python deque的内在实现 本质上就是双向链表所以用于stack、队列非常方便

How collections.deque works?

Cosven

 

 

前言：在 Python 生态中，我们经常使用 collections.deque 来实现栈、队列这些只需要进行头尾操作的数据结构，它的 append/pop 操作都是 O(1) 时间复杂度。list 的 pop(0) 的时间复杂度是 O(n)， 在这个场景中，它的效率没有 deque 高。那 deque 内部是怎样实现的呢？ 我从 GitHub 上挖出了 CPython collections 模块的第二个 commit 的源码。

dequeobject 对象定义

注释写得优雅了，无法进行更加精简的总结。

/* The block length may be set to any number over 1. Larger numbers  * reduce the number of calls to the memory allocator but take more  * memory. Ideally, BLOCKLEN should be set with an eye to the  * length of a cache line.  */ #define BLOCKLEN 62 #define CENTER ((BLOCKLEN - 1) / 2)  /* A `dequeobject` is composed of a doubly-linked list of `block` nodes.  * This list is not circular (the leftmost block has leftlink==NULL,  * and the rightmost block has rightlink==NULL). A deque d's first  * element is at d.leftblock[leftindex] and its last element is at  * d.rightblock[rightindex]; note that, unlike as for Python slice  * indices, these indices are inclusive on both ends. By being inclusive  * on both ends, algorithms for left and right operations become  * symmetrical which simplifies the design.  *  * The list of blocks is never empty, so d.leftblock and d.rightblock  * are never equal to NULL.  *  * The indices, d.leftindex and d.rightindex are always in the range  * 0 <= index < BLOCKLEN.  * Their exact relationship is:  * (d.leftindex + d.len - 1) % BLOCKLEN == d.rightindex.  *  * Empty deques have d.len == 0; d.leftblock==d.rightblock;  * d.leftindex == CENTER+1; and d.rightindex == CENTER.  * Checking for d.len == 0 is the intended way to see whether d is empty.  *  * Whenever d.leftblock == d.rightblock,  * d.leftindex + d.len - 1 == d.rightindex.  *  * However, when d.leftblock != d.rightblock, d.leftindex and d.rightindex  * become indices into distinct blocks and either may be larger than the  * other.  */ typedef struct BLOCK { struct BLOCK *leftlink; struct BLOCK *rightlink; PyObject *data[BLOCKLEN]; } block; typedef struct { PyObject_HEAD block *leftblock; block *rightblock; int leftindex; /* in range(BLOCKLEN) */ int rightindex; /* in range(BLOCKLEN) */ int len; long state; /* incremented whenever the indices move */ PyObject *weakreflist; /* List of weak references */ } dequeobject;

下面是我为 Block 结构体画的一个图

                +----------------------------------------+
                |          data: 62 objects              |
 +----------+   |                                        |   +-----------+
 | leftlink |---|  | ... | Obj1 | Obj2 | Obj3 | ... |    |---| rightlink |
 +----------+   |           30     31     32             |   +-----------+
                +----------------------------------------+

创建一个 block

static block * newblock(block *leftlink, block *rightlink, int len) { block *b; /* To prevent len from overflowing INT_MAX on 64-bit machines, we  * refuse to allocate new blocks if the current len is dangerously  * close. There is some extra margin to prevent spurious arithmetic  * overflows at various places. The following check ensures that  * the blocks allocated to the deque, in the worst case, can only  * have INT_MAX-2 entries in total.  */ if (len >= INT_MAX - 2*BLOCKLEN) { PyErr_SetString(PyExc_OverflowError, "cannot add more blocks to the deque"); return NULL; } b = PyMem_Malloc(sizeof(block)); if (b == NULL) { PyErr_NoMemory(); return NULL; } b->leftlink = leftlink; b->rightlink = rightlink; return b; }

创建一个 dequeobject

1. 创建一个 block
2. 实例化一个 dequeobject Python 对象（这一块的内在逻辑目前我也不太懂）
3. leftblock 和 rightblock 指针都指向这个 block
4. leftindex 是 CENTER+1，rightindex 是 CENTER
5. 初始化其他一些属性， len state 等

这个第一步和第四步都有点意思，第一步创建一个 block，也就是说， deque 对象创建的时候，就预先分配了一块内存。第四步隐约告诉我们， 当元素来的时候，它先会被放在中间，然后逐渐往头和尾散开。

static PyObject * deque_new(PyTypeObject *type, PyObject *args, PyObject *kwds) { dequeobject *deque; block *b; if (type == &deque_type && !_PyArg_NoKeywords("deque()", kwds)) return NULL; /* create dequeobject structure */ deque = (dequeobject *)type->tp_alloc(type, 0); if (deque == NULL) return NULL; b = newblock(NULL, NULL, 0); if (b == NULL) { Py_DECREF(deque); return NULL; } assert(BLOCKLEN >= 2); deque->leftblock = b; deque->rightblock = b; deque->leftindex = CENTER + 1; deque->rightindex = CENTER; deque->len = 0; deque->state = 0; deque->weakreflist = NULL; return (PyObject *)deque; }

deque.append 实现

步骤：

1. 如果 rightblock 可以容纳更多的元素，则放在 rightblock 中
2. 如果不能，就新建一个 block，然后更新若干指针，将元素放在更新后的 rightblock 中

static PyObject * deque_append(dequeobject *deque, PyObject *item) { deque->state++; if (deque->rightindex == BLOCKLEN-1) { block *b = newblock(deque->rightblock, NULL, deque->len); if (b == NULL) return NULL; assert(deque->rightblock->rightlink == NULL); deque->rightblock->rightlink = b; deque->rightblock = b; deque->rightindex = -1; } Py_INCREF(item); deque->len++; deque->rightindex++; deque->rightblock->data[deque->rightindex] = item; Py_RETURN_NONE; }

看了 append 实现后，我们可以自行脑补一下 pop 和 popleft 的实现。

小结

deque 内部将一组内存块组织成双向链表的形式，每个内存块可以看成一个 Python 对象的数组， 这个数组与普通数据不同，它是从数组中部往头尾两边填充数据，而平常所见数组大都是从头往后。 得益于 deque 这样的结构，它的 pop/popleft/append/appendleft 四种操作的时间复杂度均是 O(1), 用它来实现队列、栈数据结构会非常方便和高效。但也正因为这样的设计， 它不能像数组那样通过 index 来访问、移除元素。链表 + 数组、或者链表 + 字典 这样的设计在实践中有很广泛的应用，比如 LRUCache, LFUCache，有兴趣的同鞋可以继续探索。

• PS1: LRUCache 在面试中不要太常见
• PS2: 出 LFUCache 题的面试官都是变态
• PS3: 头图来自 quora ，图文不怎么有关系列