,3,1,32,5107,34,83278,109,163,23,2323,32,30,1,9,3] the output should be 13\n For lst = [0,724,32,71,99,32,6,0,5,91,83,0,5,6] the output should be 11\n For lst = [0,81,12,3,1,21] the output should be 3\n For lst = [0,8,1,2,1,7] the output should be 7\n \"\"\"\n",
"reference": " def isPrime(n):\n for i in range(2,int(n**0.5)+1):\n if n%i==0:\n return False\n\n return True\n maxx = 0\n i = 0\n while i < len(lst):\n if(lst[i] > maxx and isPrime(lst[i])):\n maxx = lst[i]\n i+=1\n result = sum(int(digit) for digit in str(maxx))\n return result\n\n",
"split": "test",
"task_id": "HumanEval/94"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def check_dict_case(dict):
"""
Given a dictionary, return True if all keys are strings in lower
case or all keys are strings in upper case, else return False.
The function should return False is the given dictionary is empty.
Examples:
check_dict_case({"a":"apple", "b":"banana"}) should return True.
check_dict_case({"a":"apple", "A":"banana", "B":"banana"}) should return False.
check_dict_case({"a":"apple", 8:"banana", "a":"apple"}) should return False.
check_dict_case({"Name":"John", "Age":"36", "City":"Houston"}) should return False.
check_dict_case({"STATE":"NC", "ZIP":"12345" }) should return True.
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"def check(candidate):\\n\\n # Check some simple cases\\n assert candidate({\\\"p\\\":\\\"pineapple\\\", \\\"b\\\":\\\"banana\\\"}) == True, \\\"First test error: \\\" + str(candidate({\\\"p\\\":\\\"pineapple\\\", \\\"b\\\":\\\"banana\\\"}))\\n assert candidate({\\\"p\\\":\\\"pineapple\\\", \\\"A\\\":\\\"banana\\\", \\\"B\\\":\\\"banana\\\"}) == False, \\\"Second test error: \\\" + str(candidate({\\\"p\\\":\\\"pineapple\\\", \\\"A\\\":\\\"banana\\\", \\\"B\\\":\\\"banana\\\"}))\\n assert candidate({\\\"p\\\":\\\"pineapple\\\", 5:\\\"banana\\\", \\\"a\\\":\\\"apple\\\"}) == False, \\\"Third test error: \\\" + str(candidate({\\\"p\\\":\\\"pineapple\\\", 5:\\\"banana\\\", \\\"a\\\":\\\"apple\\\"}))\\n assert candidate({\\\"Name\\\":\\\"John\\\", \\\"Age\\\":\\\"36\\\", \\\"City\\\":\\\"Houston\\\"}) == False, \\\"Fourth test error: \\\" + str(candidate({\\\"Name\\\":\\\"John\\\", \\\"Age\\\":\\\"36\\\", \\\"City\\\":\\\"Houston\\\"}))\\n assert candidate({\\\"STATE\\\":\\\"NC\\\", \\\"ZIP\\\":\\\"12345\\\" }) == True, \\\"Fifth test error: \\\" + str(candidate({\\\"STATE\\\":\\\"NC\\\", \\\"ZIP\\\":\\\"12345\\\" })) \\n assert candidate({\\\"fruit\\\":\\\"Orange\\\", \\\"taste\\\":\\\"Sweet\\\" }) == True, \\\"Fourth test error: \\\" + str(candidate({\\\"fruit\\\":\\\"Orange\\\", \\\"taste\\\":\\\"Sweet\\\" })) \\n\\n\\n # Check some edge cases that are easy to work out by hand.\\n assert candidate({}) == False, \\\"1st edge test error: \\\" + str(candidate({}))\\n\\n\\n\\ncheck(check_dict_case)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 95,
"original": "\ndef check_dict_case(dict):\n \"\"\"\n Given a dictionary, return True if all keys are strings in lower \n case or all keys are strings in upper case, else return False.\n The function should return False is the given dictionary is empty.\n Examples:\n check_dict_case({\"a\":\"apple\", \"b\":\"banana\"}) should return True.\n check_dict_case({\"a\":\"apple\", \"A\":\"banana\", \"B\":\"banana\"}) should return False.\n check_dict_case({\"a\":\"apple\", 8:\"banana\", \"a\":\"apple\"}) should return False.\n check_dict_case({\"Name\":\"John\", \"Age\":\"36\", \"City\":\"Houston\"}) should return False.\n check_dict_case({\"STATE\":\"NC\", \"ZIP\":\"12345\" }) should return True.\n \"\"\"\n",
"reference": " if len(dict.keys()) == 0:\n return False\n else:\n state = \"start\"\n for key in dict.keys():\n\n if isinstance(key, str) == False:\n state = \"mixed\"\n break\n if state == \"start\":\n if key.isupper():\n state = \"upper\"\n elif key.islower():\n state = \"lower\"\n else:\n break\n elif (state == \"upper\" and not key.isupper()) or (state == \"lower\" and not key.islower()):\n state = \"mixed\"\n break\n else:\n break\n return state == \"upper\" or state == \"lower\" \n",
"split": "test",
"task_id": "HumanEval/95"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def count_up_to(n):
"""Implement a function that takes an non-negative integer and returns an array of the first n
integers that are prime numbers and less than n.
