





from __future__ import annotations

import random
import string
class SCREAMING_SNAKE_CASE_    :






						def __init__(   self   :   Tuple		, _A   :   str | None = None						)				->     None:







							"""simple docstring"""


							snake_case_		:      Union[str, Any]           =						passcode or self.__passcode_creator()
							snake_case_		:      Union[str, Any]           =						self.__make_key_list()
							snake_case_		:      str           =						self.__make_shift_key()






						def __str__(   self   :   int						)				->     str:







							"""simple docstring"""


							return "".join(self.__passcode						)






						def UpperCAmelCase_					(   self   :   Tuple		, _A   :   list[int]						)				->     list[int]:







							"""simple docstring"""


							for i in range(1		, len(_A						)		, 2						):
								iterlist[i] *= -1
							return iterlist






						def UpperCAmelCase_					(   self   :   Tuple						)				->     list[str]:







							"""simple docstring"""


							snake_case_		:      int           =						string.ascii_letters + string.digits
							snake_case_		:      Optional[Any]           =						[random.choice(_A						) for _ in range(random.randint(10		, 20						)						)]
							return password






						def UpperCAmelCase_					(   self   :   List[Any]						)				->     list[str]:







							"""simple docstring"""


							snake_case_		:      Union[str, Any]           =						(
							    string.ascii_letters + string.digits + string.punctuation + ' \t\n'
							)

							snake_case_		:      Tuple           =						[]

							# creates points known as breakpoints to break the key_list_options at those
							# points and pivot each substring
							snake_case_		:      Union[str, Any]           =						sorted(set(self.__passcode						)						)
							snake_case_		:      list[str]           =						[]

							# algorithm for creating a new shuffled list, keys_l, out of key_list_options
							for i in key_list_options:
								temp_list.extend(_A						)

								# checking breakpoints at which to pivot temporary sublist and add it into
								# keys_l
								if i in breakpoints or i == key_list_options[-1]:
									keys_l.extend(temp_list[::-1]						)
									temp_list.clear()

        # returning a shuffled keys_l to prevent brute force guessing of shift key
							return keys_l






						def UpperCAmelCase_					(   self   :   Dict						)				->     int:







							"""simple docstring"""


							snake_case_		:      Tuple           =						sum(self.__neg_pos([ord(_A						) for x in self.__passcode]						)						)
							return num if num > 0 else len(self.__passcode						)






						def UpperCAmelCase_					(   self   :   str		, _A   :   str						)				->     str:







							"""simple docstring"""


							snake_case_		:      List[str]           =						''

							# decoding shift like Caesar cipher algorithm implementing negative shift or
							# reverse shift or left shift
							for i in encoded_message:
								snake_case_		:      Optional[Any]           =						self.__key_list.index(_A						)
								decoded_message += self.__key_list[
								    (position - self.__shift_key) % -len(self.__key_list						)
								]

							return decoded_message






						def UpperCAmelCase_					(   self   :   List[str]		, _A   :   str						)				->     str:







							"""simple docstring"""


							snake_case_		:      Any           =						''

							# encoding shift like Caesar cipher algorithm implementing positive shift or
							# forward shift or right shift
							for i in plaintext:
								snake_case_		:      List[str]           =						self.__key_list.index(_A						)
								encoded_message += self.__key_list[
								    (position + self.__shift_key) % len(self.__key_list						)
								]

							return encoded_message


def 				SCREAMING_SNAKE_CASE__    (     __a = "Hello, this is a modified Caesar cipher" ):
	snake_case_		:      Union[str, Any]           =						ShuffledShiftCipher()
	return cipa.decrypt(cipa.encrypt(__a ) )


if __name__ == "__main__":
						import doctest

						doctest.testmod()





import re
import tempfile
import unittest
from pathlib import Path

from datasets.utils.metadata import DatasetMetadata

def  lowercase_						(						_A     :       str		):

      """simple docstring"""




      lowerCamelCase__						:							Optional[Any]       =    min(re.search("^ +"       ,   _A		).end() if t.startswith(" "		) else 0 for t in string.splitlines()		)
      return "\n".join([line[indent_level:] for line in string.splitlines() if indent_level < len(_A		)]		)


A :       Optional[int]						=   "\\n---\nlanguage:\n- zh\n- en\ntask_ids:\n- sentiment-classification\n---\n# Begin of markdown\n\nSome cool dataset card\n"

