HeyixInn0/Reorganized-humanevalplus · Datasets at Hugging Face

src_lang null	solution stringlengths 132 1.99k	compare_func stringclasses 1 value	demos sequencelengths 0 8	entry_func stringlengths 1 30	import_str sequencelengths 0 1	doc_string stringlengths 0 1.07k	task_name stringclasses 1 value	dataset_name stringclasses 1 value	tgt_lang stringclasses 1 value	test_cases sequencelengths 12 1.1k ⌀	data_id stringlengths 11 13	prefix stringlengths 115 1.36k
null	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 """ for idx, elem in enumerate(numbers): for idx2, elem2 in enumerate(numbers): if idx != idx2: distance = abs(elem - elem2) if distance < threshold: return True return False	import numpy as np def is_floats(x) -> bool: # check if it is float; List[float]; Tuple[float] if isinstance(x, float): return True if isinstance(x, (list, tuple)): return all(isinstance(i, float) for i in x) if isinstance(x, np.ndarray): return x.dtype == np.float64 or x.dtype == np.float32 return False def assertion(out, exp, atol): exact_match = out == exp if atol == 0 and is_floats(exp): atol = 1e-6 if not exact_match and atol != 0: assert np.allclose(out, exp, rtol=1e-07, atol=atol) else: assert exact_match	[ [ "[1.0, 2.0, 3.0], 0.5", "False" ], [ "[1.0, 2.8, 3.0, 4.0, 5.0, 2.0], 0.3", "True" ] ]	has_close_elements	[ "from typing import List" ]	Check if in given list of numbers, are any two numbers closer to each other than given threshold.	code_generation	HumanEval_plus	python	[ [ "[1.0, 2.0, 3.9, 4.0, 5.0, 2.2], 0.3", "True" ], [ "[1.0, 2.0, 3.9, 4.0, 5.0, 2.2], 0.05", "False" ], [ "[1.0, 2.0, 5.9, 4.0, 5.0], 0.95", "True" ], [ "[1.0, 2.0, 5.9, 4.0, 5.0], 0.8", "False" ], [ "[1.0, 2.0, 3.0, 4.0, 5.0, 2.0], 0.1", "True" ], [ "[1.1, 2.2, 3.1, 4.1, 5.1], 1.0", "True" ], [ "[1.1, 2.2, 3.1, 4.1, 5.1], 0.5", "False" ], [ "[1.0, 2.5, 3.0, 4.5, 5.0, 6.5], 0.4", "False" ], [ "[1.0, 2.0, 3.0, 2.9, 5.0, 6.0], 0.1", "False" ], [ "[0.5, 0.6, 0.7, 0.8, 0.9], 0.05", "False" ], [ "[10.5, 20.5, 30.5, 25.5, 40.5], 4.0", "False" ], [ "[1.1, 2.2, 3.3, 4.4, 5.5, 6.6, 7.7], 0.2", "False" ], [ "[0.1, 0.5, 1.0, 1.5, 2.0], 0.1", "False" ], [ "[1.2, 2.4, 3.6, 4.8], 0.8", "False" ], [ "[-1.0, -0.5, 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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 """
null	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('( ) (( )) (( )( ))') ['()', '(())', '(()())'] """ result = [] current_string = [] current_depth = 0 for c in paren_string: if c == '(': current_depth += 1 current_string.append(c) elif c == ')': current_depth -= 1 current_string.append(c) if current_depth == 0: result.append(''.join(current_string)) current_string.clear() return result	import numpy as np def is_floats(x) -> bool: # check if it is float; List[float]; Tuple[float] if isinstance(x, float): return True if isinstance(x, (list, tuple)): return all(isinstance(i, float) for i in x) if isinstance(x, np.ndarray): return x.dtype == np.float64 or x.dtype == np.float32 return False def assertion(out, exp, atol): exact_match = out == exp if atol == 0 and is_floats(exp): atol = 1e-6 if not exact_match and atol != 0: assert np.allclose(out, exp, rtol=1e-07, atol=atol) else: assert exact_match	[ [ "'( ) (( )) (( )( ))'", "['()', '(())', '(()())']" ] ]	separate_paren_groups	[ "from typing import List" ]	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.	