最佳答案

Twitter上有一个不错的帖子，介绍了实现all_equal()函数的各种方法。

给定一个列表输入，最好的提交是:

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

其他方法

下面是线程的结果:

Have groupby() compare adjacent entries. This has an early-out for a mismatch, does not use extra memory, and it runs at C speed. g = itertools.groupby(s) next(g, True) and not next(g, False) Compare two slices offset from one another by one position. This uses extra memory but runs at C speed. s[1:] == s[:-1] Iterator version of slice comparison. It runs at C speed and does not use extra memory; however, the eq calls are expensive. all(map(operator.eq, s, itertools.islice(s, 1, None))) Compare the lowest and highest values. This runs at C speed, doesn't use extra memory, but does cost two inequality tests per datum. min(s) == max(s) # s must be non-empty Build a set. This runs at C speed and uses little extra memory but requires hashability and does not have an early-out. len(set(t))==1. At great cost, this handles NaNs and other objects with exotic equality relations. all(itertools.starmap(eq, itertools.product(s, repeat=2))) Pull out the first element and compare all the others to it, stopping at the first mismatch. Only disadvantage is that this doesn't run at C speed. it = iter(s) a = next(it, None) return all(a == b for b in it) Just count the first element. This is fast, simple, elegant. It runs at C speed, requires no additional memory, uses only equality tests, and makes only a single pass over the data. t.count(t[0]) == len(t)

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。

可以使用map和lambda吗

lst = [1,1,1,1,1,1,1,1,1]

print all(map(lambda x: x == lst[0], lst[1:]))

[编辑:这个答案针对当前投票最多的itertools。Groupby(这是一个很好的答案)稍后回答。

在不重写程序的情况下，最具渐近性能和可读性的方法如下:

all(x==myList[0] for x in myList)

(是的，这甚至适用于空列表!这是因为这是python具有惰性语义的少数情况之一。)

这将在尽可能早的时间失败，因此它是渐近最优的(期望时间大约是O(#惟一)而不是O(N)，但最坏情况时间仍然是O(N))。这是假设你之前没有看过这些数据……

(如果你关心性能，但不太关心性能，你可以先做通常的标准优化，比如将myList[0]常量从循环中提升出来，并为边缘情况添加笨拙的逻辑，尽管这是python编译器最终可能会学会如何做的事情，因此除非绝对必要，否则不应该这样做，因为它会破坏最小收益的可读性。)

如果你更关心性能，这是上面速度的两倍，但有点啰嗦:

def allEqual(iterable):
    iterator = iter(iterable)
    
    try:
        firstItem = next(iterator)
    except StopIteration:
        return True
        
    for x in iterator:
        if x!=firstItem:
            return False
    return True

如果你更关心性能(但还不足以重写你的程序)，请使用当前投票最多的itertools。它的速度是allEqual的两倍，因为它可能是优化的C代码。(根据文档，它应该(类似于这个答案)没有任何内存开销，因为惰性生成器永远不会被计算到列表中…这可能会让人担心，但伪代码表明，分组的“列表”实际上是惰性生成器。)

如果你更关心性能，请继续阅读…

关于性能的旁注，因为其他答案都在谈论它，因为一些未知的原因:

... if you have seen the data before and are likely using a collection data structure of some sort, and you really care about performance, you can get .isAllEqual() for free O(1) by augmenting your structure with a Counter that is updated with every insert/delete/etc. operation and just checking if it's of the form {something:someCount} i.e. len(counter.keys())==1; alternatively you can keep a Counter on the side in a separate variable. This is provably better than anything else up to constant factor. Perhaps you can also use python's FFI with ctypes with your chosen method, and perhaps with a heuristic (like if it's a sequence with getitem, then checking first element, last element, then elements in-order).

当然，可读性也有好处。

简单的解决方案是应用set on list

如果所有元素都相同，len将为1，否则大于1

lst = [1,1,1,1,1,1,1,1,1]
len_lst = len(list(set(lst)))

print(len_lst)

1


lst = [1,2,1,1,1,1,1,1,1]
len_lst = len(list(set(lst)))
print(len_lst)

2