


import csv
import os

import pytest

from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.csv import CsvDatasetReader, CsvDatasetWriter

from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases






def 				UpperCamelCase      (			__magic_name__  :							Any					,					__magic_name__  :							Optional[Any]  )     ->						Optional[Any]:
		"""simple docstring"""




		assert isinstance(__magic_name__					,					__magic_name__  )
		assert dataset.num_rows == 4
		assert dataset.num_columns == 3
		assert dataset.column_names == ["col_1", "col_2", "col_3"]
		for feature, expected_dtype in expected_features.items():
				assert dataset.features[feature].dtype == expected_dtype






@pytest.mark.parametrize("""keep_in_memory"""					,					[False, True]  )
def 				UpperCamelCase      (			__magic_name__  :							Optional[int]					,					__magic_name__  :							List[Any]					,					__magic_name__  :							str  )     ->						Optional[Any]:
		"""simple docstring"""




		lowercase__      =	tmp_path / """cache"""
		lowercase__      =	{"""col_1""": """int64""", """col_2""": """int64""", """col_3""": """float64"""}
		with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
				lowercase__      =	CsvDatasetReader(__magic_name__					,					cache_dir=__magic_name__					,					keep_in_memory=__magic_name__  ).read()
		_check_csv_dataset(__magic_name__					,					__magic_name__  )






@pytest.mark.parametrize(
    """features"""					,					[
        None,
        {"""col_1""": """string""", """col_2""": """int64""", """col_3""": """float64"""},
        {"""col_1""": """string""", """col_2""": """string""", """col_3""": """string"""},
        {"""col_1""": """int32""", """col_2""": """int32""", """col_3""": """int32"""},
        {"""col_1""": """float32""", """col_2""": """float32""", """col_3""": """float32"""},
    ]					,					)
def 				UpperCamelCase      (			__magic_name__  :							Optional[Any]					,					__magic_name__  :							List[str]					,					__magic_name__  :							Optional[Any]  )     ->						List[str]:
		"""simple docstring"""




		lowercase__      =	tmp_path / """cache"""
		# CSV file loses col_1 string dtype information: default now is "int64" instead of "string"
		lowercase__      =	{"""col_1""": """int64""", """col_2""": """int64""", """col_3""": """float64"""}
		lowercase__      =	features.copy() if features else default_expected_features
		lowercase__      =	(
		    Features({feature: Value(__magic_name__  ) for feature, dtype in features.items()}  ) if features is not None else None
		)
		lowercase__      =	CsvDatasetReader(__magic_name__					,					features=__magic_name__					,					cache_dir=__magic_name__  ).read()
		_check_csv_dataset(__magic_name__					,					__magic_name__  )






@pytest.mark.parametrize("""split"""					,					[None, NamedSplit("""train"""  ), """train""", """test"""]  )
def 				UpperCamelCase      (			__magic_name__  :							Tuple					,					__magic_name__  :							Dict					,					__magic_name__  :							str  )     ->						Optional[Any]:
		"""simple docstring"""




		lowercase__      =	tmp_path / """cache"""
		lowercase__      =	{"""col_1""": """int64""", """col_2""": """int64""", """col_3""": """float64"""}
		lowercase__      =	CsvDatasetReader(__magic_name__					,					cache_dir=__magic_name__					,					split=__magic_name__  ).read()
		_check_csv_dataset(__magic_name__					,					__magic_name__  )
		assert dataset.split == split if split else "train"






