Python合并两个字典的常用方法与效率比较
本文实例讲述了Python合并两个字典的常用方法与效率比较。分享给大家供大家参考。具体分析如下:
下面的代码举例了5种合并两个字典的方法,并且做了个简单的性能测试
#!/usr/bin/python import time def f1(d1, d2): return dict(d1, **d2) def f2(d1, d2): return dict(d1.items() + d2.items()) def f3(d1, d2): d = d1.copy() d.update(d2) return d def f4(d1, d2): d1.update(d2) return d1 def f5(d1, d2): d = dict(d1) d.update(d2) return d def f6(d1, d2): return (lambda a, b: (lambda a_copy: a_copy.update(b) or a_copy)(a.copy()))(d1, d2) def f7(d1, d2): d = {} d.update(d1) d.update(d2) return d def t(f, n): st = time.time() for i in range(1000000): dic1 = {'a':'AA','b':'BB','c':'CC'} dic2 = {'A':'aa','B':'bb','C':'cc'} f(dic1, dic2) et = time.time() print '%s cost:%s'%(n, et-st) t(f1, 'f1') t(f2, 'f2') t(f3, 'f3') t(f4, 'f4') t(f5, 'f5') t(f6, 'f6') t(f7, 'f7')
除了f4方法会对字典d1造成破坏性修改之外,另外的几种方法都是把合并的结果作为新的字典返回。
下面是测试结果:
f1 cost:2.382999897 f2 cost:4.45399999619 f3 cost:3.02100014687 f4 cost:1.73000001907 f5 cost:2.3710000515 f6 cost:2.89700007439 f7 cost:2.35600018501
可以看出f4最为高效,如果不需要保留原字典的话推荐使用f4方法。
希望本文所述对大家的Python程序设计有所帮助。

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