"""simple docstring"""
from __future__ import annotations







def 		__a  (      _SCREAMING_SNAKE_CASE						,	_SCREAMING_SNAKE_CASE  )      ->list[int]:
  a__:	dict[int, int]     				=      {}
  for index, val in enumerate(_SCREAMING_SNAKE_CASE  ):
    a__:	str     				=      target - val
    if compl in chk_map:
      return [chk_map[compl], index]
    a__:	Union[str, Any]     				=      index
  return []


if __name__ == "__main__":
 import doctest

 doctest.testmod()
 print(f"{two_sum([2, 7, 11, 15], 9) = }")



"""simple docstring"""
from sklearn.datasets import load_iris
from sklearn.model_selection import train_test_split
from sklearn.neighbors import KNeighborsClassifier

# Load iris file
lowercase__   			=      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
lowercase__			,   lowercase__			,   lowercase__			,   lowercase__   			=      train_test_split(
    iris['data'], iris['target'], random_state=4
)

# KNN

lowercase__   			=      KNeighborsClassifier(n_neighbors=1)
knn.fit(X_train, y_train)

# new array to test
lowercase__   			=      [[1, 2, 1, 4], [2, 3, 4, 5]]

lowercase__   			=      knn.predict(X_new)

print(
    f"\nNew array: \n {X_new}\n\nTarget Names Prediction: \n"
    f" {iris['target_names'][prediction]}"
)