for example:
count_up_to(5) => [2,3]
count_up_to(11) => [2,3,5,7]
count_up_to(0) => []
count_up_to(20) => [2,3,5,7,11,13,17,19]
count_up_to(1) => []
count_up_to(18) => [2,3,5,7,11,13,17]
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"def check(candidate):\\n\\n assert candidate(5) == [2,3]\\n assert candidate(6) == [2,3,5]\\n assert candidate(7) == [2,3,5]\\n assert candidate(10) == [2,3,5,7]\\n assert candidate(0) == []\\n assert candidate(22) == [2,3,5,7,11,13,17,19]\\n assert candidate(1) == []\\n assert candidate(18) == [2,3,5,7,11,13,17]\\n assert candidate(47) == [2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41, 43]\\n assert candidate(101) == [2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41, 43, 47, 53, 59, 61, 67, 71, 73, 79, 83, 89, 97]\\n\\n\\n\\ncheck(count_up_to)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 96,
"original": "\ndef count_up_to(n):\n \"\"\"Implement a function that takes an non-negative integer and returns an array of the first n\n integers that are prime numbers and less than n.\n for example:\n count_up_to(5) => [2,3]\n count_up_to(11) => [2,3,5,7]\n count_up_to(0) => []\n count_up_to(20) => [2,3,5,7,11,13,17,19]\n count_up_to(1) => []\n count_up_to(18) => [2,3,5,7,11,13,17]\n \"\"\"\n",
"reference": " primes = []\n for i in range(2, n):\n is_prime = True\n for j in range(2, i):\n if i % j == 0:\n is_prime = False\n break\n if is_prime:\n primes.append(i)\n return primes\n\n",
"split": "test",
"task_id": "HumanEval/96"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def multiply(a, b):
"""Complete the function that takes two integers and returns
the product of their unit digits.
Assume the input is always valid.
Examples:
multiply(148, 412) should return 16.
multiply(19, 28) should return 72.
multiply(2020, 1851) should return 0.
multiply(14,-15) should return 20.
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"def check(candidate):\\n\\n # Check some simple cases\\n assert candidate(148, 412) == 16, \\\"First test error: \\\" + str(candidate(148, 412)) \\n assert candidate(19, 28) == 72, \\\"Second test error: \\\" + str(candidate(19, 28)) \\n assert candidate(2020, 1851) == 0, \\\"Third test error: \\\" + str(candidate(2020, 1851))\\n assert candidate(14,-15) == 20, \\\"Fourth test error: \\\" + str(candidate(14,-15)) \\n assert candidate(76, 67) == 42, \\\"Fifth test error: \\\" + str(candidate(76, 67)) \\n assert candidate(17, 27) == 49, \\\"Sixth test error: \\\" + str(candidate(17, 27)) \\n\\n\\n # Check some edge cases that are easy to work out by hand.\\n assert candidate(0, 1) == 0, \\\"1st edge test error: \\\" + str(candidate(0, 1))\\n assert candidate(0, 0) == 0, \\\"2nd edge test error: \\\" + str(candidate(0, 0))\\n\\n\\n\\ncheck(multiply)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 97,
"original": "\ndef multiply(a, b):\n \"\"\"Complete the function that takes two integers and returns \n the product of their unit digits.\n Assume the input is always valid.\n Examples:\n multiply(148, 412) should return 16.\n multiply(19, 28) should return 72.\n multiply(2020, 1851) should return 0.\n multiply(14,-15) should return 20.\n \"\"\"\n",
"reference": " return abs(a % 10) * abs(b % 10)\n",
"split": "test",
"task_id": "HumanEval/97"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def count_upper(s):
"""
Given a string s, count the number of uppercase vowels in even indices.