@pytest.mark.parametrize("""path_type"""					,					[str, list]  )
def 				UpperCamelCase      (			__magic_name__  :							Optional[int]					,					__magic_name__  :							Tuple					,					__magic_name__  :							Optional[int]  )     ->						Union[str, Any]:
		"""simple docstring"""




		if issubclass(__magic_name__					,					__magic_name__  ):
				lowercase__      =	csv_path
		elif issubclass(__magic_name__					,					__magic_name__  ):
				lowercase__      =	[csv_path]
		lowercase__      =	tmp_path / """cache"""
		lowercase__      =	{"""col_1""": """int64""", """col_2""": """int64""", """col_3""": """float64"""}
		lowercase__      =	CsvDatasetReader(__magic_name__					,					cache_dir=__magic_name__  ).read()
		_check_csv_dataset(__magic_name__					,					__magic_name__  )






def 				UpperCamelCase      (			__magic_name__  :							Tuple					,					__magic_name__  :							str					,					__magic_name__  :							List[str]=("train",)  )     ->						Union[str, Any]:
		"""simple docstring"""




		assert isinstance(__magic_name__					,					__magic_name__  )
		for split in splits:
				lowercase__      =	dataset_dict[split]
				assert dataset.num_rows == 4
				assert dataset.num_columns == 3
				assert dataset.column_names == ["col_1", "col_2", "col_3"]
				for feature, expected_dtype in expected_features.items():
						assert dataset.features[feature].dtype == expected_dtype






@pytest.mark.parametrize("""keep_in_memory"""					,					[False, True]  )
def 				UpperCamelCase      (			__magic_name__  :							Dict					,					__magic_name__  :							Optional[Any]					,					__magic_name__  :							List[Any]  )     ->						Tuple:
		"""simple docstring"""




		lowercase__      =	tmp_path / """cache"""
		lowercase__      =	{"""col_1""": """int64""", """col_2""": """int64""", """col_3""": """float64"""}
		with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
				lowercase__      =	CsvDatasetReader({"""train""": csv_path}					,					cache_dir=__magic_name__					,					keep_in_memory=__magic_name__  ).read()
		_check_csv_datasetdict(__magic_name__					,					__magic_name__  )






@pytest.mark.parametrize(
    """features"""					,					[
        None,
        {"""col_1""": """string""", """col_2""": """int64""", """col_3""": """float64"""},
        {"""col_1""": """string""", """col_2""": """string""", """col_3""": """string"""},
        {"""col_1""": """int32""", """col_2""": """int32""", """col_3""": """int32"""},
        {"""col_1""": """float32""", """col_2""": """float32""", """col_3""": """float32"""},
    ]					,					)
def 				UpperCamelCase      (			__magic_name__  :							List[str]					,					__magic_name__  :							Optional[Any]					,					__magic_name__  :							List[str]  )     ->						str:
		"""simple docstring"""




		lowercase__      =	tmp_path / """cache"""
		# CSV file loses col_1 string dtype information: default now is "int64" instead of "string"
		lowercase__      =	{"""col_1""": """int64""", """col_2""": """int64""", """col_3""": """float64"""}
		lowercase__      =	features.copy() if features else default_expected_features
		lowercase__      =	(
		    Features({feature: Value(__magic_name__  ) for feature, dtype in features.items()}  ) if features is not None else None
		)
		lowercase__      =	CsvDatasetReader({"""train""": csv_path}					,					features=__magic_name__					,					cache_dir=__magic_name__  ).read()
		_check_csv_datasetdict(__magic_name__					,					__magic_name__  )






@pytest.mark.parametrize("""split"""					,					[None, NamedSplit("""train"""  ), """train""", """test"""]  )
def 				UpperCamelCase      (			__magic_name__  :							List[Any]					,					__magic_name__  :							List[Any]					,					__magic_name__  :							Union[str, Any]  )     ->						Any:
		"""simple docstring"""




		if split:
				lowercase__      =	{split: csv_path}
		else:
				lowercase__      =	{"""train""": csv_path, """test""": csv_path}
		lowercase__      =	tmp_path / """cache"""
		lowercase__      =	{"""col_1""": """int64""", """col_2""": """int64""", """col_3""": """float64"""}
		lowercase__      =	CsvDatasetReader(__magic_name__					,					cache_dir=__magic_name__  ).read()
		_check_csv_datasetdict(__magic_name__					,					__magic_name__					,					splits=list(path.keys()  )  )
		assert all(dataset[split].split == split for split in path.keys()  )