code_generation	HumanEval_plus	python	[ [ "(()()) ((())) () ((())()())", "['(()())', '((()))', '()', '((())()())']" ], [ "() (()) ((())) (((())))", "['()', '(())', '((()))', '(((())))']" ], [ "(()(())((())))", "['(()(())((())))']" ], [ "( ) (( )) (( )( ))", "['()', '(())', '(()())']" ], [ "()", "['()']" ], [ "(())", "['(())']" ], [ "((()))()", "['((()))', '()']" ], [ "()()()", "['()', '()', '()']" ], [ "()(()())()", "['()', '(()())', '()']" ], [ "(((()()((())))))", "['(((()()((())))))']" ], [ "((()()))(())", "['((()()))', '(())']" ], [ "()(()()((())))", "['()', '(()()((())))']" ], [ "()()()(((()())))()(())", "['()', '()', '()', '(((()())))', '()', '(())']" ], [ "(((())))()((()()))", "['(((())))', '()', '((()()))']" ], [ "(((())))()(((())))()((()()))((()()))", "['(((())))', '()', '(((())))', '()', '((()()))', '((()()))']" ], [ 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'()']" ], [ "()()((((()()((()))))))()(()())()(()()((())))()", "['()', '()', '((((()()((()))))))', '()', '(()())', '()', '(()()((())))', '()']" ], [ "()()(((((()()((()))))))()(()())()(()))()", "['()', '()', '(((((()()((()))))))()(()())()(()))', '()']" ], [ "((() ((()()(((((( )))))))()()))) (()(()))()(()())", "['((()((()()(((((()))))))()())))', '(()(()))', '()', '(()())']" ], [ "((( ) ((( )) () (( ))))) (((( )))) (( ))", "['((()((())()(()))))', '(((())))', '(())']" ], [ "(()) (()) ((() ((())))()) ((())(()))()", "['(())', '(())', '((()((())))())', '((())(()))', '()']" ], [ "((()) ()) ()(()) (()(())())", "['((())())', '()', '(())', '(()(())())']" ], [ "((()) (())() (())(()))()(((())))((()()))((()))", "['((())(())()(())(()))', '()', '(((())))', '((()()))', '((()))']" ], [ "(((())))(((())))(((())))(((())))(((())))(((())))(((())))(((())))(((())))(((())))", "['(((())))', '(((())))', '(((())))', '(((())))', '(((())))', '(((())))', '(((())))', '(((())))', '(((())))', '(((())))']" ], [ "(((())))(((())))(((())))(((())))(((())))(((())))(((())))(((())))(((())))(((())))()()()()()", "['(((())))', '(((())))', '(((())))', '(((())))', '(((())))', '(((())))', '(((())))', '(((())))', '(((())))', '(((())))', '()', '()', '()', '()', '()']" ], [ "()()()()()()((()))()()()((()))()()()((()))()()()((()))()()()((()))()()()((()))()()()((()))()()()", "['()', '()', '()', '()', '()', '()', '((()))', '()', '()', '()', '((()))', '()', '()', '()', '((()))', '()', '()', '()', '((()))', '()', '()', '()', '((()))', '()', '()', '()', '((()))', '()', '()', '()', '((()))', '()', '()', '()']" ], [ "() ( ) (( )) ((( )))()(()()()) ((()())())() (()()()()()())", "['()', '()', '(())', '((()))', '()', '(()()())', '((()())())', '()', '(()()()()()())']" ], [ "((( ) (((()) (()) ((() ((())))()) ((())(()))()( )) () (( ))))) (((( )))) (( ))", "['((()(((())(())((()((())))())((())(()))()())()(()))))', '(((())))', '(())']" ], [ "(()()()()()())", "['(()()()()()())']" ], [ "(()) (()) ", "['(())', '(())']" ], [ "((( ) (((())) (()) ((() ((())((((((() ((() ((() ())))))))))))()) ((())(()))()( )) () (( ))))) (((( )))) (( ))", "['((()(((()))(())((()((())((((((()((()((()())))))))))))())((())(()))()())()(()))))', '(((())))', '(())']" ], [ "(()) ((((() ((()()(((((( )))))))()()))) (()(()))()(()()))) ", "['(())', '((((()((()()(((((()))))))()())))(()(()))()(()())))']" ], [ "((( ) (((()(())())) (()) ((() ((())((((((() ((() ((() ())))))))))))()) ((())(()))()( )) () (( ))))) (((( )))) (( ))", "['((()(((()(())()))(())((()((())((((((()((()((()())))))))))))())((())(()))()())()(()))))', '(((())))', '(())']" ], [ "()(())", "['()', '(())']" ], [ "(())()", "['(())', '()']" ], [ "(()(()))", "['(()(()))']" ], [ "((( ) (((()(())()) (()) ((() ((())((((((() ((() ((() ())))))))))))()) ((())(()))()( )) (())(()))()((((()))((())))((()()))((())))() (( ))))) (((( )))) (( ))", "['((()(((()(())())(())((()((())((((((()((()((()())))))))))))())((())(()))()())(())(()))()((((()))((())))((()()))((())))()(()))))', '(((())))', '(())']" ], [ "(())(())", "['(())', '(())']" ], [ " (()) (()) ((() ((())))()) ((())(()))()", "['(())', '(())', '((()((())))())', '((())(()))', '()']" ], [ "((())(()))()", "['((())(()))', '()']" ], [ "()((()()()()()()((()))()()()((()))()()()((()))()()()((()))()()()((()))()()()((()))()()()((()))()()()))", "['()', '((()()()()()()((()))()()()((()))()()()((()))()()()((()))()()()((()))()()()((()))()()()((()))()()()))']" ], [ "(()(())())", "['(()(())())']" ], [ "", "[]" ], [ "((( ) )(((())) (()(())(( ))))) (((( )))) (( ))", "['((())(((()))(()(())(()))))', '(((())))', '(())']" ], [ "((()) ()) ()(( )) (()(())())", "['((())())', '()', '(())', '(()(())())']" ], [ "(()()()())", "['(()()()())']" ], [ "()(()())()(())", "['()', '(()())', '()', '(())']" ], [ "()()()()()()((()))()()()((()))()()(())", "['()', '()', '()', '()', '()', '()', '((()))', '()', '()', '()', '((()))', '()', '()', '(())']" ], [ "(()(()))()(()())", "['(()(()))', '()', '(()())']" ], [ "((()())())()", "['((()())())', '()']" ], [ "((( ) (((()) (()) ((() ((()))))()) (()()()()()())((())(()))()( )) () (( ())))) (((( )))) (( ))", "['((()(((())(())((()((()))))())(()()()()()())((())(()))()())()((()))))', '(((())))', '(())']" ], [ "((( )) ()) ()(()) (()(())())", "['((())())', '()', '(())', '(()(())())']" ], [ "((((((()) ((() ((() ())))))))))", "['((((((())((()((()())))))))))']" ], [ "(((()) ()) ())", "['(((())())())']" ], [ "(())((()(((())))((()()))(((((()) (())() (())(())((())((( ) (((()) (()) ((() ((())))()) (()()()()()())((())(()))()( )) () (( ())))) (((( )))) (( )))))()))((())))))", "['(())', '((()(((())))((()()))(((((())(())()(())(())((())((()(((())(())((()((())))())(()()()()()())((())(()))()())()((()))))(((())))(()))))()))((())))))']" ], [ "( ) (( )) (( )( )) ()()()", "['()', '(())', '(()())', '()', '()', '()']" ], [ "(())(()())()((((((()))))))", "['(())', '(()())', '()', '((((((()))))))']" ], [ "( )", "['()']" ], [ "((()))", "['((()))']" ], [ "((( ) ((( )) () (( ))))) (((( )))) (( ))", "['((()((())()(()))))', '(((())))', '(())']" ], [ "((( ) ((( )((( ) ((( )) () (( ))))) (((( )))) (( ))) () (( ))))) (((( )))) (( ))", "['((()((()((()((())()(()))))(((())))(()))()(()))))', '(((())))', '(())']" ], [ "() ( ) (( )) ((( )))()(()()()) ((()())())()(()()()()()())", "['()', '()', '(())', '((()))', '()', '(()()())', '((()())())', '()', '(()()()()()())']" ], [ "(((())))(((())))(((())))(((())))(((())))(((())))(((())))(((())()(())))(((())))(((())))()()()()()", "['(((())))', '(((())))', '(((())))', '(((())))', '(((())))', '(((())))', '(((())))', '(((())()(())))', '(((())))', '(((())))', '()', '()', '()', '()', '()']" ], [ "((()())())()(()()()()()())", "['((()())())', '()', '(()()()()()())']" ], [ "((()))(()()())", "['((()))', '(()()())']" ], [ "((( ))) (( ))", "['((()))', '(())']" ], [ "(((())))", "['(((())))']" ], [ "((() ((()()))))()(()()())()(()())", "['((()((()()))))', '()', '(()()())', '()', '(()())']" ], [ "(((((((() (((()()))))))))))", "['(((((((()(((()()))))))))))']" ], [ "((()))()(())", "['((()))', '()', '(())']" ], [ "()()()()()()((()))()()()((()))()()()((()))()()()((()))()()()", "['()', '()', '()', '()', '()', '()', '((()))', '()', '()', '()', '((()))', '()', '()', '()', '((()))', '()', '()', '()', '((()))', '()', '()', '()']" ], [ "(()())()", "['(()())', '()']" ], [ "((())(()(()(()))()(()())()()((()))()()()((()))()))()", "['((())(()(()(()))()(()())()()((()))()()()((()))()))', '()']" ], [ "((( ) ((( )) () (( ))))) (((( )) )) (( ))", "['((()((())()(()))))', '(((())))', '(())']" ], [ "((()())())()(()(((()())()(()()))()(()())()()((())))()()()((())())()()()())", "['((()())())', '()', '(()(((()())()(()()))()(()())()()((())))()()()((())())()()()())']" ], [ "(((()())))", "['(((()())))']" ], [ "(())()()()((()))()()()", "['(())', '()', '()', '()', '((()))', '()', '()', '()']" ] ]	HumanEval/1	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('( ) (( )) (( )( ))') ['()', '(())', '(()())'] """
