import random, numpy as np
from time import time
array = [random.randint(1, 30) for _ in range(1000000)]
# ~ array = np.array(array)

def balanced_mark(lst):
    return sum(1 if item % 2 else -1 for item in lst) == 0

def balanced_peilonrayz(items):
    return len(items) == 2 * sum(i % 2 for i in items)

def balanced_delta(items: Iterable[Number]) -> bool:
    """Is the amount of even and odd numbers the same in `items`?"""
    return sum(-1 if n % 2 else 1 for n in items) == 0

def balanced_kangalioo_compact(lst):
    num_even = sum(item % 2 == 0 for item in lst)
    num_odd = sum(item % 2 == 1 for item in lst)
    return num_even == num_odd

def balanced_kangalioo_expanded(lst): # equivalent to gazoh's solution
    num_even = 0
    num_odd = 0
    for number in lst:
        if number % 2 == 0: # even
            num_even += 1
        else: # odd
            num_odd += 1
    return num_even == num_odd

def balanced_alex(lst):
    return len([number for number in lst if number % 2 == 0]) == len(lst) / 2

def balanced_alex_2(lst):
    n = len(lst)
    if n % 2 != 0:
        return False
    return len([number for number in lst if number % 2 == 0]) == n / 2

def balanced_anonymous(lst):
    def is_even(number: int) -> bool:
        return (number % 2) == 0

    # list empty: return True by choice
    if len(lst) == 0:
        return True

    return len([item for item in lst if is_even(item)]) == len([item for item in lst if not is_even(item)])

def balanced_mti2935(lst):
    return(sum(map(lambda x: x%2, lst))==0.5*len(lst))

# ~ def balanced_numpy(lst):
    # ~ return (array % 2).sum() * 2 == len(lst)

results = {}
for name, fn in [(name, var) for name, var in globals().items() if isinstance(name, str) and name.startswith("balanced_")]:
    times = []
    for i in range(3):
        start_time = time()
        (fn)(array)
        times.append(time() - start_time)
    avg_time = sum(times) / len(times)
    results[name] = avg_time

for name, time in sorted(results.items(), key=lambda pair: pair[1]):
    print(f"{results[name]:.3f}s mean time - {name}")