关于使用reduce()和lambda。这里有一个工作代码，我个人认为比其他一些答案更好。

reduce(lambda x, y: (x[1]==y, y), [2, 2, 2], (True, 2))

返回一个元组，其中第一个值是布尔值，如果所有项都相同或不相同。

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。

>>> a = [1, 2, 3, 4, 5, 6]
>>> z = [(a[x], a[x+1]) for x in range(0, len(a)-1)]
>>> z
[(1, 2), (2, 3), (3, 4), (4, 5), (5, 6)]
# Replacing it with the test
>>> z = [(a[x] == a[x+1]) for x in range(0, len(a)-1)]
>>> z
[False, False, False, False, False]
>>> if False in z : Print "All elements are not equal"

将您的输入转换为一个集:

len(set(the_list)) <= 1

使用set可以删除所有重复的元素。<= 1使它在输入为空时正确地返回True。

这要求输入中的所有元素都是可哈希的。例如，如果传入一个列表的列表，就会得到一个TypeError。

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。

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)