




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 					UpperCamelCase_(     snake_case							:	List[str]							,    snake_case							:	Union[str, Any]					):

							'''simple docstring'''






							snake_case_      =				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}}"					)
							snake_case_      =				DatasetInfosDict.from_directory(snake_case					)
							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 					UpperCamelCase_(     snake_case							:	Optional[Any]							,    snake_case							:	DatasetInfo					):

							'''simple docstring'''






							snake_case_      =				str(snake_case					)
							dataset_info.write_to_directory(snake_case					)
							snake_case_      =				DatasetInfo.from_directory(snake_case					)
							assert dataset_info == reloaded
							assert os.path.exists(os.path.join(snake_case							,    "dataset_info.json"					)					)


def 					UpperCamelCase_(     ):

							'''simple docstring'''






							snake_case_      =				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							,    )
							snake_case_      =				dataset_info._to_yaml_dict()
							assert sorted(snake_case					) == 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)					)
							snake_case_      =				yaml.safe_dump(snake_case					)
							snake_case_      =				yaml.safe_load(snake_case					)
							assert dataset_info_yaml_dict == reloaded


def 					UpperCamelCase_(     ):

							'''simple docstring'''






							snake_case_      =				DatasetInfo()
							snake_case_      =				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 					UpperCamelCase_(     snake_case							:	List[Any]							,    snake_case							:	DatasetInfosDict					):

							'''simple docstring'''






							snake_case_      =				str(snake_case					)
							dataset_infos_dict.write_to_directory(snake_case					)
							snake_case_      =				DatasetInfosDict.from_directory(snake_case					)

							# the config_name of the dataset_infos_dict take over the attribute
							for config_name, dataset_info in dataset_infos_dict.items():
														snake_case_      =				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
														snake_case_      =				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(snake_case							,    "README.md"					)					)










'''simple docstring'''





_SCREAMING_SNAKE_CASE							:       Optional[int]						=			"Alexander Joslin"

import operator as op

from .stack import Stack


def 					UpperCamelCase_(     snake_case							:	str					):

							'''simple docstring'''






							snake_case_      =				{"*": op.mul, "/": op.truediv, "+": op.add, "-": op.sub}

							snake_case_      =				Stack()
							snake_case_      =				Stack()

							for i in equation:
														if i.isdigit():
																					# RULE 1
																					operand_stack.push(int(snake_case					)					)
														elif i in operators:
																					# RULE 2
																					operator_stack.push(snake_case					)
														elif i == ")":
																					# RULE 4
																					snake_case_      =				operator_stack.peek()
																					operator_stack.pop()
																					snake_case_      =				operand_stack.peek()
																					operand_stack.pop()
																					snake_case_      =				operand_stack.peek()
																					operand_stack.pop()

																					snake_case_      =				operators[opr](snake_case							,    snake_case					)
																					operand_stack.push(snake_case					)

    # RULE 5
							return operand_stack.peek()


if __name__ == "__main__":
		_SCREAMING_SNAKE_CASE							:       List[Any]						=			"(5 + ((4 * 2) * (2 + 3)))"
		# answer = 45
		print(F"{equation} = {dijkstras_two_stack_algorithm(equation)}")




