O(1).或更准确地说，它等于按照您传递的任何序列查找单个索引的big-O随机访问时间，而list具有O(1)随机访问索引(就像tuple). 简化了，它所做的只是seq[random.randrange(len(seq))]，它显然等效于单个索引查找操作.

O(1). Or to be more precise, it's equivalent to the big-O random access time for looking up a single index in whatever sequence you pass it, and list has O(1) random access indexing (as does tuple). Simplified, all it does is seq[random.randrange(len(seq))], which is obviously equivalent to a single index lookup operation.

将其作为O(n)的示例是collections.deque，其中deque中间的索引是O(n)(尽管具有较大的常数除数，所以除非deque是达到数千个元素范围或更高).因此，基本上，不要使用deque，如果它会变大并且打算重复从中选择随机元素，请坚持使用list，tuple，str，byte/bytearray， array.array和其他具有O(1)索引的序列类型.

An example where it would be O(n) is collections.deque, where indexing in the middle of the deque is O(n) (with a largish constant divisor though, so it's not that expensive unless the deque is reaching the thousands of elements range or higher). So basically, don't use a deque if it's going to be large and you plan to select random elements from it repeatedly, stick to list, tuple, str, byte/bytearray, array.array and other sequence types with O(1) indexing.