


'''simple docstring'''

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

def _SCREAMING_SNAKE_CASE      (A = 8       )       ->       str:






       """simple docstring"""







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

def _SCREAMING_SNAKE_CASE      (A  , A       )       ->       str:






       """simple docstring"""







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

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

def _SCREAMING_SNAKE_CASE      (A  , A       )       ->       str:






       """simple docstring"""







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

def _SCREAMING_SNAKE_CASE      (A  , A       )       ->       List[Any]:






       """simple docstring"""







       pass  # Put your code here...

def _SCREAMING_SNAKE_CASE      (A  , A       )       ->       Dict:






       """simple docstring"""







       pass  # Put your code here...

def _SCREAMING_SNAKE_CASE      (A  , A       )       ->       Optional[Any]:






       """simple docstring"""







       pass  # Put your code here...

def _SCREAMING_SNAKE_CASE      (A  , A = 8       )       ->       bool:






       """simple docstring"""







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

       lowercase__      			= any(char in ascii_uppercase for char in password       )
       lowercase__      			= any(char in ascii_lowercase for char in password       )
       lowercase__      			= any(char in digits for char in password       )
       lowercase__      			= 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 _SCREAMING_SNAKE_CASE      ()       ->       Any:






       """simple docstring"""







       lowercase__      			= int(input('''Please indicate the max length of your password: '''       ).strip()       )
       lowercase__      			= input(
           '''Please indicate the characters that must be in your password: '''       ).strip()
       print('''Password generated:'''  , password_generator(A       )       )
       print(
           '''Alternative Password generated:'''  , alternative_password_generator(A  , A       )  , )
       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_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


lowercase_									=   {'configuration_xlnet': ['XLNET_PRETRAINED_CONFIG_ARCHIVE_MAP', 'XLNetConfig']}

try:
  if not is_sentencepiece_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowercase_									=   ['XLNetTokenizer']

try:
  if not is_tokenizers_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowercase_									=   ['XLNetTokenizerFast']

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowercase_									=   [
      'XLNET_PRETRAINED_MODEL_ARCHIVE_LIST',
      'XLNetForMultipleChoice',
      'XLNetForQuestionAnswering',
      'XLNetForQuestionAnsweringSimple',
      'XLNetForSequenceClassification',
      'XLNetForTokenClassification',
      'XLNetLMHeadModel',
      'XLNetModel',
      'XLNetPreTrainedModel',
      'load_tf_weights_in_xlnet',
  ]

try:
  if not is_tf_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowercase_									=   [
      'TF_XLNET_PRETRAINED_MODEL_ARCHIVE_LIST',
      'TFXLNetForMultipleChoice',
      'TFXLNetForQuestionAnsweringSimple',
      'TFXLNetForSequenceClassification',
      'TFXLNetForTokenClassification',
      'TFXLNetLMHeadModel',
      'TFXLNetMainLayer',
      'TFXLNetModel',
      'TFXLNetPreTrainedModel',
  ]


if TYPE_CHECKING:
  from .configuration_xlnet import XLNET_PRETRAINED_CONFIG_ARCHIVE_MAP, XLNetConfig

  try:
    if not is_sentencepiece_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_xlnet import XLNetTokenizer

  try:
    if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_xlnet_fast import XLNetTokenizerFast

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_xlnet import (
        XLNET_PRETRAINED_MODEL_ARCHIVE_LIST,
        XLNetForMultipleChoice,
        XLNetForQuestionAnswering,
        XLNetForQuestionAnsweringSimple,
        XLNetForSequenceClassification,
        XLNetForTokenClassification,
        XLNetLMHeadModel,
        XLNetModel,
        XLNetPreTrainedModel,
        load_tf_weights_in_xlnet,
    )

  try:
    if not is_tf_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_tf_xlnet import (
        TF_XLNET_PRETRAINED_MODEL_ARCHIVE_LIST,
        TFXLNetForMultipleChoice,
        TFXLNetForQuestionAnsweringSimple,
        TFXLNetForSequenceClassification,
        TFXLNetForTokenClassification,
        TFXLNetLMHeadModel,
        TFXLNetMainLayer,
        TFXLNetModel,
        TFXLNetPreTrainedModel,
    )

else:
  import sys

  lowercase_									=   _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)


