





'''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]}"""
)










'''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}""")



