



from unittest import TestCase

from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset






class    SCREAMING_SNAKE_CASE			(							lowerCamelCase__					):





							def 						UpperCamelCase_					(   self		:		Optional[int]	):

											'''simple docstring'''
											return [
											    {"col_1": 3, "col_2": "a"},
											    {"col_1": 2, "col_2": "b"},
											    {"col_1": 1, "col_2": "c"},
											    {"col_1": 0, "col_2": "d"},
											]





							def 						UpperCamelCase_					(   self		:		Any	):

											'''simple docstring'''
											__a       =		{"""col_1""": [3, 2, 1, 0], """col_2""": ["""a""", """b""", """c""", """d"""]}
											return Dataset.from_dict(__lowercase	)





							def 						UpperCamelCase_					(   self		:		List[str]	):

											'''simple docstring'''
											__a       =		self._create_example_records()
											__a       =		Dataset.from_list(__lowercase	)
											self.assertListEqual(dset.column_names      ,				["""col_1""", """col_2"""]	)
											for i, r in enumerate(__lowercase	):
															self.assertDictEqual(__lowercase      ,				example_records[i]	)





							def 						UpperCamelCase_					(   self		:		Tuple	):

											'''simple docstring'''
											__a       =		self._create_example_records()
											__a       =		Dataset.from_list(__lowercase	)
											__a       =		Dataset.from_dict({k: [r[k] for r in example_records] for k in example_records[0]}	)
											self.assertEqual(dset.info      ,				dset_from_dict.info	)





							def 						UpperCamelCase_					(   self		:		List[str]	):  # checks what happens with missing columns

											'''simple docstring'''
											__a       =		[{"""col_1""": 1}, {"""col_2""": """x"""}]
											__a       =		Dataset.from_list(__lowercase	)
											self.assertDictEqual(dset[0]      ,				{"""col_1""": 1}	)
											self.assertDictEqual(dset[1]      ,				{"""col_1""": None}	)  # NB: first record is used for columns





							def 						UpperCamelCase_					(   self		:		Union[str, Any]	):  # checks if the type can be inferred from the second record

											'''simple docstring'''
											__a       =		[{"""col_1""": []}, {"""col_1""": [1, 2]}]
											__a       =		Dataset.from_list(__lowercase	)
											self.assertEqual(dset.info.features["""col_1"""]      ,				Sequence(Value("""int64"""	)	)	)







							def 						UpperCamelCase_					(   self		:		Optional[int]	):

											'''simple docstring'''
											__a       =		Dataset.from_list([]	)
											self.assertEqual(len(__lowercase	)      ,				0	)
											self.assertListEqual(dset.column_names      ,				[]	)





from math import sqrt

def   lowerCAmelCase__						(							_SCREAMING_SNAKE_CASE       :			int    ):
				"""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(sqrt(_SCREAMING_SNAKE_CASE    ) + 1    )				,     6    ):
								if number % i == 0 or number % (i + 2) == 0:
												return False
				return True

def   lowerCAmelCase__						(							_SCREAMING_SNAKE_CASE       :			int = 1_0001    ):
				"""simple docstring"""







				__a       =		0
				__a       =		1
				while count != nth and number < 3:
								number += 1
								if is_prime(_SCREAMING_SNAKE_CASE    ):
												count += 1
				while count != nth:
								number += 2
								if is_prime(_SCREAMING_SNAKE_CASE    ):
												count += 1
				return number


if __name__ == "__main__":
						print(F"""{solution() = }""")