null	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 """ return number % 1.0	import numpy as np def is_floats(x) -> bool: # check if it is float; List[float]; Tuple[float] if isinstance(x, float): return True if isinstance(x, (list, tuple)): return all(isinstance(i, float) for i in x) if isinstance(x, np.ndarray): return x.dtype == np.float64 or x.dtype == np.float32 return False def assertion(out, exp, atol): exact_match = out == exp if atol == 0 and is_floats(exp): atol = 1e-6 if not exact_match and atol != 0: assert np.allclose(out, exp, rtol=1e-07, atol=atol) else: assert exact_match	[ [ "3.5", "0.5" ] ]	truncate_number	[]	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.	code_generation	HumanEval_plus	python	[ [ "3.5", "0.5" ], [ "1.33", "0.33000000000000007" ], [ "123.456", "0.45600000000000307" ], [ "999.99999", "0.9999900000000252" ], [ "0.3333333", "0.3333333" ], [ "1.0", "0.0" ], [ "1.5", "0.5" ], [ "0.5", "0.5" ], [ "0.999999", "0.999999" ], [ "500.00678", "0.006779999999992015" ], [ "11.11", "0.10999999999999943" ], [ "0.25", "0.25" ], [ "5.99", "0.9900000000000002" ], [ "1.284163165748358", "0.2841631657483581" ], [ "1.8517611088029418", "0.8517611088029418" ], [ "0.7713842427275083", "0.7713842427275083" ], [ "3.1842364304976463", "0.18423643049764626" ], [ "1.0738831860229472", "0.07388318602294719" ], [ "0.04320870526393539", "0.04320870526393539" ], [ "1.1369261836552624", "0.13692618365526243" ], [ "1.0630407193724771", "0.06304071937247713" ], [ "10.291122396192739", "0.2911223961927387" ], [ "1.7558893686701653", "0.7558893686701653" ], [ "0.9650030856354603", "0.9650030856354603" ], [ 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"4.6600822358584795", "0.6600822358584795" ], [ "1.8813790109677413", "0.8813790109677413" ], [ "4.869263033194584", "0.8692630331945841" ], [ "774025829.4255886", "0.42558860778808594" ], [ "182374053.9140266", "0.9140265882015228" ], [ "7.122831784956886e-14", "7.122831784956886e-14" ], [ "2.998720971722422", "0.9987209717224221" ], [ "1723108272.3818932", "0.3818931579589844" ], [ "2172041431.581541", "0.5815410614013672" ], [ "123456788.98954034", "0.9895403385162354" ], [ "5.995693783949557", "0.995693783949557" ], [ "6.990901192878196", "0.9909011928781961" ], [ "85459139.52462885", "0.5246288478374481" ], [ "9.93444512586173", "0.9344451258617301" ], [ "1915434693.6848624", "0.6848623752593994" ] ]	HumanEval/2	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 """
null	"from typing import List\n\n\ndef below_zero(operations: List[int]) -> bool:\n \"\"\" You're give(...TRUNCATED)	"\nimport numpy as np\n\ndef is_floats(x) -> bool:\n # check if it is float; List[float]; Tuple[f(...TRUNCATED)	[ [ "[1, 2, 3]", "False" ], [ "[1, 2, -4, 5]", "True" ] ]	below_zero	[ "from typing import List" ]	" You're given a list of deposit and withdrawal operations on a bank account that starts with zero b(...TRUNCATED)	code_generation	HumanEval_plus	python	[["[]","False"],["[1, 2, -3, 1, 2, -3]","False"],["[1, 2, -4, 5, 6]","True"],["[1, -1, 2, -2, 5, -5,(...TRUNCATED)	HumanEval/3	"from typing import List\n\n\ndef below_zero(operations: List[int]) -> bool:\n \"\"\" You're give(...TRUNCATED)
null	"from typing import List\n\n\ndef mean_absolute_deviation(numbers: List[float]) -> float:\n \"\"\(...TRUNCATED)	"\nimport numpy as np\n\ndef is_floats(x) -> bool:\n # check if it is float; List[float]; Tuple[f(...TRUNCATED)	[ [ "[1.0, 2.0, 3.0, 4.0]", "1.0" ] ]	mean_absolute_deviation	[ "from typing import List" ]	" For a given list of input numbers, calculate Mean Absolute Deviation around the mean of this datas(...TRUNCATED)	code_generation	HumanEval_plus	python	[["[1.0, 2.0, 3.0]","0.6666666666666666"],["[1.0, 2.0, 3.0, 4.0]","1.0"],["[1.0, 2.0, 3.0, 4.0, 5.0](...TRUNCATED)	HumanEval/4	"from typing import List\n\n\ndef mean_absolute_deviation(numbers: List[float]) -> float:\n \"\"\(...TRUNCATED)
