




import secrets
from random import shuffle
from string import ascii_letters, ascii_lowercase, ascii_uppercase, digits, punctuation







def      lowerCamelCase_						(			UpperCamelCase__							: int = 8 )	->			str:





				"""simple docstring"""


				__lowerCamelCase									=       ascii_letters + digits + punctuation
				return "".join(secrets.choice(lowerCamelCase_ ) for _ in range(lowerCamelCase_ ) )







def      lowerCamelCase_						(			UpperCamelCase__							: str					,	UpperCamelCase__							: int )	->			str:





				"""simple docstring"""


				i -= len(lowerCamelCase_ )
				__lowerCamelCase									=       i // 3
				__lowerCamelCase									=       i % 3
				# chars = chars_incl + random_letters(ascii_letters, i / 3 + remainder) +
				#     random_number(digits, i / 3) + random_characters(punctuation, i / 3)
				__lowerCamelCase									=       (
				    chars_incl
				    + random(lowerCamelCase_					,	quotient + remainder )
				    + random(lowerCamelCase_					,	lowerCamelCase_ )
				    + random(lowerCamelCase_					,	lowerCamelCase_ )
				)
				__lowerCamelCase									=       list(lowerCamelCase_ )
				shuffle(lowerCamelCase_ )
				return "".join(lowerCamelCase_ )

				# random is a generalised function for letters, characters and numbers







def      lowerCamelCase_						(			UpperCamelCase__							: str					,	UpperCamelCase__							: int )	->			str:





				"""simple docstring"""


				return "".join(secrets.choice(lowerCamelCase_ ) for _ in range(lowerCamelCase_ ) )







def      lowerCamelCase_						(			UpperCamelCase__							: List[str]					,	UpperCamelCase__							: Union[str, Any] )	->			List[Any]:





				"""simple docstring"""


				pass  # Put your code here...







def      lowerCamelCase_						(			UpperCamelCase__							: List[str]					,	UpperCamelCase__							: str )	->			str:





				"""simple docstring"""


				pass  # Put your code here...







def      lowerCamelCase_						(			UpperCamelCase__							: Optional[Any]					,	UpperCamelCase__							: int )	->			Optional[int]:





				"""simple docstring"""


				pass  # Put your code here...







def      lowerCamelCase_						(			UpperCamelCase__							: str					,	UpperCamelCase__							: int = 8 )	->			bool:





				"""simple docstring"""


				if len(lowerCamelCase_ ) < min_length:
								# Your Password must be at least 8 characters long
								return False

				__lowerCamelCase									=       any(char in ascii_uppercase for char in password )
				__lowerCamelCase									=       any(char in ascii_lowercase for char in password )
				__lowerCamelCase									=       any(char in digits for char in password )
				__lowerCamelCase									=       any(char in punctuation for char in password )

				return upper and lower and num and spec_char
				# Passwords should contain UPPERCASE, lowerase
				# numbers, and special characters







def      lowerCamelCase_						(			)	->			List[Any]:





				"""simple docstring"""


				__lowerCamelCase									=       int(input('Please indicate the max length of your password: ' ).strip() )
				__lowerCamelCase									=       input(
				    'Please indicate the characters that must be in your password: ' ).strip()
				print('Password generated:'					,	password_generator(lowerCamelCase_ ) )
				print(
				    'Alternative Password generated:'					,	alternative_password_generator(lowerCamelCase_					,	lowerCamelCase_ )					,	)
				print('[If you are thinking of using this passsword, You better save it.]' )


if __name__ == "__main__":
					main()








from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


UpperCamelCase__ :   Optional[Any]						=							{
    '''configuration_whisper''': ['''WHISPER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''WhisperConfig''', '''WhisperOnnxConfig'''],
    '''feature_extraction_whisper''': ['''WhisperFeatureExtractor'''],
    '''processing_whisper''': ['''WhisperProcessor'''],
    '''tokenization_whisper''': ['''WhisperTokenizer'''],
}

try:
						if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						UpperCamelCase__ :   str						=							['''WhisperTokenizerFast''']

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						UpperCamelCase__ :   List[Any]						=							[
						    '''WHISPER_PRETRAINED_MODEL_ARCHIVE_LIST''',
						    '''WhisperForConditionalGeneration''',
						    '''WhisperModel''',
						    '''WhisperPreTrainedModel''',
						    '''WhisperForAudioClassification''',
						]

try:
						if not is_tf_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						UpperCamelCase__ :   Tuple						=							[
						    '''TF_WHISPER_PRETRAINED_MODEL_ARCHIVE_LIST''',
						    '''TFWhisperForConditionalGeneration''',
						    '''TFWhisperModel''',
						    '''TFWhisperPreTrainedModel''',
						]

try:
						if not is_flax_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						UpperCamelCase__ :   List[str]						=							[
						    '''FlaxWhisperForConditionalGeneration''',
						    '''FlaxWhisperModel''',
						    '''FlaxWhisperPreTrainedModel''',
						    '''FlaxWhisperForAudioClassification''',
						]


if TYPE_CHECKING:
						from .configuration_whisper import WHISPER_PRETRAINED_CONFIG_ARCHIVE_MAP, WhisperConfig, WhisperOnnxConfig
						from .feature_extraction_whisper import WhisperFeatureExtractor
						from .processing_whisper import WhisperProcessor
						from .tokenization_whisper import WhisperTokenizer

						try:
												if not is_tokenizers_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .tokenization_whisper_fast import WhisperTokenizerFast

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_whisper import (
												    WHISPER_PRETRAINED_MODEL_ARCHIVE_LIST,
												    WhisperForAudioClassification,
												    WhisperForConditionalGeneration,
												    WhisperModel,
												    WhisperPreTrainedModel,
												)

						try:
												if not is_tf_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_tf_whisper import (
												    TF_WHISPER_PRETRAINED_MODEL_ARCHIVE_LIST,
												    TFWhisperForConditionalGeneration,
												    TFWhisperModel,
												    TFWhisperPreTrainedModel,
												)

						try:
												if not is_flax_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_flax_whisper import (
												    FlaxWhisperForAudioClassification,
												    FlaxWhisperForConditionalGeneration,
												    FlaxWhisperModel,
												    FlaxWhisperPreTrainedModel,
												)

else:
						import sys

						UpperCamelCase__ :   Optional[Any]						=							_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)



