'''simple docstring'''

import secrets
from random import shuffle
from string import ascii_letters, ascii_lowercase, ascii_uppercase, digits, punctuation
def       __UpperCamelCase	(       UpperCAmelCase = 8					):
 lowercase__    :   Tuple						= ascii_letters + digits + punctuation
 return "".join(secrets.choice(UpperCAmelCase					) for _ in range(UpperCAmelCase					)					)
def       __UpperCamelCase	(       UpperCAmelCase		,					UpperCAmelCase					):
 i -= len(UpperCAmelCase					)
 lowercase__    :   Optional[int]						= i // 3
 lowercase__    :   List[str]						= i % 3
 # chars = chars_incl + random_letters(ascii_letters, i / 3 + remainder) +
 #     random_number(digits, i / 3) + random_characters(punctuation, i / 3)
 lowercase__    :   Any						= (
     chars_incl
     + random(UpperCAmelCase		,					quotient + remainder					)
     + random(UpperCAmelCase		,					UpperCAmelCase					)
     + random(UpperCAmelCase		,					UpperCAmelCase					)
 )
 lowercase__    :   str						= list(UpperCAmelCase					)
 shuffle(UpperCAmelCase					)
 return "".join(UpperCAmelCase					)

 # random is a generalised function for letters, characters and numbers
def       __UpperCamelCase	(       UpperCAmelCase		,					UpperCAmelCase					):
 return "".join(secrets.choice(UpperCAmelCase					) for _ in range(UpperCAmelCase					)					)
def       __UpperCamelCase	(       UpperCAmelCase		,					UpperCAmelCase					):
 pass  # Put your code here...
def       __UpperCamelCase	(       UpperCAmelCase		,					UpperCAmelCase					):
 pass  # Put your code here...
def       __UpperCamelCase	(       UpperCAmelCase		,					UpperCAmelCase					):
 pass  # Put your code here...
def       __UpperCamelCase	(       UpperCAmelCase		,					UpperCAmelCase = 8					):







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

 lowercase__    :   Union[str, Any]						= any(char in ascii_uppercase for char in password					)
 lowercase__    :   Optional[Any]						= any(char in ascii_lowercase for char in password					)
 lowercase__    :   List[str]						= any(char in digits for char in password					)
 lowercase__    :   str						= 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       __UpperCamelCase	(       ):
 lowercase__    :   Tuple						= int(input('''Please indicate the max length of your password: '''					).strip()					)
 lowercase__    :   Any						= input(
     '''Please indicate the characters that must be in your password: '''					).strip()
 print('''Password generated:'''		,					password_generator(UpperCAmelCase					)					)
 print(
     '''Alternative Password generated:'''		,					alternative_password_generator(UpperCAmelCase		,					UpperCAmelCase					)		,					)
 print('''[If you are thinking of using this passsword, You better save it.]'''					)


if __name__ == "__main__":
  main()


'''simple docstring'''

import unittest

from datasets import load_dataset

from transformers.pipelines import pipeline
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_torch, slow



@is_pipeline_test
@require_torch
class       UpperCAmelCase  (						unittest.TestCase ):





       '''simple docstring'''



       @require_torch
       def _lowerCAmelCase(						self			)  ->  int:
        lowercase__    :   str						= pipeline(
            task='''zero-shot-audio-classification'''     ,       model='''hf-internal-testing/tiny-clap-htsat-unfused'''			)
        lowercase__    :   Optional[Any]						= load_dataset('''ashraq/esc50'''			)
        lowercase__    :   Tuple						= dataset['''train''']['''audio'''][-1]['''array''']
        lowercase__    :   Optional[Any]						= audio_classifier(__lowerCAmelCase     ,       candidate_labels=['''Sound of a dog''', '''Sound of vaccum cleaner''']			)
        self.assertEqual(
            nested_simplify(__lowerCAmelCase			)     ,       [{'''score''': 0.5_0_1, '''label''': '''Sound of a dog'''}, {'''score''': 0.4_9_9, '''label''': '''Sound of vaccum cleaner'''}]     ,       )

       @unittest.skip('''No models are available in TF'''			)
       def _lowerCAmelCase(						self			)  ->  str:
        pass

       @slow
       @require_torch
       def _lowerCAmelCase(						self			)  ->  Tuple:
        lowercase__    :   List[str]						= pipeline(
            task='''zero-shot-audio-classification'''     ,       model='''laion/clap-htsat-unfused'''     ,       )
        # This is an audio of a dog
        lowercase__    :   int						= load_dataset('''ashraq/esc50'''			)
        lowercase__    :   str						= dataset['''train''']['''audio'''][-1]['''array''']
        lowercase__    :   Any						= audio_classifier(__lowerCAmelCase     ,       candidate_labels=['''Sound of a dog''', '''Sound of vaccum cleaner''']			)

        self.assertEqual(
            nested_simplify(__lowerCAmelCase			)     ,       [
                {'''score''': 0.9_9_9, '''label''': '''Sound of a dog'''},
                {'''score''': 0.0_0_1, '''label''': '''Sound of vaccum cleaner'''},
            ]     ,       )

        lowercase__    :   Dict						= audio_classifier([audio] * 5     ,       candidate_labels=['''Sound of a dog''', '''Sound of vaccum cleaner''']			)
        self.assertEqual(
            nested_simplify(__lowerCAmelCase			)     ,       [
                [
                    {'''score''': 0.9_9_9, '''label''': '''Sound of a dog'''},
                    {'''score''': 0.0_0_1, '''label''': '''Sound of vaccum cleaner'''},
                ],
            ]
            * 5     ,       )
        lowercase__    :   Any						= audio_classifier(
            [audio] * 5     ,       candidate_labels=['''Sound of a dog''', '''Sound of vaccum cleaner''']     ,       batch_size=5			)
        self.assertEqual(
            nested_simplify(__lowerCAmelCase			)     ,       [
                [
                    {'''score''': 0.9_9_9, '''label''': '''Sound of a dog'''},
                    {'''score''': 0.0_0_1, '''label''': '''Sound of vaccum cleaner'''},
                ],
            ]
            * 5     ,       )


       @unittest.skip('''No models are available in TF'''			)
       def _lowerCAmelCase(						self			)  ->  Union[str, Any]:
        pass