null	"from typing import List\n\n\ndef intersperse(numbers: List[int], delimeter: int) -> List[int]:\n (...TRUNCATED)	"\nimport numpy as np\n\ndef is_floats(x) -> bool:\n # check if it is float; List[float]; Tuple[f(...TRUNCATED)	[ [ "[], 4", "[]" ], [ "[1, 2, 3], 4", "[1, 4, 2, 4, 3]" ] ]	intersperse	[ "from typing import List" ]	Insert a number 'delimeter' between every two consecutive elements of input list `numbers'	code_generation	HumanEval_plus	python	[["[], 7","[]"],["[5, 6, 3, 2], 8","[5, 8, 6, 8, 3, 8, 2]"],["[2, 2, 2], 2","[2, 2, 2, 2, 2]"],["[1,(...TRUNCATED)	HumanEval/5	"from typing import List\n\n\ndef intersperse(numbers: List[int], delimeter: int) -> List[int]:\n (...TRUNCATED)
null	"from typing import List\n\n\ndef parse_nested_parens(paren_string: str) -> List[int]:\n \"\"\" I(...TRUNCATED)	"\nimport numpy as np\n\ndef is_floats(x) -> bool:\n # check if it is float; List[float]; Tuple[f(...TRUNCATED)	[ [ "'(()()) ((())) () ((())()())'", "[2, 3, 1, 3]" ] ]	parse_nested_parens	[ "from typing import List" ]	" Input to this function is a string represented multiple groups for nested parentheses separated by(...TRUNCATED)	code_generation	HumanEval_plus	python	[["(()()) ((())) () ((())()())","[2, 3, 1, 3]"],["() (()) ((())) (((())))","[1, 2, 3, 4]"],["(()(())(...TRUNCATED)	HumanEval/6	"from typing import List\n\n\ndef parse_nested_parens(paren_string: str) -> List[int]:\n \"\"\" I(...TRUNCATED)
null	"from typing import List\n\n\ndef filter_by_substring(strings: List[str], substring: str) -> List[st(...TRUNCATED)	"\nimport numpy as np\n\ndef is_floats(x) -> bool:\n # check if it is float; List[float]; Tuple[f(...TRUNCATED)	[ [ "[], 'a'", "[]" ], [ "['abc', 'bacd', 'cde', 'array'], 'a'", "['abc', 'bacd', 'array']" ] ]	filter_by_substring	[ "from typing import List" ]	Filter an input list of strings only for ones that contain given substring	code_generation	HumanEval_plus	python	[["[], john","[]"],["['xxx', 'asd', 'xxy', 'john doe', 'xxxAAA', 'xxx'], xxx","['xxx', 'xxxAAA', 'xx(...TRUNCATED)	HumanEval/7	"from typing import List\n\n\ndef filter_by_substring(strings: List[str], substring: str) -> List[st(...TRUNCATED)
null	"from typing import List, Tuple\n\n\ndef sum_product(numbers: List[int]) -> Tuple[int, int]:\n \"(...TRUNCATED)	"\nimport numpy as np\n\ndef is_floats(x) -> bool:\n # check if it is float; List[float]; Tuple[f(...TRUNCATED)	[ [ "[]", "(0, 1)" ], [ "[1, 2, 3, 4]", "(10, 24)" ] ]	sum_product	[ "from typing import List, Tuple" ]	" For a given list of integers, return a tuple consisting of a sum and a product of all the integers(...TRUNCATED)	code_generation	HumanEval_plus	python	[["[]","(0, 1)"],["[1, 1, 1]","(3, 1)"],["[100, 0]","(100, 0)"],["[3, 5, 7]","(15, 105)"],["[10]","((...TRUNCATED)	HumanEval/8	"from typing import List, Tuple\n\n\ndef sum_product(numbers: List[int]) -> Tuple[int, int]:\n \"(...TRUNCATED)
null	"from typing import List, Tuple\n\n\ndef rolling_max(numbers: List[int]) -> List[int]:\n \"\"\" F(...TRUNCATED)	"\nimport numpy as np\n\ndef is_floats(x) -> bool:\n # check if it is float; List[float]; Tuple[f(...TRUNCATED)	[ [ "[1, 2, 3, 2, 3, 4, 2]", "[1, 2, 3, 3, 3, 4, 4]" ] ]	rolling_max	[ "from typing import List, Tuple" ]	" From a given list of integers, generate a list of rolling maximum element found until given moment(...TRUNCATED)	code_generation	HumanEval_plus	python	[["[]","[]"],["[1, 2, 3, 4]","[1, 2, 3, 4]"],["[4, 3, 2, 1]","[4, 4, 4, 4]"],["[3, 2, 3, 100, 3]","[(...TRUNCATED)	HumanEval/9	"from typing import List, Tuple\n\n\ndef rolling_max(numbers: List[int]) -> List[int]:\n \"\"\" F(...TRUNCATED)