def 				UpperCamelCase      (			__magic_name__  :							Tuple  )     ->						List[str]:
		"""simple docstring"""




		with open(__magic_name__					,					encoding="""utf-8"""  ) as csvfile:
				yield from csv.reader(__magic_name__  )






def 				UpperCamelCase      (			__magic_name__  :							Any					,					__magic_name__  :							int  )     ->						Any:
		"""simple docstring"""




		lowercase__      =	tmp_path / """cache"""
		lowercase__      =	os.path.join(__magic_name__					,					"""tmp.csv"""  )
		lowercase__      =	CsvDatasetReader({"""train""": csv_path}					,					cache_dir=__magic_name__  ).read()
		CsvDatasetWriter(dataset["""train"""]					,					__magic_name__					,					num_proc=1  ).write()

		lowercase__      =	iter_csv_file(__magic_name__  )
		lowercase__      =	iter_csv_file(__magic_name__  )

		for rowa, rowa in zip(__magic_name__					,					__magic_name__  ):
				assert rowa == rowa






def 				UpperCamelCase      (			__magic_name__  :							Union[str, Any]					,					__magic_name__  :							Dict  )     ->						List[str]:
		"""simple docstring"""




		lowercase__      =	tmp_path / """cache"""
		lowercase__      =	os.path.join(__magic_name__					,					"""tmp.csv"""  )
		lowercase__      =	CsvDatasetReader({"""train""": csv_path}					,					cache_dir=__magic_name__  ).read()
		CsvDatasetWriter(dataset["""train"""]					,					__magic_name__					,					num_proc=2  ).write()

		lowercase__      =	iter_csv_file(__magic_name__  )
		lowercase__      =	iter_csv_file(__magic_name__  )

		for rowa, rowa in zip(__magic_name__					,					__magic_name__  ):
				assert rowa == rowa







def 				UpperCamelCase      (			__magic_name__  :							Any					,					__magic_name__  :							Dict  )     ->						Union[str, Any]:
		"""simple docstring"""




		lowercase__      =	tmp_path / """cache"""
		lowercase__      =	os.path.join(__magic_name__					,					"""tmp.csv"""  )
		lowercase__      =	CsvDatasetReader({"""train""": csv_path}					,					cache_dir=__magic_name__  ).read()
		with pytest.raises(__magic_name__  ):
				CsvDatasetWriter(dataset["""train"""]					,					__magic_name__					,					num_proc=0  )





import math






def 				UpperCamelCase      (			__magic_name__  :							int  )     ->						bool:
		"""simple docstring"""




		if 1 < number < 4:
				# 2 and 3 are primes
				return True
		elif number < 2 or number % 2 == 0 or number % 3 == 0:
				# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
				return False

		# All primes number are in format of 6k +/- 1
		for i in range(5					,					int(math.sqrt(__magic_name__  ) + 1  )					,					6  ):
				if number % i == 0 or number % (i + 2) == 0:
						return False
		return True






def 				UpperCamelCase      (			__magic_name__  :							int = 1000					,					__magic_name__  :							int = 1000  )     ->						int:
		"""simple docstring"""




		lowercase__      =	[0, 0, 0]  # length, a, b
		for a in range((a_limit * -1) + 1					,					__magic_name__  ):
				for b in range(2					,					__magic_name__  ):
						if is_prime(__magic_name__  ):
								lowercase__      =	0
								lowercase__      =	0
								while is_prime((n**2) + (a * n) + b  ):
										count += 1
										n += 1
								if count > longest[0]:
										lowercase__      =	[count, a, b]
		lowercase__      =	longest[1] * longest[2]
		return ans


if __name__ == "__main__":
	print(solution(1_0_0_0, 1_0_0_0))

