from sklearn.model_selection import train_test_split

X = [1, 2, 3, 4, 5]
y = [10, 20, 30, 40, 50]

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.4, random_state=1)

print(len(X_test))

import pandas as pd

df = pd.DataFrame({'A': ['x', 'x', 'y', 'y'], 'B': [1, 2, 3, 4]})
result = df.groupby('A').agg({'B': 'sum'})
print(result.loc['x']['B'])

def dec(func):
    print("dec called", end=" ")
    return func

@dec
def f():
    print("f called")

f()

def dec(func):
    def inner():
        print("decorated")
    
f = dec(lambda: print("hello"))
f()

def dec1(func):
    def wrap():
        print("1", end=" ")
        func()
    return wrap

def dec2(func):
    def wrap():
        print("2", end=" ")
        func()
    return wrap

@dec1
@dec2
def f():
    print("f")

f()

from functools import wraps

def dec(func):
    @wraps(func)
    def wrapper():
        pass
    return wrapper

@dec
def f():
    """I am docstring"""
    return 42

print(f.__name__, f.__doc__)

def outer(msg):
    def dec(func):
        def wrapper(*args):
            print(msg, end=" ")
            return func(*args)
        return wrapper
    return dec

@outer("hello")
@outer("bye")
def f(x):
    print(x)

f("!")

import time

def timer(func):
    def wrapper():
        start = time.time()
        func()
        end = time.time()
        print("Elapsed:", round(end - start, 2), end=" ")
    return wrapper

@timer
def f():
    time.sleep(0.1)
    print("f done", end=" ")

f()

class dec:
    def __init__(self, func):
        self.func = func
        print("init", end=" ")

    def __call__(self):
        print("before", end=" ")
        self.func()
        print("after", end=" ")

@dec
def f():
    print("f called", end=" ")

f()