null

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 """ for idx, elem in enumerate(numbers): for idx2, elem2 in enumerate(numbers): if idx != idx2: distance = abs(elem - elem2) if distance < threshold: return True return False

import numpy as np def is_floats(x) -> bool: # check if it is float; List[float]; Tuple[float] if isinstance(x, float): return True if isinstance(x, (list, tuple)): return all(isinstance(i, float) for i in x) if isinstance(x, np.ndarray): return x.dtype == np.float64 or x.dtype == np.float32 return False def assertion(out, exp, atol): exact_match = out == exp if atol == 0 and is_floats(exp): atol = 1e-6 if not exact_match and atol != 0: assert np.allclose(out, exp, rtol=1e-07, atol=atol) else: assert exact_match

[ [ "[1.0, 2.0, 3.0], 0.5", "False" ], [ "[1.0, 2.8, 3.0, 4.0, 5.0, 2.0], 0.3", "True" ] ]

has_close_elements

[ "from typing import List" ]

Check if in given list of numbers, are any two numbers closer to each other than given threshold.

code_generation

HumanEval_plus

python

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HumanEval/0

from typing import List def has_close_elements(numbers: List[float], threshold: float) -> bool: """ Check if in given list of numbers, are any two numbers closer to each other than given threshold. >>> has_close_elements([1.0, 2.0, 3.0], 0.5) False >>> has_close_elements([1.0, 2.8, 3.0, 4.0, 5.0, 2.0], 0.3) True """

null

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('( ) (( )) (( )( ))') ['()', '(())', '(()())'] """ result = [] current_string = [] current_depth = 0 for c in paren_string: if c == '(': current_depth += 1 current_string.append(c) elif c == ')': current_depth -= 1 current_string.append(c) if current_depth == 0: result.append(''.join(current_string)) current_string.clear() return result

import numpy as np def is_floats(x) -> bool: # check if it is float; List[float]; Tuple[float] if isinstance(x, float): return True if isinstance(x, (list, tuple)): return all(isinstance(i, float) for i in x) if isinstance(x, np.ndarray): return x.dtype == np.float64 or x.dtype == np.float32 return False def assertion(out, exp, atol): exact_match = out == exp if atol == 0 and is_floats(exp): atol = 1e-6 if not exact_match and atol != 0: assert np.allclose(out, exp, rtol=1e-07, atol=atol) else: assert exact_match