For example:
count_upper('aBCdEf') returns 1
count_upper('abcdefg') returns 0
count_upper('dBBE') returns 0
"""
|
codegen
|
{
"ground_truth": "{\"functional\": \"def check(candidate):\\n\\n # Check some simple cases\\n assert candidate('aBCdEf') == 1\\n assert candidate('abcdefg') == 0\\n assert candidate('dBBE') == 0\\n assert candidate('B') == 0\\n assert candidate('U') == 1\\n assert candidate('') == 0\\n assert candidate('EEEE') == 2\\n\\n # Check some edge cases that are easy to work out by hand.\\n assert True\\n\\n\\n\\ncheck(count_upper)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 98,
"original": "\ndef count_upper(s):\n \"\"\"\n Given a string s, count the number of uppercase vowels in even indices.\n \n For example:\n count_upper('aBCdEf') returns 1\n count_upper('abcdefg') returns 0\n count_upper('dBBE') returns 0\n \"\"\"\n",
"reference": " count = 0\n for i in range(0,len(s),2):\n if s[i] in \"AEIOU\":\n count += 1\n return count\n",
"split": "test",
"task_id": "HumanEval/98"
}
|
openai_humaneval
|
Read the following function signature and docstring, and fully implement the function described in Python. Your response should only contain the code for this function.
def closest_integer(value):
'''
Create a function that takes a value (string) representing a number
and returns the closest integer to it. If the number is equidistant
from two integers, round it away from zero.
Examples
>>> closest_integer("10")
10
>>> closest_integer("15.3")
15
Note:
Rounding away from zero means that if the given number is equidistant
from two integers, the one you should return is the one that is the
farthest from zero. For example closest_integer("14.5") should
return 15 and closest_integer("-14.5") should return -15.
'''
|
codegen
|
{
"ground_truth": "{\"functional\": \"def check(candidate):\\n\\n # Check some simple cases\\n assert candidate(\\\"10\\\") == 10, \\\"Test 1\\\"\\n assert candidate(\\\"14.5\\\") == 15, \\\"Test 2\\\"\\n assert candidate(\\\"-15.5\\\") == -16, \\\"Test 3\\\"\\n assert candidate(\\\"15.3\\\") == 15, \\\"Test 3\\\"\\n\\n # Check some edge cases that are easy to work out by hand.\\n assert candidate(\\\"0\\\") == 0, \\\"Test 0\\\"\\n\\n\\n\\ncheck(closest_integer)\"}",
"style": "rule"
}
| null |
{
"dataset": "openai_humaneval",
"index": 99,
"original": "\ndef closest_integer(value):\n '''\n Create a function that takes a value (string) representing a number\n and returns the closest integer to it. If the number is equidistant\n from two integers, round it away from zero.\n\n Examples\n >>> closest_integer(\"10\")\n 10\n >>> closest_integer(\"15.3\")\n 15\n\n Note:\n Rounding away from zero means that if the given number is equidistant\n from two integers, the one you should return is the one that is the\n farthest from zero. For example closest_integer(\"14.5\") should\n return 15 and closest_integer(\"-14.5\") should return -15.\n '''\n",
"reference": " from math import floor, ceil\n\n if value.count('.') == 1:\n # remove trailing zeros\n while (value[-1] == '0'):\n value = value[:-1]\n\n num = float(value)\n if value[-2:] == '.5':\n if num > 0:\n res = ceil(num)\n else:\n res = floor(num)\n elif len(value) > 0:\n res = int(round(num))\n else:\n res = 0\n\n return res\n\n",
"split": "test",
"task_id": "HumanEval/99"
}
|
End of preview. Expand
in Data Studio
README.md exists but content is empty.
- Downloads last month
- 82