Python 开发中有哪些高级技巧?这是知乎上一个问题,我总结了一些常见的技巧在这里,可能谈不上多高级,但掌握这些至少可以让你的代码看起来 Pythonic 一点。如果你还在按照类C语言的那套风格来写的话,在 code review 恐怕会要被吐槽了。
列表推导式
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>>> chars = [ c for c in 'python' ] >>> chars [ 'p' , 'y' , 't' , 'h' , 'o' , 'n' ] |
字典推导式
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>>> dict1 = { 'a' : 1 , 'b' : 2 , 'c' : 3 , 'd' : 4 , 'e' : 5 } >>> double_dict1 = {k:v * 2 for (k,v) in dict1.items()} >>> double_dict1 { 'a' : 2 , 'b' : 4 , 'c' : 6 , 'd' : 8 , 'e' : 10 } |
集合推导式
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>>> set1 = { 1 , 2 , 3 , 4 } >>> double_set = {i * 2 for i in set1} >>> double_set { 8 , 2 , 4 , 6 } |
合并字典
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>>> x = { 'a' : 1 , 'b' : 2 } >>> y = { 'c' : 3 , 'd' : 4 } >>> z = { * * x, * * y} >>> z { 'a' : 1 , 'b' : 2 , 'c' : 3 , 'd' : 4 } |
复制列表
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>>> nums = [ 1 , 2 , 3 ] >>> nums[::] [ 1 , 2 , 3 ] >>> copy_nums = nums[::] >>> copy_nums [ 1 , 2 , 3 ] |
反转列表
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>>> reverse_nums = nums[:: - 1 ] >>> reverse_nums [ 3 , 2 , 1 ] PACKING / UNPACKING |
变量交换
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>>> a,b = 1 , 2 >>> a ,b = b,a >>> a 2 >>> b 1 |
高级拆包
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>>> a, * b = 1 , 2 , 3 >>> a 1 >>> b [ 2 , 3 ] |
或者
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>>> a, * b, c = 1 , 2 , 3 , 4 , 5 >>> a 1 >>> b [ 2 , 3 , 4 ] >>> c 5 |
函数返回多个值(其实是自动packing成元组)然后unpacking赋值给4个变量
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>>> def f(): ... return 1 , 2 , 3 , 4 ... >>> a, b, c, d = f() >>> a 1 >>> d 4 |
列表合并成字符串
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>>> " " .join([ "I" , "Love" , "Python" ]) 'I Love Python' |
链式比较
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>>> if a > 2 and a < 5 : ... pass ... >>> if 2 <a< 5 : ... pass yield from # 没有使用 field from def dup(n): for i in range (n): yield i yield i # 使用yield from def dup(n): for i in range (n): yield from [i, i] for i in dup( 3 ): print (i) >>> 0 0 1 1 2 2 |
in 代替 or
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>>> if x = = 1 or x = = 2 or x = = 3 : ... pass ... >>> if x in ( 1 , 2 , 3 ): ... pass |
字典代替多个if else
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def fun(x): if x = = 'a' : return 1 elif x = = 'b' : return 2 else : return None def fun(x): return { "a" : 1 , "b" : 2 }.get(x) |
有下标索引的枚举
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>>> for i, e in enumerate ([ "a" , "b" , "c" ]): ... print (i, e) ... 0 a 1 b 2 c |
生成器
注意区分列表推导式,生成器效率更高
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>>> g = (i * * 2 for i in range ( 5 )) >>> g <generator object <genexpr> at 0x10881e518 > >>> for i in g: ... print (i) ... 0 1 4 9 16 |
默认字典 defaultdict
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>>> d = dict () >>> d[ 'nums' ] KeyError: 'nums' >>> >>> from collections import defaultdict >>> d = defaultdict( list ) >>> d[ "nums" ] [] |
字符串格式化
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>>> lang = 'python' >>> f '{lang} is most popular language in the world' 'python is most popular language in the world' |
列表中出现次数最多的元素
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>>> nums = [ 1 , 2 , 3 , 3 ] >>> max ( set (nums), key = nums.count) 3 |
或者
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from collections import Counter >>> Counter(nums).most_common()[ 0 ][ 0 ] 3 |
读写文件
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>>> with open ( "test.txt" , "w" ) as f: ... f.writelines( "hello" ) |
判断对象类型,可指定多个类型
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>>> isinstance (a, ( int , str )) True |
类似的还有字符串的 startswith,endswith
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>>> "http://foofish.net" .startswith(( 'http' , 'https' )) True >>> "https://foofish.net" .startswith(( 'http' , 'https' )) True __str__ 与 __repr__ 区别 >>> str (datetime.now()) '2018-11-20 00:31:54.839605' >>> repr (datetime.now()) 'datetime.datetime(2018, 11, 20, 0, 32, 0, 579521)' |
前者对人友好,可读性更强,后者对计算机友好,支持 obj == eval(repr(obj))
使用装饰器
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def makebold(f): return lambda : "<b>" + f() + "</b>" def makeitalic(f): return lambda : "<i>" + f() + "</i>" @makebold @makeitalic def say(): return "Hello" >>> say() <b><i>Hello< / i>< / b> |
不使用装饰器,可读性非常差
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def say(): return "Hello" >>> makebold(makeitalic(say))() <b><i>Hello< / i>< / b> |
总结
以上所述是小编给大家介绍的Python 开发中的高级技巧,希望对大家有所帮助,如果大家有任何疑问请给我留言,小编会及时回复大家的。在此也非常感谢大家对服务器之家网站的支持!