[ [ "'( ) (( )) (( )( ))'", "['()', '(())', '(()())']" ] ]

separate_paren_groups

[ "from typing import List" ]

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.

code_generation

HumanEval_plus

python

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HumanEval/1

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('( ) (( )) (( )( ))') ['()', '(())', '(()())'] """

null

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 """ return number % 1.0

import numpy as np def is_floats(x) -> bool: # check if it is float; List[float]; Tuple[float] if isinstance(x, float): return True if isinstance(x, (list, tuple)): return all(isinstance(i, float) for i in x) if isinstance(x, np.ndarray): return x.dtype == np.float64 or x.dtype == np.float32 return False def assertion(out, exp, atol): exact_match = out == exp if atol == 0 and is_floats(exp): atol = 1e-6 if not exact_match and atol != 0: assert np.allclose(out, exp, rtol=1e-07, atol=atol) else: assert exact_match

[ [ "3.5", "0.5" ] ]

truncate_number

[]

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.

code_generation

HumanEval_plus

python

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"0.8692630331945841" ], [ "774025829.4255886", "0.42558860778808594" ], [ "182374053.9140266", "0.9140265882015228" ], [ "7.122831784956886e-14", "7.122831784956886e-14" ], [ "2.998720971722422", "0.9987209717224221" ], [ "1723108272.3818932", "0.3818931579589844" ], [ "2172041431.581541", "0.5815410614013672" ], [ "123456788.98954034", "0.9895403385162354" ], [ "5.995693783949557", "0.995693783949557" ], [ "6.990901192878196", "0.9909011928781961" ], [ "85459139.52462885", "0.5246288478374481" ], [ "9.93444512586173", "0.9344451258617301" ], [ "1915434693.6848624", "0.6848623752593994" ] ]

HumanEval/2

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 """

null

"from typing import List\n\n\ndef below_zero(operations: List[int]) -> bool:\n \"\"\" You're give(...TRUNCATED)

"\nimport numpy as np\n\ndef is_floats(x) -> bool:\n # check if it is float; List[float]; Tuple[f(...TRUNCATED)

[ [ "[1, 2, 3]", "False" ], [ "[1, 2, -4, 5]", "True" ] ]

below_zero

[ "from typing import List" ]

" You're given a list of deposit and withdrawal operations on a bank account that starts with zero b(...TRUNCATED)

code_generation

HumanEval_plus

python

[["[]","False"],["[1, 2, -3, 1, 2, -3]","False"],["[1, 2, -4, 5, 6]","True"],["[1, -1, 2, -2, 5, -5,(...TRUNCATED)

HumanEval/3

"from typing import List\n\n\ndef below_zero(operations: List[int]) -> bool:\n \"\"\" You're give(...TRUNCATED)

null

"from typing import List\n\n\ndef mean_absolute_deviation(numbers: List[float]) -> float:\n \"\"\(...TRUNCATED)

"\nimport numpy as np\n\ndef is_floats(x) -> bool:\n # check if it is float; List[float]; Tuple[f(...TRUNCATED)

[ [ "[1.0, 2.0, 3.0, 4.0]", "1.0" ] ]

mean_absolute_deviation

[ "from typing import List" ]

" For a given list of input numbers, calculate Mean Absolute Deviation around the mean of this datas(...TRUNCATED)

code_generation

HumanEval_plus

python

[["[1.0, 2.0, 3.0]","0.6666666666666666"],["[1.0, 2.0, 3.0, 4.0]","1.0"],["[1.0, 2.0, 3.0, 4.0, 5.0](...TRUNCATED)

HumanEval/4

"from typing import List\n\n\ndef mean_absolute_deviation(numbers: List[float]) -> float:\n \"\"\(...TRUNCATED)

null

"from typing import List\n\n\ndef intersperse(numbers: List[int], delimeter: int) -> List[int]:\n (...TRUNCATED)

"\nimport numpy as np\n\ndef is_floats(x) -> bool:\n # check if it is float; List[float]; Tuple[f(...TRUNCATED)

[ [ "[], 4", "[]" ], [ "[1, 2, 3], 4", "[1, 4, 2, 4, 3]" ] ]

intersperse

[ "from typing import List" ]

