对于您而言，唯一的区别是性能：append是两倍的速度。
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+=将右侧列表的 所有 元素复制到左侧列表中。
比较字节码，我们可以假设appendversion在LOAD_ATTR+CALL_FUNCTION和+ = version- 中浪费了周期BUILD_LIST。显然BUILD_LIST大于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
我们可以通过减少LOAD_ATTR开销来进一步提高性能：
>>> timeit.Timer('a("something")', 's = []; a = s.append').timeit()
0.15924410999923566
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