code: 
  
  
  
  
  
  '''simple docstring'''
  
  
  
  
  from sklearn.datasets import load_iris
  from sklearn.model_selection import train_test_split
  from sklearn.neighbors import KNeighborsClassifier
  
  # Load iris file
  a__				: List[Any]									=    load_iris()
  iris.keys()
  
  
  print(f"""Target names: \n {iris.target_names} """)
  print(f"""\n Features: \n {iris.feature_names}""")
  
  # Train set e Test set
  a__			,					a__			,					a__			,					a__				: Dict									=    train_test_split(
      iris['''data'''], iris['''target'''], random_state=4
  )
  
  # KNN
  
  a__				: List[str]									=    KNeighborsClassifier(n_neighbors=1)
  knn.fit(X_train, y_train)
  
  # new array to test
  a__				: Union[str, Any]									=    [[1, 2, 1, 4], [2, 3, 4, 5]]
  
  a__				: int									=    knn.predict(X_new)
  
  print(
      f"""\nNew array: \n {X_new}\n\nTarget Names Prediction: \n"""
      f""" {iris['target_names'][prediction]}"""
  )
  
  
  
  
style_context: 
  
  
  
  
  
  '''simple docstring'''
  
  
  
  
  def 	__lowerCamelCase (  UpperCAmelCase_       )      ->str:
  	snake_case__  					=      len(UpperCAmelCase_       )
  	for i in range(length - 1       ):
  		snake_case__  					=      False
  		for j in range(length - 1 - i       ):
  			if collection[j] > collection[j + 1]:
  				snake_case__  					=      True
  				snake_case__					,     snake_case__  					=      collection[j + 1], collection[j]
  		if not swapped:
  			break  # Stop iteration if the collection is sorted.
  	return collection
  
  
  if __name__ == "__main__":
  			import doctest
  			import time
  
  			doctest.testmod()
  
  			a__				: Dict									=    input('''Enter numbers separated by a comma:''').strip()
  			a__				: Dict									=    [int(item) for item in user_input.split(''',''')]
  			a__				: Tuple									=    time.process_time()
  			print(*bubble_sort(unsorted), sep=''',''')
  			print(f"""Processing time: {(time.process_time() - start)%1e9 + 7}""")
  
  
  
  