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       _snake_case	(   lowerCAmelCase							:   str   , lowerCAmelCase							:   Any	):
		"""simple docstring"""







		SCREAMING_SNAKE_CASE_  :		Tuple				      =    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_  :		str				      =    DatasetInfosDict.from_directory(lowerCAmelCase	)
		assert dataset_infos
		assert dataset_infos["default"].dataset_size == 4_2




@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=4_2   , ),
    ]   , )
def       _snake_case	(   lowerCAmelCase							:   Optional[Any]   , lowerCAmelCase							:   DatasetInfo	):
		"""simple docstring"""







		SCREAMING_SNAKE_CASE_  :		List[str]				      =    str(lowerCAmelCase	)
		dataset_info.write_to_directory(lowerCAmelCase	)
		SCREAMING_SNAKE_CASE_  :		List[str]				      =    DatasetInfo.from_directory(lowerCAmelCase	)
		assert dataset_info == reloaded
		assert os.path.exists(os.path.join(lowerCAmelCase   , "dataset_info.json"	)	)




def       _snake_case	(   ):
		"""simple docstring"""







		SCREAMING_SNAKE_CASE_  :		List[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": 4_2}]   , download_checksums={}   , download_size=1_3_3_7   , post_processing_size=4_4_2   , dataset_size=1_2_3_4   , size_in_bytes=1_3_3_7 + 4_4_2 + 1_2_3_4   , )
		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_  :		Optional[Any]				      =    yaml.safe_dump(lowerCAmelCase	)
		SCREAMING_SNAKE_CASE_  :		Optional[Any]				      =    yaml.safe_load(lowerCAmelCase	)
		assert dataset_info_yaml_dict == reloaded




def       _snake_case	(   ):
		"""simple docstring"""







		SCREAMING_SNAKE_CASE_  :		str				      =    DatasetInfo()
		SCREAMING_SNAKE_CASE_  :		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=4_2   , )
            }	),
        DatasetInfosDict(
            {
                "v1": DatasetInfo(dataset_size=4_2	),
                "v2": DatasetInfo(dataset_size=1_3_3_7	),
            }	),
    ]   , )
def       _snake_case	(   lowerCAmelCase							:   Dict   , lowerCAmelCase							:   DatasetInfosDict	):
		"""simple docstring"""







		SCREAMING_SNAKE_CASE_  :		Optional[int]				      =    str(lowerCAmelCase	)
		dataset_infos_dict.write_to_directory(lowerCAmelCase	)
		SCREAMING_SNAKE_CASE_  :		int				      =    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_  :		Any				      =    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_  :		Tuple				      =    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 defaultdict




def       _snake_case	(   lowerCAmelCase							:   int	):
		"""simple docstring"""







		SCREAMING_SNAKE_CASE_  :		Any				      =    1
		SCREAMING_SNAKE_CASE_  :		Tuple				      =    True
		for v in tree[start]:
				if v not in visited:
						ret += dfs(lowerCAmelCase	)
		if ret % 2 == 0:
				cuts.append(lowerCAmelCase	)
		return ret




def       _snake_case	(   ):
		"""simple docstring"""







		dfs(1	)


if __name__ == "__main__":
		__lowerCamelCase   ,						__lowerCamelCase					:	Union[str, Any]       =  10, 9
		__lowerCamelCase					:	Optional[int]       =  defaultdict(list)
		__lowerCamelCase					:	dict[int, bool]       =  {}
		__lowerCamelCase					:	list[int]       =  []
		__lowerCamelCase					:	Optional[Any]       =  0
		__lowerCamelCase					:	Any       =  [(2, 1), (3, 1), (4, 3), (5, 2), (6, 1), (7, 2), (8, 6), (9, 8), (10, 8)]
		for u, v in edges:
				tree[u].append(v)
				tree[v].append(u)
		even_tree()
		print(len(cuts) - 1)
