Python 开发中有哪些高级技巧?收藏这是知乎上一个问题，我总结了一些常见的高级技巧在这里，可能谈不上多高级，技巧但掌握这些至少可以让你的收藏代码看起来 Pythonic 一点。如果你还在按照类C语言的高级那套风格来写的b2b信息网话，在 code review 恐怕会要被吐槽了。技巧 列表推导式 >>> chars = [ c for c in python ] >>> chars [p,收藏 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<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 >>> 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 <generator object <genexpr> 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高级元素 >>> 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,技巧 (int, str)) True 类似的免费信息发布网还有字符串的 startswith，endswith >>> "http://foofish.net".startswith((http,收藏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，高级后者对计算机友好，技巧支持 obj == eval(repr(obj)) 使用装饰器 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，收藏可读性非常差 高级def say(): return "Hello" >>> makebold(makeitalic(say))() <b><i>Hello</i></b> |
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