这是一种简单的方法:

result = mylist and all(mylist[0] == elem for elem in mylist)

这稍微复杂一点，它会引起函数调用开销，但语义更清楚地说明:

def all_identical(seq):
    if not seq:
        # empty list is False.
        return False
    first = seq[0]
    return all(first == elem for elem in seq)

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)

你可以:

reduce(and_, (x==yourList[0] for x in yourList), True)

python让你导入operator.and_这样的操作符是相当烦人的。从python3开始，还需要导入functools.reduce。

(您不应该使用此方法，因为如果它发现不相等的值，它不会中断，而是会继续检查整个列表。这里只是作为完整性的回答。)

不管怎样，这是最近在python想法邮件列表中出现的。事实证明，已经有一个itertools配方可以做到这一点

def all_equal(iterable):
    "Returns True if all the elements are equal to each other"
    g = groupby(iterable)
    return next(g, True) and not next(g, False)

据说它的性能非常好，有一些不错的属性。

短路:一旦发现第一个不相等的项，它就会停止从可迭代对象中消费项目。 不要求项是可哈希的。 它是懒惰的，只需要O(1)个额外的内存来进行检查。

换句话说，我不能把提出这个解决方案的功劳占为己有，甚至我也不能把找到它的功劳占为己有。

这是一段具有良好的Python性的代码，并且平衡了简单性和明显性，我认为，这应该也适用于相当老的Python版本。

def all_eq(lst):
    for idx, itm in enumerate(lst):
        if not idx:   # == 0
            prev = itm
        if itm != prev:
            return False
        prev = itm
    return True

您可以使用.nunique()来查找列表中唯一项的数量。

def identical_elements(list):
    series = pd.Series(list)
    if series.nunique() == 1: identical = True
    else:  identical = False
    return identical



identical_elements(['a', 'a'])
Out[427]: True

identical_elements(['a', 'b'])
Out[428]: False