def return_42():
    return 42  # An explicit return statement


print(return_42())  # The caller code gets 42


num = return_42()
print(num)


print(return_42() * 2)


print(return_42() + 5)


def get_even(numbers):
    even_nums = [num for num in numbers if not num % 2]
    return even_nums


num = get_even([1, 2, 3, 4, 5, 6])
print(num)


def mean(sample):
    return sum(sample) / len(sample)


num = mean([1, 2, 3, 4])
print(num)


def add_one(x):
    # No return statement at all
    result = x + 1


value = add_one(5)
print(value)


return_value = print("Hello, World")

print(return_value)


def print_greeting():
    print("Hello, World")


print_greeting()


def return_greeting():
    return "Hello, World"


print(return_greeting())


def add(a, b):
    result = a + b
    return result


print(add(2, 2))


import statistics as st


def describe(sample):
    return st.mean(sample), st.median(sample), st.mode(sample)


sample = [10, 2, 4, 7, 9, 3, 9, 8, 6, 7]
mean, median, mode = describe(sample)

print(mean)

print(median)

print(mode)

desc = describe(sample)
print(desc)

print(type(desc))


print(divmod(15, 3))

print(divmod(8, 3))


def omit_return_stmt():
    # Omit the return statement
    pass


print(omit_return_stmt())


def bare_return():
    # Use a bare return
    return


print(bare_return())


def return_none_explicitly():
    # Return None explicitly
    return None


print(return_none_explicitly())


def variance(data, ddof=0):
    mean = sum(data) / len(data)
    return sum((x - mean) ** 2 for x in data) / (len(data) - ddof)


print(variance([3, 4, 7, 5, 6, 2, 9, 4, 1, 3]))


def variance(data, ddof=0):
    n = len(data)
    mean = sum(data) / n
    total_square_dev = sum((x - mean) ** 2 for x in data)
    return total_square_dev / (n - ddof)


print(variance([3, 4, 7, 5, 6, 2, 9, 4, 1, 3]))


counter = 0


def increment():
    global counter
    counter += 1


increment()
print(counter)


counter = 0


def increment(var):
    return var + 1


increment(counter)


print(counter)


# Explicitly assign a new value to counter
counter = increment(counter)
print(counter)


def my_abs(number):
    if number > 0:
        return number
    elif number < 0:
        return -number


print(my_abs(-15))

print(my_abs(15))

print(my_abs(0))


def my_abs(number):
    if number > 0:
        return number
    elif number < 0:
        return -number
    else:
        return 0


print(my_abs(-15))

print(my_abs(15))

print(my_abs(0))


def my_abs(number):
    if number < 0:
        return -number
    return number


print(my_abs(-15))

print(my_abs(15))

print(my_abs(0))


def is_divisible(a, b):
    if not a % b:
        return True
    return False


print(is_divisible(4, 2))


print(is_divisible(7, 4))


def is_divisible(a, b):
    return not a % b


print(is_divisible(4, 2))


print(is_divisible(7, 4))


def both_true(a, b):
    return a and b


print(both_true(1, 2))


def both_true(a, b):
    if a and b:
        return True
    return False


print(both_true(1, 2))

print(both_true(1, 0))


def both_true(a, b):
    return True if a and b else False


print(both_true(1, 2))

print(both_true(1, 0))


def both_true(a, b):
    return bool(a and b)


print(both_true(1, 2))

print(both_true(1, 0))


def my_any(iterable):
    for item in iterable:
        if item:
            # Short-circuit
            return True
    return False


print(my_any([0, 0, 1, 0, 0]))


print(my_any([0, 0, 0, 0, 0]))


def dead_code():
    return 42
    # Dead code
    print("Hello, World")


print(dead_code())


def no_dead_code(condition):
    if condition:
        return 42
    print("Hello, World")


print(no_dead_code(True))

print(no_dead_code(False))


import statistics as st
from collections import namedtuple


def describe(sample):
    Desc = namedtuple("Desc", ["mean", "median", "mode"])
    return Desc(
        st.mean(sample),
        st.median(sample),
        st.mode(sample),
    )


sample = [10, 2, 4, 7, 9, 3, 9, 8, 6, 7]
stat_desc = describe(sample)

print(stat_desc)


# Get the mean by its attribute name
print(stat_desc.mean)


# Get the median by its index
print(stat_desc[1])


# Unpack the values into three variables
mean, median, mode = describe(sample)

print(mean)


print(mode)


def by_factor(factor):
    def multiply(number):
        return factor * number

    return multiply


double = by_factor(2)
print(double(3))

print(double(4))


triple = by_factor(3)
print(triple(3))

print(triple(4))


def by_factor(factor):
    return lambda number: factor * number


double = by_factor(2)
print(double(3))

print(double(4))


import time


def my_timer(func):
    def _timer(*args, **kwargs):
        start = time.time()
        result = func(*args, **kwargs)
        end = time.time()
        print(f"Execution time: {end - start}")
        return result

    return _timer


@my_timer
def delayed_mean(sample):
    time.sleep(1)
    return sum(sample) / len(sample)


print(delayed_mean([10, 2, 4, 7, 9, 3, 9, 8, 6, 7]))


class Circle:
    def __init__(self, radius):
        self.radius = radius

    # Class implementation...


class Square:
    def __init__(self, side):
        self.side = side

    # Class implementation...


def shape_factory(shape_name, *args, **kwargs):
    shapes = {"circle": Circle, "square": Square}
    return shapes[shape_name](*args, **kwargs)


circle = shape_factory("circle", radius=20)
print(type(circle))

print(circle.radius)


square = shape_factory("square", side=10)
print(type(square))

print(square.side)


def func(value):
    try:
        return float(value)
    except ValueError:
        return str(value)
    finally:
        print("Run this before returning")


print(func(9))

print(func("one"))


def gen():
    yield 1
    yield 2
    return 3


g = gen()
print(g)

print(next(g))

print(next(g))

print(next(g))