Insert a number 'delimeter' between every two consecutive elements of input list `numbers'

code_generation

HumanEval_plus

python

[["[], 7","[]"],["[5, 6, 3, 2], 8","[5, 8, 6, 8, 3, 8, 2]"],["[2, 2, 2], 2","[2, 2, 2, 2, 2]"],["[1,(...TRUNCATED)

HumanEval/5

"from typing import List\n\n\ndef intersperse(numbers: List[int], delimeter: int) -> List[int]:\n (...TRUNCATED)

null

"from typing import List\n\n\ndef parse_nested_parens(paren_string: str) -> List[int]:\n \"\"\" I(...TRUNCATED)

"\nimport numpy as np\n\ndef is_floats(x) -> bool:\n # check if it is float; List[float]; Tuple[f(...TRUNCATED)

[ [ "'(()()) ((())) () ((())()())'", "[2, 3, 1, 3]" ] ]

parse_nested_parens

[ "from typing import List" ]

" Input to this function is a string represented multiple groups for nested parentheses separated by(...TRUNCATED)

code_generation

HumanEval_plus

python

[["(()()) ((())) () ((())()())","[2, 3, 1, 3]"],["() (()) ((())) (((())))","[1, 2, 3, 4]"],["(()(())(...TRUNCATED)

HumanEval/6

"from typing import List\n\n\ndef parse_nested_parens(paren_string: str) -> List[int]:\n \"\"\" I(...TRUNCATED)

null

"from typing import List\n\n\ndef filter_by_substring(strings: List[str], substring: str) -> List[st(...TRUNCATED)

"\nimport numpy as np\n\ndef is_floats(x) -> bool:\n # check if it is float; List[float]; Tuple[f(...TRUNCATED)

[ [ "[], 'a'", "[]" ], [ "['abc', 'bacd', 'cde', 'array'], 'a'", "['abc', 'bacd', 'array']" ] ]

filter_by_substring

[ "from typing import List" ]

Filter an input list of strings only for ones that contain given substring

code_generation

HumanEval_plus

python

[["[], john","[]"],["['xxx', 'asd', 'xxy', 'john doe', 'xxxAAA', 'xxx'], xxx","['xxx', 'xxxAAA', 'xx(...TRUNCATED)

HumanEval/7

"from typing import List\n\n\ndef filter_by_substring(strings: List[str], substring: str) -> List[st(...TRUNCATED)

null

"from typing import List, Tuple\n\n\ndef sum_product(numbers: List[int]) -> Tuple[int, int]:\n \"(...TRUNCATED)

"\nimport numpy as np\n\ndef is_floats(x) -> bool:\n # check if it is float; List[float]; Tuple[f(...TRUNCATED)

[ [ "[]", "(0, 1)" ], [ "[1, 2, 3, 4]", "(10, 24)" ] ]

sum_product

[ "from typing import List, Tuple" ]

" For a given list of integers, return a tuple consisting of a sum and a product of all the integers(...TRUNCATED)

code_generation

HumanEval_plus

python

[["[]","(0, 1)"],["[1, 1, 1]","(3, 1)"],["[100, 0]","(100, 0)"],["[3, 5, 7]","(15, 105)"],["[10]","((...TRUNCATED)

HumanEval/8

"from typing import List, Tuple\n\n\ndef sum_product(numbers: List[int]) -> Tuple[int, int]:\n \"(...TRUNCATED)

null

"from typing import List, Tuple\n\n\ndef rolling_max(numbers: List[int]) -> List[int]:\n \"\"\" F(...TRUNCATED)

"\nimport numpy as np\n\ndef is_floats(x) -> bool:\n # check if it is float; List[float]; Tuple[f(...TRUNCATED)

[ [ "[1, 2, 3, 2, 3, 4, 2]", "[1, 2, 3, 3, 3, 4, 4]" ] ]

rolling_max

[ "from typing import List, Tuple" ]

" From a given list of integers, generate a list of rolling maximum element found until given moment(...TRUNCATED)

code_generation

HumanEval_plus

python

[["[]","[]"],["[1, 2, 3, 4]","[1, 2, 3, 4]"],["[4, 3, 2, 1]","[4, 4, 4, 4]"],["[3, 2, 3, 100, 3]","[(...TRUNCATED)

HumanEval/9

"from typing import List, Tuple\n\n\ndef rolling_max(numbers: List[int]) -> List[int]:\n \"\"\" F(...TRUNCATED)