元组比Python中的列表更有效吗？

在实例化和检索元素时,元组和列表之间是否存在性能差异？

通常,您可能希望元组稍快一些.但是你绝对应该测试你的特定情况(如果差异可能会影响你的程序的性能 - 记住"过早优化是所有邪恶的根源").

Python使这很容易:timeit是你的朋友.

$ python -m timeit "x=(1,2,3,4,5,6,7,8)"
10000000 loops, best of 3: 0.0388 usec per loop

$ python -m timeit "x=[1,2,3,4,5,6,7,8]"
1000000 loops, best of 3: 0.363 usec per loop

和...

$ python -m timeit -s "x=(1,2,3,4,5,6,7,8)" "y=x[3]"
10000000 loops, best of 3: 0.0938 usec per loop

$ python -m timeit -s "x=[1,2,3,4,5,6,7,8]" "y=x[3]"
10000000 loops, best of 3: 0.0649 usec per loop

所以在这种情况下,元组的实例化速度几乎要快一个数量级,但是对于列表,项目访问实际上要快一些!因此,如果您创建了几个元组并多次访问它们,那么使用列表实际上可能会更快.

当然,如果你想改变一个项目,列表肯定会更快,因为你需要创建一个全新的元组来改变它的一个项目(因为元组是不可变的).

摘要

元组往往比几乎每个类别中的列表表现更好:

1)元组可以不断折叠.

2)可以重用元组而不是复制元组.

3)元组是紧凑的,不会过度分配.

4)元组直接引用它们的元素.

元组可以不断折叠

常量元组可以通过Python的窥孔优化器或AST优化器进行预先计算.另一方面,列表从头开始构建:

    >>> from dis import dis

    >>> dis(compile("(10, 'abc')", '', 'eval'))
      1           0 LOAD_CONST               2 ((10, 'abc'))
                  3 RETURN_VALUE   

    >>> dis(compile("[10, 'abc']", '', 'eval'))
      1           0 LOAD_CONST               0 (10)
                  3 LOAD_CONST               1 ('abc')
                  6 BUILD_LIST               2
                  9 RETURN_VALUE 

元组不需要复制

运行tuple(some_tuple)立即返回.由于元组是不可变的,因此不必复制它们:

>>> a = (10, 20, 30)
>>> b = tuple(a)
>>> a is b
True

相反,list(some_list)要求将所有数据复制到新列表:

>>> a = [10, 20, 30]
>>> b = list(a)
>>> a is b
False

元组不会过度分配

由于元组的大小是固定的,因此它可以比需要过度分配以使append()操作有效的列表更紧凑地存储.

这为元组提供了一个很好的空间优势:

>>> import sys
>>> sys.getsizeof(tuple(iter(range(10))))
128
>>> sys.getsizeof(list(iter(range(10))))
200

以下是Objects/listobject.c中的注释,它解释了列表正在执行的操作:

/* This over-allocates proportional to the list size, making room
 * for additional growth.  The over-allocation is mild, but is
 * enough to give linear-time amortized behavior over a long
 * sequence of appends() in the presence of a poorly-performing
 * system realloc().
 * The growth pattern is:  0, 4, 8, 16, 25, 35, 46, 58, 72, 88, ...
 * Note: new_allocated won't overflow because the largest possible value
 *       is PY_SSIZE_T_MAX * (9 / 8) + 6 which always fits in a size_t.
 */

$ python3.6 -m timeit -s 'a = (10, 20, 30)' 'a[1]'
10000000 loops, best of 3: 0.0304 usec per loop
$ python3.6 -m timeit -s 'a = [10, 20, 30]' 'a[1]'
10000000 loops, best of 3: 0.0309 usec per loop

$ python3.6 -m timeit -s 'a = (10, 20, 30)' 'x, y, z = a'
10000000 loops, best of 3: 0.0249 usec per loop
$ python3.6 -m timeit -s 'a = [10, 20, 30]' 'x, y, z = a'
10000000 loops, best of 3: 0.0251 usec per loop

    typedef struct {
        Py_ssize_t ob_refcnt;
        struct _typeobject *ob_type;
        Py_ssize_t ob_size;
        PyObject *ob_item[2];     /* store a pointer to 10 and a pointer to 20 */
    } PyTupleObject;

    PyObject arr[2];              /* store a pointer to 10 and a pointer to 20 */

    typedef struct {
        Py_ssize_t ob_refcnt;
        struct _typeobject *ob_type;
        Py_ssize_t ob_size;
        PyObject **ob_item = arr; /* store a pointer to the two-pointer array */
        Py_ssize_t allocated;
    } PyListObject;

>>> def a():
...     x=[1,2,3,4,5]
...     y=x[2]
...
>>> def b():
...     x=(1,2,3,4,5)
...     y=x[2]
...
>>> import dis
>>> dis.dis(a)
  2           0 LOAD_CONST               1 (1)
              3 LOAD_CONST               2 (2)
              6 LOAD_CONST               3 (3)
              9 LOAD_CONST               4 (4)
             12 LOAD_CONST               5 (5)
             15 BUILD_LIST               5
             18 STORE_FAST               0 (x)

  3          21 LOAD_FAST                0 (x)
             24 LOAD_CONST               2 (2)
             27 BINARY_SUBSCR
             28 STORE_FAST               1 (y)
             31 LOAD_CONST               0 (None)
             34 RETURN_VALUE
>>> dis.dis(b)
  2           0 LOAD_CONST               6 ((1, 2, 3, 4, 5))
              3 STORE_FAST               0 (x)

  3           6 LOAD_FAST                0 (x)
              9 LOAD_CONST               2 (2)
             12 BINARY_SUBSCR
             13 STORE_FAST               1 (y)
             16 LOAD_CONST               0 (None)
             19 RETURN_VALUE