在Python中，“.append()"和".append()"之间有什么区别?和"+ = []"? [英] In Python, what is the difference between ".append()" and "+= []"?

问题描述

两者之间有什么区别

some_list1 = []
some_list1.append("something")

和

some_list2 = []
some_list2 += ["something"]

推荐答案

对于您而言，唯一的区别是性能:append的速度是原来的两倍.

For your case the only difference is performance: append is twice as fast.

Python 3.0 (r30:67507, Dec  3 2008, 20:14:27) [MSC v.1500 32 bit (Intel)] on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> import timeit
>>> timeit.Timer('s.append("something")', 's = []').timeit()
0.20177424499999999
>>> timeit.Timer('s += ["something"]', 's = []').timeit()
0.41192320500000079

Python 2.5.1 (r251:54863, Apr 18 2007, 08:51:08) [MSC v.1310 32 bit (Intel)] on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> import timeit
>>> timeit.Timer('s.append("something")', 's = []').timeit()
0.23079359499999999
>>> timeit.Timer('s += ["something"]', 's = []').timeit()
0.44208112500000141

通常情况下，append会将一个项目添加到列表中，而+=会将右侧列表的 all 个元素复制到左侧列表中.

In general case append will add one item to the list, while += will copy all elements of right-hand-side list into the left-hand-side list.

更新:性能分析

比较字节码，我们可以假定append版本浪费了LOAD_ATTR + CALL_FUNCTION的周期，而+ =版本浪费了BUILD_LIST的周期.显然，BUILD_LIST胜过LOAD_ATTR + CALL_FUNCTION.

Comparing bytecodes we can assume that append version wastes cycles in LOAD_ATTR + CALL_FUNCTION, and += version -- in BUILD_LIST. Apparently BUILD_LIST outweighs LOAD_ATTR + CALL_FUNCTION.

>>> import dis
>>> dis.dis(compile("s = []; s.append('spam')", '', 'exec'))
  1           0 BUILD_LIST               0
              3 STORE_NAME               0 (s)
              6 LOAD_NAME                0 (s)
              9 LOAD_ATTR                1 (append)
             12 LOAD_CONST               0 ('spam')
             15 CALL_FUNCTION            1
             18 POP_TOP
             19 LOAD_CONST               1 (None)
             22 RETURN_VALUE
>>> dis.dis(compile("s = []; s += ['spam']", '', 'exec'))
  1           0 BUILD_LIST               0
              3 STORE_NAME               0 (s)
              6 LOAD_NAME                0 (s)
              9 LOAD_CONST               0 ('spam')
             12 BUILD_LIST               1
             15 INPLACE_ADD
             16 STORE_NAME               0 (s)
             19 LOAD_CONST               1 (None)
             22 RETURN_VALUE

我们可以通过消除LOAD_ATTR开销来进一步提高性能:

We can improve performance even more by removing LOAD_ATTR overhead:

>>> timeit.Timer('a("something")', 's = []; a = s.append').timeit()
0.15924410999923566

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