



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  __lowerCamelCase (       lowerCamelCase__					,			lowerCamelCase__						):

				"""simple docstring"""


				lowercase__					:   str													=					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}}"						)
				lowercase__					:   str													=					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  __lowerCamelCase (       lowerCamelCase__					,			lowerCamelCase__						):

				"""simple docstring"""


				lowercase__					:   Union[str, Any]													=					str(lowerCamelCase__						)
				dataset_info.write_to_directory(lowerCamelCase__						)
				lowercase__					:   Tuple													=					DatasetInfo.from_directory(lowerCamelCase__						)
				assert dataset_info == reloaded
				assert os.path.exists(os.path.join(lowerCamelCase__					,			"dataset_info.json"						)						)


def  __lowerCamelCase (       ):

				"""simple docstring"""


				lowercase__					:   Optional[Any]													=					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=1_337					,			post_processing_size=442					,			dataset_size=1_234					,			size_in_bytes=1_337 + 442 + 1_234					,			)
				lowercase__					:   str													=					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)						)
				lowercase__					:   List[str]													=					yaml.safe_dump(lowerCamelCase__						)
				lowercase__					:   int													=					yaml.safe_load(lowerCamelCase__						)
				assert dataset_info_yaml_dict == reloaded


def  __lowerCamelCase (       ):

				"""simple docstring"""


				lowercase__					:   Dict													=					DatasetInfo()
				lowercase__					:   List[str]													=					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=1_337						),
            }						),
    ]					,			)
def  __lowerCamelCase (       lowerCamelCase__					,			lowerCamelCase__						):

				"""simple docstring"""


				lowercase__					:   Dict													=					str(lowerCamelCase__						)
				dataset_infos_dict.write_to_directory(lowerCamelCase__						)
				lowercase__					:   Union[str, Any]													=					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():
								lowercase__					:   str													=					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
								lowercase__					:   str													=					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 collections import Counter
from timeit import timeit


def  __lowerCamelCase (       lowerCamelCase__ = ""					,			):

				"""simple docstring"""


				return sum(c % 2 for c in Counter(input_str.replace(" "					,			""						).lower()						).values()						) < 2


def  __lowerCamelCase (       lowerCamelCase__ = ""						):

				"""simple docstring"""


				if len(lowerCamelCase__						) == 0:
								return True
				lowercase__					:   str													=					input_str.replace(" "					,			""						).lower()
				# character_freq_dict: Stores the frequency of every character in the input string
				lowercase__					:   dict[str, int]													=					{}

				for character in lower_case_input_str:
								lowercase__					:   List[Any]													=					character_freq_dict.get(lowerCamelCase__					,			0						) + 1
				lowercase__					:   List[Any]													=					0

				for character_count in character_freq_dict.values():
								if character_count % 2:
												odd_char += 1
				if odd_char > 1:
								return False
				return True


def  __lowerCamelCase (       lowerCamelCase__ = ""						):

				"""simple docstring"""


				print("\nFor string = "					,			lowerCamelCase__					,			":"						)
				print(
				    "> can_string_be_rearranged_as_palindrome_counter()"					,			"\tans ="					,			can_string_be_rearranged_as_palindrome_counter(lowerCamelCase__						)					,			"\ttime ="					,			timeit(
				        "z.can_string_be_rearranged_as_palindrome_counter(z.check_str)"					,			setup="import __main__ as z"					,			)					,			"seconds"					,			)
				print(
				    "> can_string_be_rearranged_as_palindrome()"					,			"\tans ="					,			can_string_be_rearranged_as_palindrome(lowerCamelCase__						)					,			"\ttime ="					,			timeit(
				        "z.can_string_be_rearranged_as_palindrome(z.check_str)"					,			setup="import __main__ as z"					,			)					,			"seconds"					,			)


if __name__ == "__main__":
				lowerCAmelCase__					  =  input(
				    '''Enter string to determine if it can be rearranged as a palindrome or not: '''
				).strip()
				benchmark(check_str)
				lowerCAmelCase__					  =  can_string_be_rearranged_as_palindrome_counter(check_str)
				print(f'''{check_str} can {"" if status else "not "}be rearranged as a palindrome''')




