





"""simple docstring"""




import os

import pytest
import yaml

from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict




@pytest.mark.parametrize(
    "files"			,				[
        ["full:README.md", "dataset_infos.json"],
        ["empty:README.md", "dataset_infos.json"],
        ["dataset_infos.json"],
        ["full:README.md"],
    ]			,				)
def _a (  SCREAMING_SNAKE_CASE__      :  Union[str, Any]			,				SCREAMING_SNAKE_CASE__      :  List[str]       )	->    Any:

							'''simple docstring'''






							SCREAMING_SNAKE_CASE__       :      Optional[int]     =						tmp_path_factory.mktemp("dset_infos_dir"       )
							if "full:README.md" in files:
														with open(dataset_infos_dir / "README.md"			,				"w"       ) as f:
																					f.write("---\ndataset_info:\n  dataset_size: 42\n---"       )
							if "empty:README.md" in files:
														with open(dataset_infos_dir / "README.md"			,				"w"       ) as f:
																					f.write(""       )
    # we want to support dataset_infos.json for backward compatibility
							if "dataset_infos.json" in files:
														with open(dataset_infos_dir / "dataset_infos.json"			,				"w"       ) as f:
																					f.write("{\"default\": {\"dataset_size\": 42}}"       )
							SCREAMING_SNAKE_CASE__       :      Tuple     =						DatasetInfosDict.from_directory(lowerCamelCase__       )
							assert dataset_infos
							assert dataset_infos["default"].dataset_size == 42




@pytest.mark.parametrize(
    "dataset_info"			,				[
        DatasetInfo(),
        DatasetInfo(
            description="foo"			,				features=Features({"a": Value("int32"       )}       )			,				builder_name="builder"			,				config_name="config"			,				version="1.0.0"			,				splits=[{"name": "train"}]			,				download_size=42			,				),
    ]			,				)
def _a (  SCREAMING_SNAKE_CASE__      :  Any			,				SCREAMING_SNAKE_CASE__      :  DatasetInfo       )	->    Optional[int]:

							'''simple docstring'''






							SCREAMING_SNAKE_CASE__       :      List[str]     =						str(lowerCamelCase__       )
							dataset_info.write_to_directory(lowerCamelCase__       )
							SCREAMING_SNAKE_CASE__       :      Optional[Any]     =						DatasetInfo.from_directory(lowerCamelCase__       )
							assert dataset_info == reloaded
							assert os.path.exists(os.path.join(lowerCamelCase__			,				"dataset_info.json"       )       )




def _a (  )	->    Tuple:

							'''simple docstring'''






							SCREAMING_SNAKE_CASE__       :      str     =						DatasetInfo(
							    description="foo"			,				citation="bar"			,				homepage="https://foo.bar"			,				license="CC0"			,				features=Features({"a": Value("int32"       )}       )			,				post_processed={}			,				supervised_keys=()			,				task_templates=[]			,				builder_name="builder"			,				config_name="config"			,				version="1.0.0"			,				splits=[{"name": "train", "num_examples": 42}]			,				download_checksums={}			,				download_size=13_37			,				post_processing_size=4_42			,				dataset_size=12_34			,				size_in_bytes=13_37 + 4_42 + 12_34			,				)
							SCREAMING_SNAKE_CASE__       :      Union[str, Any]     =						dataset_info._to_yaml_dict()
							assert sorted(lowerCamelCase__       ) == sorted(DatasetInfo._INCLUDED_INFO_IN_YAML       )
							for key in DatasetInfo._INCLUDED_INFO_IN_YAML:
														assert key in dataset_info_yaml_dict
														assert isinstance(dataset_info_yaml_dict[key]			,				(list, dict, int, str)       )
							SCREAMING_SNAKE_CASE__       :      Any     =						yaml.safe_dump(lowerCamelCase__       )
							SCREAMING_SNAKE_CASE__       :      Dict     =						yaml.safe_load(lowerCamelCase__       )
							assert dataset_info_yaml_dict == reloaded




def _a (  )	->    List[str]:

							'''simple docstring'''






							SCREAMING_SNAKE_CASE__       :      Optional[int]     =						DatasetInfo()
							SCREAMING_SNAKE_CASE__       :      Any     =						dataset_info._to_yaml_dict()
							assert dataset_info_yaml_dict == {}







@pytest.mark.parametrize(
    "dataset_infos_dict"			,				[
        DatasetInfosDict(),
        DatasetInfosDict({"default": DatasetInfo()}       ),
        DatasetInfosDict({"my_config_name": DatasetInfo()}       ),
        DatasetInfosDict(
            {
                "default": DatasetInfo(
                    description="foo"			,				features=Features({"a": Value("int32"       )}       )			,				builder_name="builder"			,				config_name="config"			,				version="1.0.0"			,				splits=[{"name": "train"}]			,				download_size=42			,				)
            }       ),
        DatasetInfosDict(
            {
                "v1": DatasetInfo(dataset_size=42       ),
                "v2": DatasetInfo(dataset_size=13_37       ),
            }       ),
    ]			,				)
def _a (  SCREAMING_SNAKE_CASE__      :  Any			,				SCREAMING_SNAKE_CASE__      :  DatasetInfosDict       )	->    List[Any]:

							'''simple docstring'''






							SCREAMING_SNAKE_CASE__       :      List[Any]     =						str(lowerCamelCase__       )
							dataset_infos_dict.write_to_directory(lowerCamelCase__       )
							SCREAMING_SNAKE_CASE__       :      Tuple     =						DatasetInfosDict.from_directory(lowerCamelCase__       )

							# the config_name of the dataset_infos_dict take over the attribute
							for config_name, dataset_info in dataset_infos_dict.items():
														SCREAMING_SNAKE_CASE__       :      Dict     =						config_name
														# the yaml representation doesn't include fields like description or citation
														# so we just test that we can recover what we can from the yaml
														SCREAMING_SNAKE_CASE__       :      int     =						DatasetInfo._from_yaml_dict(dataset_info._to_yaml_dict()       )
							assert dataset_infos_dict == reloaded

							if dataset_infos_dict:
														assert os.path.exists(os.path.join(lowerCamelCase__			,				"README.md"       )       )













from __future__ import annotations




def _a (  SCREAMING_SNAKE_CASE__      :  list[float]			,				SCREAMING_SNAKE_CASE__      :  list[float]       )	->    float:

							'''simple docstring'''






							SCREAMING_SNAKE_CASE__       :      List[Any]     =						sorted(numsa + numsa       )
							SCREAMING_SNAKE_CASE__   ,SCREAMING_SNAKE_CASE__       :      Dict     =						divmod(len(SCREAMING_SNAKE_CASE__       )			,				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()
		_lowerCamelCase :    List[str]  							= [float(x) for x in input('''Enter the elements of first array: ''').split()]
		_lowerCamelCase :    Any  							= [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)}")






