还有一个纯Python递归选项:

def checkEqual(lst):
    if len(lst)==2 :
        return lst[0]==lst[1]
    else:
        return lst[0]==lst[1] and checkEqual(lst[1:])

然而，由于某些原因，它在某些情况下比其他选项慢两个数量级。从C语言的角度来看，我希望这更快，但事实并非如此!

另一个缺点是Python中有递归限制，在这种情况下需要进行调整。比如用这个。

如果你对一些更有可读性的东西感兴趣(但当然不是那么高效)，你可以尝试:

def compare_lists(list1, list2):
    if len(list1) != len(list2): # Weed out unequal length lists.
        return False
    for item in list1:
        if item not in list2:
            return False
    return True

a_list_1 = ['apple', 'orange', 'grape', 'pear']
a_list_2 = ['pear', 'orange', 'grape', 'apple']

b_list_1 = ['apple', 'orange', 'grape', 'pear']
b_list_2 = ['apple', 'orange', 'banana', 'pear']

c_list_1 = ['apple', 'orange', 'grape']
c_list_2 = ['grape', 'orange']

print compare_lists(a_list_1, a_list_2) # Returns True
print compare_lists(b_list_1, b_list_2) # Returns False
print compare_lists(c_list_1, c_list_2) # Returns False

我怀疑这是“最python化的”，但类似于:

>>> falseList = [1,2,3,4]
>>> trueList = [1, 1, 1]
>>> 
>>> def testList(list):
...   for item in list[1:]:
...     if item != list[0]:
...       return False
...   return True
... 
>>> testList(falseList)
False
>>> testList(trueList)
True

会成功的。

还有一个纯Python递归选项:

def checkEqual(lst):
    if len(lst)==2 :
        return lst[0]==lst[1]
    else:
        return lst[0]==lst[1] and checkEqual(lst[1:])

然而，由于某些原因，它在某些情况下比其他选项慢两个数量级。从C语言的角度来看，我希望这更快，但事实并非如此!

另一个缺点是Python中有递归限制，在这种情况下需要进行调整。比如用这个。

比使用set()处理序列(而不是可迭代对象)更快的解决方案是简单地计算第一个元素。这假设列表是非空的(但这是微不足道的检查，并决定什么结果应该在一个空列表)

x.count(x[0]) == len(x)

一些简单的基准:

>>> timeit.timeit('len(set(s1))<=1', 's1=[1]*5000', number=10000)
1.4383411407470703
>>> timeit.timeit('len(set(s1))<=1', 's1=[1]*4999+[2]', number=10000)
1.4765670299530029
>>> timeit.timeit('s1.count(s1[0])==len(s1)', 's1=[1]*5000', number=10000)
0.26274609565734863
>>> timeit.timeit('s1.count(s1[0])==len(s1)', 's1=[1]*4999+[2]', number=10000)
0.25654196739196777

出现使用itertools。Groupby(参见itertools食谱):

from itertools import groupby

def all_equal(iterable):
    g = groupby(iterable)
    return next(g, True) and not next(g, False)

或不带groupby:

def all_equal(iterator):
    iterator = iter(iterator)
    try:
        first = next(iterator)
    except StopIteration:
        return True
    return all(first == x for x in iterator)

您可以考虑使用许多其他的一行程序:

Converting the input to a set and checking that it only has one or zero (in case the input is empty) items def all_equal2(iterator): return len(set(iterator)) <= 1 Comparing against the input list without the first item def all_equal3(lst): return lst[:-1] == lst[1:] Counting how many times the first item appears in the list def all_equal_ivo(lst): return not lst or lst.count(lst[0]) == len(lst) Comparing against a list of the first element repeated def all_equal_6502(lst): return not lst or [lst[0]]*len(lst) == lst

但它们也有一些缺点，即:

all_equal and all_equal2 can use any iterators, but the others must take a sequence input, typically concrete containers like a list or tuple. all_equal and all_equal3 stop as soon as a difference is found (what is called "short circuit"), whereas all the alternatives require iterating over the entire list, even if you can tell that the answer is False just by looking at the first two elements. In all_equal2 the content must be hashable. A list of lists will raise a TypeError for example. all_equal2 (in the worst case) and all_equal_6502 create a copy of the list, meaning you need to use double the memory.

在Python 3.9中，使用perfplot，我们得到这些计时(越低的Runtime [s]越好):