值得收藏,Python 开发中的高级技巧

这篇文章主要介绍了Python 开发中的高级技巧,非常不错,具有收藏价值,感兴趣的朋友一起看看吧

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

 >>> chars = [ c for c in 'python' ] >>> chars ['p', 'y', 't', 'h', 'o', 'n']

字典推导式

 >>> 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

 >>> set1 = {1,2,3,4} >>> double_set = {i*2 for i in set1} >>> double_set {8, 2, 4, 6}

合并字典

 >>> 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

 >>> nums = [1,2,3] >>> nums[::] [1, 2, 3] >>> copy_nums = nums[::] >>> copy_nums [1, 2, 3]

反转列表

 >>> reverse_nums = nums[::-1] >>> reverse_nums [3, 2, 1] PACKING / UNPACKING

变量交换

 >>> a,b = 1, 2 >>> a ,b = b,a >>> a 2 >>> b 1 

高级拆包

 >>> a, *b = 1,2,3 >>> a 1 >>> b [2, 3]

或者

 >>> 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

 >>> def f(): ...   return 1, 2, 3, 4 ... >>> a, b, c, d = f() >>> a 1 >>> d 4

列表合并成字符串

 >>> " ".join(["I", "Love", "Python"]) 'I Love Python'

链式比较

 >>> if a > 2 and a <5: ... pass>>> if 2>> 0 0 1 1 2 2

in 代替 or

 >>> 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

 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

 >>> 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

 >>> g = (i**2 for i in range(5)) >>> g  at 0x10881e518> >>> for i in g: ...   print(i) ... 0 1 4 9 16

默认字典 defaultdict

 >>> d = dict() >>> d['nums'] KeyError: 'nums' >>> >>> from collections import defaultdict >>> d = defaultdict(list) >>> d["nums"] []

字符串格式化

 >>> 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

 >>> nums = [1,2,3,3] >>> max(set(nums), key=nums.count) 3

或者

 from collections import Counter >>> Counter(nums).most_common()[0][0] 3

读写文件

 >>> with open("test.txt", "w") as f: ...   f.writelines("hello")

判断对象类型,可指定多个类型

 >>> isinstance(a, (int, str)) True

类似的还有字符串的 startswith,endswith

 >>> "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

 def makebold(f): return lambda: "" + f() + "" def makeitalic(f): return lambda: "" + f() + "" @makebold @makeitalic def say(): return "Hello" >>> say() Hello

不使用装饰器,可读性非常差

 def say(): return "Hello" >>> makebold(makeitalic(say))() Hello

总结

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