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' ]
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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 }
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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 }
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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 }
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复制列表
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>>> nums = [ 1 , 2 , 3 ]
>>> nums[::]
[ 1 , 2 , 3 ]
>>> copy_nums = nums[::]
>>> copy_nums
[ 1 , 2 , 3 ]
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反转列表
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>>> reverse_nums = nums[:: - 1 ]
>>> reverse_nums
[ 3 , 2 , 1 ]
PACKING / UNPACKING
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变量交换
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>>> a,b = 1 , 2
>>> a ,b = b,a
>>> a
2
>>> b
1
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高级拆包
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>>> a, * b = 1 , 2 , 3
>>> a
1
>>> b
[ 2 , 3 ]
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或者
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>>> a, * b, c = 1 , 2 , 3 , 4 , 5
>>> a
1
>>> b
[ 2 , 3 , 4 ]
>>> c
5
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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
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列表合并成字符串
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>>> " " .join([ "I" , "Love" , "Python" ])
'I Love Python'
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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
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2
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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
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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)
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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
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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
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9
16
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默认字典 defaultdict
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>>> d = dict ()
>>> d[ 'nums' ]
KeyError: 'nums'
>>>
>>> from collections import defaultdict
>>> d = defaultdict( list )
>>> d[ "nums" ]
[]
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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'
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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
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或者
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from collections import Counter
>>> Counter(nums).most_common()[ 0 ][ 0 ]
3
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读写文件
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>>> with open ( "test.txt" , "w" ) as f:
... f.writelines( "hello" )
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判断对象类型,可指定多个类型
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>>> isinstance (a, ( int , str ))
True
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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)'
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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>
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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>
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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!