在 Python 中遍历 deque 的时间复杂度是多少？

如果你的结构是这样的：

elements = deque([1,2,3,4])
for i in range(len(elements)):
    print(elements[i])

您不是在遍历 deque，而是在遍历对象，然后索引到 .这使得迭代多项式时间，因为每个索引操作都是 O（n）。然而，实际上迭代是线性时间。rangedequeelements[i]deque

for x in elements:
    print(x)

这是一个快速的实证测试：

import timeit
import pandas as pd
from collections import deque

def build_deque(n):
    return deque(range(n))

def iter_index(d):
    for i in range(len(d)):
        d[i]

def iter_it(d):
    for x in d:
        x

r = range(100, 10001, 100)

index_runs = [timeit.timeit('iter_index(d)', 'from __main__ import build_deque, iter_index, iter_it; d = build_deque({})'.format(n), number=1000) for n in r]
it_runs = [timeit.timeit('iter_it(d)', 'from __main__ import build_deque, iter_index, iter_it; d = build_deque({})'.format(n), number=1000) for n in r]

df = pd.DataFrame({'index':index_runs, 'iter':it_runs}, index=r)
df.plot()

以及生成的图：

现在，我们实际上可以看到迭代器协议是如何为 CPython 源代码中的对象实现的：deque

首先，对象本身：deque

typedef struct BLOCK {
    struct BLOCK *leftlink;
    PyObject *data[BLOCKLEN];
    struct BLOCK *rightlink;
} block;

typedef struct {
    PyObject_VAR_HEAD
    block *leftblock;
    block *rightblock;
    Py_ssize_t leftindex;       /* 0 <= leftindex < BLOCKLEN */
    Py_ssize_t rightindex;      /* 0 <= rightindex < BLOCKLEN */
    size_t state;               /* incremented whenever the indices move */
    Py_ssize_t maxlen;
    PyObject *weakreflist;
} dequeobject;

因此，正如评论中所述，a 是“块”节点的双向链接列表，其中块本质上是 python 对象指针的数组。现在对于迭代器协议：deque

typedef struct {
    PyObject_HEAD
    block *b;
    Py_ssize_t index;
    dequeobject *deque;
    size_t state;          /* state when the iterator is created */
    Py_ssize_t counter;    /* number of items remaining for iteration */
} dequeiterobject;

static PyTypeObject dequeiter_type;

static PyObject *
deque_iter(dequeobject *deque)
{
    dequeiterobject *it;

    it = PyObject_GC_New(dequeiterobject, &dequeiter_type);
    if (it == NULL)
        return NULL;
    it->b = deque->leftblock;
    it->index = deque->leftindex;
    Py_INCREF(deque);
    it->deque = deque;
    it->state = deque->state;
    it->counter = Py_SIZE(deque);
    PyObject_GC_Track(it);
    return (PyObject *)it;
}

// ...

static PyObject *
dequeiter_next(dequeiterobject *it)
{
    PyObject *item;

    if (it->deque->state != it->state) {
        it->counter = 0;
        PyErr_SetString(PyExc_RuntimeError,
                        "deque mutated during iteration");
        return NULL;
    }
    if (it->counter == 0)
        return NULL;
    assert (!(it->b == it->deque->rightblock &&
              it->index > it->deque->rightindex));

    item = it->b->data[it->index];
    it->index++;
    it->counter--;
    if (it->index == BLOCKLEN && it->counter > 0) {
        CHECK_NOT_END(it->b->rightlink);
        it->b = it->b->rightlink;
        it->index = 0;
    }
    Py_INCREF(item);
    return item;
}

正如你所看到的，迭代器实质上是跟踪一个块索引、一个指向一个块的指针，以及一个 deque 中总项的计数器。如果计数器达到零，它就会停止迭代，如果没有，它会抓取当前索引处的元素，递增索引，递减计数器，并负责检查是否移动到下一个块。换句话说，在 Python 中，一个 deque 可以表示为列表列表，例如 ，它迭代d = [[1,2,3],[4,5,6]]

for block in d:
    for x in block:
        ...