






from __future__ import annotations

import typing
from collections import Counter





def 	lowerCAmelCase_		(lowercase__						:       int       )		->    typing.Counter[int]:


				'''simple docstring'''




				lowerCAmelCase__      			=						Counter()
				for base in range(1     ,					max_perimeter + 1       ):
								for perpendicular in range(lowercase__     ,					max_perimeter + 1       ):
												lowerCAmelCase__      			=						(base * base + perpendicular * perpendicular) ** 0.5
												if hypotenuse == int(lowercase__       ):
																lowerCAmelCase__      			=						int(base + perpendicular + hypotenuse       )
																if perimeter > max_perimeter:
																				continue
																triplets[perimeter] += 1
				return triplets





def 	lowerCAmelCase_		(lowercase__						:       int = 10_00       )		->    int:


				'''simple docstring'''




				lowerCAmelCase__      			=						pythagorean_triple(lowercase__       )
				return triplets.most_common(1       )[0][0]


if __name__ == "__main__":
							print(F'''Perimeter {solution()} has maximum solutions''')













from typing import Optional

import pyspark

from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class  lowerCAmelCase_       (				snake_case__					):




							def __init__(   self     :   str ,							SCREAMING_SNAKE_CASE_     :   pyspark.sql.DataFrame ,							SCREAMING_SNAKE_CASE_     :   Optional[NamedSplit] = None ,							SCREAMING_SNAKE_CASE_     :   Optional[Features] = None ,							SCREAMING_SNAKE_CASE_     :   bool = True ,							SCREAMING_SNAKE_CASE_     :   str = None ,							SCREAMING_SNAKE_CASE_     :   bool = False ,							SCREAMING_SNAKE_CASE_     :   str = None ,							SCREAMING_SNAKE_CASE_     :   bool = True ,							SCREAMING_SNAKE_CASE_     :   str = "arrow" ,							**SCREAMING_SNAKE_CASE_     :   Optional[Any] ,							):
											super().__init__(
											    split=SCREAMING_SNAKE_CASE_ ,							features=SCREAMING_SNAKE_CASE_ ,							cache_dir=SCREAMING_SNAKE_CASE_ ,							keep_in_memory=SCREAMING_SNAKE_CASE_ ,							streaming=SCREAMING_SNAKE_CASE_ ,							**SCREAMING_SNAKE_CASE_ ,							)
											lowerCAmelCase__      			=						load_from_cache_file
											lowerCAmelCase__      			=						file_format
											lowerCAmelCase__      			=						Spark(
											    df=SCREAMING_SNAKE_CASE_ ,							features=SCREAMING_SNAKE_CASE_ ,							cache_dir=SCREAMING_SNAKE_CASE_ ,							working_dir=SCREAMING_SNAKE_CASE_ ,							**SCREAMING_SNAKE_CASE_ ,							)




							def 						__snake_case					(   self     :   List[str]	):
											if self.streaming:
															return self.builder.as_streaming_dataset(split=self.split	)
											lowerCAmelCase__      			=						None if self._load_from_cache_file else DownloadMode.FORCE_REDOWNLOAD
											self.builder.download_and_prepare(
											    download_mode=SCREAMING_SNAKE_CASE_ ,							file_format=self._file_format ,							)
											return self.builder.as_dataset(split=self.split	)





