


from __future__ import annotations






def 					UpperCamelCase   (      __magic_name__	:				list[float]       ,       __magic_name__	:				list[float]	)  ->    float:
		"""simple docstring"""




		lowercase__	     =						sorted(numsa + numsa	)
		lowercase__     ,      lowercase__	     =						divmod(len(__magic_name__	)       ,       2	)
		if mod == 1:
				return all_numbers[div]
		else:
				return (all_numbers[div] + all_numbers[div - 1]) / 2


if __name__ == "__main__":
	import doctest

	doctest.testmod()
	A			:						Optional[Any]        =  [float(x) for x in input('Enter the elements of first array: ').split()]
	A			:						List[str]        =  [float(x) for x in input('Enter the elements of second array: ').split()]
	print(F'The median of two arrays is: {median_of_two_arrays(array_a, array_a)}')









'''simple docstring'''



from unittest import TestCase

from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset
class UpperCAmelCase_       (     __A					):




      """simple docstring"""




      def 					A__   (			self      :		Optional[int]		)	->	List[str]:


       '''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 					A__   (			self      :		Any		)	->	List[str]:


       '''simple docstring'''

       lowercase       : List[str]						={'''col_1''': [3, 2, 1, 0], '''col_2''': ['''a''', '''b''', '''c''', '''d''']}
       return Dataset.from_dict(UpperCAmelCase		)






      def 					A__   (			self      :		Any		)	->	Tuple:


       '''simple docstring'''

       lowercase       : Tuple						=self._create_example_records()
       lowercase       : Tuple						=Dataset.from_list(UpperCAmelCase		)
       self.assertListEqual(dset.column_names  ,   ['''col_1''', '''col_2''']		)
       for i, r in enumerate(UpperCAmelCase		):
        self.assertDictEqual(UpperCAmelCase  ,   example_records[i]		)






      def 					A__   (			self      :		Dict		)	->	List[str]:


       '''simple docstring'''

       lowercase       : Optional[Any]						=self._create_example_records()
       lowercase       : Union[str, Any]						=Dataset.from_list(UpperCAmelCase		)
       lowercase       : Tuple						=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 					A__   (			self      :		str		)	->	List[Any]:  # checks what happens with missing columns


       '''simple docstring'''

       lowercase       : Tuple						=[{'''col_1''': 1}, {'''col_2''': '''x'''}]
       lowercase       : Optional[Any]						=Dataset.from_list(UpperCAmelCase		)
       self.assertDictEqual(dset[0]  ,   {'''col_1''': 1}		)
       self.assertDictEqual(dset[1]  ,   {'''col_1''': None}		)  # NB: first record is used for columns






      def 					A__   (			self      :		List[Any]		)	->	int:  # checks if the type can be inferred from the second record


       '''simple docstring'''

       lowercase       : List[Any]						=[{'''col_1''': []}, {'''col_1''': [1, 2]}]
       lowercase       : Union[str, Any]						=Dataset.from_list(UpperCAmelCase		)
       self.assertEqual(dset.info.features['''col_1''']  ,   Sequence(Value('''int64'''		)		)		)






      def 					A__   (			self      :		int		)	->	str:


       '''simple docstring'''

       lowercase       : List[str]						=Dataset.from_list([]		)
       self.assertEqual(len(UpperCAmelCase		)  ,   0		)
       self.assertListEqual(dset.column_names  ,   []		)