A :       str						=   "\\n---\n---\n# Begin of markdown\n\nSome cool dataset card\n"


A :       Optional[Any]						=   "\\n# Begin of markdown\n\nSome cool dataset card\n"







class      _lowercase					(				unittest.TestCase):


       """simple docstring"""




       def 		lowerCAmelCase	(  self				:     List[Any]			):


             '''simple docstring'''



             with tempfile.TemporaryDirectory() as tmp_dir:
                   lowerCamelCase__						:							List[str]       =    Path(__lowerCamelCase			) / "README.md"
                   with open(__lowerCamelCase   , "w+"			) as readme_file:
                         readme_file.write(__lowerCamelCase			)
                   lowerCamelCase__						:							Dict       =    DatasetMetadata.from_readme(__lowerCamelCase			)
                   self.assertDictEqual(__lowerCamelCase   , {"language": ["zh", "en"], "task_ids": ["sentiment-classification"]}			)

                   with open(__lowerCamelCase   , "w+"			) as readme_file:
                         readme_file.write(__lowerCamelCase			)
                   lowerCamelCase__						:							Optional[Any]       =    DatasetMetadata.from_readme(__lowerCamelCase			)
                   self.assertDictEqual(__lowerCamelCase   , {}			)

                   with open(__lowerCamelCase   , "w+"			) as readme_file:
                         readme_file.write(__lowerCamelCase			)
                   lowerCamelCase__						:							int       =    DatasetMetadata.from_readme(__lowerCamelCase			)
                   self.assertEqual(__lowerCamelCase   , {}			)





       def 		lowerCAmelCase	(  self				:     Any			):


             '''simple docstring'''



             lowerCamelCase__						:							List[str]       =    _dedent(
                 "\\n            annotations_creators:\n            - found\n            language_creators:\n            - found\n            language:\n            - en\n            license:\n            - unknown\n            multilinguality:\n            - monolingual\n            pretty_name: Test Dataset\n            size_categories:\n            - 10K<n<100K\n            source_datasets:\n            - extended|other-yahoo-webscope-l6\n            task_categories:\n            - question-answering\n            task_ids:\n            - open-domain-qa\n            "			)
             assert DatasetMetadata.from_yaml_string(__lowerCamelCase			)

             lowerCamelCase__						:							Dict       =    _dedent(
                 "\\n            annotations_creators:\n            - found\n            language:\n            - en\n            license:\n            - unknown\n            multilinguality:\n            - monolingual\n            pretty_name: Test Dataset\n            size_categories:\n            - 10K<n<100K\n            source_datasets:\n            - extended|other-yahoo-webscope-l6\n            task_categories:\n            - question-answering\n            task_ids:\n            - open-domain-qa\n            task_ids:\n            - open-domain-qa\n            "			)
             with self.assertRaises(__lowerCamelCase			):
                   DatasetMetadata.from_yaml_string(__lowerCamelCase			)

             lowerCamelCase__						:							Optional[Any]       =    _dedent(
                 "\\n            annotations_creators:\n            - found\n            language_creators:\n            - found\n            language:\n            - en\n            license:\n            - unknown\n            multilinguality:\n            - monolingual\n            pretty_name: Test Dataset\n            size_categories:\n            - 10K<n<100K\n            source_datasets:\n            - extended|other-yahoo-webscope-l6\n            task_categories:\n            - text-classification\n            task_ids:\n            - multi-class-classification\n            paperswithcode_id:\n            - squad\n            configs:\n            - en\n            train-eval-index:\n            - config: en\n              task: text-classification\n              task_id: multi_class_classification\n              splits:\n                train_split: train\n                eval_split: test\n              col_mapping:\n                text: text\n                label: target\n              metrics:\n                - type: accuracy\n                  name: Accuracy\n            extra_gated_prompt: |\n              By clicking on “Access repository” below, you also agree to ImageNet Terms of Access:\n              [RESEARCHER_FULLNAME] (the \"Researcher\") has requested permission to use the ImageNet database (the \"Database\") at Princeton University and Stanford University. In exchange for such permission, Researcher hereby agrees to the following terms and conditions:\n              1. Researcher shall use the Database only for non-commercial research and educational purposes.\n            extra_gated_fields:\n              Company: text\n              Country: text\n              I agree to use this model for non-commerical use ONLY: checkbox\n            "			)
             assert DatasetMetadata.from_yaml_string(__lowerCamelCase			)


